Traffic Safety Research (TSR) is an academic-led, international, interdisciplinary, peer-reviewed, Fair Open Access scientific journal. It was founded in 2021 with a clear objective to contribute to the global transition toward the Safe System approach in road transportation. The TSR publishes high-quality research from a wide range of disciplines—including engineering, psychology, sociology, economics, medicine, political science, and other relevant fields—that help to explain and address road traffic injuries and fatalities. The journal places strong emphasis on the real-world relevance of both the research questions and the findings. Why another journal? Read our mission statement. Publication topics? Read more about the journal's focus and scope. What papers get published? See our operational quality criteria and check out the TSR's webinars on excellence in traffic safety research. Do I need to pay? Read more about our financing model and production fees. Indexing? Read about the TSR's current indexing status. Who is behind? Meet the editorial team.
Technology & Society | LTH | Lund University
The effect of navigation modalities on driver performance, workload and user experience: a simulator study
Young novice drivers are overrepresented in crash statistics, highlighting the need for effective training interventions. Swedish authorities have discussed simulator-based screening tests to improve licensing outcomes. This study investigated how visual versus auditory navigation instructions affect driving performance, cognitive load, and user experience in a driving simulator. A highly relevant comparison as the real-world driving tests uses auditive navigation through an examinator. Fifty students at an automotive high school with prior driving simulator experience were assigned to either a visual or auditory instruction group. Participants completed urban driving scenarios with intersections and roundabouts, while metrics such as speed, lane positioning, acceleration/braking, distance to other vehicles, and adherence to traffic rules and instructions were recorded. Cognitive load and user experience were assessed post-drive using NASA-TLX and Likert-scale surveys. Participants receiving auditory instructions committed significantly fewer breaches than those with visual instructions, suggesting there is less driving performance compromise in the auditory navigation condition as compared to the visual navigation condition. No significant difference between groups appeared for cognitive load. These results suggest that auditory instructions better reflect real-world driving test conditions and may enhance the ecological validity of simulator-based screening tests for novice drivers.
Copyright (c) 2026 Marius Brudvik Norell, Birgitta Thorslund https://creativecommons.org/licenses/by/4.0
Assessing how physical and mental fatigue affect driving speed on the Banda Aceh–Medan highway, Indonesia
This study was motivated by the relatively high number of traffic accidents along Banda Aceh–Medan highway, where driver fatigue has been repeatedly cited as the key contributing factor. The research aimed to determine the extent to which physical and mental fatigue influence driving speed behavior on this long-distance route. A quantitative survey was conducted with 400 drivers, both professional and private, using the validated fatigue scales and Structural Equation Modeling for the data analysis. The results indicated that physical fatigue negatively affects speed stability, while mental fatigue significantly increases speed variability. Nevertheless, both physical and mental fatigue explaining 57.8% of the variance in driving speed. These findings highlight the dual cognitive and physiological dimensions of fatigue, emphasizing its role in impaired speed regulation and increased accident risk. This study contributes to existing knowledge by quantifying the distinct effects of physical and mental fatigue on driving performance in a real-world setting, thereby offering empirical support for targeted fatigue management interventions on long-distance routes.
Copyright (c) 2026 Yusria Darma, Sofyan Saleh, Juliana Fisaini, Sugiarto Sugiarto, Puteri Rezeki Saida, Faiza Mauladea https://creativecommons.org/licenses/by/4.0
Supporting success: teaching driving to learners with neurodevelopmental disorders
Driving education can be challenging for individuals with neurodevelopmental disorders (NDDs) due to the various symptoms which accompanies the disorders. However, previous research on NDDs and driving has prioritized cognitive deficits over specific mitigation strategies for driver training. This study aims to explore driving instructors' experiences of teaching individuals with NDDs with the research questions: (i) what challenges do driving instructors experience when working with individuals with NDDs during the process of teaching and learning to drive? and (ii) how do driving instructors address these challenges in terms of teaching methods and strategies? Thirteen certified Swedish driving instructors with experience teaching students with NDDs participated in semi-structured interviews which were analyzed using qualitative content analysis. The findings reveal both cognitive and structural challenges, for example difficulties processing information in various traffic situations and the need for additional resources. The driving instructors emphasized the importance of clear communication and creating a structured and supportive environment. To meet the needs of learners with NDDs, they described using a range of adaptive strategies. These include breaking down tasks into smaller steps, using repetition, giving clear and concrete instructions, and incorporating illustrations and demonstrations to enhance understanding. The results highlight the importance of targeted, individualized support within driver education for learners with NDDs. They also provide practical insights into current teaching approaches and highlight areas for recommended focus. By shedding light on instructional strategies, this study informs both practice and policy, contributing to a more inclusive, effective and accessible driver education system for individuals with NDDs.
Copyright (c) 2026 Lina Hertzberg, Birgitta Thorslund, Helena Selander https://creativecommons.org/licenses/by/4.0
To pass or not to pass: a field experiment on human values in interactions with automated vehicles
Vulnerable road users (VRUs), such as pedestrians and cyclists, are at high risk in road traffic, accounting for more than half of all global traffic fatalities. Ensuring safe interactions with highly automated vehicles (AVs) requires understanding and predicting VRUs' behaviour. This study investigated the relevance and predictive role of human values alongside environmental factors in real-world VRU-AV interactions. In a field experiment using a Wizard-of-Oz paradigm, 28 pedestrians and 29 cyclists interacted with an oncoming vehicle in a space-sharing scenario. Human values were assessed both qualitatively and quantitatively, while distance to the vehicle and driving mode (AV vs. manually driven) were manipulated. Results show that numerous human values (e.g. comprehensibility, legal compliance, self-efficacy, relaxedness) were rated as highly relevant, but only values related to relaxed interaction significantly predicted pedestrians' behaviour. Distance predicted interaction behaviour for VRU groups, whereas driving mode had no effect. Overall, the findings highlight the importance of considering both environmental factors and human values. The study demonstrates that values provide a broader perspective for understanding VRU behaviour and informing the design of safe, trustworthy, and acceptable VRU-AV interactions.
Copyright (c) 2026 Josephine Halama, Julius Alexander Knittel, Stefan Brandenburg https://creativecommons.org/licenses/by/4.0
Prevalence of drink driving in road traffic in Denmark
Driving under the influence of alcohol (DUI) is among the riskiest traffic behaviours road users can conduct. To combat drink driving, clarifying its prevalence is paramount. The objective of this study is to map DUI prevalence in Denmark and separate DUI prevalence into geography (police districts), time of day and day of the week, gender and road user modes. In April 2018 to December 2019, 116,378 DUI breath test samples were taken in all (12) Danish police districts. The survey was designed to mirror real life traffic prevalence; thus, the screened road user would represent the average road user. For each sample, road user mode, gender, age were recorded, and the road user was screened for breath alcohol concentration (BrAC). In the case of a positive screening outcome, a more specific breath test was conducted. This was followed by a blood sample in case of BrAC>0.25 mg/L (corresponding to BAC>0.5 g/L). All road users subject to the legal blood alcohol content (BAC) limit of 0.5 g/L were included in the study, i.e. drivers of personal vehicles, vans, lorries, buses, motorcycles, tractors and mopeds. DUI prevalence for drivers “on wheels” was compared to DUI prevalence for drivers in personal injury accidents (PIA). Overall DUI prevalence was 0.2% (95% CI: 0.18%–0.23%). DUI prevalence was lowest in the police district Copenhagen (urban area) and highest in police district Bornholm (most rural area). Twice as many male as female drivers were DUI (0.24% (95% CI: 0.21%–0.28%) and 0.12% (95% CI: 0.08%–0.16%), respectively). Middle-aged drivers were the group with the highest DUI prevalence (0.27%). DUI prevalence in personal injury accidents was disproportionately high in the age group 25–44 suggesting higher BACs and/or a higher accident risk. Moped riders had a significantly higher DUI prevalence (3.1%) than any other road user group. Moreover, the share of DUI personal injury accidents including moped riders was disproportionately high (23.0%) compared to their share of traffic (0.6%). This is probably because of a combination of high BACs due to alcohol addiction and a high vulnerability due to unprotection. DUI primarily took place in the early morning. Overall DUI prevalence in Denmark has been declining over the years. The typical DUI road user is a moped rider, middle-aged male, riding early in the morning.
Copyright (c) 2026 Tove Hels, Lars Klit Reiff, Harry Lahrmann, Tanja Kidholm Osmann Madsen https://creativecommons.org/licenses/by/4.0
Extracting roadway vertical alignment from USGS LiDAR point cloud data using an Artificial Neural Network based method
Vertical grades and vertical curvature significantly influence traffic safety. However, obtaining accurate and large-scale data on roadway vertical alignment remains a major challenge. This paper presents a cost-effective and efficient method for estimating roadway vertical alignment using publicly available aerial LiDAR data provided by the United States Geological Survey. An Artificial Neural Network (ANN) model was proposed to predict whether a LiDAR point belongs to a vertical curve or a tangent segment. Due to the limited availability of actual roadway vertical alignment data and the substantial data requirements of machine learning models, a synthetic training dataset was generated by systematically varying road grades and segment lengths to represent realistic combinations of tangents, crest and sag curves. This approach ensured that the model was exposed to a wide range of geometric configurations and allowed it to learn generalized relationships between vertical alignment features and their corresponding geometric parameters. The model was then independently evaluated by comparing the vertical alignment estimated from the extracted aerial LiDAR data for two-lane two-way rural roadways, Route 152 in New Jersey and Route 299 in California, with their corresponding actual vertical alignment data. In addition, a case study was conducted on another rural two-lane highway in which the model was used to compute safe speeds for each roadway segment. The resulting speeds were then compared with the posted speed limits along the corridor. The satisfactory estimation results of this study indicate that the proposed approach can be used for conducting large-scale analyses to estimate vertical alignment using publicly available LiDAR data.
Copyright (c) 2026 Mojibulrahman Jami, Bekir Bartin, Kaan Ozbay https://creativecommons.org/licenses/by/4.0
Human rights jurisprudence and road safety outcomes: the ECtHR's impact on European traffic policy
This article examines the European Court of Human Rights (ECtHR) approach to enhancing road safety across Europe in implementing the right to life under Article 2 of the European Convention on Human Rights. By analyzing formative judgments such as Smiljanić v. Croatia, this article demonstrates that the Court has slowly begun recognizing road traffic risks as an issue impacting the right to life by imposing substantive and procedural positive obligations on states. This article argues that the ECtHR's jurisprudence establishes structural standards to prevent dangerous driving, build public confidence, and ensure that states can build their capacity for preventative work in the area of road safety.
Copyright (c) 2025 Seyed Hesamoddin Lesani https://creativecommons.org/licenses/by/4.0
Intelligent Speed Assistance: an on-road evaluation
Although approximately 29% of traffic fatalities involve excessive speed, individual vehicle technology that can reduce speeding has not been widely studied or implemented in the United States (U.S). Starting in 2022, NYC DCAS conducted the largest public pilot of active Intelligent Speed Assistance (ISA) in the U.S., with approximately 400 vehicles equipped with a device that prevents acceleration when the vehicle is traveling faster than a preset threshold over the speed limit (typically 11 mph). Using an “opportunity to speed” framework (i.e., only account for driving time when a driver is traveling at least 5 mph below the speed limit), an analysis of 270 vehicles equipped with ISA showed there was a 64.18% relative decrease in the time driven >11 mph over the posted speed limit following ISA activation compared to before activation. This decrease in time spent speeding was not seen in non-equipped control vehicles. Speeding drive time reduction ranged from ~50% on 25 mph local roads, which have speed safety cameras set to the same enforced speed threshold, to 77% reduction on 50 mph roads. In addition, the impact of ISA on speeding behaviour of habitual speeders in 130 vehicles was similar to that on the primary cohort, indicating active ISA is effective at significantly reducing severe speeding across a wide range of drivers and fleets.
Copyright (c) 2026 Alexander K. Epstein, Sarah Yahoodik, Alyssa Brodeur, Juwon Drake, Tomomi Landsman https://creativecommons.org/licenses/by/4.0
Is that what people want? An initial study on the intention to use self-driving taxis in the city of Zurich
Fully autonomous Level-4 electric taxis, operating independently without a human driver, are no longer a novelty and are already operating on public roads in the USA and other countries. It is clear that the mobility sector is facing extensive changes, which also affects cities like Zurich. But to what extent will those transport concepts be adopted in cities in the future? Are Level-4 self-driving electric taxis welcome on its streets? This study examined whether this revolution in passenger transport would find acceptance on the streets of Zurich. We explored in which cases, by whom, and for which routes autonomous taxis would be utilized. An online survey with 302 participants assessed the potential intent to use these taxis both during the day and night. The questionnaire was developed based on various theoretical models of technology acceptance and other traffic-related studies and was specifically adapted to the conditions in Zurich. The results showed that factors such as safety and utility evaluations, social influences, and attitudes toward new technologies are significant predictors of usage intention in Zurich. The results also indicate that respondents are not yet fully prepared to hand over control, although the participants expressed an interest in this new technology and an intention to use it. Sociodemographic factors such as age, gender, or education level showed no consistent influence. Based on these findings, several practical implications were identified and subsequently developed, such as highlighting the relevance of safety and user-friendliness in self-driving taxis.
Copyright (c) 2026 Lea Häberli, Sabrina Hofer, Markus Hackenfort https://creativecommons.org/licenses/by/4.0
A framework for reliable traffic surrogate safety assessment based on multi-object tracking data
Multiple object tracking (MOT) systems enable the recording of traffic situations and the movements of road users in high detail. These data form the basis for safety-related analyses such as surrogate safety assessment (SSA), which often involves detecting, quantifying, and analysing conflict situations. Due to the rarity of actual conflicts even occasional data errors can significantly affect SSA outcomes. Consequently, high-quality data are essential. However, a gap remains between MOT and SSA research, particularly regarding the impact of data quality on the reliability of SSA results. This study addresses that gap by proposing a framework that explicitly accounts for the effects of data quality to ensure reliable SSA outcomes. Since it treats the data-generating MOT system as a black box, the framework can also be applied by practitioners using historical datasets or in cases of restricted access to the MOT system. Using the surrogate safety measures (SSMs) time-to-collision (TTC) and post-encroachment time (PET), we illustrate how data inaccuracies affect conflict detection and show how the proposed framework can reveal critical data limitations. We also demonstrate its ability to identify the need for data correction methods and to analyse the effects of such methods on SSA outcomes. Finally, our findings underline the importance of scenario-specific data evaluation for ensuring reliable SSA results and suggest that robustness against data inaccuracies should be considered a key criterion when selecting SSMs.
Copyright (c) 2025 Markus Steinmaßl, Moritz Beeking, Natasha Troth, Karl Rehrl https://creativecommons.org/licenses/by/4.0
The logic of empirical testing of accident prediction models
This paper explains the logic of empirical testing of accident prediction models. The key element of empirical testing is to make out-of-sample predictions of the number of accidents. This means that a model developed in sample A is applied, without modification, to predict the number of accidents in sample B. The procedure is illustrated in two samples formed by randomisation. A model fitted to the first sample was applied to predict the number of accidents in the second sample. The model was only partly supported. In general, any accident prediction model is likely to be merely a local statistical description of a particular data set. If tested by means of out-of-sample predictions, the model is very likely to be falsified. This does not mean that accident prediction models do not show general tendencies, but these tendencies are likely to be empirically supported only at a qualitative level, or at best an ordinal level of numerical measurement. In this sense accident prediction models are similar to many models developed in economics. The models predict the direction, and in some cases the relative strength of statistical relationships, but not their precise numerical values.
Copyright (c) 2026 Rune Elvik https://creativecommons.org/licenses/by/4.0
Towards a European key performance indicator for safe urban roads: lessons from the Trendline project
Key Performance Indicators (KPIs) are an important instrument for road safety policy making. This paper presents a KPI for safe urban roads that was developed and tested in the European Trendline project. Based on discussions with 18 experts from 8 countries, it was decided to start with the basic indicator ‘Share of 30 km/h road length of the total length of urban roads’ which was tested in five pilot countries using available local, national and international (GIS) databases. The share of 30 km/h roads appeared to differ considerably between the pilot countries, ranging from less than 1% in the city of Silistra in Bulgaria to 73% in the Netherlands. The pilots showed that it is possible to calculate the KPI, although it is important to check the quality of the speed limit data and there will be some differences in selections due to data availability and local context. Also the use of additional indicators related to the concept of safe speeds was explored in the pilots. The calculation of these indicators appeared to be more challenging and further research is recommended to further develop these additional KPIs.
Copyright (c) 2025 Wendy Weijermars, Elisabete Rodrigues, Johannes Mesimäki, Simon Sternlund, Maria Georgieva, Jan Hendrik van Petegem, Teun Uijtdewilligen, Augusto Torbay, Ana Amaro, Ana Vidigal, Fernando Rosa, Wouter Van den Berghe https://creativecommons.org/licenses/by/4.0
Comparative analysis of methodologies for In-built Network-wide Road Safety Assessments
In-built Network-wide Road Safety Assessment (IRSA) procedures involve the visual inspection of road design characteristics, and assigning scores to sections of the road network based on the availability and condition of the road characteristics. The main objective of the study was to evaluate two IRSA methodologies developed for rural highways, that is the Simplified methodology, and the Networkwide Proactive methodology (NWA Proactive). Both methodologies are applied on a 10.41 km, two-lane undivided rural road section in Latina Province, Italy. The assessment focused on comparing the reliability and predictive performance of these methods. The results revealed that the level of agreement of the rankings from both methods is moderate, while, they both showed poor correlation with crash history. This indicates that there is a need for continuous testing and development of IRSA methodologies since existing ones have a great variation in terms of the choice of parameters such as; risk factors, segmentation approach, risk formulation, and ranking categories. The insights derived from this study are very relevant to road technicians and practitioners involved in road safety assessment procedures.
Copyright (c) 2026 Elvis Chia Ngwah, Stephen Kome Fondzenyuya, Steffel Ludivin Feudjio Tezong, Brayan González-Hernández, Davide Shingo Usami, Luca Persia https://creativecommons.org/licenses/by/4.0
Language matters: an experimental study of language patterns' effects on traffic safety perceptions in Germany
Traffic crashes claim over 1.19 million lives globally each year, yet public support for proven safety measures remains limited. Research suggests that media language patterns may influence public perceptions of traffic violence and policy preferences. This study replicates Goddard et al.'s (2019) experimental design study in the German context, examining how editorial patterns in crash reporting affect responsibility attribution, penalty preferences, and policy support. Using a randomized controlled experiment (N = 1,537), participants read one of three versions of a fictitious news article: status-quo language reflecting common German reporting patterns, agent-focused language avoiding victim-blaming formulations, or agent-focused plus contextual information. Results show that shifting from victim-focused to agent-focused language substantially reduced pedestrian responsibility attribution (from 48.9% to 44.4%) and increased responsibility attributed to the driver (from 43.5% to 48.1%). Adding contextual information enlarged these effects, with driver responsibility attribution reaching 54.8% and pedestrian responsibility attribution dropping to 33.2%. Contextual framing also increased support for structural interventions and reduced support for campaigns appealing to individual behavior. These findings confirm that language patterns in German road traffic collision reporting—including metonymy, passive voice, reflexive verbs, and the lack of context information—systematically shift perceived responsibility toward vulnerable road users. The study demonstrates that more precise language in traffic reporting can increase public support for evidence-based safety policies, suggesting an ethical imperative for improved editorial practices.
Copyright (c) 2025 Dirk von Schneidemesser, Hugo Caviola https://creativecommons.org/licenses/by/4.0
The effect on cyclist safety of daytime running lights
On average, Danes cycle 1.3 kilometres per person per day. However, according to emergency department statistics, each year more than 16,000 cyclists are injured in Denmark. In an effort to improve cyclist safety we tested the effect of daytime running lights (DRL) on the number of cyclist accidents. Using a randomised controlled trial design, 5,380 voluntary cyclist participants were randomly assigned to a test group (using DRL continuously for one year) or a control group (using their usual light routine for one year). Participants were provided with accident surveys once each month. A total of 230 accidents were reported: 121 in the test group and 109 in the control group. Most accidents were multi-party accidents (MPAs), took place in winter and in daylight. Safety effect of DRL was estimated as incidence rate ratio (IRR) between the test and control group. The incidence rate is the number of accidents per person-month. Reports of single-bicycle accidents (SBAs) in daylight were used to correct for potential report bias following Madsen et al. (2013). For multiparty personal injury accidents (PIAs), the corrected overall effect of DRL was a 25% risk reduction. The effect was insignificant. For all multiparty accidents, the corrected overall effect of DRL was an insignificant 30% risk reduction. For multiparty accidents in the dark, the effect of DRL was a significant 71% risk reduction. This is surprising, since it would be fair to assume that DRL primarily would affects accidents in daylight, where cyclists typically do not have lights on. The finding is likely due to participants in the test group having much better lighting at night than participants in the control group—or simply because some cyclists in the control group non-compliantly with the Road Traffic Act did not use lights at night during the experiment.
Copyright (c) 2025 Tove Hels, Tanja Kidholm Osmann Madsen, Michelle Cederstrøm Christensen, Anders Brogaard Tallaksen, Harry Lahrmann https://creativecommons.org/licenses/by/4.0
The maximum allowable handlebar disturbance: an indicator for the ex-ante evaluation of cycling fall prevention interventions
Falls due to disturbances are a common cause of serious cycling injuries, yet evaluation approaches to systematically evaluate interventions aimed at improving balance recovery are lacking. Current ex-post evaluations are hindered by sparse crash data, and existing ex-ante approaches often lack generalizability or rely on surrogate measures that are not validated against fall risk. This study introduces the Maximum Allowable Handlebar Disturbance (MAHD), a novel performance indicator that quantifies the largest handlebar disturbance a cyclist can recover from without falling. The MAHD captures the cyclist's resilience to disturbances and provides a direct, interpretable measure of intervention effectiveness. We propose two methods for determining MAHD: (1) controlled treadmill experiments with induced handlebar disturbances and safe fall conditions and (2) simulations using bicycle dynamics and cyclist control models. Together, these methods allow quantitative ex-ante evaluation and systematic comparison of interventions targeting cyclist control, bicycle design, and infrastructure features such as curbs and road shoulders. With further validation, the MAHD offers practical value for researchers, engineers, and policymakers seeking to design safer bicycles, training programs, and road environments and improve evidencebased resource allocation. In the future, this could reduce fall-related cycling injuries.
Copyright (c) 2026 Marco M. Reijne, Frans C. T. van der Helm, Arend L. Schwab https://creativecommons.org/licenses/by/4.0
The validity of the short driver behaviour questionnaire in varying road users groups in India: age, gender, and driving frequency
The Driver Behaviour Questionnaire (DBQ) is a widely used tool for assessing driving behaviours and their implications for road safety. This study examined the factor structure of the DBQ in an Indian context, where cultural and regulatory conditions may shape aberrant driving patterns differently. Data were collected from 1,665 drivers across multiple states through both online and in-person surveys, with 1,657 valid responses retained after outlier removal. The dataset included 28 DBQ items rated on a 5-point Likert scale, along with demographic variables. Exploratory Factor Analysis (EFA) was conducted to explore alternative two-, three-, and four-factor structures, followed by Confirmatory Factor Analysis (CFA) to evaluate the model fit. EFA suggested a two-factor solution as a simpler data-driven representation; however, it demonstrated weak reliability in one factor and a limited ability to distinguish between constructs. In contrast, the four-factor solution not only explained more variance (37.55%) with balanced reliability across factors, but also aligned with theoretical expectations and prior DBQ research. CFA further confirmed the superiority of the four-factor model, which yielded stronger fit indices (χ²/df = 7.601, CFI = .851, RMSEA = .063) and demonstrated measurement invariance across gender, age, and driving frequency. The four factors—Risky and Rule-Violating Behaviours, Safe and Responsible Driving Practices, Driving Errors and Cognitive Lapses, and Distracted and Emotionally Influenced Driving—offer a robust, culturally adapted framework for understanding driver behaviour in India. This validated structure provides a reliable basis for identifying high-risk behaviours and guiding evidence-based road safety interventions.
Copyright (c) 2025 Rahul Kshatriya, Pooja K M, Yogeshwar V Navandar, K Krishnamurthy https://creativecommons.org/licenses/by/4.0
Determinants of crash numbers and constellations at turbo roundabouts in Germany
Turbo roundabouts are a relatively new design. Thus far, research on their safety has focused on comparisons with other types of intersection and the effects of physical lane dividers. This study investigates crash patterns at German turbo roundabouts, based on a largely complete sample of such roundabouts and detailed data on infrastructure characteristics, traffic volumes and crashes. We calculate the crash rates for turbo roundabouts as a whole, as well as for their individual elements, including entries and exits, and the circulatory roadway. In addition, crash constellations are analysed and crash prediction models are computed, for all crashes and for the two most relevant crash constellations right-of-way and rear-end crashes. The results confirm earlier research findings that turbo roundabouts effectively combine high capacity with high safety levels. The results add new insights, thanks to the more detailed analysis. Entries and right-of-way crashes are most relevant, followed by rear-end crashes which mainly occur at the circulatory roadway. Crash constellations differ significantly between the different elements of the roundabouts, traffic volumes increase crash numbers for all designs and elements. We find no significant effects of the different types of marked lane dividers in our sample, this suggests that drivers do not respect solid lines and that physical dividers are potentially needed to prevent drivers from changing lanes in the circulatory roadway. The detailed analysis of crash patterns in this study enables specific recommendations to be made for improving safety at turbo roundabouts further and exploiting their potential more effectively.
Copyright (c) 2025 Armin Kollascheck, Martin Bärwolff, Julian Schmitz, Justin Geistefeldt, Sebastian Hanteschel, Regine Gerike https://creativecommons.org/licenses/by/4.0
Safe System, Vision Zero, and Sustainable Safety: a scoping review
In this study, we provide a scoping review of the research literature on Vision Zero, Safe System and Sustainable Safety. Using a simplified PRISMA approach, we identify 129 studies, describing what year and where the studies are from, which topics the studies are about, and how the terms are used. Using a thematic analysis of the abstracts of the 129 studies, we identify seven main study topics in the studies. The most prevalent study topics are: 1) Case study/Implementation study, 2) Study on principles, 3) Study on practical/strategic use, 4) Study on "readiness", or factors that inhibit or promote implementation, 5) Vulnerable road users, inequality and social justice, 6) Results of measures and potential, and 7) Future challenges and solutions. We describe knowledge status, knowledge gaps and questions for future research within each study topic. The studies find that entities that have formally implemented the Safe System have relatively low levels of implementation, due to implementation barriers and operationalization challenges. The studies find that it is not necessarily clearly defined what Vision Zero/Safe System is in practice, and that the concept must be interpreted and translated by those who will implement it. Thus, current road safety policies do not fully realise the potential improvements that Safe System can provide, because the principles are not followed to a sufficient extent. A Norwegian study estimate that the number of road fatalities in Norway can be reduced by 50%–70% by following the Safe System principles fully and systematically. Thus, a major challenge, also in mature Safe System contexts, is to facilitate actual Safe System implementation, by mapping barriers/facilitators and Safe System readiness, and defining actions to realise the full potential of Safe System implementation.
Copyright (c) 2025 Tor-Olav Nævestad, Ingeborg Storesund Hesjevoll, Rune Elvik, Øyvind Lothe Brunstad, Jenny Blom https://creativecommons.org/licenses/by/4.0
Using crowdsourced data to assess safety in developing countries: the case study of Eastern Cairo, Egypt
Crowdsourced data refers to data that is collected and shared by a large number of individuals or organizations, often through the use of digital technologies such as mobile devices and social media. The shortage in crash data collection in developing countries makes it difficult to fully understand and address road safety issues in these regions. In developing countries, crowdsourced data can be a valuable tool for collecting crash data and improving road safety, particularly in urban areas where the majority of road crashes occur. This study is the first to develop safety performance functions using crowdsourced data by adopting a Negative Binomial structure model and Full Bayes (FB) model to investigate traffic safety for urban road networks and provide insights into the impact of roadway characteristics. Furthermore, as a part of the safety management process, network screening has been undergone through applying two different methods to rank the most hazardous road segments: Potential Collision Reduction (PCR) method (adopted in the Highway Safety Manual (HSM)) as well as a graphical method using GIS tools to compare and validate. The analysis revealed that segment length, number of lanes, and pedestrian density were significant factors positively associated with crash frequency. FB models with spatial correlation showed better performance in terms of logic and model fit compared to traditional models. The analysis found that both PCR and GIS-based kriging methods effectively identified hazardous segments, with kriging using summation criteria providing more consistent results when validated against PCR outcomes. Recommendations were proposed to improve pedestrian behavior, and control access points and U-turns, based on the observed impact on safety. Lastly, recommendations were suggested for policymakers to ensure safer roads and limitations regarding data coverage and the need for complementary official crash data were highlighted to guide future research.
Copyright (c) 2025 Mahmoud Ahmed Farrag, Ali Zain Elabdeen Heikal, Mohamed Shawky Ahmed, Ahmed Osama Amer https://creativecommons.org/licenses/by/4.0
Investigation on road traffic safety in rural areas using trajectory data: case studies at two measurement sites
Analyses of daily driving patterns and near misses offer valuable insights into road safety, particularly as crashes are expected to become increasingly rare. While research has largely focused on highway and urban environments, rural areas remain underexplored. This study addresses this gap by investigating traffic behavior with a specific focus on safety-relevant scenarios at two rural sites in Germany, located south of Berlin along the Federal Road 179. We collected trajectory data and video material over a two-week observation period at each site. Although no accidents or critical conflicts were observed, several behavioral patterns emerged that may comprise traffic safety. Drivers frequently exceed the speed limits and engaged in overtaking maneuvers at intersections. Additionally, vehicles on the main road often yielded their right of way to avoid potential conflicts with turning traffic. The study further reveals that road users adapt their behavior to existing—yet underdeveloped—infrastructure, posing a potential safety risk. In particular, heavy vehicles such as trucks or motorhomes were observed making turns by crossing oncoming lanes, and vulnerable road users have to use the main road, coming into conflict with motorized traffic. These findings underscore the importance of targeted safety assessment and infrastructure improvements in rural traffic environment to reduce the potential of conflicts between different road users.
Copyright (c) 2025 Lars Klitzke, Claudia Leschik, Richard Lüdtke, Kay Gimm https://creativecommons.org/licenses/by/4.0
Quantifying the upper levels of Hydén's traffic safety pyramid using global data
Hydén's pyramid qualitatively displays the number of conflicts and road user crashes in different severities. Fatal crashes are on the top of the pyramid, undisturbed passages mark the base of it. To quantify the pyramid, open data from the German Accident Atlas and closed data from the Berlin Police have been analysed with respect to time of the week, crash severity, and conflict-type. The data display distinctive weekly patterns that may reflect the traffic state at the hour of the week. Analysing the ratio among these levels for different crash severity levels seems to demonstrate that serious crashes and fatal crashes sometimes follow a different pattern than property-damage-only crashes, or crashes with lightly injured people. A similar result holds true for the conflict-types. This may indicate that their genesis is a mixed bag: sometimes, the mechanisms are different, and sometimes, they are not.
Copyright (c) 2025 Marek Junghans, Andreas Leich, Ronald Nippold, Peter Wagner https://creativecommons.org/licenses/by/4.0
Severity Indices as measurement tools for road safety in mountainous highway sections: case study of the Centinela–La Rumorosa highway
The evaluation of road safety in highway infrastructure requires tools that enable the objective identification and prioritization of risk conditions. This study proposes the development of Severity Indices (SI), a quantitative tool designed to assess the severity level of road segments based on geometric and safety-related variables. Unlike traditional approaches based on qualitative audits, the SI allows for the establishment of severity levels through the integration of measurable and reproducible data. The guiding research question is: How can an index be constructed to quantify the level of road risk based on the physical characteristics of the road and their relationship to crash incidence? To validate the methodology, it was applied to the Centinela–La Rumorosa Highway in Baja California, Mexico—a roadway with high geometric complexity. Variables such as curvature, slope, superelevation, signage, and containment devices were analyzed and correlated with crash records using statistical and spatial analysis in Minitab version 21.1.0. A total of 35 critical points were identified in the descending direction and 28 in the ascending direction, to which SI values were assigned. The results show that this tool allows road safety assessments to be transformed into quantifiable, comparable, and technically informed decision-making processes. The development of the Severity Indices represents a significant methodological contribution to improving road safety evaluation, particularly in contexts where it is necessary to prioritize interventions based on evidence and consistent technical criteria.
Copyright (c) 2025 Itzel Núñez López, Leonel García, Julio Calderón-Ramirez, Marco Montoya-Alcaraz, Manuel Gutiérrez, Alejandro Sánchez-Atondo https://creativecommons.org/licenses/by/4.0
What characterizes bicycle and e-scooter accidents not included in official accident statistics? Lessons learned from the ReCyCLIST project in Agder, Norway
This study explores the characteristics of bicycle, e-bike, and e-scooter accidents that are not included in official Norwegian accident statistics, focusing on findings from the ReCyCLIST project in Agder County. Traditional accident reporting systems overlook most incidents involving vulnerable road users (VRUs), particularly single accidents, which represent the majority of such cases. ReCyCLIST introduced a digital self-reporting tool deployed in hospitals and clinics, collecting 671 accident cases between June 2022 and April 2024. The study analyses 487 incidents that occurred in traffic environments, revealing that 73% were single accidents, predominantly caused by infrastructure issues or loss of balance, rather than collisions. The data also highlight demographic differences in accident patterns by age, gender, and vehicle type. Notably, women were more frequently involved in e-scooter accidents, and men were overrepresented in racing bike collisions. Multivariate analysis shows that vehicle type, especially racing bikes, is a strong predictor of collisions. The findings emphasize the critical role of underreported single accidents and provide actionable insights for urban planning and policy development aimed at improving micromobility safety.
Copyright (c) 2025 Torkel Bjørnskau, Ingeborg Storesund Hesjevoll, Rikke Ingebrigtsen, Katrine Karlsen, Petr Pokorny, Hanne Beate Sundfør, Kjell Vegard Weyde, Odd Mjåland https://creativecommons.org/licenses/by/4.0
How can we integrate road safety into occupational health and safety management ‘to save lives beyond 2025’? A study of safety management among drivers at work
The Academic Expert Group (AEG) recommendations related to the 4th Global Ministerial Conference on Road Safety in 2025, suggests a strategy of ‘Saving Lives Beyond 2025’, through integrating road safety into occupational health and safety management; implementing safety management systems like ISO:39001, or ISO:45001, and through working with safety culture. In this study, we study commitment to road safety and the prevalence of road safety management measures, according to the Safety Ladder approach (Nævestad et al 2018). Based on survey data, we compare professional drivers at work; bus drivers (n = 305) and truck drivers (n = 298) and employees who drive at work who are not professional drivers (‘work drivers’) (n = 355). We also draw on data from qualitative interviews. We find that organizations with work drivers have a lower focus on road safety, and that they have introduced fewer safety management measures, compared to organizations with professional drivers. However, the study also shows that there is still potential for improvement in organizations with truck drivers and bus drivers. These also have an unexploited potential when it comes to implementing effective measures. Multivariate analyses indicate the importance of the Safety Ladder practices, as they influence safety culture, which in turn is related to driving style and accident involvement. Specifying the AEG recommendations into more concrete actionable steps, we suggest specific management practices that organisations can employ, based on the Safey Ladder approach, and specific third-party actions to motivate organisations to implement the management practices.
Copyright (c) 2025 Tor-Olav Nævestad, Jenny Blom, Ingeborg Storesund Hesjevoll https://creativecommons.org/licenses/by/4.0
Lateral shifting behavior of vehicles at horizontal curves and its influencing factors: application of LightGBM and SHAP
Horizontal curves are disproportionately associated with severe crashes due to increased vehicle instability and lane departure risks. This issue is particularly critical in low- and middle-income countries (LMICs), where poor lane discipline, mixed traffic, and geometric inconsistencies amplify crash potential. Despite its significance, lateral shifting (LS) behavior on horizontal curves remains understudied in LMIC contexts. This study addresses the research question: What are the key factors influencing the lateral shifting behavior of vehicles on rural horizontal curves, and how can they be modeled and interpreted effectively in LMIC conditions? Using trajectory data from 8,748 vehicles across 18 curve segments in India, an explainable machine learning framework is developed. Light Gradient Boosting Machine (LightGBM) was selected for its superior performance in classification metrics compared to other ML models. SHapley Additive exPlanations (SHAP) were integrated to interpret model outputs and quantify feature contributions, while Shannon entropy was applied to assess prediction uncertainty. Findings reveal that lane type, vehicle speed, curve radius, lateral clearance, superelevation, and traffic interactions, especially oncoming vehicles, significantly influence lateral shifting behavior. SHAP analysis uncovers nonlinear effects and interaction patterns, including a threshold response to speed and clearance. Notably, the influence of preceding vehicles differs from oncoming traffic, suggesting asymmetric behavioral responses rarely captured in prior studies. This research fills four major gaps in existing literature related to context, terrain, feature scope, and methodology. It provides data-driven insights to support safer curve design and lane departure countermeasures tailored to LMIC road environments.
Copyright (c) 2025 Samrat Debbarma, Wahengbam Ratankumar, Subhadip Biswas https://creativecommons.org/licenses/by/4.0
An investigation of traffic safety knowledge, behaviour and risk perception for schoolchildren: a case study of India
School-going children in India are disproportionately vulnerable to traffic-related injuries due to behavioural, infrastructural, and systemic shortcomings. Despite growing awareness of road safety, a major gap persists in understanding how cognitive and social factors jointly influence children’s safety orientation across different travel modes. This study examines the relationship between risk perception, safety attitudes, observed adult behaviours, and self-reported risky practices among Indian school children aged 12–18 commuting by two-wheelers, cars, auto-rickshaws, school buses, or private/state buses. Using a structured questionnaire, data were collected from 925 students across two Indian states through both online and offline surveys. Descriptive statistics, Exploratory Factor Analysis (EFA), and Multiple Regression Analysis were employed to identify latent constructs and assess the predictive influence of attitudinal, perceptual, and observational factors on children’s safety behaviour. Although most students demonstrated adequate safety awareness, observed adult misbehaviour and permissive risk attitudes significantly predicted unsafe practices. Regression analyses revealed that adult rule violations (β = 0.099–0.307) and limited risk perception explained up to 50% of variance in risky acts. School bus users showed higher behavioural awareness and safer attitudes (β = 0.439), while two-wheeler, auto-rickshaw, and private/state bus commuters displayed greater risk-taking tendencies. The study concludes that children’s traffic safety is shaped by cognitive, social, and environmental factors rather than knowledge alone. Mode-specific, context-sensitive interventions integrating behavioural education, parental and driver involvement, and structured supervision are essential to bridge the gap between awareness and safe action among young commuters.
Copyright (c) 2025 Manjunath Ishwar Borakanavar, Akhilmith V, Hoai Nguyen Pham, Yogeshwar V Navandar, K Krishnamurthy https://creativecommons.org/licenses/by/4.0
How accurate do car driver report their travelled speed before an accident: a comparison with insights of the Event Data Recorder
Statements of drivers are often used to gain insights into accident causations, whose understanding is an important factor for the development of effective prevention strategies. The coming into effect of the General Safety Regulation 2019 led to an increasing availability of objective vehicle data in the form of Event Data Recorders (EDR) in Germany as well as the whole European Union. This creates the possibility to examine the accuracy of the driver statements in more detail. Among others, maladjusted vehicle speed is an important crash contributing factor. Therefore, a good understanding about the quality and applicability of the drivers' reported speed can be important. The goal of the present study is to examine the accuracy of speed reports from German drivers in the context of accident research. To this end, the reported speeds and speed violations were evaluated with respect to their consistency with the EDR data. Additionally, it was investigated whether there is a relationship between the accuracy of the statements and the role in causing the accident on the one hand and the time elapsed between the accident and the report of the driven speed on the other hand. Based on data from the Audi Accident Research Unit (AARU), this study compares drivers' self-reported speeds prior to an accident obtained by standardized telephone interviews with the respective recorded EDR speeds of the crash vehicles. It was shown that driver reported speed violations significantly less often and to a smaller extent than they were committed based on the EDR data. The reported speeds were significantly lower than the recorded speeds from the EDR data. Furthermore, this effect was significantly stronger for the other accident participants, which tended to underestimate their speed more than the accident causers. This result might be explained by a certain group of other accident participants which were driving very fast (> 200 km/h) on the motorway, as is elaborated in detail in the discussion. There was no significant correlation between the accuracy of the reported speed and the timing of the respective interviews. In conclusion, the drivers’ statements regarding the driven speed were found to be relatively inaccurate, which is why they can only be used with caution and in conjunction with more reliable data. Still, the reported speed can be valuable to evaluate the general plausibility of the drivers' statements concerning the accident.
Copyright (c) 2025 Karen Tschech, Thomas Schenk, Daniel Popp, Volker Alt, Stefanie Weber https://creativecommons.org/licenses/by/4.0
The importance of infrastructure and road safety culture for pedestrian safety: a comparison of three European and three African countries
Walking is a primary mode of transport in urban Africa, yet it remains unsafe, challenging, and unpleasant. In contrast, several European countries have implemented systematic policies to promote walking through Safe System principles. This study compares pedestrian safety in three African countries (Tanzania, Ghana, Zambia), with three European countries with excellence in road safety and Safe System implementation (Norway, the Netherlands, Sweden). Data includes focus group interviews with African road users and stakeholders (n = 48), fieldwork, and surveys of pedestrians in the African (n = 753) and the European countries (n = 1109). The aims are to examine: (1) pedestrians' perceptions of infrastructure, traffic situation, and traffic safety culture, (2) pedestrians' accident involvement and (3) factors influencing pedestrians' accident involvement. Our results show that pedestrian safety in the studied African countries is not only related to material factors (e.g. safe system infrastructure); it is also related to cultural factors (e.g. societal status of pedestrians, traffic safety culture). We discuss how policy strategies should address both types of factors. Our results indicate that Safe System implementation in the studied African countries is likely to improve pedestrian safety. However, working with infrastructure is not sufficient; cultural factors, including the sociocultural position of pedestrians, must also be addressed. We also discuss how infrastructure, traffic situation and traffic safety culture are related to larger framework conditions, like urban planning, public transport systems, and economy.
Copyright (c) 2025 Tor-Olav Nævestad, Sonja Forward, Enoch F. Sam, Jaqueline Masaki, Daniel Mwamba, Thomas Miyoba, Filbert Francis, Anthony Fiangor, Jenny Blom, Ingeborg Storesund Hesjevoll, Aliaksei Laureshyn https://creativecommons.org/licenses/by/4.0
TARGET setting for high severity collisions: tolerance-based assessment of risk for generalized event thresholds
Vision Zero represents a road safety approach with aspirations toward eliminating serious and fatal injuries associated with traffic collisions. Given the well-described relationship between speed at impact and injury outcomes, many researchers have used a variety of methodological approaches to develop speed thresholds associated with human injury tolerance levels for serious and fatal injuries. The goal of this study was to present a framework based on state-of-the-art injury risk models using the latest field data and featuring biomechanically-relevant predictors in order to create safe impact speed thresholds. Tolerance-based Assessment of Risk for Generalized Event Thresholds (TARGET) values for safe speeds for several sets of the most commonly observed collision geometries and partners were estimated using previously-developed injury risk models. Consistent with prior literature, an injury tolerance level of 10% risk at the MAIS3+ severity level was evaluated given its association with high severity injury outcomes. Leveraging models built on German collision data for VRUs, the safe impact speed thresholds were 34 kph for pedestrians and 49 kph for cyclists and motorcyclists. Using models built on U.S. collision data for collisions involving passenger vehicles, the thresholds for closing speed were 99 kph for a frontal collision, 73 kph for a near-side collision, and 126 kph for a rear-end collision. The TARGET values established in this study are consistent with those previously developed and can serve as a validation of these previous studies. As an additional demonstrative, we highlighted other factors (increased age and vehicle seating position) that affect serious and fatal injury risk and were associated with decreased safe impact speed thresholds. This study used a data-driven approach, injury risk models with additional biomechanically-relevant predictors, and the most modern collision data to provide a more precise approach to quantify generalized speed thresholds associated with biomechanical tolerance for humans involved in automotive collisions. Given the relationships between speed and injury risk, reducing speed in a collision below these thresholds is key to mitigating serious and fatal injury outcomes. The objective injury risk approach used in this study enables traffic safety practitioners to determine the relative effect of related safety countermeasures on reaching the goals of Vision Zero and a Safe System Approach.
Copyright (c) 2025 Eamon T. Campolettano, John M. Scanlon, Timothy L. McMurry, Kristofer D. Kusano, Trent Victor https://creativecommons.org/licenses/by/4.0
Road safety culture and the Safe System: comparing beliefs and behaviours in African and European countries
The study compares national road safety culture (RSC) in three European countries—Norway, Sweden, and the Netherlands—which are widely recognized as leaders in Safe System implementation and have maintained the world's best road safety records for several years, with three African countries with poorer road safety records—Ghana, Tanzania, Zambia. The primary focus is on continental-level comparisons, to identify the elements of RSC where we see the biggest differences between the African and the European countries. The study is based on survey data collected from car drivers and pedestrians (n = 3772), interviews (n = 46) and fieldwork. The study is explorative, as it examines four different RSC elements. This is important, as there are few other studies comparing RSC across African and European countries, including several transport modes. The elements of RSC where we see the biggest differences between the African and the European countries are: (a) fatalistic beliefs about road safety and (b) the social valuation of walking as a mode of transport, compared with motorized transport. The fatalistic beliefs are related to road safety violations, which in turn are related to accident involvement. Thus, influencing fatalistic beliefs regarding road safety, and increasing the cultural valuation of walking and pedestrians are likely to improve road safety in the African countries. Finally, interviewees in the African countries pointed to corruption as a potential factor impeding the efficiency of enforcement. We have not measured this, but future studies of RSC should also include beliefs and practices related to corruption, as these are likely to be related to the level of road violations.
Extreme value analysis for safety benefit estimation of adaptive cruise control (ACC)
As new automated features enter the automotive market, we need methods to assess their safety in a rapid, proactive, and iterative way. The traditional way of relying on crash statistics does not meet these needs. An alternative is to use extrapolation techniques designed to deal with rare events, such as extreme value theory (EVT). In this paper, we applied EVT to estimate the risk of collision with and without adaptive cruise control (ACC) during steady-state car following. We defined a Bayesian regression model to estimate the parameters of the Weibull distribution for block maxima (BM) of the brake threat number (BTN). We used a small, open-access dataset collected during a platooning experiment on a test track, with and without ACC. We found that it is extremely unlikely that the use of ACC will result in a rear-end crash under normal car-following circumstances, a finding consistent with the general expectation that ACC is safer than manual driving. However, we found that the relative risk of ACC was actually higher than the human control baseline. The reason is that the baseline represents a cautious driving style which may not be typical of the driving style in real traffic. Nonetheless, EVT can measure the expected safety benefit of a vehicle system even without a large dataset. The BTN was an appropriate safety metric to compare automated and manual driving modes, as it accounts for specific brake behavior and performance.
Copyright (c) 2025 Alberto Morando https://creativecommons.org/licenses/by/4.0
Predicting injury severity in vehicle-to-pedestrian collisions: evidence from Madhya Pradesh state, India
The present research examines characteristics of vehicle-to-pedestrian collisions and assesses the factors affecting such crashes in Madhya Pradesh using accident record data from Madhya Pradesh Road Development Corporation and Accident Response System, encompassing 6104 accident entries across 16 variables. To address data heterogeneity, Latent Class Clustering was employed, and a Random Forest Algorithm was used for predictive modelling to accurately classify injury severity based on various predictors. The latent clustering identified three distinct classes: Class 1 (27.7%) associated with fewer severe injuries, attributed to effective traffic controls; Class 2 (8.7%), characterized by reduced injury rates, linked to well-organized traffic systems; and Class 3 (63.5%), which showed a higher incidence of severe injuries, primarily due to narrow, poorly designed, or infrastructure-deficient roads and excessive speeding. The Random Forest Classifier effectively used predictors such as age, gender, violation type, traffic control, and vehicle type, achieving 97.2% precision and 89.2% recall, and an overall accuracy of 88.8%. The Decision Tree model further highlighted the relative importance of each variable in predicting injury severity. The model’s performance was benchmarked against baseline classifiers including logistic regression, Support Vector Machine, and Decision Tree, confirming the superior accuracy and robustness of the Random Forest approach. This study emphasizes the need for proactive road safety measures and provides a robust analytical framework for injury severity classification, supporting the development of targeted interventions to improve pedestrian safety in India.
Copyright (c) 2025 Chinmay Gayan, Bivina G. R., Yogeshwar V. Navandar https://creativecommons.org/licenses/by/4.0
Explaining acceptance and acceptability of connected automated vehicles: the impact of evaluations of attributes and traffic complexity
Connected Automated Vehicles (CAVs) may, when available, be able to reduce greenhouse gasses emissions caused by the transport sector, and may increase traffic safety. In order for CAVs to be adopted by the public, they first need to be accepted (i.e., evaluated positively). Therefore, it is critical to identify the predictors of CAVs’ acceptability (general evaluation before experience) and acceptance (willingness to use after experience). We examined to what extent evaluations of different attributes of CAVs are related to acceptability and acceptance, and to what extent acceptability and acceptance are related. Specifically, we hypothesised that more positive evaluations of safety, trustworthiness, instrumental, and hedonic attributes would be related to higher acceptability before experiencing a CAV, and to acceptance after experiencing a CAV. To be able to assess acceptance, we conducted a driving simulator experiment (N = 46). This enabled participants to experience a CAV in both a low and high traffic complexity scenario, and we could examine to what extent experiencing a CAV influences the evaluation of CAVs. Our results show that experiencing a CAV can enhance perceived safety and trustworthiness of CAVs. Further, both acceptability and acceptance were higher when the CAV was evaluated more positively on the attributes before and after experiencing a CAV, respectively. Safety attributes were more strongly related to acceptability than acceptance, while hedonic and instrumental attributes were more strongly related to acceptance than acceptability. In contrast to our expectations, traffic complexity did not affect acceptance, perceived safety, or trustworthiness of CAVs after the simulated drive. These results suggest that policies aimed at enhancing safety, driving pleasure, trustworthiness of CAVs, and by ensuring that CAVs are able to meet people’s mobility needs could increase both acceptability and acceptance of CAVs.
Copyright (c) 2025 Jorick M. M. Post, Ayҫa Berfu Ünal, Janet L. Veldstra, Dick de Waard, Linda Steg https://creativecommons.org/licenses/by/4.0
Effects of heavy trucks on cyclists during overtaking manoeuvres: a controlled study
Since December 2023, so-called High-Capacity Transport vehicles (up to 34.5 m length) are allowed on parts of the Swedish network of primarily divided roads. Investigations are ongoing under which premises longer HCT vehicles can be allowed on undivided rural roads, where cyclists and other active travellers may be present. On rural roads, overtaking manoeuvres are a frequently occurring encounter between cyclists and motorists. The fear related to dangerous overtakes is a major deterrent to rural cycling, and the aerodynamic load generated especially by large vehicles may pose a danger in that it could affect cyclist stability. To systematically investigate the effects of lateral distance, overtaking vehicle speed and truck length on cyclists stability and perception of discomfort, a controlled study was conducted in a laboratory setting. In a 700 m long tent, 23 experienced road cyclists rode on free rollers while being overtaken by a 16.5 m and a 32.5 m long truck combination at 50 and 80 km/h, with lateral distances of 1 m, 1.5 m and 2 m. Additionally, a reference overtake was run, reflecting a full lane change at reduced speed (16.5 m truck, 50 km/h, 3.5 m). Lateral distance had the largest impact on aerodynamic load and discomfort ratings, followed by speed. The length of the truck only had a minor effect. The cyclists’ lateral position on the rollers was not affected by any of the three factors, but increased slightly from before to during to after the overtaking manoeuvre, regardless of the condition. Based on these findings, a full lane change is recommended when overtaking cyclists. To which extent a speed adaptation is appropriate as compensatory measure needs to be investigated further.
Copyright (c) 2025 Katja Kircher, Sogol Kharrazi, Lennart Cider, Jesper Sandin, Lena Larsson https://creativecommons.org/licenses/by/4.0
Traffic offenses, court charges, and repeated citations among teen drivers with traffic violations
Teen drivers with traffic violations are at high-risk for motor vehicle collisions (MVCs), yet this group is understudied. This study described traffic offenses, court charges (or dispositions), and repeated citations among teen drivers cited for traffic offenses, and examined factors associated with repeated citations. Deidentified traffic citation records for teen drivers ages 15–17, between January 2018 and May 2022, were obtained from Ohio's Franklin County Juvenile Traffic Court in the United States. Frequencies for demographics, traffic offenses, court charges, and repeated citations (e.g., citation tickets) were generated and compared using Chi-square tests and linear mixed models. The final sample included 5 364 unique teen drivers (62.2% were male) with 6232 unique traffic citation tickets (13.9% were repeated citations). The most common traffic offense was speeding (28.5%), while the most frequent court charge was being an adjudicated juvenile traffic offender (38.2%). The likelihood of repeated citations increased by 3.61 (95% CI: 2.76–4.73) per additional year of driver’s age. Males (OR = 1.78; 95% CI: 1.43–2.21) and speeding offenses (OR = 2.29, 95% CI: 1.77–2.96) had higher odds of receiving a repeated citation than their respective counterparts. Males were more likely to be traffic offenders and receive repeated citations compared to females, consistent with established research on sex-related differences in driving behaviors. Speeding, a known risk factor for MVC-related fatalities, was associated with greater odds of repeated citations. Understanding the characteristics of traffic violations is crucial for developing targeted interventions, especially for males and speeding offenders, to promote safe driving and mitigate MVC risk.
Copyright (c) 2025 Priyanka Sridharan, Rebecca J. McAdams, Saroj Bista, Dominique Rose, Corinne Peek-Asa, Jingzhen Yang https://creativecommons.org/licenses/by/4.0
Winter slip-and-fall accidents in Finland: characteristics and views on their prevention
Outdoor falls, such as winter slip-and-fall accidents, represent a substantial pedestrian safety issue in countries with cold and snowy winters like Finland. Such falls are typically not considered traffic accidents nor are they included in traffic safety policy objectives or accident statistics. This survey study aimed to explore experiences of winter slip-and-fall accidents in Finland, estimate their frequency and investigate views regarding their prevention to inform efforts aiming to increase the role of walking. Data was collected with an online survey directed to Finnish residents (n=1,215), which queried the characteristics of slip-and-falls occurring during the winter of 2020–2021, their consequences, and views regarding their prevention. The results suggest that slip-and-falls occur often in Finland, with just over one third of respondents having experienced at least one. Slip-and-falls frequently occurred on yards or pavements and in icy or snowy conditions, and frequently reported contributing factors include unexpected slippery spots on the walking surface, poor winter maintenance and poor footwear traction. Respondents considered improved winter maintenance and using appropriate footwear, such as anti-slip devices, as important ways to prevent falls. The results suggest that the walking during winter in Finland is not safe, and a combination of personal and public measures could result in the most effective strategy to prevent slip-and-falls. The omission of slip-and-fall accidents from traffic safety policy arguably results in a misleading image of pedestrian safety. The results of this study support the inclusion of pedestrian falls as pedestrian single accidents.
Copyright (c) 2025 Johannes Mesimäki, Fanny Malin, Merja Penttinen https://creativecommons.org/licenses/by/4.0
Built environment characteristics and driving speed in 30 km/h zones: a Dutch national analysis
Road authorities are systematically expanding 30 km/h zones to enhance safety. This requires understanding how built environment characteristics are associated with driving speeds, but only a few studies, typically based on small samples, focus on 30 km/h streets. Using a spatial error model, this study examines the relationship between built environment factors and 85th percentile speeds on 47,000 km of Dutch 30 km/h streets (N=159.000). Driving speed and traffic volume data were estimated using floating car data, while built environment characteristics were collected from public sources. The results show that higher driving speeds are associated with greater traffic volumes, longer street lengths, closed pavement, separated bicycle tracks, visually marked bicycle lanes, and longer road sections. Features linked to lower driving speeds include curves, speed humps, raised intersections, exit constructions at zone entrances, narrower carriageways, roadside parking, nearby premises, and higher address densities. Furthermore, the identified interaction effects show that measures like speed humps and raised intersections have greater impacts in high-speed environments (i.e. long and busy streets with closed pavement) but limited effects in low-speed settings. These findings emphasize the need to consider combinations of road design elements and their context-dependent effects to understand driving speed on 30 km/h streets. Out study provides valuable insights into the effectiveness of speed-reduction measures, offering guidance for interventions targeting streets with excessive speeds.
Copyright (c) 2025 Paul Schepers, Werner van Loo, Wouter Mieras, Hans Drolenga, Dick de Waard, Marco Helbich https://creativecommons.org/licenses/by/4.0
Long combination vehicles overtaking cyclists: a field study in regular traffic
Increased cycling, also in rural areas, is important for transitioning to a more sustainable transport system. Also, long combination vehicles (LCVs), in Sweden labelled high-capacity transport (HCT; up to 34.5 m, the previous limit was 25.25 m) can contribute to this goal. If granted access to a larger share of the road network, those trucks can be used more effectively. However, cycling and other active transport on those roads may be negatively impacted. To investigate direct and indirect effects on cyclists when LCVs are using the same road, a study was conducted in real traffic. Nineteen experienced road cyclists rode on a 5 km long rural road segment. Three trucks of different lengths were driven along the same route, instructed to overtake the cyclists where possible and with a full lane change. This generated 175 overtakes by the trucks and 607 overtakes by other traffic. The cyclists reported the overtakes with the trucks to feel safe and found the length of the truck not to be relevant if a full lane change was made while overtaking. The trucks needed more time to overtake than other traffic, and they also waited longer for an overtaking opportunity. In a car-following situation, the clearance of the following vehicles was influenced by the lead vehicle, making it especially important for heavy vehicles to give cyclists a wide berth. Pending further investigations, the conclusion is that for cyclists to feel safe, a full lane change when overtaking should be standard procedure not only for LCVs, but for motorised traffic in general.
Copyright (c) 2025 Katja Kircher, Jesper Sandin https://creativecommons.org/licenses/by/4.0
A hybrid Structural Equation Modeling and Fuzzy-set Qualitative Comparative Analysis framework for using limited samples to relate cycling performance to behavioral traits
The objective of this investigation was to explore a hybrid application of Structural Equation Modelling (SEM) and Fuzzy-set Qualitative Comparative Analysis (FsQCA) to assess the impact of safety-related behavioural traits on the performance of bicyclists using a limited sample of data as a case study. These behavioural characteristics of cyclists are fundamental when specific cyclist groups are targeted for safety countermeasures. The data were collected from individuals who completed a survey and participated in bicycle simulator experiments. Each of the items in the survey aimed to describe how keen the rider is to take risks. The motivation for the study is the recognition that traditional statistical methods have limitations related to the model structure and the type of variables they can analyze, especially where sample sizes are limited. To address these limitations and to estimate complex relationships between variables, SEM can be used to assess the individual effect of each variable on the response variable(s). In the real-world context, however, a combination of variables can affect response variables. To address this issue, this study used the hybrid SEM-FsQCA approach, in which SEM was applied as the first step in analyzing the latent behavioural variables. Then, using the outputs of the previous step, FsQCA was applied to assess the effect of combinations of variables on the performance of cyclists. Based on SEM, none of the factors significantly affected performance, likely due to the low sample size. However, when applying FsQCA, it was observed that combinations of factors significantly affect performance. This hybrid approach was seen to be promising for the case study application and, in that context, to have the potential, even with smaller samples, to significantly contribute to a deep understanding of the safety-related behavioral traits, which can be used in designing targeted countermeasures to improve their safety.
Copyright (c) 2025 Mahsa Jafari, Bhagwant Persaud, Carmelo D'Agostino https://creativecommons.org/licenses/by/4.0
Data-driven high friction surface treatment applications for roadway safety
The Kentucky Transportation Cabinet (KYTC) Highway Safety Improvement Program (HSIP) has been utilizing a data-driven high friction surface treatment (HFST) program as a proven safety countermeasure for wet weather and roadway departure crashes. This report will walk through the origins of the study and the process to identify candidate locations for HFST and development of a pavement friction program. The project has constructed over forty sites in 2023, including a mixture of rural corridor curves, signalized intersection approaches, and limited access freeway ramps. The project utilized a mixture of pavement friction data, pavement resurfacing lists, and specific crash data. The sites are being reviewed to show the benefits through a before and after crash analysis and pavement condition over time based on traffic volumes, weather, and other factors.
Copyright (c) 2025 Austin Obenauf, Mike Vaughn, Ryland Potter, Isaac Briskin https://creativecommons.org/licenses/by/4.0
Come together: an exploration on social driving behaviour of automated vehicles
Interaction between road users is a fundamental part of the traffic system. The advent of automated vehicles (AVs) has given rise to requirements for interactions between AVs and other road users, expressed in high-level terms like ‘demonstrate anticipatory behaviour’, ‘not confusing other road users’, and ‘being predictable and manageable for other road users’. Operationalizing these social driving behaviours requires social science knowledge on human interaction. However, translating social driving behaviour requirements unambiguously to the engineering domain necessitates that social scientists have a rudimentary understanding of the language of engineers (and vice versa). The present study seeks to accommodate interdisciplinary collaboration between social scientists and engineers by providing insight into current AV technological capabilities with regards to social driving behaviour and road safety, and their development in the near future. To this end, an exploratory interview study was performed with 7 engineers with backgrounds in industry, academia, research institutes, and/or vehicle authorities. The engineers provided several real-world examples of implications of AV algorithms on social driving behaviour. Thematic analysis of the interview transcripts resulted in clusters of themes relating to the product development process: requirements (i.e., societal, legal, customers), development (i.e., process, implementation), and evaluation (i.e., assessment, monitoring). Choices made in each of these phases appear to influence the final behaviour of automated vehicles in traffic. Knowledge on social driving behaviour and its impact on traffic safety can guide these choices to ensure safe operation of AVs within the social environment of traffic.
Copyright (c) 2025 Diane Cleij, Rins de Zwart, Reinier J. Jansen https://creativecommons.org/licenses/by/4.0
Evaluating urban intersections: a comparative study of roundabouts versus protected U-turns—which is better?
Effective urban traffic management is a significant challenge in rapidly urbanizing areas with increased vehicular usage, impacting both congestion and safety. Busy cities, like many urban centers, face these issues. Roundabouts, known for their ability to reduce severe crashes, represent a traditional approach to intersection design. However, in high-traffic conditions, roundabouts can become less efficient, leading to increased congestion. Alternatively, protected U-turns, which are a relatively modern approach, are designed to handle high traffic volumes more effectively. They potentially reduce waiting times and improve overall traffic flow but may pose different safety and longitudinal challenges. This study aims to explore these complexities by analyzing the effectiveness of roundabouts and protected U-turns in the context of the unique urban landscape of the Hail City in Saudi Arabia. PTV VISSIM was used for dynamic traffic simulation, providing a realistic representation of traffic patterns in Hail City. Parameters such as vehicle queuing lengths, wait times, and overall intersection capacity are comprehensively evaluated. The simulation settings are adjusted to reflect different traffic densities and patterns, thus ensuring a thorough understanding of the performance of each intersection type under varied conditions. Additionally, various statistical analysis techniques were used to better understand the relationship between the independent and dependent variables. Results showed scenarios of high traffic volume, roundabouts led to longer vehicle queues and increased wait times. On the other hand, protected U-turns exhibited a notable capability to manage high-volume traffic, effectively reducing congestion and improving intersection throughput. This research may contribute to urban traffic management literature, offering insightful guidelines for future intersection design and traffic flow optimization in rapidly urbanizing cities.
Copyright (c) 2025 Nawaf Alnawmasi, Hisham Jashami, Qiuqi Cai https://creativecommons.org/licenses/by/4.0
Bridging the gap: understanding the factors affecting pedestrian safety perceptions in the age of driverless vehicles
he advent of autonomous technologies necessitates a deeper understanding of pedestrian behavior and safety in environments where pedestrians need to interact with driverless vehicles (DV). Our study explores how pedestrians perceive and react to DVs compared with Human-Driven Vehicles (HDV), focusing on objective measures such as gap acceptance (GA) and psychophysiological indicators like Electro-dermal Activity (EDA). Structured in three phases, the study comprises a preliminary questionnaire to gauge public perception, followed by immersive virtual reality (VR) simulations that mimic real-world traffic scenarios within a VR environment, and concludes with a post-experiment survey. The simulation experiment was designed to analyze pedestrian responses to varying traffic scenarios developed using DVs and HDVs, measuring EDA to assess emotional and stress responses leading to changes in the gap acceptance behavior. The study employed hypothesis testing to assess DV's impact on pedestrians' psychophysiological reactions that can lead to changes in pedestrian behavior. This study also explored the effect of education level and perception of pedestrians towards automation technology that may influence outcomes. The analysis of EDA showed higher stress levels in scenarios involving DVs measured using the Galvanic Skin Response component. This result heightened stress response may be attributed to the unpredictability and novelty of DVs. The analysis with gap acceptance (GA) time revealed significant differences in GA times across traffic scenarios. Pedestrians exhibited longer GA times with DVs than HDVs, suggesting cautious crossing behavior. Our results underscore the impact of traffic scenarios on pedestrian behavior and stress levels, highlighting the influence of driverless technology on pedestrian dynamics.
Copyright (c) 2025 Saki Rezwana, Mohammad Razaur Rahman Shaon, Nicholas Lownes, Eric Jackson https://creativecommons.org/licenses/by/4.0
Modeling the effects of drive error and impairment on crash injury severity
Under the safe system approach, drivers will inevitably make mistakes and errors that can contribute to crashes. Driver errors are widely cited as one of the critical reasons for crash occurrence in safety literature. Despite universal acceptance, the discussion of their effects on crash injury outcomes is limited. The primary objective of this study is to quantify the effects of driver errors in the crash injury severity model at urban intersections. To obtain research objectives, driver errors were categorized as sequential events in a driving task. Combinations of driver error categories were created and ranked based on their odds-ratios with injury severity levels. Furthermore, driver impairment was considered in combination with the driver error categories to explore the compounding effects on crash consequences. Multiple ordered logit models were estimated to quantify the effect of driver errors and their interactions with driver impairment on the crash injury levels at uncontrolled, sign-controlled, and signal-controlled intersections. Improved model performance was observed when driver error combinations were modeled along with traditional crash variables. The exploration of multiple model formulations indicated that including driver impairment as an error category can yield informative inferences from both theoretical and modeling perspectives. Appropriate countermeasures were recommended for major contributing factors to improve intersection safety based on modeling results. It is expected that this study can offer specific insights into explanatory variables and help safety professionals to develop effective countermeasures.
Copyright (c) 2025 Mohammad Razaur Rahman Shaon, Xiao Qin, Eric Jackson https://creativecommons.org/licenses/by/4.0
Evaluation of the human interaction with automated vehicles on highways
Human-driven vehicles (HVs) will be interacting with automated vehicles (AVs) at AV market penetrations between 0% and 100%. However, little is known about how HVs interact with AVs. This study addresses knowledge gaps related to how HVs will interact with AVs on highways. The research was conducted in Oregon State University's Passenger Car Driving Simulator. Additionally, a Shimmer3 GSR+ sensor was used to measure participants' galvanic skin response (GSR). Two independent variables (i.e. leading vehicle speed and autonomy) were selected and resulted in a 2x2 factorial design. Participants were also exposed to two hard-braking scenarios: one with a leading HV and one with a leading AV. A post-drive survey included questions about the participant's level of comfort following HVs and AVs. The driving simulator experiment was successfully completed by 36 participants. Results from the linear mixed model show that driver level of stress was 70% higher in hard-brake scenarios involving HVs versus AVs. Of the 78 hard-braking scenarios tested in this study, 10 crashes were observed (4 with an HV, 6 with an AV). Half of the participants involved in a crash with an HV perceived the leading vehicle to be at fault, while all the participants who crashed with an AV blamed themselves for the error. Additionally, drivers over the age of 34.5 were found to give AVs 2% larger headways than HVs, while younger drivers gave AVs 18% smaller headways than HVs. Zero participants above the age of 34.5 years self-reported being ‘unconcerned’ when following an AV in the post-drive survey, while 38% of participants under the age of 34.5 did. This study supports the need for a better understanding of how human drivers will interact with AVs to calibrate human driver models when AV market penetrations are between 0% and 100%.
Copyright (c) 2025 Cadell Chand, Hisham Jashami, Haizhong Wang, David Hurwitz https://creativecommons.org/licenses/by/4.0
Applying model-based recursive partitioning to improve pedestrian exposure models to support transportation safety analyses
Pedestrians are among the most vulnerable road users in urban areas, and their safety is a growing concern for transportation planners and engineers. Pedestrians are at disproportionately high risk for injuries or fatalities in crashes with motor vehicles, highlighting the critical need to address their safety. To address the dangers urban pedestrians face, the relationship between pedestrian crashes and their contributing factors must first be understood. One way to do this is to use statistical models relating pedestrian crash frequency with quantifiable contributing factors, such as land use, demographics, and roadway characteristics. Perhaps the most important of these factors is pedestrian exposure, which is often difficult to obtain because pedestrian volumes are not as widely available as vehicle volumes. Since pedestrian volumes are not available across an entire network, they are often estimated using statistical models—for example, negative binomial (NB) regression—rather than being directly observed. These models are typically a ‘one-size-fits-all’ approach, applying the same model to estimate pedestrian exposure across the entire network. However, relationships between pedestrian exposure and explanatory features—such as population, infrastructure design, and land use context—might differ significantly with respect to the context of an individual location. To address this issue, this paper proposes a model-based recursive partitioning (MBRP) algorithm to develop pedestrian exposure models. The MBRP approach combines traditional statistical methods (e.g. NB regression) with recursive data partitioning techniques commonly found in tree-based machine learning methods. This innovative approach yields a collection of exposure models stratified according to selected input variables with unique relationships between explanatory variables and exposure. The proposed method was tested on pedestrian exposure data from North Carolina significantly improved predictions of pedestrian volumes by approximately 10%. Therefore, the MBRP algorithm presents a promising tool for advancing pedestrian safety analyses in practical applications.
Copyright (c) 2025 Jakob C. Wiegand, Vikash V. Gayah https://creativecommons.org/licenses/by/4.0
Pedestrians' attributions of risk and safety in traffic: case of Türkiye
Pedestrians constitute between 17%–33% of all road traffic deaths depending on the region. For this reason, factors influencing the risky as well as safe behaviours of pedestrians need to be examined. The current study aims to understand risk and safety attributions of this road user group. A total of 254 pedestrians aged between 18 and 68 participated in the study. The participants filled out a demographic information form and Causal Dimension Scale-II (CDSII), which is composed of a qualitative and a quantitative part. CDSII is a self-report measure assessing how individuals evaluate the causes of events in various dimensions. The CDSII was filled out twice by the respondents: once for the riskiest and once for the safest situations experienced as a pedestrian. For 6 out of 9 situations in which pedestrians feel at risk, the most common reason was problematic drivers. Elimination of and decrease in crash risk were the most important reasons for feeling safe in areas separating pedestrians and drivers. The results showed that there is a difference between causal evaluations of risky and safe situations. The findings of this study point out to several points that require attention. One of these is the driver-pedestrian interactions. To overcome this, effective enforcement and well-functioning infrastructural improvements can be suggested.
Copyright (c) 2025 Gizem Findik, Haluk Oğuz Öngören, Bahar Öz https://creativecommons.org/licenses/by/4.0
Surrogate safety evaluation of incorrect pedestrian detection at signalized intersections
The design and operations of signalized intersections are critical for the safety and mobility of all road users. Traditionally, video detection systems have surpassed conventional inductive loops in vehicle detection, offering advantages such as user-friendly interfaces, easy installation, versatile applications, and cost-effective maintenance. Recent technological advancements have expanded the capabilities of video detection systems to include automated pedestrian detection. Pedestrian timing treatment at signalized intersections typically involves two approaches: assuming pedestrian demand during each phase (pedestrian recall operations) or activating pedestrian demand when a button is pressed. Automated Pedestrian Video Detection Systems (APVDS) represent a newer approach where pedestrian calls are automatically initiated upon detecting pedestrians within the detection zone. Both pedestrian push buttons and APVDSs have their pros and cons. While push buttons can cause confusion and incorrect usage among pedestrians, APVDSs theoretically address these issues by autonomously determining pedestrian phase needs. However, challenges arise due to differing pedestrian behaviors compared to vehicles, potentially leading to missed or false calls and unsafe pedestrian actions. This study examines the impact of two APVDS issues: missed pedestrian calls and false pedestrian calls. It also compares the effects of incorrect calls under various operational strategies, including APVDS with and without controller pedestrian recycle, pedestrian recall operations, and push-button operations, with and without pedestrian recycle, across different times of the day to replicate varying vehicular and pedestrian demands. Using Vissim microsimulation software and Surrogate Safety Assessment Model (SSAM), experiments were conducted to replicate field conditions closely. This microsimulation approach enables the measurement and analysis of missed and false calls' impact on surrogate safety measures, providing valuable insights challenging to obtain in real-world conditions. The results contribute to pedestrian traffic signal strategies and enhancing pedestrian safety at signalized intersections in urban environments.
Copyright (c) 2024 Slavica Gavric, Ismet Goksad Erdagi, Aleksandar Stevanovic https://creativecommons.org/licenses/by/4.0
Estimating intersections' near-crash conflicts with the drone-based image-recording data
Recognizing the fact that the information from historical crash data cannot sufficiently reflect the risk level of target intersections under the current driving populations, some traffic safety researchers proposed to use various surrogate measures of safety (SMoS) from either roadside video records or simulation results for estimating near-crash conflicts and performing proactive safety assessment. Along the same line of research but taking advantage of the high-quality drone-based image-recording data (DIRD), this study presents a new effective surrogate variable, named ‘Extra Brake Required to Avoid a Crash’ (EBRAC), which offers a convenient, reliable, and direct tool for traffic professionals to perform the same analyses and risk rankings for resource allocation. The proposed new surrogate variable, featuring its direct relevance to road users’ maneuvers, e.g. braking from high-precision time-varying braking rate information uniquely available from the DIRD, has reflected crash-prone contributors attributed to driving behaviors and intersections’ overall environments. Hence, after proper field calibration, the proposed method based on EBRAC is directly applicable for estimating near-crash conflicts at other intersections in the same region without further adjustment or employing other advanced statistical techniques to integrate the information from multiple safety surrogates. The effectiveness of the proposed method with the new safety surrogate has been evaluated with field data from five intersections and 20 approaches; the results confirm that its performances, evaluated with two popular statistical tests, are either comparable to or better than the two state-of-the-art methods.
Copyright (c) 2025 Yen-Lin Huang, Yen-Hsiang Chen https://creativecommons.org/licenses/by/4.0