Cumulative lateral position: a new measure for driver performance in curves
DOI:
https://doi.org/10.55329/xmls1738Keywords:
curve design, curve, driving, geometry, lateral control, measure, SDLPAbstract
Vehicle control can be described with lateral and longitudinal control measures. The Standard Deviation of Lateral Position (SDLP) is probably the most common measure to reflect lateral control. Indices such as mean Lateral Position (MLP) and Time-to-Line Crossing (TLC) have also been used to describe driver behaviour. Even though all these measures have demonstrated their value, in some specific cases, these measures may indicate that driver behaviour is deteriorated while that may not necessarily be the case. When negotiating curves for example, most drivers prefer to not to follow the centre of the lane. We propose a new index, called the Cumulative Lateral Position (CLP), an index that does not suffer from drawbacks of the earlier mentioned measures in these conditions. We also applied the CLP in a practical case. In a simulator experiment drivers negotiated three types of curves: traditional circular (CIR), clothoid (CLO), and a new curve, a polynomial curve with continuous curvature (CON). Results show that the CLP index, unlike the older measures, is able to well summarise the trajectory on a road curve and is sensitive in distinguishing different driving behaviour with respect to variations in road geometry, even in cases where these differences are small. The proposed methodology can be used to evaluate both new and existing roads design solutions, and showed in this experiment that driving behaviour was safest in the continuous curve.
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Author Biographies
Nicola Bongiorno, University of Messina, Italy
Nicola Bongiorno currently works for Anas, an Italian road infrastructures management company. He received his master degree in Civil Engineering from the University of Messina and his Ph.D. from the University Mediterranea of Reggio Calabria. The present manuscript is based on work he did while he was a visiting scientist at the University of Groningen. His research focuses on human factors and road user behaviour.
CRediT statement: Conceptualization, Data Curation, Formal analysis, Investigation, Methodology, Software, Writing—original draft, Writing—review & editing.
Orazio Pellegrino, University of Messina, Italy
Orazio Pellegrino is a professor in ‘Construction of Roads, Railways and Airports’, specialised in road safety. Recently, his research focused also on visual behaviour of drivers in real and simulated environments.
CRediT statement: Conceptualization, Data Curation, Formal analysis, Methodology, Visualisation, Writing—original draft, Writing—review & editing.
Arjan Stuiver, University of Groningen, the Netherlands
Arjan Stuiver, PhD, is a traffic researcher at the Traffic Psychology group in the Clinical and Neuropsychology department at the University of Groningen in the Netherlands. He obtained his MSc. in Artificial Intelligence and has a Ph.D. in Behavioural and Social Sciences. As a researcher he uses driving and cycling simulation to study traffic safety and road user behaviour.
CRediT statement: Conceptualization, Data Curation, Investigation, Methodology, Software, Writing—review & editing.
Dick de Waard, University of Groningen, the Netherlands
Dick de Waard is a professor in ‘Traffic Psychology and the retention of Mobility’. He is specialised in human behaviour in surface transportation and aviation. He is experienced in the study of dual task performance, effects of Advanced Driving Assistance Systems, the detection of impaired driving, and human error.
CRediT statement: Conceptualization, Formal analysis, Investigation, Methodology, Supervision, Writing – Original Draft, Writing - Review & Editing.
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Copyright (c) 2022 Nicola Bongiorno, Orazio Pellegrino, Arjan Stuiver, Dick de Waard
This work is licensed under a Creative Commons Attribution 4.0 International License.
