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What factors influence driver behaviour characteristics when pedestrians cross the road? Insights from the UDRIVE naturalistic driving study

  • Silvia F. Varotto*
  • , Girish Kumaar Srinivasan Ravi Kumar
  • , Ruomei Liu
  • , Matheus H.W. Stratermans
  • , Reyzha Wikki Zaninshi
  • , Eleonora Papadimitriou
  • , Meng Wang
  • *Corresponding author for this work

Research output: Contribution to journal › Article › Scientific › peer-review

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Abstract

In urban areas, drivers frequently interact with vulnerable road users. On-road studies have shown that drivers are more likely to have safety-relevant interactions with pedestrians when they are inattentive and when pedestrians behave unexpectedly. Notwithstanding these behavioural effects, most microscopic traffic flow models do not accurately describe driver response to pedestrian crossing behaviour. This study investigates the factors influencing driver behaviour characteristics when pedestrians cross the road in front of the vehicle. The data were collected in the UDRIVE naturalistic driving study in France and the UK. The interactions with pedestrians in daylight were identified using the MobilEye® smart camera. The minimum time to zebra and the maximum deceleration during each interaction were investigated in regression models. The results showed that, controlling for the initial speed of the subject vehicle, the minimum time to zebra during interactions was significantly shorter when the pedestrian crossed while the driver had a green traffic light, the vehicle segment was medium, and other pedestrians had already crossed. Controlling for initial speed and acceleration, the maximum deceleration during interactions was lower when the pedestrian crossed while the driver had a green traffic light, no other pedestrians had already crossed, the pedestrian was not a child, teenager or elderly person, and the pedestrian did not glance toward the vehicle. These factors can be incorporated into traffic simulations to describe driver responses more realistically. Further research is needed to understand the influence of the driver’s state because most drivers looked toward pedestrians.

Original languageEnglish
Article number102013
Number of pages14
JournalTransportation Research Interdisciplinary Perspectives
Volume37
DOIs
Publication statusPublished - 2026

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 11 - Sustainable Cities and Communities
    SDG 11 Sustainable Cities and Communities

Keywords

  • Driver behaviour
  • Naturalistic driving
  • Pedestrians
  • Regression model

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