@article{ref1,
title="Using vehicular trajectory data to explore risky factors and unobserved  heterogeneity during lane-changing",
journal="Accident analysis and prevention",
year="2020",
author="Chen, Qinghong and Gu, Ruifeng and Huang, Helai and Lee, Jaeyoung and Zhai, Xiaoqi and Li, Ye",
volume="151",
number="",
pages="e105871-e105871",
abstract="This study aims to investigate contributing factors to potential collision risks  during lane-changing processes from the perspective of vehicle groups and explore  the unobserved heterogeneity of individual lane-changing maneuvers. Vehicular  trajectory data, extracted from the Federal Highway Administration's Next Generation  Simulation dataset, are utilized and 579 lane-changing vehicle groups are examined. Stopping distance indexes are developed to evaluate the potential collision risks of  lane-changing vehicle groups. Three mixed binary logit models and three mixed logit  models with heterogeneity in means and variances are established based on different  perception reaction time. Model estimation results show that several variables  significantly affect the risk status of lane-changing vehicle groups, including the  mean values of clearance distance and speed differences between the leading vehicle  in the current lane and the subject vehicle, standard deviations of clearance  distance, and speed differences between these two vehicles, as well as standard  deviations of the speed difference between the subject vehicle and the following  vehicle in the target lane. Interestingly, the influences of the last three  variables differ considerably across the observations and the mean of the random  parameter for standard deviations of clearance distance between CLV and SV is  associated with the mean speed difference between CLV and SV. Since one of the  explanations is individual heterogeneity, personalized designs for advanced driver  assistance system would be an effective measure to reduce the risk.<p /> <p>Language: en</p>",
language="en",
issn="0001-4575",
doi="10.1016/j.aap.2020.105871",
url="http://dx.doi.org/10.1016/j.aap.2020.105871"
}