TY  - JOUR
PY  - 2019//
TI  - Human-like car-following model for autonomous vehicles considering the cut-in behavior of other vehicles in mixed traffic
JO  - Accident analysis and prevention
A1  - Fu, Rui
A1  - Li, Zhen
A1  - Sun, Qinyu
A1  - Wang, Chang
SP  - e105260
EP  - e105260
VL  - 132
IS  - 
N2  - Car-following is a common driving behavior which has a significant effect on driver safety and comfort. Although a large number of studies have focused on car-following models for autonomous vehicles (AV) and connected vehicles (CV), car-following models for AV and CV which consider cut-ins in mixed traffic have not been investigated. In this study, a human-like car-following model for AV and CV was developed by examining the effect of cut-in vehicles on car-following behavior and the expectations of drivers. The cut-in position, reaction time, acceleration, and desired distance were investigated on a real freeway in an instrumented vehicle. Corresponding to results from previous studies, the cut-in vehicles maintain a safe distance from the preceding vehicle and a larger distance from the following vehicle to avoid conflict. Analysis of the behavior of the following driver illustrates that in the keeping stages, the reaction time after the cut-in is 0.85 s for the acceleration stimulus and 0.70 s for the deceleration stimulus. These times are shorter than the response time before the cut-in for the acceleration (1.95 s) and deceleration stimuli (1.66 s). The acceleration, rate of increase in the acceleration with the relative speed, and the desired distance are lower after than before the cut-in events. In this paper, a human-like car-following model for cut-in situations is proposed, which is designed for autonomous vehicles. Unlike previous car-following models, the proposed model has a shorter response time and lower deceleration in cut-in situations. The proposed model may help to improve car-following safety, driver comfort, and trust in AVs and CVs.<br><br>Copyright © 2019 Elsevier Ltd. All rights reserved.<p />  <p>Language: en</p>
LA  - en
SN  - 0001-4575
UR  - http://dx.doi.org/10.1016/j.aap.2019.105260
ID  - ref1
ER  -