TY - JOUR
T1 - Strategic car-following gap model considering the effect of cut-ins from adjacent lanes
AU - Dou, Yangliu
AU - Ni, Daiheng
AU - Wang, Zhao
AU - Wang, Jianqiang
AU - Yan, Fengjun
N1 - Publisher Copyright:
© The Institution of Engineering and Technology 2016.
PY - 2016/12/1
Y1 - 2016/12/1
N2 - Drivers are typically faced with two competing challenges when following a preceding vehicle: They need to leave sufficient space in front to ensure safety, while doing so the probability of cut-ins by other vehicles increases as the car-following gap (CFG) becomes large. Therefore, a strategic CFG that addresses both challenges becomes critical. This study proposes a method to address the problem through an overall objective function of CFG and velocity considering the safety hazard and the probability of cut-ins by other vehicles. Based on this, seeking the strategic CFG translates to finding the optimal solution that minimises the overall objective function. With the support of field data, the method along with concrete models are instantiated and application of the method is elaborated. The method presented in this study can be used to enhance traffic safety and improve traffic management in a connected vehicle environment that promises cooperative adaptive cruise control and cooperative crash avoidance systems.
AB - Drivers are typically faced with two competing challenges when following a preceding vehicle: They need to leave sufficient space in front to ensure safety, while doing so the probability of cut-ins by other vehicles increases as the car-following gap (CFG) becomes large. Therefore, a strategic CFG that addresses both challenges becomes critical. This study proposes a method to address the problem through an overall objective function of CFG and velocity considering the safety hazard and the probability of cut-ins by other vehicles. Based on this, seeking the strategic CFG translates to finding the optimal solution that minimises the overall objective function. With the support of field data, the method along with concrete models are instantiated and application of the method is elaborated. The method presented in this study can be used to enhance traffic safety and improve traffic management in a connected vehicle environment that promises cooperative adaptive cruise control and cooperative crash avoidance systems.
UR - https://www.scopus.com/pages/publications/85006717885
U2 - 10.1049/iet-its.2016.0149
DO - 10.1049/iet-its.2016.0149
M3 - 文章
AN - SCOPUS:85006717885
SN - 1751-956X
VL - 10
SP - 658
EP - 665
JO - IET Intelligent Transport Systems
JF - IET Intelligent Transport Systems
IS - 10
ER -