TY - JOUR
T1 - The Effects of Stop-and-go Wave on the Immediate Follower and Change in Driver Characteristics
AU - Wang, Jianqun
AU - Chai, Rui
AU - Xue, Xiaoqing
N1 - Publisher Copyright:
© 2016 The Authors. Published by Elsevier Ltd.
PY - 2016
Y1 - 2016
N2 - The vehicles in the condition of car-following perform different features comparing their motion in free traffic, and the discrepancy reflect driving style, which serves as important part of uncertainly of traffic. Several phenomena and driving characteristics, such as hysteresis in velocity-spacing curve, were found and utilized to improve the understanding of driving and some other safety study. Here we show that the hysteresis phenomenon is discrepant between drivers in stop-and-go waves (a special case of car-following which is relative stable), and the diversity which indicates driver style (such as aggressive and timid) is quantified using some low order car-following models. By calculating driving characteristics and examining the trajectory data in NGSim dataset, we demonstrated the safe distance - which was usually considered adiabatically on velocity - was significantly affected by driving characteristics. We further analyzed statistical properties of driving characteristics in NGSim data, and on eventual we provided a classification method to evaluate security of car-following behavior and to adjust the safe distance for different drivers.
AB - The vehicles in the condition of car-following perform different features comparing their motion in free traffic, and the discrepancy reflect driving style, which serves as important part of uncertainly of traffic. Several phenomena and driving characteristics, such as hysteresis in velocity-spacing curve, were found and utilized to improve the understanding of driving and some other safety study. Here we show that the hysteresis phenomenon is discrepant between drivers in stop-and-go waves (a special case of car-following which is relative stable), and the diversity which indicates driver style (such as aggressive and timid) is quantified using some low order car-following models. By calculating driving characteristics and examining the trajectory data in NGSim dataset, we demonstrated the safe distance - which was usually considered adiabatically on velocity - was significantly affected by driving characteristics. We further analyzed statistical properties of driving characteristics in NGSim data, and on eventual we provided a classification method to evaluate security of car-following behavior and to adjust the safe distance for different drivers.
KW - Drivers characteristics
KW - Minimum car-following distance
KW - Newell
KW - Response time
UR - http://www.scopus.com/inward/record.url?scp=84976447812&partnerID=8YFLogxK
U2 - 10.1016/j.proeng.2016.01.261
DO - 10.1016/j.proeng.2016.01.261
M3 - Conference article
AN - SCOPUS:84976447812
SN - 1877-7058
VL - 137
SP - 289
EP - 298
JO - Procedia Engineering
JF - Procedia Engineering
ER -