摘要
为了探究车辆跟驰中车头间距与速度的关系函数,采用高精度车载GPS设备获取了大量基于时间序列的车辆跟驰数据,根据实测车头间距—平均速度关系构建了改进的优化速度函数.对原优化速度函数和改进的优化速度函数进行了参数标定,并对两个函数进行了微观向宏观交通参数的推导,结果表明,改进的优化速度函数能更好地描述车辆跟驰中微观和宏观交通参数之间的关系.最后对基于两种函数的全速度差跟驰模型进行了数值模拟,结果表明,基于改进的优化速度函数的跟驰模型具有更好的稳定性.
To research the numerical relationship between headway and speed,field data of car-following is gathered by vehicles equipped with high precision GPS,and a Modified Optimal Velocity model（M-OVM for short） is built based on the field data.The original OVM and the M-OVM are calibrated and extended to the macroscopic parameters,the result shows that the M-OVM can describe the relationship of traffic parameters with a higher accuracy.Furthermore,simulations are conducted to analyze the characteristics of the car-following model with the M-OVM,the result shows that the M-OVM can improve the stability of the car-following model.
作者
杨龙海
赵顺
徐洪
YANG Long-hai ZHAO Shun XU Hong(School of Transportation Science and Engineering, Harbin Institute of Technology, Harbin 150090, China Shenzhen Urban Transport Planning Center, Shenzhen 518021, Guangdong, China)
出处
《交通运输系统工程与信息》
EI
CSCD
北大核心
2017年第2期41-46,67,共7页
Journal of Transportation Systems Engineering and Information Technology
关键词
城市交通
跟驰模型
非线性回归
优化速度函数
交通流理论
urban traffic
car-following model
nonlinear calibration
optimal velocity model
traffic flow theory
