基于安全距离的手动-自动驾驶混合交通流研究
The Mixed Traffic Flow of Manual-automated Driving Based on Safety Distance
摘要 随着汽车技术的发展,道路上自动驾驶的车辆在未来会越来越多,给道路交通带来了巨大影响.本文引入了经典的Gipps安全距离规则,对NaSch模型进行改进,提出了基于安全距离的自动驾驶元胞自动机交通流模型.然后,利用数值模拟的方法研究了自动驾驶车辆对道路交通流的影响,研究获得一些新的结论.第一,通过降低自动驾驶车辆系统的反应时间,可大幅提高道路通行能力,最高可达2倍.第二,当自动驾驶车辆系统的反应时间降到0.5 s以下时,其对道路通行能力的影响可忽略.第三,道路上自动驾驶车辆的比例对道路通行能力和交通拥堵有显著影响.当自动驾驶车辆的比例达到80%时,通行能力可达到全手动驾驶交通流的2倍,交通拥堵可以降低50%.第四,在全自动驾驶的交通流中,增大自动驾驶反应时间会减少交通拥堵.特别是当密度在30~60 veh/km的范围内时作用更为明显,拥堵比例下降最高可达到20%,可以作为一种缓解拥堵的策略.
Abstract:
With the development of vehicle technology, more and more autonomous vehicles appear on street, which will greatly impact on road traffic. This paper improves the NaSch cellular automata model by taking into account the Gipps safe distance algorithm. The traffic flow mixed by manual and autonomous vehicles are studied using numerical simulation method, and several new conclusions are drawn. First, the highway capacity can be dramatically increased, up to twice of the original capacity value, by adjusting the reaction time of the autonomous driving vehicle. Second, the influence of the reaction time on the highway traffic capacity can be ignored, when the value of the reaction time is reduced to 0.5s. Third, the proportion of the autonomous vehicles in traffic has significant impact on the road capacity and traffic congestion. When the autonomous vehicles is 80%, the highway capacity will be twice of the capacity of the traffic flow consisting of only manual vehicles and the traffic congestion can be reduced up to 50%. Fourth, in the fully autonomous driving traffic flow, increasing the autonomous driving reaction time can reduce the traffic congestion. Especially, when the density is in the range of 30~60 veh/km, the congestion can be reduced 20%, which can be used as an important strategy of traffic congestion mitigation.
Author: QIU Xiao-ping MA Li-na ZHOU Xiao-xia YANG Da
作者单位: 西南交通大学交通运输与物流学院,成都610031; 西南交通大学综合交通运输智能化国家地方联合工程实验室,成都610031; 西南交通大学综合运输四川省重点实验室,成都610031 西南交通大学交通运输与物流学院,成都,610031 西南交通大学交通运输与物流学院,成都610031; 西南交通大学综合交通运输智能化国家地方联合工程实验室,成都610031
年,卷(期): 2016, 16(4)
分类号: U491.2
机标分类号: U49 O39
在线出版日期: 2016年9月8日
基金项目: 国家自然科学基金/National Natural Science Foundation of China (51278429,51408509);成都市科技局项目/Science and Technology Bureau of Chengdu(2014RK0000056ZF);四川省科技厅项目/Science and Technology Department of Sichuan Province(2014-RK00-00072-ZF);中央高校基本业务经费/Fundamental Research Funds for the Central Universities