摘要
根据对实时路况的数据处理方式,常见的动态路径规划策略可分为瞬时阻抗T-SPF和平均阻抗A-SPF两种方式。如何验证这些策略的个体效益及其对城市路网的中长期影响一直是相关系统部署的核心问题。针对这一问题,通过Vissim的Car2X模块与自定义程序实现了仿真中的动态转向,并以现实路网为蓝本,对T-SPF和A-SPF在不同程度的市场占有率情况下的运行性能进行了测试。测试结果表明2种现有策略都存在各自的问题;当市场占有率达到15%以上时,T-SPF策略可能令路网的通行容量处于振荡状态,而实施了A-SPF的路网的平均延误和通行量表现稳定,但在个体效益方面表现还不如静态策略。建议为城市路网实施路径规划时设计新的策略以及与之匹配的信号优化机制。
Traditional strategies of dynamic route planning can be divided into Transient-value-based Shortest-Path- Finding (T-SPF) and Average-value-based Shortest-Path-Finding (A-SPF) in term of processing for real-time traffic con-ditions. It is significant for traffic management departments to know how to balance individual benefits and long-term im- pacts of these strategies. To this end〉 a series of situations based on actual road networks are simulated. Vissim Car2X module and customized programs are applied to achieve dynamic steering during the simulations. The results show that the performances of T-SPF and A-SPF under different levels of market share have their own problems. When the market share is higher than 15%,the T-SPF strategy may cause an oscillatory state in traffic capacity of urban road networks. The A-SPF strategy can achieve stable performance in average delay and traffic throughput of road networks under the same conditions. However, it shows poor performance in individual benefit. Suggestions for solving these problems are coordination of a new route planning strategy, and enhancement of an adaptive signal control policy.
出处
《交通信息与安全》
CSCD
2017年第3期90-97,共8页
Journal of Transport Information and Safety
基金
国家自然科学基金项目(51138003)资助
关键词
智能交通
城市路网
路径规划策略
微观交通仿真
车载导航
自动驾驶汽车
intelligent transportation
urban road networks
route planning strategy
microscopic traffic simula-tion
in-vehicle navigation
autonomous vehicle