摘要：
With the increasing popularity of GPS Systems and vehicle navigation devices, an increasing number of drivers are accustomed to plotting their travel routes through using intelligent navigation devices.For most existing routing methods, the results of path planning are merely depending on urban roads' geographic information, historical travel information or the real-time traffic status provided by traffic information centers.However, since the number of vehicles is continuously increasing in the urban environment, the interaction among vehicles has become one of the most significant factors that affects the travel time.Thus, those existing routing methods are not suitable for the demands of current urban navigation.To address this new challenge, it is necessary to design an improved routing method, which can consider the mutual interactions among urban vehicles.Recently, the Vehicular Ad-Hoc Network (VANET) has been one of the most promising achievements for the development of Intelligent Transportation System (ITS) in terms of vehicular information transmission.In VANET, taking advantage of vehicular onboard network devices and Dedicated Short Range Communications (DSRC) protocol, the vehicles can achieve real-time communication with other vehicles or urban infrastructures.Moreover, vehicles can share their routing planning and retrieve real-time traffic information from the Intelligent Transportation System Center via these communication technologies.Nevertheless, it is still a serious and realistic challenge to make more accurate prediction of vehicles' routing planning when it considers the dynamic changes of future traffic status in road;especially the changes are resulted from the current routing planning.Therefore, this paper proposes a collaborative route planning method (CoRP), which is more rational and adaptable for urban vehicles to plot their travel routes.In this paper, we firstly give an analysis to the vehicle running process and the interactions among vehicles.Based on the above analysis, we draw a conclusion that the travel process of urban vehicles can be converted into a queuing problem.Furthermore, we quantify the interaction among those urban vehicles while they are making travel planning, and then put forward a quantify algorithm to evaluate their interactions.At last, we come up with an optimal method targeting at minimizing total time spend (TTS) for routing vehicles.Given the proposed method, CoRP can reduce the negative influence on each vehicle in the routing process, and can provide more rational and practical routing plans for urban drivers.The simulation shows that CoRP can decrease the number of retarded vehicles on the road by 18%-30%, and reduce the total time spend of all vehicles by 14%-29% when compared to some classical routing methods.Therefore, the proposed CoRP can enhance the collaboration among vehicles, and it is more practical for the real urban environment.%随着智能导航设备的不断普及,越来越多的驾驶员使用智能导航设备来选择自己的行驶路径.现有的选路方法往往采用城市道路地理信息、历史行驶信息以及交通信息中心提供的实时交通状态来进行路径的规划.而城市车辆数目增加使得车辆间的相互作用逐渐成为了影响车辆行驶时间的主要因素之一,现有的选路方法已经无法满足现今城市的导航需求.因此有必要设计一种能够考虑选路车辆间相互作用的新型选路算法来应对这种新的变化.该文首先对车辆运动过程中的相互作用进行了研究,并量化了车辆选路行为对其他车辆的影响,进而提出了一种车联网环境下的城市车辆协同选路方法(Collaborative Route Planning,CoRP).该方法通过收集并分析联网车辆的行驶规划信息,在为车辆提供更适用于实际交通情况的路径规划方案的同时减少车辆选路行为对其它车辆带来的负面影响.仿真实验表明,相较于现有的选路方法,该方法能够提升城市车辆选路的协同性,降低了18%~30%的道路最大滞留车辆数目,并减少了14%~29%的车辆整体行驶时间开销,在很大程度上改善了城市道路拥塞的情况.
