Impact Of Guidance Information On Travel Time Reliability Of Road Network In Connected Vehicle Environment

Travel time reliability of road network (TTR) is one of the important indexes to effectively evaluate the performance of road network. Providing real-time traffic guidance information can help travelers make more reasonable travel plans and achieve the equilibrium distribution of the network traffic in time and space, which can effectively improve the TTR. Compared with traditional traffic guidance system, connected vehicle guidance system (CVGS) can provide travelers with more timely and accurate travel information in transit by using vehicle to vehicle (V2V) communication and vehicle to infrastructure (V2I) communication. Therefore, CVGS can help fully perform its effect and further improve travel efficiency of road network. In a word, studying the impact of connected vehicle guidance information on TTR is of important significance to improve the quality of travel.The impact of connected vehicle guidance information on TTR was studied from two aspects including statistical characteristics and sensitivity by conducting simulation experiments. And the travel time reliability model in connected vehicle environment (TTR-CV model) was established. Firstly, the domestic and foreign studies about travel time reliability, travel time reliability in traffic guidance information environment and travel time reliability in connected vehicle environment were summarized. Based on these existing research results, the main research contents of this paper were put forward. Secondly, the concept, type and basic theory of traditional traffic network guidance system were introduced. Besides, the key technology of connected vehicle guidance system and simulation technology of connected vehicle guidance were analyzed in detail. Then, the basic theory of travel time reliability was summarized. And the influence factors of the travel time reliability in connected vehicle were analyzed.Through the analysis of the general network system reliability model, and in view of the deficiency of the traditional travel time reliability model, improved travel time reliability modeles were proposed. At the same time, considering the influence of connected vehicle characteristics on traveler’s route choice behavior, the route choice behavior model in connected vehicle environment (RCB-CV model) was established. Later, based on improved travel time reliability modeles and RCB-CV model, the TTR-CV model was designed. Finally, based on the empirical analysis of simple road network, the connected vehicle guidance simulation scenario was constructed by using EstiNet simulation software. And the impact of connected vehicle guidance information on TTR was studied from two aspects including statistical characteristics and sensitivity. Moreover, the prediction accuracy of TTR-CV model was analyzed.The results show that there is a difference between TTR in ordinary scenarios (without connected vehicle guidance) and TTR in connected vehicle guidance scenarios. Compared to the ordinary scenarios, the TTR in connected vehicle guidance scenarios was improved by 75.70% in general; By conducting sensitivity analysis, it is clearly that congestion level (CL), market penetration rate (PR), compliance rate (CR), following rate (FR) and delay time of guidance information release (DT) all have an impact on TTR. Under the impact of these five connected vehicle characteristic indexes, the maximum improved proportion of TTR were 182.74%,134.04%,135.31%,47.67% and 109.66% respectively; The root mean square error of TTR-CV model prediction is 3.21%, which means the TTR-CV model has a better prediction effect.