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Journal of Advanced Transportation
Volume 2017, Article ID 2415312, 9 pages
https://doi.org/10.1155/2017/2415312
Research Article

Modeling Travel Time Reliability of Road Network Considering Connected Vehicle Guidance Characteristics Indexes

MOE Key Laboratory for Transportation Complex Systems Theory and Technology, Beijing Jiaotong University, Beijing 100044, China

Correspondence should be addressed to Jiangfeng Wang; nc.ude.utjb@gnefgnaijgnaw

Received 10 January 2017; Revised 18 February 2017; Accepted 14 March 2017; Published 29 March 2017

Academic Editor: Xiaobo Qu

Copyright © 2017 Jiangfeng Wang et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Travel time reliability (TTR) is one of the important indexes for effectively evaluating the performance of road network, and TTR can effectively be improved using the real-time traffic guidance information. Compared with traditional traffic guidance, connected vehicle (CV) guidance can provide travelers with more timely and accurate travel information, which can further improve the travel efficiency of road network. Five CV characteristics indexes are selected as explanatory variables including the Congestion Level (CL), Penetration Rate (PR), Compliance Rate (CR), release Delay Time (DT), and Following Rate (FR). Based on the five explanatory variables, a TTR model is proposed using the multilogistic regression method, and the prediction accuracy and the impact of characteristics indexes on TTR are analyzed using a CV guidance scenario. The simulation results indicate that 80% of the RMSE is concentrated within the interval of 0 to 0.0412. The correlation analysis of characteristics indexes shows that the influence of CL, PR, CR, and DT on the TTR is significant. PR and CR have a positive effect on TTR, and the average improvement rate is about 77.03% and 73.20% with the increase of PR and CR, respectively, while CL and DT have a negative effect on TTR, and TTR decreases by 31.21% with the increase of DT from 0 to 180 s.