A New Approach for Real-Time Traffic Delay Estimation Based on Cooperative Vehicle-Infrastructure Systems at the Signal Intersection

被引:0
作者
Haiqing Liu
Laxmisha Rai
Jianchun Wang
Chuanxiang Ren
机构
[1] Shandong University of Science and Technology,College of Transportation
[2] Shandong University of Science and Technology,College of Electronics, Communication and Physics
来源
Arabian Journal for Science and Engineering | 2019年 / 44卷
关键词
CVIS; Traffic delay; Benchmark vehicle; Webster model; Markov model;
D O I
暂无
中图分类号
学科分类号
摘要
Confined by the real-time and accuracy of traditional traffic collecting parameters, the existing traffic delay estimation models are generally with poor performance in guiding practical applications. In the Cooperative Vehicle-Infrastructure System, the real-time entire space-time driving state information of a single intelligent vehicle provides new data supporting for road traffic status evaluation. Fully extracting the value of this kind of new data, this paper proposes a new real-time traffic delay estimation method based on the Webster signalized intersection delay model. Taking each intelligent vehicle as a benchmark point, the vehicle arriving/leaving characteristics of the signalized intersection are spatially interpolated by the stopping state of a small amount of benchmark vehicles. In order to obtain the critical queuing dissipation point, the linear fitting method is used to forecast the critical stopping time and further the Markov model is used to estimate the number of queuing vehicles at the critical stopping time. Based on the real-time vehicle queuing characteristics, a new traffic delay estimation model is built according to the Webster estimation mechanism. The case study shows that, compared with the traditional Webster model, the proposed method can effectively improve the traffic delay estimating accuracy.
引用
收藏
页码:2613 / 2625
页数:12
相关论文
共 87 条
[1]  
Saguesa JA(2015)Sensing traffic density combining V2V and V2I wireless communications Sensors 15 31794-31810
[2]  
Barrachina J(2016)Analysis of traffic stream characteristics using loop detector data Jordan J. Civil Eng. 10 403-416
[3]  
Fogue M(2016)Application of aggregated lane traffic data from dual-loop detector to crash risk evaluation J. Tongji Univ. 44 1567-1572
[4]  
AI-Jameel HAE(2017)Multi-loop inductive sensor model for vehicle traffic application Sens. Actuators A Phys. 263 580-592
[5]  
AI-Jumaili MAH(2018)Roadside magnetic sensor system for vehicle detection in urban environments IEEE Trans. Intell. Transp. Syst. 19 1365-1374
[6]  
Yang K(2016)Fuzzy model of vehicle delay to determine the level of service of two-lane roads Expert Syst. Appl. 54 48-60
[7]  
Yu RJ(1963)Settings for fixed-cycle traffic signals J. Oper. Res. Soc. 14 373-386
[8]  
Wang XS(2017)Review of delay parameter acquisition at the signalized intersection J. Chongqing Jiaotong Univ. (Nat. Sci.) 36 90-97
[9]  
Lamas-Seco J(2015)Improved AODV routing protocol based on restricted broadcasting by communication zones in large-scale VANET Arab. J. Sci. Eng. 40 857-872
[10]  
Castro PM(2016)A data transmitting scheme based on improved AODV and RSU-assisted forwarding for large-scale VANET Wirel. Pers. Commun. 91 1489-1505