Discovering Congested Routes Using Vehicle Trajectories in Road Networks

Author:

Bok Kyoung Soo1,Li He2,Lim Jong Tae1,Yoo Jae Soo1

Affiliation:

1. School of Information and Communication Engineering, Chungbuk National University, 52 Naesudong-ro, Chungbuk, Seowon-Gu, Cheongju 362-763, Republic of Korea

2. School of Software, Xidian University, No. 2 South Taibai Road, Xi’an City, Shaanxi 710071, China

Abstract

The popular route recommendation and traffic monitoring over the road networks have become important in the location-based services. The schemes to find out the congested routes were proposed by considering the number of vehicles in a road segment. However, the existing schemes do not consider the features of each road segment such as width, length, and direction in a road network. Furthermore, the existing schemes fail to consider the average moving speed of vehicles. Therefore, they can detect the incorrect density routes. To overcome such problems, we propose a new discovering scheme of congested routes through the analysis of vehicle trajectories in a road network. The proposed scheme divides each road into segments with different width and length in a road network. And then, the congested road segment is detected through the saturation degree of the road segment and the average moving speed of vehicles in the road segment. Finally, we compute the final congested routes by using a clustering scheme. The experimental results have shown that the proposed scheme can efficiently discover the congested routes in the different directions of the roads.

Funder

Ministry of Science, ICT and Future Planning

Publisher

Hindawi Limited

Subject

General Computer Science

Cited by 3 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Discovering traffic congestion through traffic flow patterns generated by moving object trajectories;Computers, Environment and Urban Systems;2020-03

2. Real time analytics of urban congestion trajectories on hadoop-mongoDB cloud ecosystem;Proceedings of the Second International Conference on Internet of things, Data and Cloud Computing;2017-03-22

3. Analyzing and Modeling Spatial Factors for Pre-decided Route Selection Behavior: A Case Study of Fire Emergency Vehicles of Allahabad City;Advances in Intelligent Systems and Computing;2015-10-25

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