Jam Eyes: A Traffic Jam Awareness and Observation System Using Mobile Phones

Xing Zhang, Haigang Gong, Zongyi Xu, Jinchuan Tang and Bang Liu

International Journal of Distributed Sensor Networks, 2012, vol. 8, issue 12, 921208

Abstract: Traffic jam is a very common and very annoying thing in urban traffic. The most annoying part in traffic jams is not that you have to wait for a long time but that you do not even know how long you have to wait and what causes the traffic jam. However, the pain of being trapped in traffic jams seems to be neglected by existing research works; they put their focuses on either mathematical modeling or optimal routing for those not trapped in traffic jams. In this paper, we propose a traffic jam awareness and observation system using mobile phones. It can tell a driver how many vehicles ahead are trapped in traffic jam and how much time the driver would probably wait. Moreover, it can provide real-time video streams from the head vehicles of the traffic queue so that the driver can see what causes the traffic jam and the progress of handling the traffic jam. The system is environment independen; it can even work when the traffic jam happens in a tunnel. Experiments show that our system can find the head vehicles of the traffic queue and give the queue length accurately, and the video streams coming from the head vehicles reflect the actual situation of the traffic jam basically.

Date: 2012
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Persistent link: https://EconPapers.repec.org/RePEc:sae:intdis:v:8:y:2012:i:12:p:921208

DOI: 10.1155/2012/921208

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