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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Yi-Ta Chuang Chih-Wei Yi Yin-Chih Lu Pei-Chuan Tsai |
| Copyright Year | 2013 |
| Description | Author affiliation: Dept. of Comput. Sci., Nat. Chiao Tung Univ., Hsinchu, Taiwan (Yi-Ta Chuang; Chih-Wei Yi) || Ind. Technol. Res. Inst., Hsinchu, Taiwan (Yin-Chih Lu; Pei-Chuan Tsai) |
| Abstract | We propose the i-Traffic system that utilizes crowd sourced data from smartphones for the traffic flow mining by shockwave techniques. Shockwave is the propagation phenomenon of vehicle accumulation or relief on roads between two traffic flows with different speeds. The movement data of vehicles in front of an intersection are collected via smartphones for the shockwave identification. To conquer the low penetration problem when the number of the movement data is low, a folding heuristic is proposed by using traffic light cycle information to virtually increase the penetration of movement data. We implement our system on a client-server architecture and perform a small scale field trial experiment to demonstrate the system capability. Our results showed that our system is able to compute traffic information, including red/green light transition information and vehicle arrival rate with mean absolute errors of 5.0/0.6 seconds and 2.43 vehicles per minute, respectively under a low penetration rate of 1.2%. |
| Starting Page | 917 |
| Ending Page | 922 |
| File Size | 1139159 |
| Page Count | 6 |
| File Format | |
| ISBN | 9780769551173 |
| ISSN | 01903918 |
| DOI | 10.1109/ICPP.2013.109 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2013-10-01 |
| Publisher Place | France |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Vehicles Servers Roads Global Positioning System Equations Smart phones Data mining location-based service crowdsourcing green computing intelligent transportation |
| Content Type | Text |
| Resource Type | Article |
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