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Traffic Jams Detection based on the GPS Trajectories Extracted from Volunteered Geographic Information
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Vahid Shokri   , Rahim Ali Abbaspour * |
| University of Tehran |
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Abstract: (3874 Views) |
| Despite the benefits of fixed sensors to collect traffic data such as quality and accessibility, factors such as dependence on equipment, lack of full coverage, the high cost of data collection, management and analysis revealed the need to develop proper infrastructure. Increasing advances in volunteer geographic information (VGI) and location-aware technologies opens new dimension to collect and publish traffic data in high volume with lower costs. Therefore, developing a system to facilitate the collection, extraction, and dissemination of traffic information by utilizing VGI was considered, but given the extent of the issue, this paper focuses on providing strategies to extract traffic jam from GPS trajectories. First in pre-processing stage, trajectories are being cleaned and irrelevant data will be removed. Then ST-matching algorithm GPS trajectories match on road network are being used. After calculating the average speed between each two consecutive points, traffic jams were determined by comparing the free-flow speed and roads network speed. In order to test and evaluate the system, GPS trajectories which is collected voluntarily by taxis between 2nd to 8th of February 2008 in Beijing, is being used. For example, results of traffic jam in the period of 16-16: 20, indicates that most of the main roads and connecting links experiencing traffic jam and this is due to the transfer of traffic from the city center and working areas to residential areas. Results of this paper show that with the appropriate participation of users in producing VGI even with low penetration rate (8/3%) traffic jam could be determined in big cities with a road network about 72720 segments with lower cost and without need of special equipment with an appropriate accuracy. |
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| Keywords: traffic data, volunteer geographic information (VGI), GPS trajectories, traffic jam |
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Full-Text [PDF 1617 kb]
(2022 Downloads)
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Type of Study: Research |
Subject:
GIS
Received: 2016/07/22 | Accepted: 2017/03/5 | Published: 2018/01/10
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