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Smart city article details
| Title | Etcs: An Efficient Traffic Congestion Scheduling Scheme Combined With Edge Computing |
|---|---|
| ID_Doc | 24476 |
| Authors | Cao A.; Fu B.; He Z. |
| Year | 2019 |
| Published | Proceedings - 21st IEEE International Conference on High Performance Computing and Communications, 17th IEEE International Conference on Smart City and 5th IEEE International Conference on Data Science and Systems, HPCC/SmartCity/DSS 2019 |
| DOI | http://dx.doi.org/10.1109/HPCC/SmartCity/DSS.2019.00378 |
| Abstract | Traffic congestion will not only cause major economic losses to the city, but also cause environmental pollution. Efficient traffic congestion scheduling is one of the key technologies for intelligent transportation. This work presents an efficient traffic congestion scheduling scheme (ETCS), which combined with edge computing. In this scheme, firstly, we designed a ITS architecture combining edge computing, which migrate computing and storage tasks from the cloud to the edge of the network, so as to meet the characteristics of low latency in computing and transmission; Secondly, we propose a method to actively detect and distribute traffic accidents, which improves the response efficiency of congestion processing; Finally, we propose a re-routing algorithm based on probabilistic selection function, which combines the low latency and real-time decision of the edge computing to quickly calculate new alternative routes for vehicles in the congestion area so as to optimize the overall road network condition. Simulation results show the effectiveness of ETCS. When compared to original vehicular mobility trace, the system reduced the average travel time in approximately 39% and the overall CO-2 emissions in 18%. © 2019 IEEE. |
| Author Keywords | edge computing vehicle re-routing; vehicle ad hoc network |
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