期刊
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
卷 17, 期 1, 页码 184-194出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TITS.2015.2464707
关键词
Event detection; distributed data fusion; belief function; VANET; V2V and V2I communication; road experiment
资金
- French Government, through the program Investments for the future [ANR-11-IDEX-0004-02]
- Celtic Plus project CoMoSeF (Cooperative Mobility Services of the Future)
One of the main ideas in the area of intelligent transport systems is to use all possible information coming from vehicles and infrastructure, in order to make the system smarter and avoid potentially dangerous situations-collisions, accidents, bottleneck, etc. However, data are sometimes unreliable due to source and communication network quality, leading vehicles or even the whole system to wrong decisions. We present a generic method for detecting dangerous events on the road. To support unreliable data sources, it uses distributed data fusion. Moreover, to deal with network failures, it relies on a self-stabilizing generic distributed algorithm. Our method mixes measurements obtained from vehicle onboard sensors, as well as wireless sensors placed close to the road and connected to road side units. Each vehicle computes how confident it is about a potential dangerous event using both local and remote data. To evaluate our approach, we implemented it using a specific hardware and software platform. Moreover, we instantiated a simple, yet efficient application to detect icy roads, based on temperature measurements. Thanks to both in-lab and actual on-the-road experiments, we demonstrate the possibility to deduce proper results from unreliable data and, consequently, the correctness and usefulness of our approach.
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