Crowd-Sensing Enhanced Parking Patrol Using Sharing Bikes’ Trajectories
نویسندگان
چکیده
Illegal vehicle parking is a common urban problem faced by major cities in the world, as it incurs traffic jams, which lead to air pollution and accidents. The government highly relies on active human efforts detect illegal events. However, such an approach extremely ineffective cover large city since police have patrol over entire roads. massive high-quality sharing bike trajectories from Mobike offer us unique opportunity design ubiquitous detection approach, most of events happen at curbsides significant impact users. result can guide schedule, i.e., send policemen region with higher risks, further improve efficiency. Inspired this idea, three main components are employed proposed framework: 1) trajectory pre-processing , filters outlier GPS points, performs map-matching, builds trajectory indexes; 2) xmlns:xlink="http://www.w3.org/1999/xlink">illegal detection models normal trajectories, extracts features evaluation utilizes distribution test-based method discover events; 3) xmlns:xlink="http://www.w3.org/1999/xlink">patrol scheduling leverages reference context, scheduling task multi-agent reinforcement learning police. Finally, extensive experiments presented validate effectiveness detection, well improvement
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ژورنال
عنوان ژورنال: IEEE Transactions on Knowledge and Data Engineering
سال: 2023
ISSN: ['1558-2191', '1041-4347', '2326-3865']
DOI: https://doi.org/10.1109/tkde.2021.3138195