@inproceedings{f011854fa93345bfaf71279670109ac0,
title = "Sensing vehicle selection scheme based on road importance in vehicular crowdsensing",
abstract = "Vehicular crowdsensing has attracted lots of attentions due to its low cost and timeliness for urban sensing applications such as traffic estimation. It is of great importance for a vehicular crowdsensing system to recruit a limited number of vehicles to achieve a maximum sensing coverage and get useful traffic data of roads. It is challenging due to the unpredictable behaviors of vehicles. In this paper, an efficient vehicle recruiting scheme is proposed based on the road importance in road network. We evaluate the performance of the proposed algorithm through detecting the traffic jam of the road network, which is implemented by simulation. The results demonstrate that the proposed algorithm outperform existing algorithms on the coverage and improving the road network detection accuracy.",
keywords = "Crowdsensing, Road network detection, Sensing vehicle selection, Traffic simulation",
author = "Haiyang Yu and Chenyang Liu and Shuai Liu and Yilong Ren and Can Yang",
note = "Publisher Copyright: {\textcopyright} ASCE.; 19th COTA International Conference of Transportation Professionals: Transportation in China - Connecting the World, CICTP 2019 ; Conference date: 06-07-2019 Through 08-07-2019",
year = "2019",
doi = "10.1061/9780784482292.194",
language = "英语",
series = "CICTP 2019: Transportation in China - Connecting the World - Proceedings of the 19th COTA International Conference of Transportation Professionals",
publisher = "American Society of Civil Engineers (ASCE)",
pages = "2224--2235",
editor = "Lei Zhang and Jianming Ma and Pan Liu and Guangjun Zhang",
booktitle = "CICTP 2019",
address = "美国",
}