Chapter
Jul 2, 2019
Sensing Vehicle Selection Scheme Based on Road Importance in Vehicular Crowdsensing
Authors: Haiyang Yu, Chenyang Liu, Shuai Liu, Yilong Ren [email protected], and Can YangAuthor Affiliations
Publication: CICTP 2019
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.
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Published In
CICTP 2019
Pages: 2224 - 2235
Copyright
© 2019 American Society of Civil Engineers.
History
Published online: Jul 2, 2019
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Authors
Affiliations
Haiyang Yu
Beijing Key Laboratory of Vehicle Road Coordination and Safety Control, Beijing 100191, China; Beihang Univ., Xue Yuan Rd. No. 37, HaiDian District, Beijing 100191, China; Hefei Innovation Research Institute, Beihang Univ., Xinzhan Hi-Tech District, Anhui 230013, China.
Chenyang Liu
Beijing Key Laboratory of Vehicle Road Coordination and Safety Control, Beijing 100191, China; Beihang Univ., Xue Yuan Rd. No. 37, HaiDian District, Beijing 100191, China.
Shuai Liu
Beijing Key Laboratory of Vehicle Road Coordination and Safety Control, Beijing 100191, China; Beihang Univ., Xue Yuan Rd. No. 37, HaiDian District, Beijing 100191, China.
Beijing Key Laboratory of Vehicle Road Coordination and Safety Control, Beijing 100191, China; Beihang Univ., Xue Yuan Rd. No. 37, HaiDian District, Beijing 100191, China; Hefei Innovation Research Institute, Beihang Univ., Xinzhan Hi-Tech District, Anhui 230013, China. E-mail: [email protected]
Can Yang
Hefei Innovation Research Institute, Beihang Univ., Xinzhan Hi-Tech District, Anhui 230013, China.
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ASCE Library Cards let you download journal articles, proceedings papers, and available book chapters across the entire ASCE Library platform. ASCE Library Cards remain active for 24 months or until all downloads are used. Note: This content will be debited as one download at time of checkout.
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