Sensing Vehicle Selection Scheme Based on Road Importance in Vehicular Crowdsensing

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. The authors 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.

Language

  • English

Media Info

  • Media Type: Web
  • Monograph Title: CICTP 2019: Transportation in China—Connecting the World

Subject/Index Terms

Filing Info

  • Accession Number: 01712544
  • Record Type: Publication
  • ISBN: 9780784482292
  • Files: TRIS, ASCE
  • Created Date: Jul 2 2019 3:06PM