A Practical and Sustainable Approach to Determining the Deployment Priorities of Automatic Vehicle Identification Sensors
Dongya Li,
Wei Wang and
Zhao De
Additional contact information
Dongya Li: Jiangsu Key Laboratory of Urban ITS, Southeast University, Nanjing 211189, China
Wei Wang: Jiangsu Key Laboratory of Urban ITS, Southeast University, Nanjing 211189, China
Zhao De: Jiangsu Key Laboratory of Urban ITS, Southeast University, Nanjing 211189, China
Sustainability, 2022, vol. 14, issue 15, 1-22
Abstract:
Monitoring vehicles’ paths is important for the management and governance of smart sustainable cities, where traffic sensors play a significant role. As a typical sensor, an automatic vehicle identification (AVI) sensor can observe the whereabouts and movements of vehicles. In this article, we introduced an indicator called the deployment score to present the deployment priorities of AVIs for a better reconstruction of vehicles’ paths. The deployment score was obtained based on a programming method for maximizing the accuracy of a recurring vehicle’s path and minimizing the number of AVI sensors. The calculation process is data-driven, where a random-work method was developed to simulate massive path data (tracks of vehicles) according to travel characteristics extracted from finite GPS data. Then, for each simulated path, a path-level bi-level programming model (P-BPM) was constructed to find the optimal layout of the AVI sensors. The solutions of the P-BPM proved to be approximate Pareto optima from a data-driven perspective. Furthermore, the PageRank method was presented to integrate the solutions; thus, the deployment score was obtained. The proposed method was validated in Chengdu City, whose results demonstrated the remarkable value of our approach.
Keywords: AVI location; random walk; path reconstruction; novel indicator; bi-level programming (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)
Downloads: (external link)
https://www.mdpi.com/2071-1050/14/15/9474/pdf (application/pdf)
https://www.mdpi.com/2071-1050/14/15/9474/ (text/html)
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:gam:jsusta:v:14:y:2022:i:15:p:9474-:d:878399
Access Statistics for this article
Sustainability is currently edited by Ms. Alexandra Wu
More articles in Sustainability from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().