Impact of personalised route recommendation in the cooperation vehicle-infrastructure systems on the network traffic flow evolution

Jianqiang Wang, Wenjuan Zhou, Shiwei Li and Danlei Shan

Journal of Simulation, 2019, vol. 13, issue 4, 239-253

Abstract: Inspired by the prevailing recommendation system application, personalised travel factors are introduced into route recommendation in order to provide more human-oriented travel service. With real-time information provided by the cooperation vehicle-infrastructure systems (CVIS), four real travel factors including distance, grade, time and toll are adopted to construct a route feature vector and an individual traveler preference feature vector, respectively. A novel route recommendation model based on Pearson’s correlation coefficient is formulated. A searching algorithm of all feasible routes is designed that achieves a better balance of time and space complexity. Considering that the traveler has heterogeneity in the numerous ways of using route recommendation information and choosing a satisfactory route, individual compliance with the route recommendation is creatively proposed and used to imitate a day-to-day route choice. A specific simulation with Monte Carlo method is conducted on a test network to show the dynamic evolution features of network traffic flow.

Date: 2019
References: Add references at CitEc
Citations:

Downloads: (external link)
http://hdl.handle.net/10.1080/17477778.2018.1515579 (text/html)
Access to full text is restricted to subscribers.

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:taf:tjsmxx:v:13:y:2019:i:4:p:239-253

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/tjsm20

DOI: 10.1080/17477778.2018.1515579

Access Statistics for this article

Journal of Simulation is currently edited by Christine Currie

More articles in Journal of Simulation from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().