Personalized route planning system based on driver preference

Ren Wang, Mengchu Zhou, Kaizhou Gao, Ahmed Alabdulwahab, Muhyaddin J. Rawa

Research output: Contribution to journalArticlepeer-review

Abstract

At present, most popular route navigation systems only use a few sensed or measured attributes to recommend a route. Yet the optimal route considered by drivers needs be based on multiple objectives and multiple attributes. As a result, these existing systems based on a single or few attributes may fail to meet such drivers’ needs. This work proposes a driver preference‐based route planning (DPRP) model. It can recommend an optimal route by considering driver preference. We collect drivers’ preferences, and then provide a set of routes for their choice when they need. Next, we present an integrated algorithm to solve DPRP, which speeds up the search process for recommending the best routes. Its computation cost can be reduced by simplifying a road network and removing invalid sub‐routes. Experimental results demonstrate its effectiveness.

Original languageEnglish (US)
Article number11
JournalSensors
Volume22
Issue number1
DOIs
StatePublished - Jan 1 2022

All Science Journal Classification (ASJC) codes

  • Analytical Chemistry
  • Information Systems
  • Atomic and Molecular Physics, and Optics
  • Biochemistry
  • Instrumentation
  • Electrical and Electronic Engineering

Keywords

  • Crowd sensing
  • Geographic information system
  • Global positioning system
  • Optimization
  • Personalization
  • Preference
  • Route planning

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