Probabilistic Time-Constrained Paths Search over Uncertain Road Networks

Wengen Li, Jihong Guan, Xiang Lian, Shuigeng Zhou, Jiannong Cao

Research output: Journal article publicationJournal articleAcademic researchpeer-review

4 Citations (Scopus)


With the proliferation of positioning technologies and GPS-enabled mobile devices, it has become very important to search for optimal paths to cover required points of interest (POIs, e.g., banks and restaurants) over road networks in many location-based services. In practice, however, traffic conditions are inherently uncertain and dynamically changing over time, which makes it rather challenging to provide accurate results for path queries based on travelling time. Inspired by this, we consider the practical settings of road networks and model them by uncertain road networks (URNs) on which the travelling time of each road is uncertain and captured by a set of travelling time samples. Then, we formalize the probabilistic time-constrained path (PTP) query over uncertain road networks to retrieve those paths that not only cover required POIs with constrained service time but also have the minimum travelling times in high confidence. We prove that PTP query problem is NP-hard. In order to answer PTP queries efficiently, we propose an efficient PTP query approach with effective pruning strategies regarding the time constraints on POIs and the probabilistic/rank requirements of queries. Extensive experiments on real road networks validate the efficiency and effectiveness of our PTP query approach.

Original languageEnglish
Pages (from-to)399-414
Number of pages16
JournalIEEE Transactions on Services Computing
Issue number2
Publication statusPublished - 1 Mar 2018


  • Location-based service
  • path search
  • service time-constrained POI
  • uncertain road network

ASJC Scopus subject areas

  • Hardware and Architecture
  • Computer Science Applications
  • Computer Networks and Communications
  • Information Systems and Management


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