Designing heterogeneous sensor networks for estimating and predicting path travel time dynamics: An information-theoretic modeling approach

With a particular emphasis on the end-to-end travel time prediction problem, this paper proposes an information-theoretic sensor location model that aims to minimize total travel time uncertainties from a set of point, point-to-point and probe sensors in a traffic network. Based on a Kalman filtering structure, the proposed measurement and uncertainty quantification models explicitly take into account several important sources of errors in the travel time estimation/prediction process, such as the uncertainty associated with prior travel time estimates, measurement errors and sampling errors. By considering only critical paths and limited time intervals, this paper selects a path travel time uncertainty criterion to construct a joint sensor location and travel time estimation/prediction framework with a unified modeling of both recurring and non-recurring traffic conditions. An analytical determinant maximization model and heuristic beam-search algorithm are used to find an effective lower bound and solve the combinatorial sensor selection problem. A number of illustrative examples and one case study are used to demonstrate the effectiveness of the proposed methodology.

• Record URL:
  • https://doi.org/10.1016/j.trb.2013.09.007
• Record URL:
  • http://www.sciencedirect.com/science/article/pii/S0191261513001677
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/issn/01912615
• Supplemental Notes:
  • Abstract reprinted with permission by Elsevier.
• Authors:
  • Xing, Tao
  • Zhou, Xuesong
  • Taylor, Jeffrey
• Publication Date: 2013-11

Language

• English

Media Info

• Media Type: Print
• Features: Appendices; Figures; References; Tables;
• Pagination: pp 66-90
• Serial:
  • Transportation Research Part B: Methodological
  • Volume: 57
  • Issue Number: 0
  • Publisher: Elsevier
  • ISSN: 0191-2615
  • Serial URL: http://www.sciencedirect.com/science/journal/01912615

Subject/Index Terms

• TRT Terms: Automatic vehicle identification; Critical path method; Design; Kalman filtering; Mathematical models; Mathematical prediction; Networks; Sensors; Travel time
• Candidate Terms: Transportation sensor systems
• Uncontrolled Terms: Network design
• Subject Areas: Highways; Planning and Forecasting; I71: Traffic Theory;

Filing Info

• Accession Number: 01505006
• Record Type: Publication
• Files: TRIS
• Created Date: Jan 27 2014 10:45AM