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Sensors 2017, 17(12), 2822; doi:10.3390/s17122822

Heterogeneous Data Fusion Method to Estimate Travel Time Distributions in Congested Road Networks

1,2,3,* , 3
State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan 430072, China
Collaborative Innovation Center of Geospatial Technology, Wuhan 430079, China
Department of Civil and Environmental Engineering, The Hong Kong Polytechnic University, Hong Kong 999077, China
Shenzhen Key Laboratory of Spatial Smart Sensing and Services, Shenzhen University, Shenzhen 518060, China
Authors to whom correspondence should be addressed.
Received: 2 November 2017 / Revised: 28 November 2017 / Accepted: 5 December 2017 / Published: 6 December 2017
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Travel times in congested urban road networks are highly stochastic. Provision of travel time distribution information, including both mean and variance, can be very useful for travelers to make reliable path choice decisions to ensure higher probability of on-time arrival. To this end, a heterogeneous data fusion method is proposed to estimate travel time distributions by fusing heterogeneous data from point and interval detectors. In the proposed method, link travel time distributions are first estimated from point detector observations. The travel time distributions of links without point detectors are imputed based on their spatial correlations with links that have point detectors. The estimated link travel time distributions are then fused with path travel time distributions obtained from the interval detectors using Dempster-Shafer evidence theory. Based on fused path travel time distribution, an optimization technique is further introduced to update link travel time distributions and their spatial correlations. A case study was performed using real-world data from Hong Kong and showed that the proposed method obtained accurate and robust estimations of link and path travel time distributions in congested road networks. View Full-Text
Keywords: travel time distribution; data fusion; evidence theory; spatial correlation; uncertainty travel time distribution; data fusion; evidence theory; spatial correlation; uncertainty

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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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Shi, C.; Chen, B.Y.; Lam, W.H.K.; Li, Q. Heterogeneous Data Fusion Method to Estimate Travel Time Distributions in Congested Road Networks. Sensors 2017, 17, 2822.

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