NDLI: Finding non-dominated paths in uncertain road networks

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Finding non-dominated paths in uncertain road networks

Content Provider	ACM Digital Library
Author	Yang, Bin Jensen, Christian S. Aljubayrin, Saad Zhang, Rui
Abstract	With the rapidly growing availability of vehicle trajectory data, travel costs such as travel time and fuel consumption can be captured accurately as distributions (e.g., travel time distributions) instead of deterministic values (e.g., average travel times). We study a new path finding problem in uncertain road networks, where paths have travel cost distributions. Given a source and a destination, we find optimal, non-dominated paths connecting the source and the destination, where the optimality is defined in terms of the stochastic dominance among cost distributions of paths. We first design an A based framework that utilizes the uncertain graph to obtain the most accurate cost distributions while finding the candidate paths. Next, we propose a three-stage dominance examination method that employs extreme values in each candidate path's cost distribution for early detection of dominated paths, thus reducing the need for expensive distributions convolutions. We conduct extensive experiments using real world road network and trajectory data. The results show that our algorithm outperforms baseline algorithms by up to two orders of magnitude in terms of query response time while achieving the most accurate results.
Starting Page	1
Ending Page	10
Page Count	10
File Format	PDF
ISBN	9781450345897
DOI	10.1145/2996913.2996964
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2016-10-31
Publisher Place	New York
Access Restriction	Subscribed
Subject Keyword	Stochastic dominance Path finding Travel cost distributions
Content Type	Text
Resource Type	Article

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