Adaptive Reliable Shortest Path in Discrete Stochastic Networks

Yi Yong Pan

doi:10.4028/www.scientific.net/AMM.587-589.1854

Paper Titles

Parking on University Campus: How to Avoid the Tragedy of Commons?
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Schedule Risk Management of Railway Station Project
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Study on the Bike Path Width Considering the Electric Bike
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Study on the Characteristics of the Bus Trip of the Elders in Nanjing
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Adaptive Reliable Shortest Path in Discrete Stochastic Networks
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Application of Projection Method Based on Combination Weight in Comprehensive Evaluation for Highway Network Planning
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Comprehensive Evaluation for Urban Rail Transit Network Based on TOPSIS Model
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Forecast of Urban Public Transport Demand in Yantai Economic and Technological Development Zone
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Freight Vehicles Regulatory Assistance System Based on Internet of Things
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Adaptive Reliable Shortest Path in Discrete Stochastic Networks

Abstract:

This paper addresses adaptive reliable shortest path problem which aims to find adaptive en-route guidance to maximize the reliability of arriving on time in stochastic networks. Such routing policy helps travelers better plan their trips to prepare for the risk of running late in the face of stochastic travel times. In order to reflect the stochastic characteristic of travel times, a traffic network is modeled as a discrete stochastic network. Adaptive reliable shortest path problem is uniformly defined in a stochastic network. Bellman’s Principle that is the core of dynamic programming is showed to be valid if the adaptive reliable shortest path is defined by optimal-reliable routing policy. A successive approximations algorithm is developed to solve adaptive reliable shortest path problem. Numerical results show that the proposed algorithm is valid using typical transportation networks.