Reliable Shortest Path Problems in Networks Under Uncertainty

Download or read book Reliable Shortest Path Problems in Networks Under Uncertainty written by Biyu Chen and published by . This book was released on 2012 with total page 454 pages. Available in PDF, EPUB and Kindle. Book excerpt: The proposed RSP model and solution algorithm are extended to incorporate travel time temporal correlations in those stochastic time-dependent (STD) networks where link travel time distributions vary by time intervals throughout the day. In the STD networks, travellers' experienced link travel time variation depends on the time instance vehicles entering the link; and the link travel time distribution is typically assumed to be fixed when these vehicles travelling on that link. This assumption, however, may violate the first in first out (FIFO) property, since traffic conditions cannot be updated when vehicles travelling on the link. To address this non-FIFO problem, a stochastic travel speed model (S-TSM) that can update travellers' experienced travel speeds during different time intervals on the link is proposed in this research. The proposed S-TSM can ensure the FIFO property of link travel times, so that the efficient multi-criteria A* algorithm can be adopted to solve the RSP problems in STD networks. Based on the proposed multi-criteria A* algorithm, a real-world ATIS-based routing system is developed to aid road users of Hong Kong making route choice decisions in road networks with travel time spatiotemporal correlations. Secondly, the proposed RSP model is incorporated in reliability-based user equilibrium (RUE) problems for traffic assignment. In this research, an effective reliable shortest path algorithm is developed to determine RSP for all user classes in one search process so as to avoid the repeated path searching for each user class. The proposed reliable shortest path algorithm is then, further incorporated into a path-based RUE assignment algorithm using a column generation method. The proposed RUE assignment algorithm does not require path enumeration and can achieve highly accurate RUE results within reasonable computational time. A numerical example demonstrates that the proposed RUE assignment algorithm is capable for solving relevant problems in road networks with demand and / or supply uncertainties. Thirdly, the proposed RSP and RUE algorithms are applied to identify critical links in large-scale road networks. The traditional method, to identify critical links, is to use a full scan approach to assess all possible link closure scenarios by means of traffic assignment methods. This full scan approach is not viable for identifying critical links in large-scale road networks, because of the large number of link closure scenarios and computational intensity of traffic assignment methods in these large-scale networks. An impact area vulnerability analysis approach is proposed in this research to evaluate the consequences of a link failure within a local impact area, rather than the entire network. Such vulnerability analysis approach reduces the problem size of the critical link identification so as to reduce the computational burden involved. Case studies on large-scale real-world networks are presented to illustrate the proposed impact area vulnerability approach and investigate the effects of stochastic demand and heterogeneous travellers' risk-taking behaviour.