TY - GEN
T1 - A Computationally Efficient Link Criticality Ranking with Perception Error and Route Overlapping for Road Transport Networks
AU - Kurmankhojayev, D.
AU - Li, G.
AU - Chen, A.
N1 - Funding Information:
The work described in this paper was jointly supported by research grants from the Research Grants Council of the Hong Kong Special Administrative Region, China (Project No. 15212217) and the Research Institute for Sustainable Urban Development at the Hong Kong Polytechnic University (1-BBWF). The first author is also supported by a Studentship from the Research Institute for Sustainable Urban Development at the Hong Kong Polytechnic University. In addition, the project 72071174 supported by National Natural Science Foundation of China at the Hong Kong Polytechnic University Shenzhen Research Institute, Shenzhen, Guangdong, China is gratefully acknowledged.
Publisher Copyright:
© 2022 IEEE.
PY - 2022/11
Y1 - 2022/11
N2 - In real-size congested road networks, ranking links with respect to their criticalities while capturing dependence of link travel costs on user behavior and travel demand is not an easy task. The existing measures either require multiple traffic assignments (i.e., full-scan) or make strong assumptions on users' rationality while using a single traffic assignment. In this study, we propose an improved link criticality index that not only alleviates the computational burden associated with the full-scan network efficiency measures, but also accounts for travelers' perception error and route overlap. The proposed link criticality index is based on the resulting stochastic user equilibrium (SUE) model with a specific discrete choice model. Particularly, we adopt the path-size logit (PSL) route choice model in the SUE model, in which a path-size factor resolves the route overlapping issue by adjusting the choice probabilities for routes with strong correlations. To solve the traffic assignment, we use a faster gradient projection algorithm based on Barzilai-Borwein step size determination scheme (GP-BB). Numerical experiments are conducted to verify and demonstrate the properties of the proposed link criticality measure with the loophole network.
AB - In real-size congested road networks, ranking links with respect to their criticalities while capturing dependence of link travel costs on user behavior and travel demand is not an easy task. The existing measures either require multiple traffic assignments (i.e., full-scan) or make strong assumptions on users' rationality while using a single traffic assignment. In this study, we propose an improved link criticality index that not only alleviates the computational burden associated with the full-scan network efficiency measures, but also accounts for travelers' perception error and route overlap. The proposed link criticality index is based on the resulting stochastic user equilibrium (SUE) model with a specific discrete choice model. Particularly, we adopt the path-size logit (PSL) route choice model in the SUE model, in which a path-size factor resolves the route overlapping issue by adjusting the choice probabilities for routes with strong correlations. To solve the traffic assignment, we use a faster gradient projection algorithm based on Barzilai-Borwein step size determination scheme (GP-BB). Numerical experiments are conducted to verify and demonstrate the properties of the proposed link criticality measure with the loophole network.
KW - link criticality index
KW - perception error
KW - route overlapping
KW - stochastic user equilibrium
UR - http://www.scopus.com/inward/record.url?scp=85143068931&partnerID=8YFLogxK
U2 - 10.1109/ICRMS55680.2022.9944582
DO - 10.1109/ICRMS55680.2022.9944582
M3 - Conference article published in proceeding or book
AN - SCOPUS:85143068931
T3 - 13th International Conference on Reliability, Maintainability, and Safety: Reliability and Safety of Intelligent Systems, ICRMS 2022
SP - 154
EP - 158
BT - 13th International Conference on Reliability, Maintainability, and Safety
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 13th International Conference on Reliability, Maintainability, and Safety, ICRMS 2022
Y2 - 21 August 2022 through 24 August 2022
ER -