01660906

Component

https://doi.org/10.1177/0361198118793329

Road network resilience is emerging as a vital planning criterion. Yet, unique and cross-comparable indices for road network resilience are scarce. One of the recent approaches determines resilience as a unique network attribute based on the system travel time at an upper envelope of operable disruptions. This upper envelope represents ‘critical states’ (or tipping points) of capacity disruptions. Critical state gives a bounding capacity degradation vector, beyond which the network cannot wholly cater to the origin–destination demand even under the best possible traffic assignment. However, solving the critical state identification problem (CSP) on real-scale networks has remained a challenge. This paper presents a weighted fictitious play algorithm to fill this gap. CSP has been previously envisaged as a two-player game between a network attacker and a network defender. Here, we make the players play iteratively, and make them learn from the competitor’s past strategies so that they converge to an equilibrium. We illustrate the method on a simple toy network, and solve it on different real-life networks. Resilience of the Anaheim city network was computed in 42.8?min., considerably outperforming—both in problem-size and solution-time—the previous, two-space genetic algorithm.

18-06526

English

pp 104-115

2018-12

Transportation Research Record: Journal of the Transportation Research Board

Print

Figures (9) ; References (46) ; Tables (2)

Algorithms; Networks; Roads; Urban highways

Road network resilience

Highways; Planning and Forecasting

TRIS, TRB, ATRI

Jan 8 2018 11:41AM

• A Generalized Single-Level Formulation for Origin–Destination Estimation under Stochastic User Equilibrium
• A Greedy Path-Based Algorithm for Traffic Assignment
• Balanced Scheduling of School Bus Trips Using a Perfect Matching Heuristic
• Characterization of Taxi Fleet Operational Networks and Vehicle Efficiency: Chicago Case Study
• Impact of Extreme Events on Transportation Infrastructure in Iowa: A Bayesian Network Approach
• Improving Scalability of Generic Online Calibration for Real-Time Dynamic Traffic Assignment Systems
• Level-Change Stackelberg Games Model for the Combined Traffic Assignment–Signal Control Equilibrium on Networks
• Link Transmission Model-Based Linear Programming Formulation for Network Design
• Modeling Day-to-Day Dynamics of Travelers’ Risky Route Choices under the Influence of Predictive Traffic Information
• Multimodal Transportation Network Modeling Based on the Generic Second Order Modeling Approach
• Network Partitioning Algorithms for Solving the Traffic Assignment Problem using a Decomposition Approach
• Optimal Information Provision at Bottleneck Equilibrium with Risk-Averse Travelers