Time-Varying Lane-Based Capacity Reversibility for Traffic Management

This paper presents a new bi-level formulation for time-varying lane-based capacity reversibility problem for traffic management. The problem is formulated as a bi-level program where the lower level is the cell-transmission-based user-optimal dynamic-traffic-assignment (UODTA) linear program. Due to its NP-hard complexity, the genetic algorithm (GA) with the simulationbased UODTA is adopted to solve multi-origin multi-destination problems. Four GA variations are proposed. GA1 is a simple GA. GA2, GA3 and GA4 with a jam-density-factor parameter (JDF) employ time-dependent congestion measures in their decoding procedures. The four algorithms are empirically tested on a grid network and compared based on solution quality, convergence speed, and CPU time. GA3 with JDF of 0.6 appears best on the three criteria. On Sioux Falls network, GA3 with JDF of 0.7 performs best. The GA with the appropriate inclusion of problem-specific knowledge and parameter calibration indeed provides excellent results when compared with the simple GA. ___________________________________ Corresponding Author: Lecturer, Department of Civil Engineering, King Mongkut’s University of Technology Thonburi, 126 Pracha-Utit Road, Bangmod, Thung-Khru, Bangkok, 10140, Thailand, E-mail: [email protected] Assistant Professor, Department of Transportation and Communication Management Science, National Cheng Kung University, 1 University Road, Tainan City, 70101, Taiwan, E-mail: [email protected]