Performance evaluation of path choice set generation algorithms for route choice modelling

Abstract

Traffic assignment and its applications are sensitive to the selection of path choice sets between an OD pair. In literature, different path generation algorithms are proposed, namely, Link Labeling, Link Elimination, Link Penalty, Simulation, and Branch and Bound. The effectiveness of these algorithms hinges on algorithmic principles and input parameters. Consequently, choosing an appropriate algorithm for practical implementation becomes challenging. This paper aims to benchmark these algorithms with a case study using a real vehicle trajectory dataset from four OD pairs from Brisbane, Australia. The paper offers both qualitative and quantitative comparisons of the algorithms. The performance of the algorithms is evaluated based on their authenticity, redundancy, and applicability. The results highlight that the simulation method outperforms the other algorithms, specifically utilizing a truncated normal distribution. The paper offers valuable insights into the selection of path-generation techniques, aiding the enhancement of traffic assignment processes.