Transit-Gym: A Simulation and Evaluation Engine for Analysis of Bus Transit Systems

TL;DR

Transit-Gym is a simulation platform designed to help transit agencies analyze and optimize bus systems by modeling demand, routes, and energy consumption, addressing complex operational challenges.

Contribution

It introduces a domain-specific language and tool-chain for intuitive large-scale transit scenario simulation and analysis, including an integrated energy consumption model.

Findings

Enables simulation of demand, route, and vehicle assignment variations.

Supports analysis of energy costs associated with transit decisions.

Facilitates evaluation of operational strategies under uncertainty.

Abstract

Public-transit systems face a number of operational challenges: (a) changing ridership patterns requiring optimization of fixed line services, (b) optimizing vehicle-to-trip assignments to reduce maintenance and operation codes, and (c) ensuring equitable and fair coverage to areas with low ridership. Optimizing these objectives presents a hard computational problem due to the size and complexity of the decision space. State-of-the-art methods formulate these problems as variants of the vehicle routing problem and use data-driven heuristics for optimizing the procedures. However, the evaluation and training of these algorithms require large datasets that provide realistic coverage of various operational uncertainties. This paper presents a dynamic simulation platform, called Transit-Gym, that can bridge this gap by providing the ability to simulate scenarios, focusing on variation of demand models, variations of route networks, and variations of vehicle-to-trip assignments. The central contribution of this work is a domain-specific language and associated experimentation tool-chain and infrastructure to enable subject-matter experts to intuitively specify, simulate, and analyze large-scale transit scenarios and their parametric variations. Of particular significance is an integrated microscopic energy consumption model that also helps to analyze the energy cost of various transit decisions made by the transportation agency of a city.