Spatial Agent-Based Model for Environmental Assessment of Passenger Transportation

Abstract

This study presents an urban transportation simulation model for lifecycle environmental performance evaluation (ALENT). ALENT integrates geographic information to quantify stations’ accessibility levels and construct real-world intercity transportation maps. A conceptual meta-theory from psychology is adopted to form the behavioral rules of passengers choosing different transport modes as influenced in part by passengers’ social networks. Operation scenarios are simulated for the year in which Hong Kong’s high-speed railway (HSR) is introduced, viewed from a lifecycle assessment perspective. The simulation results suggest that the occupancy rate of the HSR should be maintained—more than 80%—to lower the overall environmental impacts. The through train may need to be shut down to mitigate the system environmental impacts by up to 30%. ALENT can be used as a decision support tool for establishing sustainable passenger transportation systems.