An Activity-Based Model for Evaluating Multimodal Public Transport Network Configurations in Hanoi
Year: 2026
Type: preprint
Abstract: In Hanoi, rapid urbanization and high dependency on private vehicles have resulted in severe traffic congestion and air pollutant emissions. To address these issues, the city is developing an integrated multimodal transit system to encourage modal shifts toward sustainable transport modes through a massive expansion of the metro network from two to twelve lines. To evaluate this transit network expansion and anticipate its potential impacts on urban mobility, transport models can offer valuable decision support. However, existing models struggle to represent multimodal transit itineraries with station transfers, capture dense traffic dominated by two-wheelers, and simulate behavioral adaptation under dynamic congestion. In this paper, we propose an activity- and agent-based simulation model to evaluate future transit scenarios. The key contributions of this work are threefold: first, a method for constructing a multimodal graph that integrates road networks with public transit services via virtual transfer connectors; second, the implementation of a grid-based mesoscopic congestion model using passenger car units; and third, a multinomial logit mode choice model to simulate behavioral adaptation, where agents evaluate utilities across private modes (cars, motorbikes, bicycles, walking) and multimodal public transit options based on dynamic traffic congestion and transit timetables. Our model allows us to compare the current network and population with planned future scenarios. Results show that adding new metro lines and optimizing bus itineraries could more than double the modal share of public transport, increasing it from 3.11% to 6.99%, yielding a 6.18% reduction in total CO2 emissions.
Source: HAL
Language: English
Subfield: Transportation
Field: Social Sciences
Domain: Social Sciences
Open Access status: green
OpenAlex ID: W7221237883