A commuter’s mode choice decision in response to provided traveller information is directly dependent on the temporal and spatial interactions between the available travel modes, the network performance and control schemes, and the supplied traveller information. A self-developed simulation model – Intelligent Network Simulation Model (INSIM) – was employed to simulate travel scenarios in a mul...

The growth of both research on and the relevance of pedestrian simulation in the definition of strategies for urban planning increasingly reinforce its adoption and ultimate utility among practitioners and engineers. This paper reports on first steps and preliminarily results of the implementation of a platform for pedestrian simulation in multimodal exchange interfaces. Whereas most approaches...

The Multimodal Transportation Educational Virtual Appliance (MTEVA) is an application developed within the framework of the broader Coastal Science Educational Virtual Appliance (CSEVA) to enhance coastal resiliency through the integration of coastal science and transportation congestion models for emergency situations. The first generation MTEVA enabled users to perform and visualize simulatio...

This paper aims to leverage Twitter data understand travel mode choices during the pandemic. Tweets related different modes in New York City (NYC) are fetched from two most recent years (January 2020–January 2022). Building on these data, we develop classifiers, adapted natural language processing (NLP) models, determine whether individual tweets some (subway, bus, bike, taxi/Uber, and private ...

The research on the optimization of a low-carbon multimodal transportation path under uncertainty can have an important theoretical and practical significance in high-quality development situation. This paper investigates problem dual uncertainty. A hybrid robust stochastic (HRSO) model is established considering cost, time cost carbon emission cost. In order to solve this problem, catastrophic...