Exploring the Effects of Information and Communication Technology on Travel Within an Activity-Based Travel Demand Modeling System

Activity-based travel demand models (ABMs) have the capacity to represent emerging activity dimensions; however, they lack integration of physical and virtual activity spaces. This study introduces a novel ABM framework that captures the dynamic interactions between physical–virtual activity spaces and implements it within an integrated transport, land-use, and emission framework. The study develops information and communication technology (ICT) adoption models, such as internet access and device ownership, into the agent-based structure. Markov chain Monte Carlo (MCMC) and conditional probability algorithms are utilized to schedule activities in physical and virtual environment reflecting factors, such as work arrangements, employment status, mobility and ICT tool ownership. Comprehensive calibration and validation processes are performed to ensure that the model can generate population mimicking real-world conditions. A prototype version of the model is implemented for the Halifax Regional Municipality (HRM), Canada. A scenario simulation is conducted that examines the impacts of ICT tool and virtual work adoption on activity-travel patterns. Results show that increased ICT tool adoption significantly boosts the duration of virtual maintenance and discretionary activities while reducing time spent on mandatory activities. A 10% rise in virtual work reduces vehicle kilometers traveled (VKT) in HRM by 51,800 km/day and lowers carbon dioxide (CO 2 ) emissions by 6.216 metric tons/day. The study confirms the complex, nonlinear impacts of ICT on travel, while showing the potential of virtual-work in reducing peak-hour travel and VKT. The developed tools in this study can aid policymakers in assessing the impacts of virtual activities on transport and land use systems and help achieve regional sustainability goals.