Equilibrium Analysis of Full-Day Commuting with Telecommuting and Autonomous Vehicles

With the normalization of telecommuting (TLC) and the rapid advancement of autonomous vehicle (AV) technology, commuting behavior has become increasingly flexible across both temporal and spatial dimensions, exhibiting greater heterogeneity than in the past. Consequently, conventional models that focus solely on the morning peak fail to capture commuters’ full-day decision-making processes and the systematic evolution of congestion. To address this gap, this study develops a full-day commuting equilibrium model that jointly incorporates AV technology and the TLC option. The model explicitly characterizes commuters’ choices of work mode, departure timing, and parking location within a classical bottleneck framework, integrating AV parking capacity and the demand adjustments induced by TLC. Multiple equilibrium traffic patterns are derived along with both the endogenous TLC proportion and the socially optimal exogenous TLC proportion under each pattern. The model further investigates how key parameters—such as the cost of early arrival schedule delay and parking density—affect the equilibrium TLC proportion and congestion dynamics. Analytical derivations and numerical simulations demonstrate that neglecting evening commuting leads to systematic biases and highlight the critical role of a full-day framework in identifying intertemporal decision making and behavioral heterogeneity. The findings provide theoretical insights and quantitative tools for commuting modeling and policy design in the era of autonomous driving and widespread telecommuting. Funding: This work was supported by the National Natural Science Foundation of China [Grants 72271248, 72288101, 72201285], the Science and Technology Innovation Program of Hunan Province [Grant 2025RC3015], the Scientific Research Program of the Education Department of Hunan Province [Grant 24B0002], and the Laboratory of Intelligent Governance for Complex Social Systems. Supplemental Material: The online appendix is available at https://doi.org/10.1287/trsc.2025.0379 .