Using conjoint analysis to incorporate heterogeneous preferences into multimodal transit trip simulations

International Council on Systems Engineering
March 04, 2023

The majority of commuters in theUnited States use personal passenger vehicles, which have multiple negative externalities such as air pollution, greenhouse gas emissions, congestion, and vehicle crashes. The transportation sector is the largest source of greenhouse gas emissions in the United States, and personal vehicles are responsible for approximately two thirds of those emissions. Rather than attempt to further accommodate “automobility” viamore roadway infrastructure, a more sustainable development path in most urban cities is to increase public transit usage. Nonetheless, public transit has important drawbacks for some commuters. The level of service can be less than desirable depending on factors such as route scheduling, reliability, and the inconvenience of having to make transfers. Exogenous factors such as the socio-economic backgrounds of different commuters also affects people’s perspective on using public transit.

To accurately measure the impacts of policies aimed at increasing transit ridership, it is vital to have an accurate model of commuters’ decision-making processes when choosing their commute. Towards this goal, urban public transit can be modeled as a system involving a complex network of multiple mode options and travel routes, often requiring transfers between modes. Several studies have explored models of commuter mode choice, but most use single-mode trips as alternatives to driving, such as one-leg bus, metro, and bike trips, ignoring the complexities of multimodal trips that require transfers.

Read the full study in The Jounrnal of the International Council of Systems Engineering.