What question did this study set out to answer?

The central aim is to enhance an existing activity-based model to include biking behaviors and policy scenarios.

March 25, 2026Sustainable Cities and Society0 citationsOpen Access

Adding Bike Simulation Capacity to an Activity–Based Travel Demand Model and Testing Policy Scenarios

Puntos clave

The central aim is to enhance an existing activity-based model to include biking behaviors and policy scenarios.
Integrated bike destination choice sub-module in the activity-based model.
Simulated bike traffic using MATSim on the road network.
Calibrated and validated model for Okanagan, British Columbia.
Evaluated three policy scenarios: car ownership reduction, bike ownership increase, and both.
Increased bike ownership improves bike trip share by ∼15.2% compared to baseline.
Simultaneous increase in bike ownership and decrease in car ownership achieves ∼12.6% reduction in car share.
The model shows ∼7.5% higher bike network utilization and creates distinct morning peak-hour for biking.
Reduced car traffic results in ∼15.6% lower car travel time and ∼19% reduction in greenhouse gas emissions.

Resumen

• Added biker’s behavior and bike network simulation capacity to activity–based model • Captured physical-spatio–temporal constraints of biker’s in destination choice • Tested impacts of car and bike ownership scenarios • Reducing household car coupled with increasing bike is the most beneficial scenario With increased investments in bike infrastructure, the need for tools that are sensitive to bike-related policies and planning has become essential. Given the limited capacity of existing activity-based models (ABMs) to explicitly accommodate bike users’ behavior, this study adds capacity to an existing ABM to simulate bike users’ travel for policy testing purposes. Specifically, the study integrates a tour-level bike destination choice sub-module within the ABM. This sub-module operates in two stages: first, a destination choice set is generated, accommodating spatial, temporal, and physical strength constraints of bike users; then, the destination location is selected using a discrete choice model. Finally, bike traffic is simulated on the road network using MATSim. The ABM and network model are developed, calibrated, and validated for Okanagan, British Columbia. The validated model is used to evaluate three policy scenarios: (1) reduced car ownership, (2) increased bike ownership, and (3) both occurring simultaneously. Results show that with increased bike ownership, the share of bike trips rises by ∼15.2% compared to the base scenario; however, this is less effective in reducing car use than policies regulating car ownership only. When both increased bicycle ownership and reduced car ownership occur simultaneously, the highest reduction in car share (∼12.6%) occurs, accompanied by ∼18.2% increase in bike share. The integrated approach results in ∼7.5% higher bike network utilization while generating a distinct morning peak-hour. Subsequently, reduced car traffic results in ∼15.6% lower car travel time and ∼19% reduction in GHG emissions, transforming Okanagan from car-centric to bike-friendly region.

Preguntar a la IA

Me gusta

Guardar

Ver artículo completo