Bicyclist Longitudinal Motion Modeling
Cycling is being increasingly advocated as a sustainable mode of transportation due to its significant positive impacts on congestion and the environment. However, despite the growing popularity of bicycles for short-distance commuting, researchers have generally ignored the investigation of its traffic flow dynamics. This research effort proposes to model bicyclist longitudinal motion while accounting for bicycle interactions using vehicular traffic flow techniques. To achieve that objective, the study will use two naturalistic cycling datasets obtained from ring-road experiments, and will recruit participants to operate a bike-simulator in order to test the proposed model under realistic traffic conditions.
Universities and Sponsoring Organizations Involved
Morgan State University
Funding Sources and Amounts
USDOT: $120,000 (Federal), Virginia Tech: $40,000 (Match), Morgan State University: $20,385 (Match)
January 1, 2021
Expected Completion Date
December 31, 2021
Expected Research Outcomes
• Provide a comprehensive investigation of the traffic flow dynamics of bicycles.
• Develop a dynamics-based model for the description of the longitudinal motion of bicycles in both constrained and unconstrained cycling conditions.
• Model and capture bicyclist behavior variability.
• Collect bike simulator data.
Expected Equity Impacts and Benefits of Implementation
This research study would allow the development of multi-modal modeling tools that would integrate cycling behavior modeling with vehicle modeling. The simulation tools would assist city planners and policymakers in planning and decision-making processes.
Traffic flow theory, bicyclist behavior, bicyclist modeling, multi-modal modeling, car-following theory.