Double parking is a common response to limited curb availability in dense urban areas and contributes to traffic disruptions, conflicts among roadway users, and increased crash risk. Despite its prevalence, the safety and congestion impacts of double parking are not well quantified, and cities lack analytical tools to evaluate potential policy interventions. This project addresses these gaps through integrated data collection and modeling.
The research will combine video-based field observations, surveys of commercial drivers, and crash and enforcement data to characterize double-parking behavior and its effects on traffic flow and safety. Behavioral choice models will be developed to estimate the likelihood of double parking versus cruising under varying curb availability and policy conditions. By linking curb use decisions with safety and congestion outcomes, the project will provide quantitative tools to evaluate curb management strategies and support more effective urban transportation policies.