In many urban areas, curb space management is a key determinant towards a sustainable transportation system as new trends in passenger and freight transportation demand require access to this limited asset. On the passenger side, in addition to efforts to increase pedestrian and bicycle traffic, and transit ridership, the advent of ride-hailing services have created a surge in curb demand. As a reference, while a few years ago, taxis represented around 1% of the vehicle trips in San Francisco, ride-hailing trips are 15% of the total today. Similarly, e-commerce growth (double-digits yearly) and residential deliveries require more curb access for freight loading/unloading activities. Aggravating the issue, ride-hailing companies are offering goods delivery services, pressuring an already contested and congested system.
This project leverages ongoing research on the development of a bike-sharing system, transit access programs through ride-sharing, and freight trip generation, to develop an integrated spatial simulation framework to quantify curb demand. The researchers will estimate aggregate passenger and freight trip generation models to quantify demand for a study area in California. They will integrate activity- and agent-based models to estimate the travel impacts for curb management strategies (e.g., loading/unloading area allocation, time restrictions, passenger vs. goods priorities).