Travel Behavior

In 2013, The California Department of Transportation-District 11 (Caltrans) launched the California Integrated Border Approach Strategy (CA-IBAS) in response to a need for a better-integrated border transportation system that reduces impacts on border communities. Work was conducted in two phases to identify ways to better address regional mobility needs and the traveler experience in California’s communities along the California-Mexico border. During Phase 1, led by METRANS, the team conducted a preliminary assessment of key institutional and policy issues at CaliforniaMexico land POEs,...

People walk a lot—to walk pets, to exercise and recreate, and to access public transit and local shops. Walk trips begin and end almost every journey, even trips made by automobile. Data from the current California Household Travel Survey (CHTS) show that walking occurs more than trips by both transit and bicycle, making it the second most common travel mode in California. Yet outside of select case studies in specific metropolitan areas, we know very little about walking behavior in California. An improved understanding of the determinants of walking will aid efforts to reduce driving and...

Transfers are a major source of travel time variability for transit passengers. Coordinating transfers between transit routes in real time can reduce passenger waiting times and travel time variability, but these benefits need to be contrasted with the delays to on-board and downstream passengers, as well as the potential for bus bunching created by holding buses for transfers. We developed a dynamic holding strategy for transfer coordination based on control theory. We then obtained the optimal control strategy, where maximum holding time is a function of real-time estimates of bus...

This project developed a quantile regression method for predicting future traffic flow at a signalized intersection by combining both historical and real-time data. The algorithm exploits nonlinear correlations in historical measurements and efficiently solves a quantile loss optimization problem using the Alternating Direction Method of Multipliers (ADMM). The resulting parameter vectors allow determining a probability distribution of upcoming traffic flow. These predictions establish an efficient, delay-minimizing control policy for the intersection. The approach is demonstrated on a...