travel behavior

This document provides the technical details for the calculations and assumptions of the Caltrans Active Transportation Benefit-Cost tool hosted by UC Davis.

This tool has been developed by the UC Davis BicyclingPlus Research Collaborative to estimate expected benefits of proposed active transportation projects.

This paper examines bike-share users’ willingness-to-walk to pick up a bike or drop off a bike at some distance from their origins or destinations if rewarded and to identify characteristics influencing willingness-to-walk.

In this report, travel behavior data from the Federal Highway Administration’s National Household Travel Survey is combined with detailed built environment data from the Environmental Protection Agency’s Smart Location Database to evaluate the relationships between personal and built environment factors and sustainable travel behaviors including vehicle miles traveled (VMT) and mode choice.

Researchers at the University of Southern California developed a real-time, distributed algorithm for offering personalized incentives to individual drivers to make socially optimal routing decisions.

This study examines the personal and trip characteristics associated with ridehailing users’ decisions to substitute other modes of travel or conduct new trips by ridehailing.

The adoption of plug-in electric vehicles (PEVs) is considered to be a potential solution to reduce transportation-related emissions. People’s vehicle choice and driving behavior will have important implications for the realized emissions reductions from PEVs. Therefore, PEV-related policy studies require good understanding of human behavior. This dissertation proposes data-driven approaches to simulate behavior and provides a discussion of the implications for three PEV-related topics.