Factors associated with emerging multimodal transportation behavior in the San Francisco Bay Area

Abstract

This paper identifies the influence of demographic, local transportation environment, and individual preferences for transportation attributes on multimodal transportation behavior in an urban environment with emergent transportation mode availability. Multimodality is the use of more than one mode of transportation during a given timeframe. Multimodality has been considered a key component of sustainable and efficient transportation systems, as this travel behavior can represent a shift away from personal vehicle use to more sustainable transportation modes, especially in urban environments with diverse transportation systems and emergent shared transportation alternatives (e.g., carsharing, ridehailing, bike sharing). However, it is unclear what factors contribute towards people being more likely to exhibit multimodal transportation behavior in modern urban environments. We assessed commuting behavior based on a survey administered in the San Francisco Bay Area according to whether residents commuted (i) exclusively by vehicle, (ii) by a mix of vehicle and non-vehicle modes, or (iii) exclusively by non-vehicle modes. A classification tree approach identified correlations between commuting classes and demographic variables, preferences for transportation attributes, and location-based information. The characterization of commuting styles could inform regional transportation policy and design that aims to reduce vehicle use by identifying the demographic, preference, and location-based considerations correlated with each commuting style.

Document Details

Document Type
Pub Defense Publication
Publication Date
Dec 01, 2021
Source ID
10.1088/2634-4505/ac392f

Entities

People

  • C Anna Spurlock
  • Emily Mcauliffe Wells
  • Gabrielle Wong-Parodi
  • Mitchell Small

Organizations

  • Carnegie Mellon University
  • United States Army Corps of Engineers
  • Vehicle Technologies Office

Tags

Readers

  • Agent-Based Social Robotics and Mobile-Assisted Learning in Virtual Environments.
  • Aviation Safety and Air Traffic Management
  • Psychometric Testing or Psychological Assessment.