Proposed Methodology for Estimating Rideshare Viability Within an Organization: Application to the MIT Community

Ridesharing as a mode of travel is a potential solution to a variety of the transportation sectors toughest challenges including congestion relief, increased energy security, reduced GHG emissions and improved travel options. However, the transportation literature provides little quantified assessment of ridesharing’s overall potential. This paper proposes a data driven methodology for estimating the viability of ridesharing at an organizational scale, and seeks to demonstrate its applicability using the Massachusetts Institute of Technology commuting population as a case. The methodology seeks to improve upon previous research by differentiating between modeled rideshare potential based on known trip characteristics, and observed rideshare behavior, within the same commuting population. By comparing rideshare potential to observed behavior,inferences can be made about the relative importance of trip characteristics vs. the importance of human attitudes in rideshare arrangements. MIT-specific results suggest that between 50% and 77% of the commuting population could rideshare on a maximum-effort day. These are values significantly higher than the 8% of the MIT community that currently choose to rideshare. Maximum achievable VMT reductions from daily ridesharing are between 9% and 27%. The disparity between the modeled potential and observed behavior suggests that human attitudes are a much larger barrier to increased rideshare participation than incompatible trip characteristics. The results suggest that policy makers seeking to increase rideshare participation may want to target large organizations and focus their efforts on personalized travel planning in an effort to improve attitudes towards ridesharing.