Research Team: PI: JR DeShazo Team: Mohja Rhoads, James Di Filippo
About this project:
This research will utilize a dataset of Lyft rides over three months in Los Angeles region, to understand how TNCs can inform and support transit. It will assess two main objectives:
1. How TNCs are assisting or replacing transit and where TNC demand is highest
Using origin and destination data from TNC pooled and non-pooled trips, we will identify the origins that service transit and the destinations that complement transit. We will then examine trip routes to establish where TNC use is most demanded, and estimate the same trip as if it were made on transit, walking, or biking.
Policy recommendations will be included discussing the findings and the transportation planning relevance. For example, suggestions might include scheduling of local shuttles, increased frequency and routes, and structuring fares with TAP cards that integrate transit and TNCs.
2. Transportation accessibility for disadvantaged communities
This objective will develop an index of transit access, vehicle availability, TNC use, income, and length and destinations of TNC trips to measure a community’s level of access to motorized mobility. Communities across Los Angeles will be compared and the lowest-served will be identified.
Policy recommendations will be included. For example, suggestions might be included using caution to regulate TNCs in such a way that discourages use by disadvantaged communities. Other suggestions might include structuring policies that incentivize use by disadvantaged communities.
Informed by the first two objectives, this research will also examine the patterns of pooled and non-pooled mobility for the purposes of informing Autonomous Vehicle (AV) Planning. Ridehailers are likely to be early AV adopters and the resulting ridehailing driving patterns are likely to mimic AV routes. The resulting travel patterns from the above analyses can inform AV planning, allowing planners to get a head-start on understanding AV usage, particularly in the context of disadvantaged communities.
What problem does this research aim to address?
In the past decade, we have seen a boon in travel opportunities engendered by technology. A major transformation has been the provision of ridehailing services such as Uber and Lyft, companies defined as Transportation Network Companies (TNCs). TNCs have cornered an under-served taxi market. Their services have been appealing to travelers of varying income levels, equipping them with enhanced access to goods and services. It is predicted that TNC use will continue to grow and form a significant portion of individual and household travel needs.
Conversely, transit ridership has fallen over the last decade. Transit has been unable to match the point-to-point mobility the private vehicle provides, pushing transit riders to secure auto-ownership to guarantee adequate levels of accessibility in their regions. As ridership plummets, transit operators are trying to figure out how they can improve their services and expand their markets.
Travelers often view TNCs as preferable to transit because they preserve the high-mobility and convenience of an auto-trip. Transit planners should learn how TNCs are used, so they can tailor transit services to increase mobility, particularly the mobility of low-income riders. It is important that our public and private systems work together to better serve our public.
What are the expected impacts and benefits of the research?
The work products will be as follows:
1. Final Report composed of Literature Reviews, Research, Findings, and Policy
2. 2-page Policy Briefs for the following:
• TNC Use and Transit
• TNC Use and Disadvantaged Communities
• TNC Use for Autonomous Vehicle Planning