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Public Transit Travel Time

Public transit travel time refers to the total time spent traveling using a public transit service, measured from a rider’s starting location to ending destination. Public transit travel time can be measured according to factors such as route travel time, dwell time and transfer time. A variety of factors influence public transit travel time, including proximity of bus/train stops to riders, first/last mile connectivity, travel speeds, the number of transfers required for a given trip and the time a rider must spend waiting at a transit stop. Public transit travel times have significant equity implications, as disadvantaged and low-income communities are more likely to have longer commute times, limited access to personal vehicles and rely on public transportation as their primary transportation mode. Public transit travel time also has significant equity impacts for people with disabilities, who experience unique challenges when using public transit and may be particularly reliant on public transit services that are timely and adapted to their needs. Title VI requirements for transit providers establish on-time performance standards and headway monitoring guidelines to ensure riders do not experience discrimination based on service design or operation practices. It is important that transit agencies eliminate inequities in public transit travel time to ensure compliance with these standards.

Understand your Datasets

Public transit travel time can be evaluated through a system’s connectivity, speed and efficiency. Explore how your project may influence public transit travel time for current and potential future riders. Evaluate public transit travel time according to key performance outcomes, including:

Connectivity: Measured through the number of transfers a rider must complete to complete a trip. Improved connectivity provides smoother journeys and can encourage use.
Speed and Efficiency: Relates to a rider’s path between connections (e.g., proximity between stops, directness of a route, ADA accessibility). Route optimization can also enhance trip speed, which can improve overall rider experience and encourage future transit use.

In addition to the factors above, Metro staff may collect and evaluate data related to rider wait times and quality of experience at stops, which contributes to overall travel speeds and impacts ridership. Metro staff can also assess accessibility-related data such as the average number of wheelchair pass-ups, elevator access and elevator outage rates, which can significantly impact public transit travel time for people with disabilities and other vulnerable riders. Planners may further choose to compare travel time across several modes of transportation to better understand passenger motivations. Metro’s LOCUS tool can provide Metro staff valuable datasets to support the assessment of such considerations.

Example Datasets:

1. LA Metro Annual On-Board Customer Satisfaction Surveys: https://www.metro.net/about/metro-research/

Instructions: Click through survey categories to download results from Metro’s Annual Onboard Customer Satisfaction Survey, in addition to viewing more detailed descriptions of some of Metro’s major projects.

Data Considerations: Metro’s Research department distributes and collects various surveys on recurring and ad hoc bases to improve the rider experience. For more information on Metro’s survey methodology, click “Methodology for Metro Research Projects” under “Annual On-Board Customer Satisfaction Surveys”

2. Measure Up! LOCUS: https://portal.locusdata.io/lametro/signup

Instructions: The interactive LOCUS dashboard is available for use by all government agencies, their private partners (including consultants) and academic institutions following the completion of an application.

Data Considerations: The Measure Up! LOCUS tool is a regional travel patterns data platform developed by LA Metro and Regional Integration of Intelligent Transportation Systems (RIITS) which allows users to extract rich travel trends with spatial, modal, equity and other trip attributes. It is comprised of three tools: a series of Excel workbooks, an online performance analytics tool and a transportation demand analytics dashboard. The platform features four consecutive years of passenger data from 2019-2022.

3. Additional LA Metro datasets related to public transit time, which may include:

Number of available buses/trains
Geographic extent of service
Busiest stations
Capacity of buses/trains
Travel speeds
Number of transfers
Distance traveled at transfers
Time to wait at stops
Proximity of bus/train stops to residents
The number and frequency of delays

Instructions: Metro staff can reach out to equityandrace@metro.net for support accessing these datasets.

Data Considerations: The COVID-19 pandemic had significant influences on ridership. Ensure you are downloading current datasets that reflect current rider behavior.

Community Demographics Profiles Alignment

Travel Time to Work by Transportation Mode
Transportation Mode by Race/Ethnicity

Explore the Index of Indicators in Metro’s Community Demographics Profiles Dashboard here.

Coordinate with Community Members

Ridership experiences can be highly individualized and community specific. Ensure you are seeking to understand public transit experiences across a wide range of riders, including more vulnerable groups like elderly people, young people and people with disabilities. Ask local community members to share their experiences, challenges and in what ways they rely upon Metro so you can incorporate these priorities into our planning process. Consider hosting a series of open houses, ridership surveys and workshops to better understand community member goals and ideal travel times and communicate potential project impacts. Ensure riders who rely on public transit for critical services are heard, and their perspectives considered. Continue meeting regularly with internal and external stakeholders throughout project phases to sustain open communication and dialogue with community members.

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