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Results for “first/last mile”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Ride Pingo to Transit

In this project, we developed an on-demand microtransit first- and last-mile service. To integrate the service with fixed-route transit, we developed a feature called Transit Connect that prioritized riders’ on-time arrival at the transit station over other service requirements. We first prototyped service and related algorithms in a simulated environment, and then piloted the service in the city of Kent, Washington. Our algorithm incorporates request-specific hard drop-off deadlines to ensure timely arrivals for transit transfers. In the pilot, these constraints were obtained from GTFS Realtime data to accurately determine the schedule of the transit and the location of the stations. This approach introduced the ability to accept or decline new requests based on the timing of transit connections for these new requests and connection status of onboarding customers. The pilot (called “Ride Pingo to Transit”) deployed a fleet of three 14-person vans, ran from September 2021 to March 2023, and served a total of 21,329 trips. Transit Connect was offered for drop-offs at both Kent Station and the Kent Valley hub. In total, 2,844 such trips were completed. This dataset was collected from our pilot, which includes the following: - Requests: List of all trip requests, including those that were actually served and those not materialized. - Fleet: Daily vehicle service logs. - Service details: Daily vehicle stop logs (boarding and alighting). - Trip types: First mile, last mile, or point-to-point. ![pingo to transit](pingo-to-transit.jpg)

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2026

Bike and Scoot to Transit

In this project, we developed a micromobility first-mile service for customers to access public transit. We launched this service as a pilot in the Seattle area that incentivized transit customers to bike or scoot to transit. The objective was to learn how to integrate different micromobility services and provide a unified reward program. Our pilot was called “Bike and Scoot to Transit” and ran from November 2022 to September 2023. More than a dozen locations were selected near transit hubs and light rail/train stations as preferred parking locations. Trips ending at those locations were partially funded. The pilot supported 19,226 qualified trips and distributed $73,000 in total benefits for the participants of the pilot. This dataset was collected from our pilot, which includes the following: - Monthly data: Monthly trip and funding summaries. - Data summary: Data broken down based on the micromobility service provider and equipment. - Trip data: List of all trips recorded during the pilot. - Pricing models: Fees charged by micromobility service providers. ![bike to transit](bike-transit.png)

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2026

Onboard/Origin-Destination Survey - Phoenix - 2007

In 2007, the Valley Metro Regional Public Transportation Authority, with consultant support, conducted an origin and destination survey of Valley Metro riders. The self-administered surveys were conducted among riders of fixed-route bus service: Local, Circulator, Limited, Rural, Express, and RAPID bus. Data collection was performed from October 8 through December 18, 2007. The objectives of the survey were to examine the demographics and travel behavior characteristics of Valley Metro riders. The survey data used for this analysis were appropriately weighted and expanded to represent the unlinked trips made by Valley Metro riders.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2026

Onboard/Origin-Destination Survey - Phoenix - 2015

Valley Metro conducted an on-board transit survey during spring 2015. This project gathered updated travel behavior data from transit users that encompassed all rail and bus fixed-route services in the Phoenix metropolitan planning area. The study’s goal was to compile statistically accurate information about transit riders and how they use the transit system.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2026

Passenger Survey - Washington DC Metrorail - 2012

The primary purposes of the survey were to update ridership by the jurisdiction of residence for use in Metrorail’s operating subsidy allocation and to collect demographic, travel, and access data for Title VI compliance, system planning, and operation analyses. It was not a customer opinion survey; the focus was on ridership and travel characteristics.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2026

Metrobus Survey - Washington DC - 2014

The primary purposes of the survey were to update ridership by the jurisdiction of residence for use in Metrobus’ operating subsidy allocation and to collect demographic, travel, and access data for Title VI compliance, system planning, and operation analyses. It was not a customer opinion survey; the focus was on ridership and travel characteristics.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2026

Riders Survey - Miami-Dade County MetroBus - 2004

This survey was completed as part of the Miami North Corridor project on all 286 Metrobus routes of Miami-Dade Transit, and on Metrorail at all stations.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2026

Transit Survey - Miami-Dade Metrorail - 2009

This Miami-Dade Metrorail Survey obtained ridership characteristics such as origin-destination patterns, trip purpose, and mode of access and egress. The data obtained from this survey was used to update and validate the Southeast Regional Planning Model (SERPM v6.5) and for transportation planning in the region.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2026

Transit Rider/Travel Behavior Inventory Survey - Minneapolis-St. Paul Metro - 2005

The survey was an on-board survey of transit riders on all regular route services for bus and light-rail in the Minneapolis-Saint Paul metropolitan area. The primary purpose of the study was to gather the data needed to update the mode choice models that are an integral component of the regional travel forecast model maintained by the Metropolitan Council, the metropolitan planning organization for the Minneapolis-Saint Paul metropolitan area. The survey instrument focused on identifying characteristics of the trip taken by each transit rider, including origin, destination, trip purpose, and mode of access. The survey also collected relevant socioeconomic and demographic information.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2026

Transit Rider/Travel Behavior Inventory Survey - Minneapolis-St. Paul Metro - 2010

The Metropolitan Council administered a system-wide transit on-board survey between September and November 2010 as part of the 2010 Travel Behavior Inventory to provide detailed transit usage patterns and rider information to support modeling and planning efforts. The study’s focus was to capture only the most current and reliable data necessary to determine future public transportation needs in the Minneapolis region. The study was structured to collect detailed transit ridership data for different routes during different times of day to develop a disaggregate transit trip table that will support advanced travel demand modeling. The study was designed to leverage existing data sources, such as the 2005 on-board survey, to provide the best quality data to update the Travel Behavior Inventory in the Minneapolis-Saint Paul metropolitan area.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2026

Transit Rider/Travel Behavior Inventory Survey - Minneapolis-St. Paul Metro - 1990

The 1990 transit on-board survey aimed to update the 1988 survey, which was conducted as part of the Preliminary Engineering Study for the Hennepin County Light Rail Transit System. The 1988 study received Regional Transit Board funding, and survey results could be applied to a mode split model for projecting ridership on the proposed Light Rail Transit System. However, this survey was designed with the 1990 Travel Behavior Inventory in mind. The intention had been to update the 1988 survey in 1990 to be compatible with the 1990 Travel Behavior Inventory data. The results of the 1990 survey were used primarily to create a table of observed transit trips between each of the 1,200 traffic analysis zones in the region. This trip table was used to calibrate a new mode split model, which estimated future year travel by mode. The 1990 update survey focused on new routes and routes that had changed significantly since 1988. To preserve compatibility with the 1988 survey, the same survey questionnaire card was used, together with the same survey procedures for data collection. The procedures randomly sampled bus patrons during the transit trip, asking key questions about the patron and the transit trip. The survey card was intended for patrons to fill out quickly so it could be completed during the transit trip. The questions focused on conditions that have proven over time to significantly influence ridership. In all, a total of 20,126 valid survey records were processed. Adding surrogate trips, the survey data file is composed of a total of 27,159 trip records . About 10% of the records were filled out by persons who had answered more than one questionnaire.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2026

Onboard Transit Survey - Philadelphia Regional - 2012

The main purpose of the survey was to gather current data on how the transit system was being used in 2010. The survey asked passengers a series of questions about their household characteristics and the trip that they were making on the day of the survey. The survey was conducted in three phases between December 2010 and December 2011. Close to 1.1 million unlinked trips are made on an average weekday on all 140 routes systemwide. The survey results suggest several different populations of users. At the low end of the economic spectrum are passengers who really have no other transit option besides public transit. There is also a group of passengers that appear to be somewhat better off financially. They could be categorized as middle-income households, and many of these passengers may have other options for transportation, but they choose to take public transit because it makes sense for them from a financial or time-savings standpoint. Finally, there may be a smaller group of passengers who may live and work downtown in relatively high-paying positions. These passengers can afford to take a taxi but choose to ride transit because of its convenience.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2026

Travel Decision Survey - San Francisco - 2012

On behalf of the San Francisco Municipal Transportation Agency (SFMTA), Corey, Canapary & Galanis undertook a Travel Decision Survey within the City and County of San Francisco, as well the eight surrounding Bay Area counties of Alameda, Contra Costa, San Mateo, Marin, Santa Clara, Napa, Sonoma, and Solano. The primary goals of this study were to accurately assess mode share for trips within San Francisco (including trips to or from San Francisco, but excluding through trips) among city residents and residents of other Bay Area counties; provide additional trip details, including trip purpose information for each trip in the mode-share question series; and use the mode-share percentages collected on this survey in conjunction with total trip estimates provided by SFMTA to project the number of trips by mode on an average day in San Francisco.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2026

Travel Decision Survey - San Francisco - 2013

On behalf of the San Francisco Municipal Transportation Agency (SFMTA), Corey, Canapary & Galanis undertook a Travel Decision Survey within the City and County of San Francisco, as well as the eight surrounding Bay Area counties of Alameda, Contra Costa, San Mateo, Marin, Santa Clara, Napa, Sonoma, and Solano. The primary goals of this study were to: 1. Assess percent mode share for travel in San Francisco for evaluation of the SFMTA Strategic Objective 2.3: Mode Share target of 50% non-private auto travel by FY 2018 with a 95% confidence level and margin of error ±5% or less. 2. Evaluate the above statement based on number of trips to, from, and within San Francisco by Bay Area residents. Trips by visitors to the Bay Area and for commercial purposes are not included. 3. Provide additional trip details, including trip purpose for each trip in the mode-share question series. 4. Collect demographic data on the population of Bay Area residents who travel to, from, and within San Francisco. 5. Collect data on travel behavior and opinions that support other SFMTA strategy and project evaluation needs.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2026

Travel Decision Survey - San Francisco - 2014

On behalf of the San Francisco Municipal Transportation Agency (SFMTA), Corey, Canapary & Galanis undertook a Travel Decision Survey within the City and County of San Francisco, as well as the eight surrounding Bay Area counties of Alameda, Contra Costa, San Mateo, Marin, Santa Clara, Napa, Sonoma, and Solano. The primary goals of this study were to: 1. Assess percent mode share for travel in San Francisco for evaluation of the SFMTA Strategic Objective 2.3: Mode Share target of 50% non-private auto travel by FY 2018 with a 95% confidence level and margin of error ±5% or less. 2. Evaluate the above statement based on number of trips to, from, and within San Francisco by Bay Area residents. Trips by visitors to the Bay Area and for commercial purposes are not included. 3. Provide additional trip details, including trip purpose for each trip in the mode-share question series. 4. Collect demographic data on the population of Bay Area residents who travel to, from, and within San Francisco. 5. Collect data on travel behavior and opinions that support other SFMTA strategy and project evaluation needs.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2026

Travel Decision Survey - San Francisco - 2015

On behalf of the San Francisco Municipal Transportation Agency (SFMTA), Corey, Canapary & Galanis undertook a Travel Decision Survey within the City and County of San Francisco, as well as the eight surrounding Bay Area counties of Alameda, Contra Costa, San Mateo, Marin, Santa Clara, Napa, Sonoma, and Solano. The primary goals of this study were to: 1. Assess percent mode share for travel in San Francisco for evaluation of the SFMTA Strategic Objective 2.3: Mode Share target of 50% non-private auto travel by FY 2018 with a 95% confidence level and margin of error ±5% or less. 2. Evaluate the above statement based on number of trips to, from, and within San Francisco by Bay Area residents. Trips by visitors to the Bay Area and for commercial purposes are not included. 3. Provide additional trip details, including trip purpose for each trip in the mode-share question series. 4. Collect demographic data on the population of Bay Area residents who travel to, from, and within San Francisco. 5. Collect data on travel behavior and opinions that support other SFMTA strategy and project evaluation needs.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2026

Travel Decision Survey - San Francisco - 2017

On behalf of the San Francisco Municipal Transportation Agency (SFMTA), Corey, Canapary & Galanis undertook a Travel Decision Survey within the City and County of San Francisco, as well as the eight surrounding Bay Area counties of Alameda, Contra Costa, San Mateo, Marin, Santa Clara, Napa, Sonoma, and Solano. The primary goals of this study were to: 1. Assess percent mode share for travel in San Francisco for evaluation of the SFMTA Strategic Objective 2.3: Mode Share target of 50% non-private auto travel by FY 2018 with a 95% confidence level and margin of error ±5% or less. 2. Evaluate the above statement based on number of trips to, from, and within San Francisco by Bay Area residents. Trips by visitors to the Bay Area and for commercial purposes are not included. 3. Provide additional trip details, including trip purpose for each trip in the mode-share question series. 4. Collect demographic data on the population of Bay Area residents who travel to, from, and within San Francisco. 5. Collect data on travel behavior and opinions that support other SFMTA strategy and project evaluation needs.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗