Literature Reviews

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Demand-Responsive Transit & Microtransit Definition

Demand-Responsive Transit (DRT) is a flexible transportation service that adapts to the specific travel needs of its users, and is typically shared among users. Instead of following fixed routes and schedules, DRT services are typically booked in advance and operate within a defined area. DRT started decades ago as Dial-a-Ride or paratransit, which serves a specific population (e.g. elderly) or with a specific technology (e.g. phone calls for day-ahead reservations), but has been generalized recently to serve general populations and more advanced communication technologies (e.g., wireless and internet for real-time reservations). As a form of transit, it can serve multiple passengers on a journey, though the service may use anything from passenger cars to small buses to provide the service. It may also include deviated route service, in which an otherwise fixed-route service may make unscheduled stops within a corridor or service zone to pick up or drop off passengers.

Microtransit is a subset of DRT, often characterized by the use of new technologies to optimize and manage the public transit service with a specific focus on either population, spatial coverage or coordination with general public transit. It blends aspects of traditional public transit and private ride-hailing services, offering shared rides that are dynamically routed. Microtransit is generally operated within defined service zones or along a corridor, often with designated stops at key destinations like employment centers or transfer points to other transportation services [1].

References

How Demand-Responsive Transit & Microtransit affects Health

Demand-responsive transit and microtransit can benefit public health by improving accessibility. Microtransit services are often more direct or even door-to-door and can serve users with limited mobility. They typically target users whose transportation needs are not met by traditional public transit, including shift workers, low-income individuals, the elderly, disabled, and communities with low levels of fixed-route public transit service [1], [2]. A study on demand-responsive microtransit programs’ return on social investment found that social benefits can outweigh costs by 4 to 6 times, due to their ability to increase access to essential services, foster social inclusion, and improve sustainability [1].
While there are some case studies on microtransit programs, there is limited research on public health impacts. Additional research is needed to understand the extent to which microtransit can meet transportation needs that are not filled by public transit, and how it can best serve different populations and uses, and how it impacts public health. Some of this research is in progress. For example, the "Safety and Public Health Impacts of Microtransit Services" research initiative at the University of Massachusetts Amherst is currently evaluating safety and public health impacts of microtransit services [3].
Finally, on-demand transit/microtransit programs are often meant to improve equitable access, but there is little research on how to design programs to best meet that goal. Survey data from four US cities found that men, younger riders, the highly educated, and transit riders were more likely to be interested in using microtransit. Additional research is needed to understand who on-demand transit/microtransit most frequently serves, and how that impacts public health across demographic groups.

How Demand-Responsive Transit & Microtransit affects Safety

Passenger safety is one factor that may encourage people to use demand-responsive transit or microtransit, particularly people who are hesitant to take fixed-route public transit. In cases where walking to a fixed route transit stop can be dangerous, like in areas with limited sidewalks and high-speed arterial routes, a door-to-door service can offer a safer journey [1]. In cases where microtransit algorithms select stops for passengers to most efficiently route them, the algorithms may not incorporate local traffic and pedestrian infrastructure, leaving riders exposed to dangerous intersections [2]. Drivers may use their discretion, however, to bring passengers to a safer stopping point and ignore the algorithm’s recommendation. Even microtransit services that are not door-to-door can offer safety improvements over fixed-route services when walk routes are hazardous; microtransit programs designed around a smaller customer base can flexibly tailor their stations to ensure they are both in safe areas to wait and located close to where riders need them, and nimbly alter them based on customer feedback. Ensuring driver competency is key for safe microtransit systems; in cases where pilot programs use private contractors, rather than operators that must follow Federal Transit Administration standards, driver screening may be less stringent [2].

How Demand-Responsive Transit & Microtransit affects Energy and Environment

The environmental benefits of demand-responsive transit and microtransit depend on the types of trips and vehicles they are replacing and generating. In theory, microtransit programs could pool passengers and thereby reduce emissions relative to drive-alone private vehicle trips [1], particularly if they use zero-emission vehicle technology. On-demand microtransit services tend to use vans that seat between four and twelve passengers. But empty vehicles [2], combined with vehicle miles lost to deadheading (trips with no passengers), can in some cases generate more emissions than private driving tips. Microtransit programs function as paratransit in some regions, and are notoriously expensive to provide in large part because they are often underutilized.

Demand responsive transit/microtransit programs in areas with limited public transit may offer a first- last-mile connection to transit, and thus enable less intensive car use. One study of suburban microtransit programs found that the majority of microtransit trips could not have been made with fixed-route public transit, and so microtransit largely either replaced ride-hail and private driving trips or generated new trips [3]. In particular, the study identified that microtransit induced trips among people without access to their own cars, and thus generated new vehicle miles traveled. More research is needed on the emissions and energy impacts of demand responsive transit and microtransit programs.

  1. J. R. Lazarus, J. D. Caicedo, A. M. Bayen, and S. A. Shaheen, “To Pool or Not to Pool? Understanding opportunities, challenges, and equity considerations to expanding the market for pooling,” Transp. Res. Part Policy Pract., vol. 148, pp. 199–222, 2021.

  2. N. Haglund, M. N. Mladenović, R. Kujala, C. Weckström, and J. Saramäki, “Where did Kutsuplus drive us? Ex post evaluation of on-demand micro-transit pilot in the Helsinki capital region,” Res. Transp. Bus. Manag., vol. 32, p. 100390, 2019.

  3. A. M. Liezenga, T. Verma, J. R. Mayaud, N. Y. Aydin, and B. van Wee, “The first mile towards access equity: Is on-demand microtransit a valuable addition to the transportation mix in suburban communities?,” Transp. Res. Interdiscip. Perspect., vol. 24, p. 101071, Mar. 2024, doi: 10.1016/j.trip.2024.101071.

How Demand-Responsive Transit & Microtransit affects Social Equity

On-demand microtransit programs address four aspects of equity: geographic, temporal, economic and social equity. First, microtransit expands transit service by providing flexible routes in lower-density suburban and rural areas where fixed-route services are inefficient or cost-ineffective. Second, microtransit fills gaps in transit operating hours, such as late nights or weekends. Third is economic equity. Microtransit programs are often specifically designed to facilitate commutes and provide a lower-cost alternative to private driving to get to work [2]. Lastly, microtransit placed in disadvantaged neighborhoods can improve mobility access for people who can least afford cars, or people who face mobility barriers, such as elders, low-income individuals, and people with disabilities [3]. Findings are mixed as to whether microtransit programs offer a first-last mile solution to enhance transit ridership, or replace transit trips. Ridership outcomes depend on the specific demands and existing transportation alternatives [1].

  1. E. Martin and S. Shaheen, “Synthesis Report: Findings and Lessons Learned from the Independent Evaluation of the Mobility on Demand Sandbox Demonstrations,” Federal Transit Administration, 0242, Feb. 2023. Accessed: Apr. 02, 2024. [Online]. Available: https://www.transit.dot.gov/research-innovation/synthesis-report-findings-and-lessons-learned-independent-evaluation-mobility

  2. J. Volinski, “Microtransit or General Public Demand-Response Transit Services: State of the Practice,” Transportation Research Board, Washington, D.C., Apr. 2019. doi: 10.17226/25414.

  3. A. M. Liezenga, T. Verma, J. R. Mayaud, N. Y. Aydin, and B. van Wee, “The first mile towards access equity: Is on-demand microtransit a valuable addition to the transportation mix in suburban communities?,” Transp. Res. Interdiscip. Perspect., vol. 24, p. 101071, Mar. 2024, doi: 10.1016/j.trip.2024.101071.

How Demand-Responsive Transit & Microtransit affects Land Use

The success of demand-responsive transit (DRT) and microtransit programs, measured by ridership, depends in part on land use. Whereas traditional fixed-route public transit services are most efficient in densely-populated areas, DRT/microtransit programs offer a smaller-scale alternative that can prove a more cost-effective solution in lower-density suburban and rural areas [1]. There are some exceptions: DRT/microtransit programs in urban areas are sometimes designed to complement fixed-route transit by providing a first-last mile solution to connect riders to transit, or by offering supplemental services for gaps in the transit network (during off-hours, or expanding the service area) [2]. However, evidence that DRT/microtransit can increase transit ridership in cities is mixed [3]. In rural and suburban areas, however, DRT/microtransit may serve particular demographic groups, such as older adults as a form of paratransit, and commuters who can collectively share a service to a specific jobs center [1]. In areas where vehicle ownership and use is high, and the DRT/microtransit service operates in a limited area, ridership can be low [1].

  1. R. Brumfield, “Transforming Public Transit with a Rural On-Demand Microtransit Project,” Federal Transit Administration, 0243, Apr. 2023.

  2. L. Brown, E. Martin, A. Cohen, S. Gangarde, and S. Shaheen, “Mobility on Demand (MOD) Sandbox Demonstration: Pierce Transit Limited Access Connections Evaluation Report,” Federal Transit Administration, 0237, Nov. 2022.

  3. E. Martin and S. Shaheen, “Synthesis Report: Findings and Lessons Learned from the Independent Evaluation of the Mobility on Demand Sandbox Demonstrations,” Federal Transit Administration, 0242, Feb. 2023. Accessed: Apr. 02, 2024. [Online]. Available: https://www.transit.dot.gov/research-innovation/synthesis-report-findings-and-lessons-learned-independent-evaluation-mobility

How Demand-Responsive Transit & Microtransit affects Municipal Budgets

Demand-responsive transit/microtransit services can prove a cost-effective alternative to fixed-route services in rural and outlying areas where people and destinations are spread across large geographies, and the great majority of residents drive [1]. In those cases, a tailored, small scale on-demand service can flexibly meet the needs of a small group of riders better than a larger bus service that operates on a fixed schedule can. For rural transit agencies with a small budget, a microtransit pilot program offers an opportunity to lease vehicles and pay a third-party service provider to operate the program without spending the capital costs, liability and long-term labor costs associated with a permanent in-house microtransit operation. In contrast, in urban regions where densely clustered populations can more efficiently use fixed-route services, a microtransit program can bloat a transit agency’s budget. Traditionally, on-demand transit services have mostly been limited to paratransit rides, which due to low ridership rates (vehicles are often largely empty) and labor costs, are some of the most expensive services to provide per passenger [2].

  1. J. Walker, “What is ‘Microtransit’ For?,” Human Transit. Accessed: Apr. 19, 2024. [Online]. Available: https://humantransit.org/2019/08/what-is-microtransit-for.html

  2. “Transit agencies are paying the price for inefficient paratransit,” Via Transportation. Accessed: May 13, 2024. [Online]. Available: https://ridewithvia.com/resources/transit-agencies-are-paying-the-price-for-inefficient-paratransit

How Demand-Responsive Transit & Microtransit affects Education and Workforce

No specific literature was found; rather the focus of the literature was on the general concerns of how workers with low skills and low wages will be affected by technological substitution and how to manage the transfer of skills.

No references found

How Demand-Responsive Transit & Microtransit affects Transportation Systems Operations (and Efficiency)

Demand-responsive transit (DRT) and microtransit optimization has been studied using models and theoretical networks. From a strategic design perspective, continuous approximations of demand over time and space in highly theoretical networks were used to determine optimal flexible service types as a function of demand density [1], [2], [3], [4]. For tactical decision making, studies have used optimization methods in highly theoretical networks to optimize slack times [5], [6], longitudinal velocities [7], service cycle times [8], and compulsory stop selection and sequence [9]. Finally, from an operations standpoint, previous studies have evaluated policies such as dynamic stations [10], flag stops [4], point deviations[11], and optimal cycle lengths [12] in off-line settings. Few studies have also evaluated real-time operational strategies, such as optimal shuttle departure times [13] and routing/stopping decisions for rail connector services [14]. Generally, previous studies consider highly simplified or theoretical network conditions (e.g., grid networks, uniform travel times and uniform trip types), which can lead to suboptimal decision-making and unrealistic performance estimates. Though there are a number of DRT or microtransit pilots throughout the country, analysis and evaluation of real-world microtransit systems do not necessarily improve the overall system performance on efficiency, accessibility and financial sustainability. There is potential for DRT and microtransit service to be improved by innovative technologies, such as real-time demand prediction, real-time ride requests, coordination with both fixed-route mainline public transit and privately operated ride-hailing or mobility service. Both technologies of sensing, communication and service, and AI-powered algorithms could improve DRT and microtransit performance.

  1. L. Quadrifoglio and X. Li, “A methodology to derive the critical demand density for designing and operating feeder transit services,” Transp. Res. Part B Methodol., vol. 43, no. 10, pp. 922–935, Dec. 2009, doi: 10.1016/j.trb.2009.04.003.

  2. X. Li and L. Quadrifoglio, “Feeder transit services: Choosing between fixed and demand responsive policy,” Transp. Res. Part C Emerg. Technol., vol. 18, no. 5, pp. 770–780, Oct. 2010, doi: 10.1016/j.trc.2009.05.015.

  3. S. M. Nourbakhsh and Y. Ouyang, “A structured flexible transit system for low demand areas,” Transp. Res. Part B Methodol., vol. 46, no. 1, pp. 204–216, Jan. 2012, doi: 10.1016/j.trb.2011.07.014

  4. F. Qiu, W. Li, and A. Haghani, “A methodology for choosing between fixed‐route and flex‐route policies for transit services,” J. Adv. Transp., vol. 49, no. 3, pp. 496–509, Apr. 2015, doi: 10.1002/atr.1289.

  5. L. Fu, “Planning and Design of Flex-Route Transit Services,” Transp. Res. Rec. J. Transp. Res. Board, vol. 1791, no. 1, pp. 59–66, Jan. 2002, doi: 10.3141/1791-09.

  6. B. Smith, M. Demetsky, and P. Durvasula, “A Multiobjective Optimization Model for Flexroute Transit Service Design,” J. Public Transp., vol. 6, no. 1, pp. 81–100, Mar. 2003, doi: 10.5038/2375-0901.6.1.5.

  7. L. Quadrifoglio, R. W. Hall, and M. M. Dessouky, “Performance and Design of Mobility Allowance Shuttle Transit Services: Bounds on the Maximum Longitudinal Velocity,” Transp. Sci., vol. 40, no. 3, pp. 351–363, Aug. 2006, doi: 10.1287/trsc.1050.0137.

  8. J. Zhao and M. Dessouky, “Service capacity design problems for mobility allowance shuttle transit systems,” Transp. Res. Part B Methodol., vol. 42, no. 2, pp. 135–146, 2008.

  9. F. Errico, T. G. Crainic, F. Malucelli, and M. Nonato, “The single-line design problem for demand-adaptive transit systems: a modeling framework and decomposition approach for the stationary-demand case,” Jun. 2020, Accessed: Jul. 16, 2024. [Online]. Available: https://trid.trb.org/View/1749281

  10. F. Qiu, W. Li, and J. Zhang, “A dynamic station strategy to improve the performance of flex-route transit services,” Transp. Res. Part C Emerg. Technol., vol. 48, pp. 229–240, Nov. 2014, doi: 10.1016/j.trc.2014.09.003.

  11. Y. Zheng, W. Li, and F. Qiu, “A Methodology for Choosing between Route Deviation and Point Deviation Policies for Flexible Transit Services,” J. Adv. Transp., vol. 2018, pp. 1–12, Aug. 2018, doi: 10.1155/2018/6292410.

  12. S. Chandra and L. Quadrifoglio, “A model for estimating the optimal cycle length of demand responsive feeder transit services,” Transp. Res. Part B Methodol., vol. 51, pp. 1–16, May 2013, doi: 10.1016/j.trb.2013.01.008.

  13. Z. Wang et al., “Two-Step Coordinated Optimization Model of Mixed Demand Responsive Feeder Transit,” J. Transp. Eng. Part Syst., vol. 146, no. 3, p. 04019082, Mar. 2020, doi: 10.1061/JTEPBS.0000317.

  14. Y. Yu, R. B. Machemehl, and C. Xie, “Demand-responsive transit circulator service network design,” Transp. Res. Part E Logist. Transp. Rev., vol. 76, no. C, pp. 160–175, 2015.

Note: Mobility COE research partners conducted this literature review in Spring of 2024 based on research available at the time. Unless otherwise noted, this content has not been updated to reflect newer research.

Demand-Responsive Transit & Microtransit Definition

Demand-Responsive Transit (DRT) is a flexible transportation service that adapts to the specific travel needs of its users, and is typically shared among users. Instead of following fixed routes and schedules, DRT services are typically booked in advance and operate within a defined area. DRT started decades ago as Dial-a-Ride or paratransit, which serves a specific population (e.g. elderly) or with a specific technology (e.g. phone calls for day-ahead reservations), but has been generalized recently to serve general populations and more advanced communication technologies (e.g., wireless and internet for real-time reservations). As a form of transit, it can serve multiple passengers on a journey, though the service may use anything from passenger cars to small buses to provide the service. It may also include deviated route service, in which an otherwise fixed-route service may make unscheduled stops within a corridor or service zone to pick up or drop off passengers.

Microtransit is a subset of DRT, often characterized by the use of new technologies to optimize and manage the public transit service with a specific focus on either population, spatial coverage or coordination with general public transit. It blends aspects of traditional public transit and private ride-hailing services, offering shared rides that are dynamically routed. Microtransit is generally operated within defined service zones or along a corridor, often with designated stops at key destinations like employment centers or transfer points to other transportation services [1].

References

How Demand-Responsive Transit & Microtransit affects Health

Demand-responsive transit and microtransit can benefit public health by improving accessibility. Microtransit services are often more direct or even door-to-door and can serve users with limited mobility. They typically target users whose transportation needs are not met by traditional public transit, including shift workers, low-income individuals, the elderly, disabled, and communities with low levels of fixed-route public transit service [1], [2]. A study on demand-responsive microtransit programs’ return on social investment found that social benefits can outweigh costs by 4 to 6 times, due to their ability to increase access to essential services, foster social inclusion, and improve sustainability [1].
While there are some case studies on microtransit programs, there is limited research on public health impacts. Additional research is needed to understand the extent to which microtransit can meet transportation needs that are not filled by public transit, and how it can best serve different populations and uses, and how it impacts public health. Some of this research is in progress. For example, the "Safety and Public Health Impacts of Microtransit Services" research initiative at the University of Massachusetts Amherst is currently evaluating safety and public health impacts of microtransit services [3].
Finally, on-demand transit/microtransit programs are often meant to improve equitable access, but there is little research on how to design programs to best meet that goal. Survey data from four US cities found that men, younger riders, the highly educated, and transit riders were more likely to be interested in using microtransit. Additional research is needed to understand who on-demand transit/microtransit most frequently serves, and how that impacts public health across demographic groups.

How Demand-Responsive Transit & Microtransit affects Safety

Passenger safety is one factor that may encourage people to use demand-responsive transit or microtransit, particularly people who are hesitant to take fixed-route public transit. In cases where walking to a fixed route transit stop can be dangerous, like in areas with limited sidewalks and high-speed arterial routes, a door-to-door service can offer a safer journey [1]. In cases where microtransit algorithms select stops for passengers to most efficiently route them, the algorithms may not incorporate local traffic and pedestrian infrastructure, leaving riders exposed to dangerous intersections [2]. Drivers may use their discretion, however, to bring passengers to a safer stopping point and ignore the algorithm’s recommendation. Even microtransit services that are not door-to-door can offer safety improvements over fixed-route services when walk routes are hazardous; microtransit programs designed around a smaller customer base can flexibly tailor their stations to ensure they are both in safe areas to wait and located close to where riders need them, and nimbly alter them based on customer feedback. Ensuring driver competency is key for safe microtransit systems; in cases where pilot programs use private contractors, rather than operators that must follow Federal Transit Administration standards, driver screening may be less stringent [2].

How Demand-Responsive Transit & Microtransit affects Energy and Environment

The environmental benefits of demand-responsive transit and microtransit depend on the types of trips and vehicles they are replacing and generating. In theory, microtransit programs could pool passengers and thereby reduce emissions relative to drive-alone private vehicle trips [1], particularly if they use zero-emission vehicle technology. On-demand microtransit services tend to use vans that seat between four and twelve passengers. But empty vehicles [2], combined with vehicle miles lost to deadheading (trips with no passengers), can in some cases generate more emissions than private driving tips. Microtransit programs function as paratransit in some regions, and are notoriously expensive to provide in large part because they are often underutilized.

Demand responsive transit/microtransit programs in areas with limited public transit may offer a first- last-mile connection to transit, and thus enable less intensive car use. One study of suburban microtransit programs found that the majority of microtransit trips could not have been made with fixed-route public transit, and so microtransit largely either replaced ride-hail and private driving trips or generated new trips [3]. In particular, the study identified that microtransit induced trips among people without access to their own cars, and thus generated new vehicle miles traveled. More research is needed on the emissions and energy impacts of demand responsive transit and microtransit programs.

  1. J. R. Lazarus, J. D. Caicedo, A. M. Bayen, and S. A. Shaheen, “To Pool or Not to Pool? Understanding opportunities, challenges, and equity considerations to expanding the market for pooling,” Transp. Res. Part Policy Pract., vol. 148, pp. 199–222, 2021.

  2. N. Haglund, M. N. Mladenović, R. Kujala, C. Weckström, and J. Saramäki, “Where did Kutsuplus drive us? Ex post evaluation of on-demand micro-transit pilot in the Helsinki capital region,” Res. Transp. Bus. Manag., vol. 32, p. 100390, 2019.

  3. A. M. Liezenga, T. Verma, J. R. Mayaud, N. Y. Aydin, and B. van Wee, “The first mile towards access equity: Is on-demand microtransit a valuable addition to the transportation mix in suburban communities?,” Transp. Res. Interdiscip. Perspect., vol. 24, p. 101071, Mar. 2024, doi: 10.1016/j.trip.2024.101071.

How Demand-Responsive Transit & Microtransit affects Social Equity

On-demand microtransit programs address four aspects of equity: geographic, temporal, economic and social equity. First, microtransit expands transit service by providing flexible routes in lower-density suburban and rural areas where fixed-route services are inefficient or cost-ineffective. Second, microtransit fills gaps in transit operating hours, such as late nights or weekends. Third is economic equity. Microtransit programs are often specifically designed to facilitate commutes and provide a lower-cost alternative to private driving to get to work [2]. Lastly, microtransit placed in disadvantaged neighborhoods can improve mobility access for people who can least afford cars, or people who face mobility barriers, such as elders, low-income individuals, and people with disabilities [3]. Findings are mixed as to whether microtransit programs offer a first-last mile solution to enhance transit ridership, or replace transit trips. Ridership outcomes depend on the specific demands and existing transportation alternatives [1].

  1. E. Martin and S. Shaheen, “Synthesis Report: Findings and Lessons Learned from the Independent Evaluation of the Mobility on Demand Sandbox Demonstrations,” Federal Transit Administration, 0242, Feb. 2023. Accessed: Apr. 02, 2024. [Online]. Available: https://www.transit.dot.gov/research-innovation/synthesis-report-findings-and-lessons-learned-independent-evaluation-mobility

  2. J. Volinski, “Microtransit or General Public Demand-Response Transit Services: State of the Practice,” Transportation Research Board, Washington, D.C., Apr. 2019. doi: 10.17226/25414.

  3. A. M. Liezenga, T. Verma, J. R. Mayaud, N. Y. Aydin, and B. van Wee, “The first mile towards access equity: Is on-demand microtransit a valuable addition to the transportation mix in suburban communities?,” Transp. Res. Interdiscip. Perspect., vol. 24, p. 101071, Mar. 2024, doi: 10.1016/j.trip.2024.101071.

How Demand-Responsive Transit & Microtransit affects Land Use

The success of demand-responsive transit (DRT) and microtransit programs, measured by ridership, depends in part on land use. Whereas traditional fixed-route public transit services are most efficient in densely-populated areas, DRT/microtransit programs offer a smaller-scale alternative that can prove a more cost-effective solution in lower-density suburban and rural areas [1]. There are some exceptions: DRT/microtransit programs in urban areas are sometimes designed to complement fixed-route transit by providing a first-last mile solution to connect riders to transit, or by offering supplemental services for gaps in the transit network (during off-hours, or expanding the service area) [2]. However, evidence that DRT/microtransit can increase transit ridership in cities is mixed [3]. In rural and suburban areas, however, DRT/microtransit may serve particular demographic groups, such as older adults as a form of paratransit, and commuters who can collectively share a service to a specific jobs center [1]. In areas where vehicle ownership and use is high, and the DRT/microtransit service operates in a limited area, ridership can be low [1].

  1. R. Brumfield, “Transforming Public Transit with a Rural On-Demand Microtransit Project,” Federal Transit Administration, 0243, Apr. 2023.

  2. L. Brown, E. Martin, A. Cohen, S. Gangarde, and S. Shaheen, “Mobility on Demand (MOD) Sandbox Demonstration: Pierce Transit Limited Access Connections Evaluation Report,” Federal Transit Administration, 0237, Nov. 2022.

  3. E. Martin and S. Shaheen, “Synthesis Report: Findings and Lessons Learned from the Independent Evaluation of the Mobility on Demand Sandbox Demonstrations,” Federal Transit Administration, 0242, Feb. 2023. Accessed: Apr. 02, 2024. [Online]. Available: https://www.transit.dot.gov/research-innovation/synthesis-report-findings-and-lessons-learned-independent-evaluation-mobility

How Demand-Responsive Transit & Microtransit affects Municipal Budgets

Demand-responsive transit/microtransit services can prove a cost-effective alternative to fixed-route services in rural and outlying areas where people and destinations are spread across large geographies, and the great majority of residents drive [1]. In those cases, a tailored, small scale on-demand service can flexibly meet the needs of a small group of riders better than a larger bus service that operates on a fixed schedule can. For rural transit agencies with a small budget, a microtransit pilot program offers an opportunity to lease vehicles and pay a third-party service provider to operate the program without spending the capital costs, liability and long-term labor costs associated with a permanent in-house microtransit operation. In contrast, in urban regions where densely clustered populations can more efficiently use fixed-route services, a microtransit program can bloat a transit agency’s budget. Traditionally, on-demand transit services have mostly been limited to paratransit rides, which due to low ridership rates (vehicles are often largely empty) and labor costs, are some of the most expensive services to provide per passenger [2].

  1. J. Walker, “What is ‘Microtransit’ For?,” Human Transit. Accessed: Apr. 19, 2024. [Online]. Available: https://humantransit.org/2019/08/what-is-microtransit-for.html

  2. “Transit agencies are paying the price for inefficient paratransit,” Via Transportation. Accessed: May 13, 2024. [Online]. Available: https://ridewithvia.com/resources/transit-agencies-are-paying-the-price-for-inefficient-paratransit

How Demand-Responsive Transit & Microtransit affects Education and Workforce

No specific literature was found; rather the focus of the literature was on the general concerns of how workers with low skills and low wages will be affected by technological substitution and how to manage the transfer of skills.

No references found

How Demand-Responsive Transit & Microtransit affects Transportation Systems Operations (and Efficiency)

Demand-responsive transit (DRT) and microtransit optimization has been studied using models and theoretical networks. From a strategic design perspective, continuous approximations of demand over time and space in highly theoretical networks were used to determine optimal flexible service types as a function of demand density [1], [2], [3], [4]. For tactical decision making, studies have used optimization methods in highly theoretical networks to optimize slack times [5], [6], longitudinal velocities [7], service cycle times [8], and compulsory stop selection and sequence [9]. Finally, from an operations standpoint, previous studies have evaluated policies such as dynamic stations [10], flag stops [4], point deviations[11], and optimal cycle lengths [12] in off-line settings. Few studies have also evaluated real-time operational strategies, such as optimal shuttle departure times [13] and routing/stopping decisions for rail connector services [14]. Generally, previous studies consider highly simplified or theoretical network conditions (e.g., grid networks, uniform travel times and uniform trip types), which can lead to suboptimal decision-making and unrealistic performance estimates. Though there are a number of DRT or microtransit pilots throughout the country, analysis and evaluation of real-world microtransit systems do not necessarily improve the overall system performance on efficiency, accessibility and financial sustainability. There is potential for DRT and microtransit service to be improved by innovative technologies, such as real-time demand prediction, real-time ride requests, coordination with both fixed-route mainline public transit and privately operated ride-hailing or mobility service. Both technologies of sensing, communication and service, and AI-powered algorithms could improve DRT and microtransit performance.

  1. L. Quadrifoglio and X. Li, “A methodology to derive the critical demand density for designing and operating feeder transit services,” Transp. Res. Part B Methodol., vol. 43, no. 10, pp. 922–935, Dec. 2009, doi: 10.1016/j.trb.2009.04.003.

  2. X. Li and L. Quadrifoglio, “Feeder transit services: Choosing between fixed and demand responsive policy,” Transp. Res. Part C Emerg. Technol., vol. 18, no. 5, pp. 770–780, Oct. 2010, doi: 10.1016/j.trc.2009.05.015.

  3. S. M. Nourbakhsh and Y. Ouyang, “A structured flexible transit system for low demand areas,” Transp. Res. Part B Methodol., vol. 46, no. 1, pp. 204–216, Jan. 2012, doi: 10.1016/j.trb.2011.07.014

  4. F. Qiu, W. Li, and A. Haghani, “A methodology for choosing between fixed‐route and flex‐route policies for transit services,” J. Adv. Transp., vol. 49, no. 3, pp. 496–509, Apr. 2015, doi: 10.1002/atr.1289.

  5. L. Fu, “Planning and Design of Flex-Route Transit Services,” Transp. Res. Rec. J. Transp. Res. Board, vol. 1791, no. 1, pp. 59–66, Jan. 2002, doi: 10.3141/1791-09.

  6. B. Smith, M. Demetsky, and P. Durvasula, “A Multiobjective Optimization Model for Flexroute Transit Service Design,” J. Public Transp., vol. 6, no. 1, pp. 81–100, Mar. 2003, doi: 10.5038/2375-0901.6.1.5.

  7. L. Quadrifoglio, R. W. Hall, and M. M. Dessouky, “Performance and Design of Mobility Allowance Shuttle Transit Services: Bounds on the Maximum Longitudinal Velocity,” Transp. Sci., vol. 40, no. 3, pp. 351–363, Aug. 2006, doi: 10.1287/trsc.1050.0137.

  8. J. Zhao and M. Dessouky, “Service capacity design problems for mobility allowance shuttle transit systems,” Transp. Res. Part B Methodol., vol. 42, no. 2, pp. 135–146, 2008.

  9. F. Errico, T. G. Crainic, F. Malucelli, and M. Nonato, “The single-line design problem for demand-adaptive transit systems: a modeling framework and decomposition approach for the stationary-demand case,” Jun. 2020, Accessed: Jul. 16, 2024. [Online]. Available: https://trid.trb.org/View/1749281

  10. F. Qiu, W. Li, and J. Zhang, “A dynamic station strategy to improve the performance of flex-route transit services,” Transp. Res. Part C Emerg. Technol., vol. 48, pp. 229–240, Nov. 2014, doi: 10.1016/j.trc.2014.09.003.

  11. Y. Zheng, W. Li, and F. Qiu, “A Methodology for Choosing between Route Deviation and Point Deviation Policies for Flexible Transit Services,” J. Adv. Transp., vol. 2018, pp. 1–12, Aug. 2018, doi: 10.1155/2018/6292410.

  12. S. Chandra and L. Quadrifoglio, “A model for estimating the optimal cycle length of demand responsive feeder transit services,” Transp. Res. Part B Methodol., vol. 51, pp. 1–16, May 2013, doi: 10.1016/j.trb.2013.01.008.

  13. Z. Wang et al., “Two-Step Coordinated Optimization Model of Mixed Demand Responsive Feeder Transit,” J. Transp. Eng. Part Syst., vol. 146, no. 3, p. 04019082, Mar. 2020, doi: 10.1061/JTEPBS.0000317.

  14. Y. Yu, R. B. Machemehl, and C. Xie, “Demand-responsive transit circulator service network design,” Transp. Res. Part E Logist. Transp. Rev., vol. 76, no. C, pp. 160–175, 2015.

Note: Mobility COE research partners conducted this literature review in Spring of 2024 based on research available at the time. Unless otherwise noted, this content has not been updated to reflect newer research.