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Microtransit services that provide pooled on-demand transportation with dynamic routing have been used in low-density areas since the 1970s, but improvements to routing technology have led to a resurgence of interest in the past decade. Questions remain about the effectiveness of microtransit to serve riders in low-density, car-dependent suburban areas. Better understanding of the factors underlying microtransit ridership can improve usage of these services and shift travelers to more sustainable modes in suburban areas. We compile a database of suburban microtransit programs from 32 public transit agencies in the U.S. to study internal factors (e.g., operating hours, service area) and external factors (e.g., population density, vehicle ownership) impacting ridership using a random effects model. We find that internal agency factors have a greater effect on microtransit ridership than external factors. The most impactful factor is operating a point deviation service, where vehicles have scheduled stops at one or more checkpoints within the service area (e.g., transit center or shopping center), rather than zone-based services, where vehicles pick up and drop off passengers at any time within a service area. There is high potential to convert some zone-based services to point deviation services; 52% of zone-based service areas contain a transit center that could be used as a checkpoint. For the remaining zone-based service areas, maximizing ridership may not be feasible, and using ridership as an evaluation metric can be misleading. Instead, metrics that capture the accessibility, safety, or customer satisfaction impacts of microtransit may be more appropriate for these services.

Shared on-demand mobility services, also known as microtransit, have become a major mobility provider around the world, yet this has predominantly taken place within urban areas. In areas with lower population density and poor quality public transport, such services could substantially improve accessibility. In early 2023, a regional microtransit pilot was carried out in the Ljubljana Urban Region in Slovenia. To assess the preferences towards such a service, a stated preference experiment is carried out among pilot participants, comparing car, public transport and microtransit for their daily commute. The obtained data is modelled using a Panel mixed logit model, with random parameters modelled as normally or log-normally distributed. Additionally, we also model for potential nesting effects among the alternatives. The results show participants perceive microtransit as a viable alternative, with public transport commuters finding it particularly attractive, whereas car commuters see it on par with the car. Parking price and a guaranteed parking spot tended to be key factors for decision-making. Simulating different policies, we conclude that combining subsidising microtransit and higher parking prices is the most effective strategy for achieving a modal shift primarily from car to microtransit while not affecting public transport as much.

With advances in emerging technologies, options for operating public transit services have broadened from conventional fixed-route service through semi-flexible service to on-demand microtransit. Nevertheless, guidelines for deciding between these services remain limited in the real implementation. An open-source simulation sandbox is developed that can compare state-of-the-practice methods for evaluating between the different types of public transit operations. For the case of the semi-flexible service, the Mobility Allowance Shuttle Transit (MAST) system is extended to include passenger deviations. A case study demonstrates the sandbox to evaluate and existing B63 bus route in Brooklyn, NY and compares its performance with the four other system designs spanning across the three service types for three different demand scenarios.

Electric Level 4 connected automated vehicles (CAVs) are now allowed to demonstrate their automation capability in shared mobility robotaxi and microtransit services in geofenced areas in several cities around the world. Private and public sector stake-holders need predictions of their adoption without regulatory constraints for personal mobility and use in shared mobility services. In anticipation of the future presence of CAVs in transportation vehicle fleets, governments are planning necessary regulatory and infrastructure changes. Accompanying this need for forecasts is the acknowledgement that CAV adoption decisions must be made under uncertain states of technology and infrastructure readiness. This paper presents a Bayesian predictive modelling framework for electric Level 4 CAV adoption in the 2030–2035 application context. The inputs to the Bayesian model are obtained from effectiveness estimates of CAV applications that are processed with the Monte Carlo method to account for uncertainties in these estimates. Scenarios of CAV adoption in the 2030–2035 period are analyzed using the Bayesian model, including the quantification of the value of new information obtainable from demonstration studies intended to reduce uncertainties in technology and infrastructure readiness. The results show that in the 2030–2035 application context, the CAVs are likely to be adopted, provided that the trajectory of progress in technology and infrastructure readiness continues, and potential adopters are offered opportunities to learn about Level 4 CAV technological capabilities in a real life service environment. The threshold level of the probability of adoption enhances significantly with high-reliability demonstration results that can reduce uncertainties in adoption decisions. The findings of this research can be used by private and public sector interest groups.

Electric-connected automated vehicle (CAV) shuttles, as a part of the sustainable microtransit system, have the potential to fill public transit service gaps. Following technology and traveler acceptance tests that are underway around the world, mass-produced CAVs will be considered for shared mobility service, including “first/last mile” travel between public transit hub stations and medical campuses or other activity centres. Thus, there is a need for increased knowledge on treating risk in such applications. This paper covers the planning and economic feasibility of an advanced technology level 4 automated vehicle-based microtransit system, considering uncertain service and economic feasibility factors. The methods used are advanced for addressing uncertainties in travel demand, service factors, and the economic feasibility of investments by public and private sector entities. Specifically, a probability-based macro simulation approach is used to treat demand and supply-side service factors as stochastic, and it is adapted for risk analysis in financial decision-making. The effects of uncertain life-cycle costs on fares and the rate-of-return are described. Results are favourable regarding the technical and economic feasibility of advanced technology-based microtransit first/last mile service. The findings reported here are a contribution to knowledge on the feasibility of implementing CAV-based first/last mile, and other microtransit services, under uncertainty.

In recent years, the passenger flow volume of conventional transit in major cities has declined steadily. Ground public transit often suffers from congestion during rush hours caused by frequent stops (e.g., conventional fixed-route buses) or excessively high operating costs (e.g., demand-responsive transit). While rail transit offers reliable service with dedicated right-of-way, its high capital and operational costs pose challenges for integrated planning with other transit modes. The joint design of rail, conventional buses, and DRT remains underexplored. To bridge this gap, this paper proposes and analyses a new hybrid transit system that integrates conventional transit service with demand-adaptive transit (DAT) to feed urban rail transit (the system hence called hybrid microtransit system). The main task is to optimally design the hybrid microtransit system to allocate resources efficiently across different modes. Both the conventional transit and DAT connect passengers from their origin/destination to the rail transit stations. Travelers can choose one of the services to access urban rail transit, or directly walk. Accordingly, we divide the service area into three parts and compute the user costs to access rail transit by conventional transit and DAT. The optimal design problem is hence formulated as a mixed integer program by minimizing the total system cost, which includes both the user and agency (operating) costs. Numerical experiment results demonstrate that the hybrid microtransit system performs better than the system that only has conventional transit to feed under all demand levels, achieving up to a 7% reduction in total system cost. These may provide some evidence to resolve the “first-mile” challenges of rail transit in megacities by designing better conventional transit and DAT.

On-demand microtransit services are frequently seen as an important tool in supporting first and last mile operations surrounding fixed route high frequency transit facilities, but questions remain surrounding who will use these novel services and for what purposes. In November 2019, the Utah Transit Authority launched an on-demand microtransit service in south Salt Lake County in partnership with a private mobility operator. This paper reports the results of an expressed preferences survey of 130 transit riders in the microtransit service area that was collected before and immediately after the service launched. There is not a clear relationship between current transit access mode and expressed willingness to use microtransit, although some responses from new riders indicate the novel service competes most directly with commercial transportation network company operations. The survey responses also reveal younger passengers express a more than expected willingness to use microtransit, middle-aged passengers a less than expected willingness, and older passengers neutral or no expressed opinion. The results suggest additional relationships between household size and transit use frequency, but further research is necessary. The effect of other user characteristics, including income and automobile availability, is less statistically clear and requires further research.

The increasing global focus on sustainability is bringing the question of the sustainability of transport systems—which are still exhibiting numerous negative effects as evidence of their unsustainability—to the fore. While sustainability is an often-discussed concept, tools to guide the practical implementation thereof are limited. This paper presents a framework for an inventory of indicators against which to measure the sustainability of transport systems. While the framework is validated for urban transport systems for increased mobility (here referenced as microtransit systems), the concept is investigated in the context of transport systems in general. A systematic review of the literature was used to develop a framework of 12 areas and 50 indicators of sustainability. Expert reviews, an Analytical Hierarchical Process (AHP), and an Equally Weighted Average (EWA) method were employed to allocate weights to the indicators and to validate the framework for microtransit systems. The framework contributes to the literature by identifying, categorizing, and integrating concepts related to sustainability in transport systems. It is intended to aid short-term decision-making in the design of urban transport systems, to continuously monitor the long-term progress of transport systems against sustainability goals, and to guide policy development. Future work would include enhanced empirical validation of the framework in the context of other types of transport systems, beyond microtransit.

The concept of sharing, enabled by emerging technologies, is playing an increasingly important role in contributing to a transformation toward more sustainable transportation. This study aimed to contribute to the growing body of literature on on-demand transportation services, with a particular emphasis on sharing or pooling a ride when using services such as transportation-network companies (TNCs) and microtransit. The study conducted a shared mobility survey of over 2,500 respondents from selected locales across Texas—ranging from large urban areas to small cities and rural areas. We analyzed the survey data in detail using extensive statistical analysis and inferential techniques and adopted an analysis approach toward implementation-oriented research to address the gap between theory and practice. Demographic, as well as geographic and built-environment, factors were found to play an important role in determining whether users will opt for a shared or pooled service and/or how they perceive these alternatives. The findings highlight the importance of improving safety and security, increasing awareness of the benefits of ride-sharing, and designing appropriate policy measures to promote sustainable mobility. We identified potential operational improvements, government policies, and employer programs to improve shared-ride services and encourage their use, such as reducing uncertainty in shared rides and minimizing inconvenience for passengers. A critical finding was the need to prioritize operational improvements in shared-ride trips over solely relying on financial incentives to induce behavior change. Enhanced public awareness and education were also determined to be crucial regardless of the nature of improvements, policies, or programs that are implemented.

Microtransit is a shared mobility service that operates between fixed-route transit and ride-hailing. It operates with a fleet of vans or minibuses within a service zone that is usually located in a rural or suburban car-oriented area with a transport demand that is temporally and spatially dispersed. Microtransit often expects customers to walk a short distance to pick-up/drop-off (PUDO) locations. The PUDO points need to be quickly, easily, and safely reachable by pedestrians. Thus, PUDO locations must be chosen after analyzing the walkability of the suburban area served by microtransit. This paper presents a comparison of macroscale and microscale indicators to assess the walkability of suburban neighborhoods where microtransit has to be introduced. We chose three suburban neighborhoods (Partanna Mondello, Tommaso Natale, and Mondello) in Palermo, Italy, as a study area, aiming to identify the best places to locate PUDO stops for a microtransit service. A GIS database has been built associating each link with a series of qualitative and quantitative attributes. Finally, we developed a walkability index that indicates the attractiveness of specific locations in terms of intermodal walkability. We also identified the critical pedestrian links that need actions to improve their walkability.