Search

With increasing urbanization and the demand for efficient, flexible transportation solutions, demand-responsive transportation services (DTRS) has emerged as a viable alternative to traditional public transit. However, determining the optimal fleet size to balance the investment and operational revenue remains a significant challenge for service providers. In this article, we address the optimization of fleet size in point-to-point shared demand DRTS, which widely operates within many cities. To capture the uncertain passenger demands in the future when planning the fleet size currently, we model this problem with a framework of two-stage stochastic programming with recourse. Fleet sizing decisions are made in the first stage before the uncertain demands are revealed. After the uncertainty is revealed, the second stage involves making additional decisions to maximize operational revenue. The objective is to optimize the total revenue of the first-stage decisions and the expected revenue of the recourse actions. To solve this practical problem, we resort to the Model Predictive Control method (MPC) and propose a network decomposition approach that first converts the transportation network to a nodal tree structure and then develops a Nodal Tree Recourse with Dependent Arc Capacities (NTRDAC) algorithm to obtain the exact value of the expected recourse functions. In the experiments, NTRDAC is able to produce results within seconds for transportation networks with over 30 nodes. In contrast, a commercial solver is only capable of solving networks with up to five nodes. The stability tests show that NTRDAC remains robust as the problem size varies. Lastly, the value of the stochastic solution (VSS) was evaluated, and the results indicate that it consistently outperforms the expected value solutions. Numerical experiments show that the performance of the NTRDAC algorithm is quite encouraging and fit for large-scale practical problems. [ABSTRACT FROM AUTHOR]

The integration of shared bikes and flexible transit services offers significant potential and benefits for urban transit systems. This paper presents a novel robust optimization framework for designing demand responsive connectors (DRC) that are fed by shared bikes. A two-stage model is formulated, with the first stage focusing on prereserved requests and the second stage addressing en-route random requests. The findings demonstrate that incorporating shared bikes can enhance the efficiency of serving en route late requests and reduce the required DRC vehicle fleet size. Additionally, it is observed that e-bikes are particularly suitable for this joint service due to their adaptability. [ABSTRACT FROM AUTHOR]

This article explores the theme of public transport in African literatures and aims to bridge the gap between mobilities research and African literary studies. It acknowledges the criticism that mobilities scholarship often focuses on the Global North and neglects experiences in the Global South. The article argues for a nuanced approach that considers historical and contextual specificities when studying African literary mobilities. It also emphasizes the importance of shedding light on local, intra-African forms of mobility and challenges the binary distinction between formal and informal public transportation. The article concludes by discussing the limited attention given to public transport in African literary studies and highlights the need to study its literary dimensions. The special issue of the journal further explores the politics and representations of public transport mobilities in African literatures, addressing topics such as accessibility, class, race, and the role of public transport in post-colonial societies. The studies emphasize the interconnected nature of public transport mobilities and call for more research in this area with a broader regional scope. [Extracted from the article]

The Global South, encompassing more than 80% of the world population, heavily relies on informal paratransit services with ad-hoc routes. Yet, it remains unclear how efficiently such informal public transport services organize and operate. Here, we analyze and compare the structural efficiency of more than 7000 formal and informal bus service routes in 36 cities across 22 countries globally. Intriguingly, informal transport self-organizes in ways at or above efficiency levels of centralized services. They exhibit fewer detours, more uniform paths, and comparable interconnectivities, all while remaining profitable without the major subsidies common in the Global North. These insights challenge the global perception of informal transport as an inferior alternative to centrally organized services. More generally, analyzing large-scale microscopic transport data and condensing them into informative macroscopic observables may qualitatively improve system understanding and reveal specific options to create more accessible, efficient, and sustainable public transport solutions. Informal transportation services constitute the primary form of public transport in the Global South. Here, the authors analyze the structure of route networks in cities across the globe, showing how informal routes self-organize into consistent line services that often outperform centralized services in the Global North, exhibiting fewer detours and comparable interconnectivity. [ABSTRACT FROM AUTHOR]

Modern on-demand mobility concepts have the potential to drive the mobility transition. Increasing attention is being paid to DRT (Demand Responsive Transportation) services that enable the bundling of trips with the help of dynamic routing algorithms. Many providers use a stop-based operating concept for this purpose. The transport between so-called virtual stops promises a higher fraction of shared trips and shorter vehicle detours. The aim of this paper is to investigate multiple stop network designs and their impacts on the efficiency of the operation. For this purpose, three stop network generation approaches were derived from literature and applied to the simulation environment MATSim. A scenario in the city center of Berlin is simulated, where all inner car trips are replaced by DRT. Comparing the stop network design against a door-to-door service, the results suggest a trade-off between a reduction of vehicle kilometers (up to 18%) and increased walking distances (up to 250 meters on average). [ABSTRACT FROM AUTHOR]

The intensity of local truck container transport results from the ubiquitous development of container shipping. Optimal routing of container trucks contributes to cost savings of the service provider but also the reduction of traffic and detrimental emissions. In this paper, a variant of a Mixed Fleet Heterogeneous Dial-a-Ride Problem is proposed for a container truck routing problem. Our aim is an optimal routing of trucks carrying full and empty 20-foot and 40-foot containers, with multiple pick-ups and deliveries. Transportation is performed by alternatively fuelled vehicles (AFVs) for environmental reasons. The AFVs have a limited driving range and are allowed to refuel in any alternative fuel station. The main objective is minimising the total distance subject to matching the empty container demand and supply, necessary refuelling of the trucks, and service time windows. [ABSTRACT FROM AUTHOR]

Autonomous vehicles are anticipated to revolutionize ride-sharing services and subsequently enhance the public transportation systems through a first–last-mile transit service. Within this context, a fleet of autonomous vehicles can be modeled as a Dial-a-Ride Problem with certain features. In this study, we propose a holistic solving approach to this problem, which combines the mixed-integer linear programming formulation with a novel graph dimension reduction method based on the graph embedding framework. This latter method is effective since accounting for heterogeneous travel demands of the covered territory tends to increase the size of the routing graph drastically, thus rendering the exact solving of small instances computationally infeasible. An application is provided for the real transport demand of the industrial district of "Vallée de la Chimie" in Lyon city, France. Instances involving more than 50 transport requests and 10 vehicles could be easily solved. Results suggest that this method generates routes of reduced nodes with lower vehicle kilometers traveled compared to the constrained K-means-based reduction. Reductions in terms of GHG emissions are estimated to be around 75% less than the private vehicle mode in our applied service. A sensitivity analysis is also provided. [ABSTRACT FROM AUTHOR]

Dial a ride problem (DARP) is a complex version of the pick-up and delivery problem with many practical applications in the field of transportation. This study proposes an enhanced deterministic annealing algorithm for the solution of large-scale multi-vehicle DARPs. The proposed method always explores the feasible search space; therefore, a feasible solution is guaranteed at any point of termination. This method utilises advanced local search operators to accelerate the search for optimal solutions and it relies on a linearly decreasing deterministic annealing schedule to limit poor jumps during the course of search. This study puts forward a systematic series of experiments to compare the performance of solution methods from various angles. The proposed method is compared with the most efficient methods reported in the literature i.e., the Adaptive Large Neighbourhood Search (ALNS), Evolutionary Local Search (ELS), and Deterministic Annealing (DA) using standard benchmarks. The results suggest that the proposed algorithm is on average faster than the state-of-the-art algorithms in reaching competitive objective values across the range of benchmarks. [ABSTRACT FROM AUTHOR]

The nature of paratransit services makes for increased uncertainty in trip time, leading to reported unreliability and dissatisfaction by the users. While providing travel information has proved helpful in formal bus services and has been recommended for paratransit setup, little is reported about efforts at providing information to paratransit users. This study focused on one strand of possible travel information that can be provided - Travel Time. An artificial neural network (ANN)-based model was developed to predict paratransit travel times, geared towards providing information to improve user experiences. The developed model was tested on a real-world paratransit bus route (minibus taxi) in Kumasi. A travel time survey that employed a mobile phone application was used to collect data onboard the vehicles on the study route. Two ANN models were trained. The first used only historical datasets, while the second incorporated real-time information. The results show that the model in which real-time information was included performed better than that trained with only historical data. The developed models were compared with a historical average model and a regression-based model, and the results showed that the ANN models outperformed the others. The study showed that the nature of paratransit services and the limitations of continuous data collection, notwithstanding, travel times of paratransit trips can be predicted to a reasonable level of accuracy, as can be relied upon in providing information to the users. [ABSTRACT FROM AUTHOR]

It is widely acknowledged that geographic data in Ghana and most of Sub-Sahara Africa is patchy, and lack geographic coverage and detail. This has implications for mobility and access to socioeconomic, and cultural opportunities which require address and location data typically provided through geocoding. A critical component of geocoding is a reference database to lookup matching address and location information. Accordingly, we investigate the suitability of, and the use of electoral polling stations to build a reference database for geocoding. This was undertaken by mapping their geographic coordinates, analyzing their geographic spread and detail, and outlining the database structure for building the reference database. Using the 2020 electoral polling station data for the Greater North area of Ghana, we found that 93% of the geographic coordinates can be obtained from open data sources. Also, there is high proximity with a nearest neighbor distance of 663 m, a reasonable service area of 4300 m, and a median distance of 3700 m from a community location. The widespread availability, large geographic spread and moderate detail, make polling stations a creditable data source for geocoding. It is recommended the polling station data be augmented with a detailed geographic data like those from landmarks and paratransit service. [ABSTRACT FROM AUTHOR]

Conventional public transport systems in developing countries such as the Lao People's Democratic Republic (Lao PDR), are commonly substandard, unreliable, and often have insufficient accessibility and connectivity. In many cases, paratransit, utilizing various passenger vehicles (such as trucks, TukTuks, and motorcycles), compensate for the deficiencies of conventional public transport, offering a valuable alternative for passengers. For developing nations, enhancing conventional public transport or introducing new modes requires considerable time and investment, resources that may be limited. As an alternative, this study investigates the feasibility of transforming paratransit services into Demand Responsive Transit (DRT), aiming to formalize and integrate them with existing public transport, thereby improving connectivity, accessibility, and increasing the public transport mode share. To assess the potential acceptance, future demand, and mode share of DRT in Vientiane, Lao PDR, we conducted an opinion and stated preference survey, employed a multinomial logit choice model, and used an origin-to-destination network assignment model. The findings suggest that respondents are keen on using DRT in conjunction with Bus Rapid Transit (BRT) in the future. The modeled results indicate a significant potential increase in the public transit mode share. [ABSTRACT FROM AUTHOR]

The transportation sector in India faces significant issues, such as congestion and air pollution, and is in dire need of sustainable strategies. Sharing vehicles is one of the popular sustainable strategies. Sharing auto-rickshaws, a paratransit mode, currently informally operating with a significant mode share, offers an opportunity to tackle sustainability issues. There are several challenges to integrating and promoting auto-rickshaw system as shared transportation using a formal structure of policies. The primary reason is a dearth of studies on sharing auto-rickshaws, leading to policymakers lacking knowledge and focus. The present study contributes to the literature to divert focus on sharing auto-rickshaws in India, considering Mumbai Metropolitan Region (MMR) as a study area. This study attempts to assess and model the intentions of users and non-users toward auto-rickshaw sharing using stated preference (SP) choice experiments and estimate Willingness-to-Pay (WTP) considering multiple socio-economic heterogeneities. Results highlight that the most critical attributes are travel time reliability and access time among different groups. Importance of having real-time information on trips among females and sharing auto-rickshaw users is high. The study provides a transparent direction toward ensuring efficient and integrated policymaking and guidelines for promoting auto-rickshaw sharing in urban areas of the Indian subcontinent with limited resources. • Perception of users and non-users of sharing auto-rickshaws are compared. • Segmentation analysis is used to assess heterogeneity among different subgroups. • Willingness to pay for the subgroups is estimated by Mixed-logit modeling. • Travel time reliability and Access time are most important for all sub-groups. • Clear direction to promote auto-rickshaw sharing and integrate it into policymaking. [ABSTRACT FROM AUTHOR]

In several transportation systems, vehicles can choose where to meet customers rather than stopping in fixed locations. This added flexibility, however, requires coordination between vehicles and customers that adds complexity to routing operations. This paper develops scalable algorithms to optimize these operations. First, we solve the one-stop subproblem in the ℓ 1 space and the ℓ 2 space by leveraging the geometric structure of operations. Second, to solve a multistop problem, we embed the single-stop optimization into a tailored coordinate descent scheme, which we prove converges to a global optimum. Third, we develop a new algorithm for dial-a-ride problems based on a subpath-based time–space network optimization combining set partitioning and time–space principles. Finally, we propose an online routing algorithm to support real-world ride-sharing operations with vehicle–customer coordination. Computational results show that our algorithm outperforms state-of-the-art benchmarks, yielding far superior solutions in shorter computational times and can support real-time operations in very large-scale systems. From a practical standpoint, most of the benefits of vehicle–customer coordination stem from comprehensively reoptimizing "upstream" operations as opposed to merely adjusting "downstream" stopping locations. Ultimately, vehicle–customer coordination provides win–win–win outcomes: higher profits, better customer service, and smaller environmental footprint. This paper was accepted by Chung Piaw Teo, optimization. Funding: This research was supported by the National Natural Science Foundation of China [Grants 72288101, 52221005 and 52220105001]. Supplemental Material: The e-companion and data are available at https://doi.org/10.1287/mnsc.2023.4739. [ABSTRACT FROM AUTHOR]

The fixed route dial-a-ride problem (FRDARP) is a variant of the famous dial-a-ride problem, in which all the requests are chosen between terminals that are located along a fixed route. A reduction to the shortest path problem enables finding an optimal solution for FRDARP in polynomial time. However, the basic graph construction ends up with a huge graph, which makes the reduction impractical due to its memory consumption. To this end, we propose several pruning heuristics that enable us to considerably reduce the size of the graph through its dynamic construction. Additionally, we utilize the special features of the problem to apply parallelization to the graph traversal process. Our experiments show that each of the proposed heuristics on its own improves the practical solvability of FRDARP. Moreover, using them together is considerably more efficient than any single heuristic. Finally, the experiments confirm the efficiency of our suggested parallelization policy. [ABSTRACT FROM AUTHOR]

The dial-a-ride problem (DARP) is that of satisfying a number of pickup and drop-off customer requests, using a fleet of vehicles. In real life, traffic conditions can affect expected travel times, and hence the satisfaction of rigid pickup/drop-off time windows and scheduled ride times. This article considers the DARP with customer-adaptive ride times under different service conditions and strategies. The problem is formulated as a mixed integer linear programming model that minimizes service cost and customer inconvenience. A hybrid genetic–variable neighbourhood search algorithm (GAVNS) is proposed to solve the problem. Experiments are conducted to compare the performance of GAVNS with that of an approximate column generation algorithm, and to evaluate the application of different strategies on service efficiency and customer satisfaction. The results demonstrate the efficiency of GAVNS, and that limited violations of time-window and ride-time constraints can improve the service efficiency while preserving customer satisfaction levels. [ABSTRACT FROM AUTHOR]

Transportation has an important role in people's lives, where the rate of population growth is getting higher, which results in an increase in people's need for transportation. This can increase the use of public transport transportation; this problem is closely related to the traffic flow network, especially in the city of Makassar in the Tamalanrea sub-district. The application of the feeder transport line in the city of Makassar is one form of solution to the problems that occur in the city of Makassar, namely the traffic flow network. Based on the results of the planning of the Feeder Transport Route Model, the route that has been researched can be a solution to reduce congestion on the main road, where public transportation types Metromini can be diverted to local routes with planned routes and road types, which can meet the type of public transport Metromini. For public perception, it is more dominant to agree if the feeder system is implemented in Makassar. The purpose of this study was to determine the performance of feeder transport if applied in the city of Makassar. It can be seen from the number of conflicts that have occurred due to the increasing number of public transport vehicles on the main roads of the city of Makassar. [ABSTRACT FROM AUTHOR]

Public agencies have subsidized taxi rides for people who have difficulty driving a car or using the regular transit system – targeting older residents and people with disabilities. There is interest among public agencies to add transportation network companies (TNCs), such as Uber and Lyft, to subsidized ride programs as a travel option due to the widespread availability of TNCs and high-quality service. Key issues include the need for wheelchair accessible vehicles, subsidy needs, and clients who lack or are uncomfortable using a smartphone and credit card. This research included a review of programs nationwide and interviews with program managers and clients to identify best practices. Best practices from agencies included contracting for wheelchair accessible TNC services, offering classes to help clients learn how to use the needed technologies, arranging for prepaid debit cards, creating a centralized billing system, providing a concierge service for those who need extra assistance, and setting subsidies based on need. Other recommended practices include providing high travel needs coverage, developing straightforward pricing structures, and not imposing restrictions on trip distance or trip purposes eligible for subsidy.

Public agencies have subsidized taxi rides for people who have difficulty driving a car or using the regular transit system – targeting older residents and people with disabilities. There is interest among public agencies to add transportation network companies (TNCs), such as Uber and Lyft, to subsidized ride programs as a travel option due to the widespread availability of TNCs and high-quality service. Key issues include the need for wheelchair accessible vehicles, subsidy needs, and clients who lack or are uncomfortable using a smartphone and credit card. This research included a review of programs nationwide and interviews with program managers and clients to identify best practices. Best practices from agencies included contracting for wheelchair accessible TNC services, offering classes to help clients learn how to use the needed technologies, arranging for prepaid debit cards, creating a centralized billing system, providing a concierge service for those who need extra assistance, and setting subsidies based on need. Other recommended practices include providing high travel needs coverage, developing straightforward pricing structures, and not imposing restrictions on trip distance or trip purposes eligible for subsidy.

This research brief summarizes the findings from the associated study, which examined the potential to improve transportation system efficiency by reevaluating and redefining the role of public transit and its design principles in the new context of technology and shared mobility. Specifically, it evaluated the financial feasibility of an integrative, multimodal transportation system where public and private mobility services coexist to maximize economic and environmental benefits and free up public transit resources to be reallocated more efficiently.

Low-income rural residents, especially those who do not own a car, have limited transportation options for accessing jobs, health care, education, healthy food, and other basic services. Rural transit service is often expensive, infrequent, and hard to access because of long travel distances and low development densities. Transit providers face very high operating costs of fixed-route and dial-a-ride transit services because of low farebox recovery rates.Shared-use mobility services such as ridehailing and carsharing largely serve major metropolitan areas. However, rural governments are beginning to consider whether these types of services may be able to augment existing transit services while providing cost-effective transportation access to rural residents.This policy brief summarizes findings from a UC Davis study in which researchers compared the cost-effectiveness of existing inter-city transit service in rural disadvantaged communities in California’s San Joaquin Valley to hypothetical ridesharing and carsharing services. The researchers also reviewed existing shared-use mobility pilots and consulted with experts in shared mobility and local transportation planning to develop concepts for future shared mobility pilot programs in the San Joaquin Valley.View the NCST Project Webpage

We consider the open, non-preemptive online Dial-a-Ride problem on the real line, where transportation requests appear over time and need to be served by a single server. We give a lower bound of 2.0585 on the competitive ratio, which is the first bound that strictly separates open online Dial-a-Ride on the line from open online TSP on the line in terms of competitive analysis, and is the best currently known lower bound even for general metric spaces. On the other hand, we present an algorithm that improves the best known upper bound from 2.9377 to 2.6662. The analysis of our algorithm is tight. [ABSTRACT FROM AUTHOR]

Shared mobility services involving electric autonomous shuttles have increasingly been implemented in recent years. Because of various restrictions, these services are currently offered on fixed circuits and operated with fixed schedules. This study introduces a service variant with flexible stopping patterns and schedules. Specifically, in the electric dial-a-ride problem on a fixed circuit (eDARP-FC), a fleet of capacitated electric shuttles operates on a given circuit consisting of a recharging depot and a sequence of stations where passengers can be picked up and dropped off. The shuttles may perform multiple laps, between which they may need to recharge. The goal of the problem is to determine the vehicles' stopping sequences and schedules, including recharging plans, so as to minimize a weighted sum of the total passenger excess time and the total number of laps. The eDARP-FC is formulated as a nonstandard lap-based mixed integer linear programming and is shown to be NP-Hard. Efficient polynomial time algorithms are devised for two special scheduling subproblems. These algorithms and several heuristics are then applied as subroutines within a large neighborhood search metaheuristic. Experiments on instances derived from a real-life system demonstrate that the flexible service results in a 32%–75% decrease in the excess time at the same operational costs. Funding: This work was supported by the Fonds Wetenschappelijk Onderzoek [Project Data-Driven Logistics: Grant S007318N; Project Optimizing the Design of a Hybrid Urban Mobility System: Grant G020222N; and Grant OR4Logistics]. Y. Molenbruch is partially funded by the Fonds Wetenschappelijk Onderzoek [Grant 1202719N]. The computational resources and services used in this work were provided by the Flemish Supercomputer Center funded by the Fonds Wetenschappelijk Onderzoek and the Flemish Government. Supplemental Material: The electronic companion is available at https://doi.org/10.1287/trsc.2023.1208. [ABSTRACT FROM AUTHOR]

The Government of India has approved e-rickshaws in 2015 to make paratransit services more environmentally friendly. This approval has resulted in a substantial influx of e-rickshaws across India, but little is known about the demand side of e-rickshaws. By collecting stated preferences and revealed travel patterns of 800 respondents from the city of Gurugram, we quantify the individuals' willingness to shift to e-rickshaws from their current travel mode and their willingness to pay to use e-rickshaws for their first-mile travel. Our results indicate that e-rickshaws are perceived as a cheaper travel mode, perhaps the predominant factor driving the shift of a large demand to e-rickshaws. Moreover, e-rickshaws are likely to take away market share from other paratransit modes and walking instead of personalized travel modes. Thus, the net congestion and emission impact of e-rickshaws need to be evaluated in deciding the number of e-rickshaws allowed to operate in a city. [ABSTRACT FROM AUTHOR]

Demand response (DR) is considered as one of the most important measures for balancing energy supply and demand in the smart grid paradigm. Incentive-based programs, one manifestation of DR, contribute to short-term system stability and prevent critical periods when system stability is at risk by enabling the system operator (SO) to directly change total energy demand. The fact that a third party would be empowered to interfere with internal operations is, however, also one of the major drawbacks of DR that prevents especially industrial consumers from participating with full capacity in such programs. This paper considers an alternative Incentive-based program with application to a discrete manufacturing facility where load reduction curves (LRCs) are generated a priori outlining the potential load reduction in the DR period. The SO uses the LRC to determine the desired level of load reduction for critical periods. To illustrate the generation of the LRC, this paper builds on a flexible flow shop (FFS) formulation for a discrete manufacturing facility and presents a model that includes multiple machine modes and product- and machine-specific energy consumption trajectories. Based on the FFS, a procedure is developed to generate the LRC. The paper also investigates the potential of including a battery energy storage system (BESS) into the production facility and illustrates the effects of the BESS on the LRC. [ABSTRACT FROM AUTHOR]

Ideally, public transit, by moving more people using fewer vehicles, serves as a backbone of a transportation system. However, most transit systems in the United States suffer from low ridership and high operating costs, thus they provide a significantly compromised mobility service to the transportation system users. Under current transit system design principles, such as service area requirements, inefficiencies in resource use are almost inevitable. Given the opportunities brought by new mobile technology and the environment of mobility as a service, current transit system design principles need to be reevaluated and redefined to enable transit to serve as a backbone in the transportation system. In this seed-grant project, the researchers evaluated whether building an integrated multimodal public transportation system via reallocation of transit resources is financially feasible and environmentally sustainable. They also conducted an in-depth review of related literature and discussed other concerns regarding an integrated system. Based on the results from the case study and review of other recent studies, the authors draw an optimistic conclusion about an integrated service system where public and private mobility service providers coexist.

The dial-a-ride problem with time windows is studied in this article. First, a new efficient mixed integer programming formulation is proposed by merging some of drop-off nodes into paired pick-up nodes when a size of the order forbids ridesharing, so a vehicle must visit the paired drop-off nodes directly after the pick-up, thus reducing the number of decision variables by 40% on benchmark instances. Secondly, three different constraint programming formulations are proposed for the first time, generating efficient schedules within a few seconds. Thirdly, a real-time rescheduling perspective is further studied, since the ridesharing becomes dynamic when a schedule must be provided instantly. In particular, the warm-start search method, in which a precalculated schedule is continuously revised as new orders come in, is proposed. [ABSTRACT FROM AUTHOR]

In this paper, we study a paratransit application in which children are transported every day from their homes to their special schools or medical-social establishments. To optimize this transportation system, the establishments collaborate to propose a joint transportation plan. We propose a new algorithm to jointly build vehicle routes that visit several establishments and simultaneously set the establishments' opening hours. This algorithm combines a large neighborhood search, the resolution of a route-based model, and the progressive shrinkage of the planning window. It is applied to a real case from the area of Lyon in France, including 34 schools and 575 heterogeneous users served by a heterogeneous fleet of reconfigurable vehicles. On average, we show that in addition to the 10% of saving that can be expected by sharing vehicle routes between schools, 7% of additional savings can be achieved by school bell adjustment. This cost saving also decreases average user ride times and the number of vehicles required, creating longer routes that are more attractive for driver services. Funding: This work was supported by the European Union through the European Regional Development Fund [Grant RA0012500] and by the French Région Auvergne-Rhône-Alpes through the NOMAd project. Supplemental Material: The online appendices are available at https://doi.org/10.1287/trsc.2022.1160. [ABSTRACT FROM AUTHOR]

High-capacity Connected and Autonomous Vehicles (CAVs) are expected to be extensively utilized by on-demand services. This paper aims to assess the impacts of large-scale autonomous on-demand mobility services on traffic, environment, and road safety, under various service specifications using microsimulation. To that end, an urban on-demand shuttle service was designed, optimized, based on a variation of the Dial-a-Ride optimization problem (DARP), and implemented in the road network of the city of Athens to serve different portions of demand with various capacity specifications. It was then investigated through forty mobility scenarios, with differences in policy implementation and market penetration rate of CAVs. Findings show that it led to improved network level traffic conditions, as delays decreased, and that traffic impacts evolve with fleet capacity and served demand. Furthermore, the number of conflicts decreased and the environmental conditions significantly improved, with CAVs in the network, while the traveled distance increased. [ABSTRACT FROM AUTHOR]

Public transport service in Addis Ababa is provided by both public and private operators. However, the inability of the public sector to meet the increasing transport demand has given rise to the emergence of privately owned paratransit transport services. The minibus taxi sector is the dominant public transport mode which provides a means of mobility for the majority of the city's residents. However, the service provided by the sector is still far from being efficient and has a lot of operational constraints. But, various attempts have been made by the city's transport authority to improve service provision in the city. Thus, to carry out this study, both primary and secondary data were used. Instruments like questionnaires, interviews, as well as observation were intensively employed. Finally, the Arada sub-city was selected purposively to execute the study as it is the hub for 9 taxi terminals with 25 routes radiating into several directions of the city. A total of 50 minibus taxi drivers were selected using the convenience sampling method. Results of the study revealed that the presence of complex owner-driver relations, customary operational practices, and poor institutional organization of owners' associations as well as inefficient regulation creates unpleasant work situations and hence profoundly affected service delivery. In addition, the study found that all of these situations are threatening the sustainability of the sector as most vehicle owners have less interest in staying in the business. [ABSTRACT FROM AUTHOR]

This paper analyzes in a large-scale field experiment (N = 1425) whether gift vouchers stimulate the use of a demand responsive transportation (DRT) system. This scenario is compared to a situation where customers receive environmental certificates, which report the saved carbon dioxide as a consequence of the bus ride. In our two treatments, the gift vouchers and the environmental certificates could be gained by reaching to a certain threshold of rides with the DRT service (EcoBus). We find that the demand went up more by gift vouchers (83%) compared to certificates (65%). The data show that vouchers especially outperform the certificates at the end of the treatment phase. [ABSTRACT FROM AUTHOR]

Dial-a-Ride Problem (DARP) is one of the classic routing problems with pairing and precedence constraints. Due to these types of constraints, it is quite challenging to design an efficient evolutionary algorithm for solving this problem. In this paper, a genetic algorithm in combination with a variable neighborhood descent procedure is suggested to solve the DARP. This algorithm, which is called Hybrid Genetic Algorithm (HGA), is independent of any repairing procedure or user-defined penalty factors. Instead, it uses the constraint dominance principle with respect to the number of unserved requests. Our algorithm employs an adaptive population management technique which takes into account not only the quality of solutions but also their contribution in the diversity level. To do so efficiently, this population management technique utilizes a simple arc-based representation for the DARP solutions. A route-based crossover procedure known as Route Exchange Crossover is used in the HGA. This crossover method is thoroughly compared with five other crossover techniques including a new one called Block Exchange Crossover. The HGA produces competitive solutions in comparison with the state-of-the-art methods for tackling the DARP and Heterogeneous DARP (H-DARP). It obtains the optimal solutions of all the small and medium size standard instances of the DARP and finds new best results for two large ones with unknown optimal solutions. Moreover, for 12 out of 24 new instances of the H-DARP, the best known solutions are improved using the HGA. [ABSTRACT FROM AUTHOR]

Transportation is a very important element in the well-being of mobility-impaired people. However, people with disabilities often struggle to access transportation services at all, especially if they live in mountain areas. This study is aimed at better understanding the main factors that affect the preferences for a new specialized paratransit service as BRT's feeder to serve the portion of the trip that mobility-impaired people cannot manage. We hypothesized that in addition to some observable attributes of the transportation services, such as time and travel cost, mobility-impaired people's preferences for a specialized paratransit service as BRT's feeder could be better explained by using a hybrid discrete choice model based on the Self-Determination Theory (SDT). We gathered responses through a stated-preference survey (N = 350), in which respondents faced a series of choice situations among three BRT feeder alternatives: bus, cable car and a new specialized service. We also obtained indicator ratings through a basic psychological needs satisfaction scale to identify the latent variables in relation to the SDT. Modeling results supported our hypothesis that the preferences of mobility-impaired people are better explained by considering the three innate psychological needs. We found empirical evidence linking the components of the SDT, i.e. Autonomy, Relatedness, and Competence, with preferences for the specialized transportation service as BRT's feeder in the study context. The multipliers of values of time savings derived from the model showed that mobility-impaired people place access time four times more important than travel time. We accounted for the heterogeneity in value of travel time savings and found that the greater the autonomy in mobility-impaired people the greater their sensitivity to the specialized transportation service's fare. We concluded that Autonomy, Relatedness, and Competence play an important role in the preferences of mobility-impaired people. Autonomy is a determining factor in perception of alternative fares. Competence motivates mobility-impaired people to use the specialized paratransit service as BRT's feeder, while Relatedness motivates mobility-impaired people to use the same transportation alternatives used by others. [ABSTRACT FROM AUTHOR]

Most Russian cities are currently facing major transformation processes in the public transport supply. Commercial paratransit services, known as marshrutkas, have been criticised heavily for unsafe and uncomfortable facilities as well as for anti-social business behaviour, prone to tax evasion and daily penny wars on the street. Consequently, many municipalities have enforced various strategies to restrict informal marshrutka services. This article compares the distinct policy strategies of two municipalities, Rostov on Don and Volgograd, and discusses the different outcomes. When analysing the case studies, two prevailing discourses seem to have informed the locally applied transport policies: a neoliberal, free market approach that perceives the loosely regulated commercial transport operations superior to state-led services and a rather neo-modernist perception of informal transport operation, calling for a rigorous push back of marshrutka mobility. Prominent in both policy discourses is the notion of informality as an instrument to govern the transport setting. Reviewing the developing field of informal transport studies, the article argues that the governments of the respective cities have employed (simplified) notions of informality as a legitimisation argument to take action. A closer perspective on the daily operations, however, unveils a socially institutionalised transport service full of complex operation practices beyond policy-strategic divides between the formal and informal. The contribution utilises the formal/informal nexus successfully developed in urban studies and applies it to international transport studies. Thus it enables the unveiling of insufficiencies in urban transport provision without falling in the trap of superficial modernisation narratives. [ABSTRACT FROM AUTHOR]

Autonomous vehicle (AV) technology can help disabled Americans achieve their desired level of mobility. However, realizing this potential depends on vehicle manufacturers, policymakers, and state and municipal agencies collaborating to accommodate the needs of disabled individuals at different stages of trip making through information system design, vehicle design, and infrastructure design. Integrating accessibility at this stage of the AV revolution would finally allow us an opportunity to develop a transportation system that treats accessibility as a guiding principle, not as an afterthought. This paper documents accessibility considerations for disabled individuals followed by a review of relevant Americans with Disabilities Act (ADA) regulations. The review of regulations is followed by a review of nine case studies, five corresponding to the on-demand microtransit service model and four corresponding to the paratransit service model. These case studies are essentially different prototypes currently being deployed on a pilot basis. Each of these specific case studies is then evaluated for its ability to provide potential accessibility features that would fulfill the requirement set forth by relevant ADA regulations in the absence of an operator/driver. Based on this review of relevant research, ADA regulations, and case studies, recommendations are provided for researchers, private firms, policymakers, and agencies involved in AV development and deployment. The recommendations include better collaboration and adoption of best practices to address the needs of individuals with different disability types (e.g., Cognitive, Visual, Auditory). ADA regulations should be used as one of the tools in addition to universal design principles and assistive technologies in order to maximize accessibility. • Explores how accessible autonomous vehicle (AAV) technology can co-evolve with disability regulation to meet needs through information systems, vehicle, and infrastructure design. • Evaluates case studies of emerging on-demand autonomous services to see how they meet relevant Americans with Disabilities Act (ADA) standards in the US. • Offers that vehicle design might evolve to better meet standards in the areas of 1) Voice Controlled Systems and 2) Pick Up/Drop Off Point Orientation. • Challenges that, among other collaborative improvements, public agencies can digitize transit trip data to encourage greater multimodal integration of future AAV services. [ABSTRACT FROM AUTHOR]

The Americans with Disabilities Act (ADA) requires public transit agencies to provide an equivalent transportation service for people with disabilities, known as ADA paratransit service. As the U.S. population continues to grow and age, the demand for paratransit service keeps rising, posing many challenges for transit agencies due to its high operational cost. In response, a growing number of transit agencies are looking to incorporate alternative paratransit services by forming partnerships with transportation network companies (TNCs) to provide what is known as same-day service (SDS). However, most of these partnerships are still in the pilot phase, and scant research investigates the opportunities and barriers of SDS or provides guidelines and measures for transit agencies interested in such partnerships. Considering both the characteristics of paratransit trips and riders and the operational norms of TNCs, this paper explores different conditions under which SDS trips are most appropriate and estimates potential trip diversion from conventional paratransit to SDS operated by TNCs. Trip diversion conditions include (1) trip length, which is impacted by the subsidy amount for SDS and the dynamic pricing of TNC trips, (2) level of service, which depends on the level of mobility assistance required by paratransit riders, and (3) the operational efficiency of conventional paratransit. Different settings and combinations of these conditions help transit agencies explore the potential trip diversion of SDS while considering significant barriers to the service. Using 2019 ridership data of Access paratransit, the ADA paratransit services in the Seattle region, this research finds that without an excessive subsidy amount, transit agencies can divert up to 18% of paratransit trips to SDS. This percentage can drop to as low as 11% of paratransit trips if transit agencies further limit the SDS service area to ensure the efficiency of conventional ADA paratransit. This paper concludes that although SDS provides many benefits, significant barriers inherent to TNC business models and paratransit users should be carefully examined when pursuing ADA paratransit-TNC partnerships. • Providing paratransit Same-Day Service through TNCs has many barriers. • TNCs cannot accommodate all types of ADA paratransit trips beyond curb-to-curb. • TNCs pricing limits subsidized length of SDS trips during peak and off-peak hours. • The diversion rate to SDS should not disrupt the operational efficiency of paratransit. • ADA paratransit should remain equally available when providing SDS. [ABSTRACT FROM AUTHOR]

Environmental impact becomes an emerging problem since global warming has caused climate change issues, especially natural disasters in recent years. Based on International Energy Agency (IEA), the concentration of CO2 in 2015 was 399 parts per million by volume and was about 40% higher than in the mid-1800s. Since the transportation sector accounts for great responsibility for emissions, how to reduce CO2 emissions and keep the efficiency of transportation has become a more important issue. Dial-a-ride Problem (DARP) is a new form of mobility-on-demand public transportation, and the route and schedule of DARP are flexible to accommodate customer needs. This study aims at integrating the concept of ecoefficiency into DARP, and a bi-objective dial-a-ride problem with time-dependent costs is formulated. Two objectives, CO2 emissions and travel time, are explicitly considered. The formulation considers the perspective of eco-efficiency and fluctuation of travel time for the dial-a-ride problem. A revised branch and-price solution algorithm with a large neighbor search (LNS) is adopted to solve the problem. In order to solve the two objectives simultaneously, this study applies the weighted sum with the normalization approach. Due to the difficulties of estimating emissions, a traffic simulation model is incorporated with the solution algorithm to provide emissions values. Several experiments based on a city network are conducted to evaluate objectives based on different factors, including traffic condition, time window, and maximum ride time. The results show that (1) weights for objectives need to be designed appropriately to reflect the preference; (2) the travel times and CO2 emissions reduce with respect to the increase of time window length; (3) The total travel time and CO2 emissions decrease with respect to the length of maximum ride time. [ABSTRACT FROM AUTHOR]

• Mobility-as-a-Service (MaaS) promises improved modal efficiency and integration among public transit and flexible paratransit services (FPS). • Key service dimensions and issues of flexible paratransit services are analysed in the context of MaaS. • Expected service level for these service dimensions are determined using the level of service (LOS) approach based on user perception. • Ride matching as per expected waiting time and service hours via MaaS agencies would ensure proper demand-supply match and fleet size determination. In emerging countries, flexible transport systems (FTS) are mostly informal and are provided by individual paratransit operators/drivers. These services are largely unregulated thus resulting in uncoordinated operations with poor service quality. Earnings and working conditions of paratransit drivers/operators are also poor due to loosely regulated fleet size and other operational and regulatory issues which results in further deterioration of service quality. This research identifies key service dimensions and issues of paratransit services and also determines the expected service level for these service dimensions using the level of service approach based on user perception. LOS scales are designed for different service attributes using a five-point satisfaction and importance rating system. For quantitative attributes, five-level LOS scales are determined by applying the Law of Successive Interval Scaling, whereas for qualitative attributes, the same has been developed using the frequency of response for each level of importance for each sub-attribute. Subsequently, we explore various policies and regulatory measures towards reform and redesign of paratransit services and other mobility needs. Operator profitability can be achieved both through the controlled entry of operators through the issue of permits and/or by relaxing the current service level of some service aspects which are at LOS B level of service. The LOS scales can help in future service design of paratransit services in emerging countries which can offer an affordable alternative to ridesourcing and ride-sharing using cars. The study is conducted in two medium-sized cities in India namely Rajkot and Vishakapatnam. [ABSTRACT FROM AUTHOR]

Urban mobility services face the challenge of planning their operations efficiently while complying with user preferences. In this paper, we introduce a new mathematical model called a choice-driven dial-a-ride problem (CD-DARP) which is a generalization of the dynamic DARP where passenger behavior is integrated in the operational planning using choice models and assortment optimization. We look at two types of mobility services, private and shared. Our problem extends the dynamic DARP by (i) changing its objective function to profit maximization, where both cost and revenue are variables, and (ii) incorporating assortment optimization with routing decisions in a dynamic setting. We propose a pricing scheme based on a choice model designed to offer service alternatives at the time a customer makes a request. We introduce a tailored algorithm to efficiently solve the dynamic CD-DARP. Computational results indicate that our proposed approach outperforms dynamic DARP in terms of reducing routing costs and improving the number of customers served. • A new framework is introduced for DDARP incorporating customer choice. • The routing cost is reduced while satisfying customers' requests. • CD-DARP provides more flexibility for the operator to efficiently manage the fleet. • We evaluate the proposed model on synthetic as well as New York taxi data. • Flexible time windows helps improving the service level. [ABSTRACT FROM AUTHOR]

Paratransit plays an important role in offering mobility and accessibility in local communities, especially for mobility disadvantaged group such as seniors, persons with disabilities, and persons with medical conditions. This study comprehensively evaluates the impacts of COVID-19 on paratransit services from paratransit operator and individual rider perspectives. In particular, we mine a paratransit dataset that covers trip logs of more than 800 unique riders over a seven-month period in order to understand how the pandemic impacted service and influenced trip purposes of individual riders. For service providers, our analyses show that a significant loss in paratransit ridership was accompanied by drastic changes in travel behavior among paratransit riders. Results indicate that the operator was able to deliver safe and efficient mobility services during COVID-19, but at a 60% higher cost per rider than under pre-pandemic conditions. The results also reveal a varying level of impacts for individual riders given heterogeneity among trip purposes and demographic profiles. Moreover, similarities are identified across a range of individual riders, depending on specific trip purposes and the availability of alternative travel options. This study is among the first to investigate paratransit operations during COVID-19 in terms of impacts to both operators and individual riders. The lessons learned and policy insights should be useful to other paratransit operators and policymakers in preparing for current and future pandemics. • Analyzes a dataset containing unique paratransit service records focusing on the central Alabama area. • Quantifies the impact score for each rider to further detect the change of travel behaviors before and during the pandemic. • Explores underlying patterns in the similarity of travel behaviors among frequent riders. • Provides lessons learned and policy recommendations to transit operators and transit agencies. [ABSTRACT FROM AUTHOR]

The Stop Number Problem arises in the management of a dial-a-ride system served by a fleet of autonomous electric vehicles. In such a system, clients request for a ride from an origin station to a destination station, and a fleet of capacitated vehicles must satisfy all requests. The goal is to minimize the number of pick-up/drop-off operations. In this paper we focus on a constrained unitary variant, called Unit Stop Number Problem, where each client requests for a single seat in the vehicles. This variant was recently conjectured to be NP-Hard. In this regard, we show how this problem relates to other problems known in the literature in order to derive some polynomial-time solvable variants. Moreover, we provide a positive answer to the conjecture by showing that the problem is NP-Hard for any fixed capacity greater than or equal to 2, even for the case where the graph of requests is restricted to the class of planar bipartite graphs. Our proof of NP-Hardness also improves the complexity results known in the literature for the related problems identified. [ABSTRACT FROM AUTHOR]

This study investigates the potential benefits of integrating shared autonomous vehicles and an existing transportation system by exploring a recently initiated project that integrates autonomous vehicles (AVs) with an existing on-demand ridesharing service, Via, in Arlington, Texas. We first identified the spatial patterns of the ridership on a localized scale, using geographically weighted regression (GWR) for the existing paratransit service, Handitran. Assuming that the existing ridership will be combined in the future with shared autonomous vehicles, we looked at integration options, based on the spatial patterns of supply and demand and payment options for the riders. The results suggest that the paratransit service, Handitran, is currently used by a small proportion of the eligible population, whose travel patterns differ based on their age. For instance, younger users usually ride Handitran for traveling to work, recreational activities, and routine chores, while senior riders often use the service for medical and recreational trips. The results of the GWR model indicate that the major determinants of Handitran usage are the population's percentage of older adults, racial distribution, and household vehicle ownership; the coefficients of these factors vary across the city. Hot-spot analyses' results reveal that integrating the services will improve the efficiency of the existing transportation system by responding to the excess rider demand, particularly in the downtown area. Finally, we describe the implications of implementing policies for AV integration for cities, service providers, and other stakeholders and suggest future research topics. [ABSTRACT FROM AUTHOR]

In the context of door‐to‐door transportation of people with disabilities, service quality considerations such as maximum ride time and service time consistency are critical requirements. To identify a good trade‐off between these considerations and economic objectives, we define a new variant of the multiperiod dial‐a‐ride problem called the time‐consistent dial‐a‐ride problem. A transportation planning is supposed to be time consistent if for each passenger, the same service time is used all along the planning horizon. However, considering the numerous variations in transportation demands over a week, designing consistent plans for all passengers can be too expensive. It is therefore necessary to find a compromise solution between costs and time‐consistency objectives. The time‐consistent dial‐a‐ride problem is solved using an epsilon‐constraint approach to illustrate the trade‐off between these two objectives. It computes an approximation of the Pareto front, using a matheuristic framework that combines a large neighbourhood search with the solution of set partitioning problems. This approach is benchmarked on time‐consistent vehicle routing problem literature instances. Experiments are also conducted in the context of door‐to‐door transportation for people with disabilities, using real data. These experiments support managerial insights regarding the inter‐relatedness of costs and quality of service. [ABSTRACT FROM AUTHOR]

Shared-use mobility services largely serve major metropolitan areas. However, increasingly officials, who represent rural communities, want to know whether these types of services may be able to provide more cost-effective access to rural residents than is currently possible by fixed-route and dial-a-ride transit services. Many of these officials must contend with low farebox recovery rates that threaten transit funding and subsequent cutbacks in transit services that are often strongly opposed by constituents. In this study, the cost-effectiveness of existing inter-city transit service in rural disadvantaged communities in the San Joaquin Valley (California) is compared to hypothetical ridesharing and carsharing services. The results show significant potential to reduce transit costs and reinvest those cost saving to expand shared mobility services. The cost-effectiveness analysis is supplemented with reviews of existing shared-use mobility pilots and consultations with experts in shared mobility and local transportation planning.View the NCST Project Webpage

The Electric Autonomous Dial-A-Ride Problem (E-ADARP) consists in scheduling a fleet of electric autonomous vehicles to provide ride-sharing services for customers that specify their origins and destinations. The E-ADARP considers the following perspectives: (i) a weighted-sum objective that minimizes both total travel time and total excess user ride time; (ii) the employment of electric autonomous vehicles and a partial recharging policy. This paper presents the first labeling algorithm for a path-based formulation of the DARP/E-ADARP, where the main ingredient includes: (1) fragment-based representation of paths, (2) a novel approach that abstracts fragments to arcs while ensuring excess-user-ride-time optimality, (3) construction of a sparser new graph with the abstracted arcs, which is proven to preserve all feasible routes of the original graph, and (4) strong dominance rules and constant-time feasibility checks to compute the shortest paths efficiently. This labeling algorithm is then integrated into Branch-and-Price (B&P) algorithms to solve the E-ADARP. In the computational experiments, the B&P algorithm achieves optimality in 71 out of 84 instances. Remarkably, among these instances, 50 were solved optimally at the root node without branching. We identify 26 new best solutions, improve 30 previously reported lower bounds, and provide 17 new lower bounds for large-scale instances with up to 8 vehicles and 96 requests. In total 42 new best solutions are generated on previously solved and unsolved instances. In addition, we analyze the impact of incorporating the total excess user ride time within the objectives and allowing unlimited visits to recharging stations. The following managerial insights are provided: (1) solving a weighted-sum objective function can significantly enhance the service quality, while still maintaining operational costs at nearly optimal levels, (2) the relaxation on charging visits allows us to solve all instances feasibly and further reduces the average solution cost. • We use a new paradigm to minimize (excess-)user-ride-time in the labeling algorithm. • Our CG algorithm optimizes 50 out of 84 instances at the root node. • Our CG algorithm obtains 24 better lower bounds than the best-reported results. • Our CG algorithm identifies 22 new best solutions and 15 new optimal solutions. • The B&P solves 71 out of 84 instances optimally and obtains 26 new best solutions. • The B&P obtains 30 better lower bounds compared to the best-reported results. • We investigate the impact of adding the total excess user ride time in the objectives. [ABSTRACT FROM AUTHOR]

Paratransit services offer flexible on-demand transportation filling crucial mobility gaps otherwise unmet by conventional public transportation systems. A common problem witnessed in both the developed and developing worlds is the inadequate complementarity among paratransit and conventional transit for maximized urban mobility provisions. Particularly in the Global South, such an inadequacy stems from the negative portrayal of paratransit whereas in the Global North paratransit remains underutilized. At this juncture, paratransit emerges as an important transportation segment that requires an in-depth understanding of its grained agenda demanding development. Therefore, a multi-disciplinary article-set on paratransit is constructed by involving the scholarships of transportation sciences, logistics management, planning and public policy, legal sciences, and general management. Thereby, this vast spread of literature [294 articles (1970–2023)] is excavated from two perspectives: (i) developed versus developing world's viewpoint, and (ii) understanding socio-economic planning issues at the strategic, tactical, and operational levels. Resultantly, the agenda surrounding paratransit's development is outlined in layered themes. Three primary themes and thirteen subthemes granularize the strategic, tactical, and operational agenda of socio-economic planning in this regard. Furthermore, the review draws out diverse strategic pathways conceptualizing vital implications on how knowledge of paratransit can advance in the future. [Display omitted] • An in-depth conceptual review of socio-economic planning in Paratransit. • Multi-disciplinary investigation. • Diverse developmental agenda and policy reforms suggestion. • Multi-hierarchical scanning of perspectives at the strategic, tactical, and operational level. [ABSTRACT FROM AUTHOR]

Dial-a-ride operations consist of door-to-door transportation systems designed for users with specific needs. Governments and companies offer such services, and due to the flexibility and service level required by the users, it is considerably more costly than public transportation, besides emitting higher levels of CO2\documentclass[12pt]{minimal}\usepackage{amsmath}\usepackage{wasysym}\usepackage{amsfonts}\usepackage{amssymb}\usepackage{amsbsy}\usepackage{mathrsfs}\usepackage{upgreek}\setlength{\oddsidemargin}{-69pt}\begin{document}$$_2$$\end{document}. Hence, it is crucial to analyze alternatives to improve operational costs and efficiency without compromising the quality of the service. This paper introduces a variant for the dial-a-ride problem with private fleets and common carriers (DARP-PFCC) integrated with public transportation. Requests can be served by the private fleet, the common carrier, or by integrating them into the public transportation system. In this case, users are collected at the pickup locations and taken to bus stops. After the bus trip, other vehicles serve them from the bus stops to their final destination. Bus schedules must be considered when deciding on the best integration trip. As a methodology, we solve this extension of the DARP-PFCC with a metaheuristic and machine learning hybrid method by combining a biased random key genetic algorithm with the Q-Learning and local search heuristics (BRKGA-QL). This paper also introduces some improvements to this method, particularly with respect to population quality and diversity, thanks to a new mutation method in the classical crossover operator and deterministic rules for the learning process. Computational experiments on a new benchmark data set with realistic data from Québec City show that our BRKGA-QL outperforms its previous version. In addition, we provide a qualitative analysis for the DARP-PFCC, showing that the middle mile integration with public transportation can save up to 20% in operating costs, besides reducing the traveled distances of private vehicles and common carriers. [ABSTRACT FROM AUTHOR]