Demand Responsive Transport Research Articles

Navigating autonomous demand responsive transport: stakeholder perspectives on deployment and adoption challenges

ABSTRACT As cities implement intelligent systems and public transportation users seek flexibility, autonomous demand-responsive transport (ADRT) will play an important role in a region’s broader public transportation system. We have seen this in cities where trials have been conducted. Great efforts and investments are being made in the industrial and academic sectors to make autonomous driving a reality. This study investigates the challenges and opportunities of adopting ADRT in South East Queensland, Australia. This is critical as ADRT can help be an alternative way to provide public transport, especially for first and last-mile service. The adapted methodology is an exploratory qualitative study through interviews with transport experts to provide comprehensive insights regarding the ADRT service concept, potential customer groups in terms of the supply and the demand side, potential use cases, followed by an explanation of the ADRT deployment and adoption challenges in terms of the supply side and the demand side. Accordingly, we offer recommendations mainly contributing to mindset change, education and exposure, subsidies and incentives, liability and insurance that can support policymakers, transport planners, and engineers in making effective policy choices and developing successful transportation systems, while also increasing public recognition and adoption of ADRT technology.

SAN ANTONIO TRANSPORTATION PLANNING SYSTEM: MAPPING INFRASTRUCTURE CAPACITY AND COORDINATION

Abstract Ride Connect Texas and its partnering agencies seek to develop an expanded senior mobility management system supported by a One Call One Click transportation planning system. Its purpose is to enhance on-demand transportation system coordination and the application of technology, providing consumers, service providers, and mobility managers with direct access to comprehensive transportation information. GIS mapping is used to help develop a spatial awareness of the transportation challenges among older people and individuals with a disability and the current system capacity. Interviews with transit, non-transit, and health and human service agencies will reveal factors that influence coordination among providers and opportunities for capacity expansion. Surveys and focus groups of older adults and individuals with disability will show differentiating characteristics of riders and transportation needs and challenges. GIS mapping will allow us to geocode these findings relative to the user’s street address and zip code, illustrating variations in specialized client needs, service availability, travel behavior, and available amenities for basic daily living. Mapping will identify gaps in transportation services, hot zones revealing high user demand and low system capacity, and the ability to reduce fragmentation of service through seamless technology-based coordination. The mapping element informs the measurement of a community’s transportation system capacity for this user group. The value proposition of this tool is its ability to help any community measure its readiness toward developing a comprehensive implementation strategy for coordinated demand response transportation, including resource mobilization strategies, capacity augmentation, phasing of the system, and implementation timeline.

VISUALIZING AGING EQUITY: CROSS-SECTORAL PARTNERSHIPS TO CREATE MAPPING TOOLS FOR SOCIAL CHANGE

Abstract This symposium will feature ways in which gerontologists are advancing the development of online, interactive mapping tools on aging. Utilizing GIS mapping technology and leveraging cross-sectoral partnerships, the speakers will present case illustrations of efforts to develop aging-focused mapping tools that aggregate data sources at the municipal, state, and national levels to advance a spatial awareness of supports for older adults across diverse communities. First, as an example from the nonprofit sector, the New York Academy of Medicine will present on IMAGE:NYC, The Interactive Map of Aging. This presentation will describe the utility of this tool for policymakers, planners, researchers, and social service providers. Representing work from within the academic sector, the Rutgers School of Social Work will describe an academic-public sector partnership to adapt the IMAGE:NYC map for two counties in New Jersey. Next, presenters from the University of North Texas will describe their partnership with the City of San Antonio to develop an intelligent demand responsive transportation system for older adults and individuals with disabilities. This project involves the use of GIS mapping tools and qualitative research methods to identify place-based transportation gaps and strategies for improvement. Focusing on the national level, the National Council on Aging will describe its work developing mapping tools, including a map that displays area-level rates in eligibility gaps for three federal benefit programs. With an orientation to aging equity, these tools hold promise for fostering inclusive and healthy communities where older adults of diverse intersectional socio-spatial positions can age well. This is an Environmental Gerontology Interest Group Sponsored Symposium.

A phase-based perspective on urban demand responsive transport: A case study of Viavan pilot in Helsinki Capital Region

Despite decade-long efforts, real-time demand-responsive transport (DRT) services are still struggling to be a part of sustainable urban mobility systems. Among various approaches to understand the changing nature of DRT service, a longitudinal perspective has been found very effective. This study presents the case of an urban DRT pilot operated by Viavan in the Helsinki Capital Region, Finland. Research develops and implements a framework for longitudinal analysis, while drawing from the multi-level perspective (MLP) on sustainability transitions. DRT trip data is used to understand the service trajectory longitudinally over specific phases, delineated through key changes in service design. In addition, the framework uses three-level analysis of service parameters, to provide in-depth analysis in studying inter-phase and intra-phase changes. Case study approach also provides a comprehensive service area background and service implementation context to support the analysis. Results shows the complementary role of the urban DRT to fixed public transport services and points out certain challenges for efficient coordination. In addition, the analysis points towards a set of regime factors that should be considered for further understanding of the service trajectory. In practice, special emphasis should be paid on developing the mobility ecosystem and managerial practices. Future DRT case studies should develop additional frameworks, indicators and methods by drawing from sustainability transitions theory, to further understand service trajectories over time.

Optimization of Rural Demand-Responsive Transportation through Transfer Point Allocation

Rural mobility has a lack of innovative proposals in contrast with its urban counterpart. This research aims to bring solutions that ease the implementation of reliable and flexible rural transportation. Demand-responsive transportation is chosen to develop a public transportation service providing interurban trips among several rural settlements. Given the characteristics of rural displacement demand, a novel approach is introduced to optimize the service’s economic costs: the dynamic transfer point allocation. The problem is fully formulated and an architecture is introduced describing the workflow of the whole system. Data from an interurban bus transportation service are used to build a case study of a rural area of Valencia, Spain, and develop several examples illustrating the benefits of the proposed approach. The results reveal that the dynamic creation of transfer points can simplify the transportation fleet’s itineraries and boost the amount of served travel requests. Finally, a discussion of the benefits and dangers of flexible features in rural transportation is developed, underscoring the need to achieve a balance between dynamic operation and service quality.

Understanding the behavioral intention of the rural population to use demand-responsive transport services

Global efforts to reduce carbon emissions include endeavors to raise the use of public transport means. In rural areas, this poses a distinctive challenge. Demand-responsive transport (DRT) services are a form of public transport that is regarded as a potential contribution to the required mobility behavior change. They mainly utilize small floor buses and require a pre-booking of each trip (via internet, app or telephone). Despite the growing number of active DRT services and trial operations, occupation numbers remain small. To understand this gap, this study investigates latent constructs that influence the behavioral intention of inhabitants living in rural regions to use DRT services. For this purpose, a questionnaire based on the Unified Theory of Acceptance and Use of Technology was adapted, tested independently through an exploratory factor analysis and distributed in Austria. The sample (n = 186) was subjected to a structural equation model. Results show that performance expectancy and attitude towards public transport have a significant impact on the behavioral intention of inhabitants to use DRT services in rural regions, whereas the attitude towards private cars was insignificant. Inter alia, we suggest concentrating on the determination of people’s specific everyday mobility needs in rural areas, analyzing and optimizing the public transport offer as an interrelated system, and communicating its benefits more efficiently.

Demand-responsive transport for students in rural areas: A case study in Vulkaneifel, Germany

In rural areas with low population density, demand-responsive transport (DRT) is considered a promising alternative to conventional public transport (PT). With a fleet of smaller vehicles, DRT provides a much more flexible and convenient service. This characteristic makes DRT also a potential mode of transport to serve students in rural areas. If DRT vehicles are used to serve students, then the funding for conventional school buses (or adapted public transport schedules) can be reinvested in the DRT system. This may help to relieve the financial burden experienced by DRT operators and enable the operation of a large-scale DRT service in rural areas. In this study, a demand model for school commutes based on real-world, open-source data for Landkreis Vulkaneifel, a rural region in Germany, is built. Then a feasibility study is carried out using an agent-based transport simulation framework. In the feasibility study, various setups and operational schemes are explored, which are followed by a systematic cost analysis. Based on a conservative estimation, an annual budget of around 1600 Euro per student will be needed to maintain and operate a fleet of DRT vehicles that can transport all the students in the region from home to school on time in the morning. During the remaining time of the day and on school holidays, the vehicles can be used for conventional DRT service for the public.

Designing Mobility Policies for Vulnerable Users Employing the Living Lab Approach: Cases of a Demand-Responsive Transit Service in Ljubljana and Maribor

In recent years, transport policy has strongly been oriented to develop more inclusive cities and to design mobility services aligned to specific users’ needs. In an attempt to guarantee an adequate level of accessibility, especially to vulnerable users, approaches based on the dialogue between public administration, operators, citizens and researchers (so-called “quadruple helix”) have been proposed. The two case studies presented in this article refer to the development of a minibus demand-responsive transport system, devoted mainly to people with reduced mobility, in the cities of Ljubljana and Maribor (Slovenia) designed using a Living Lab participative approach. In fact, urban mobility stakeholders were engaged in this process during the design and monitoring phases of the pilot projects. Their involvement resulted in producing positive outcomes: citizens actively participated in the projects, and the designed service was perceived to be useful and effective. Both projects were successful, as statistics demonstrate, and are expected to be confirmed and strengthened over the next few years.

Determinants of Usage and Satisfaction with Demand Responsive Transport Systems in Rural Areas

Mobility in rural areas requires increased attention, because of not only the large share of the population living there but also the difficulties and special needs that characterize the areas themselves and their residents and visitors. Demand responsive transport (DRT) systems can fill the gap for flexible and sustainable public transport in rural environments. However, since most past studies focused on the urban context, there is still a lack of knowledge on the determinants of usage and loyalty to these systems. The objective of the present study is to identify the decisive factors of DRT systems’ usage in rural areas by examining user characteristics, usage cases, and the determinants of satisfaction with such services. Insights are obtained based on survey data collected on two DRT systems in Austria—one system with a flexible timetable and predetermined stops that mainly serves suburban residents and another door-to-door service with a fixed timetable that is oriented to locals and tourists. The usage of DRT systems is modeled via regression models and the decisive factors are identified and compared among user groups and services. The findings suggest that DRT systems are used for both compulsory and non-mandatory trips and that the majority of users are female. However, the results from different user groups and services suggest that there are not unanimous determinants of the probability of traveling by DRT. With regard to overall satisfaction, it is found that it is related to satisfaction with both trip-level attributes and system design characteristics.

Multi-day fair collaboration in demand-responsive transportation

In this paper, we consider the case of companies that offer a demand-responsive transportation service, such as a shared-taxi service, and are engaged in a horizontal collaboration initiative. The goal of the coalition is to optimize the transportation operations in such a way that no company is penalized, in terms of customers served and/or working time. We present an optimization model for a multi-day planning horizon that includes constraints aimed at guaranteeing a level of fairness to all companies that can be controlled over the planning horizon and day-by-day, if beneficial. An adaptive large neighborhood search heuristic is then presented for its solution. The computational experiments show that, although the model constraints the optimization space, it still guarantees substantial savings. Moreover, they show that the model is flexible and can guarantee the sustainability in the long term of the collaboration initiative.

The effect of data science on urban sustainability through the optimization of demand-responsive transportation

The study investigated the viability of implementing a demand-responsive transportation (DRT) system within the premises of Al-Baha University to facilitate the punctual arrival of students to their classes and ensure their convenient departure from the campus. This study aims to demonstrate and elucidate how data mining enhances the efficiency of DRT systems. The case study investigates the potential improvements in DRT operations through the utilization of data mining techniques. The research employs descriptive and prescriptive techniques for mining trip planning data. The database maintained by the Deanship of Admission and Registration et al.-Baha University in Al-Baha City, Saudi Arabia, has identified 50 designated locations for student pick-up. The research establishes a comprehensive database that classifies pick-up points as spatial vectors, incorporating longitude, latitude, and counts of students. Cluster analysis and multidimensional scaling techniques are employed to minimize travel times and enhance operational efficiency by consolidating pick-up points. A completely adaptable DRT system prioritizes user satisfaction over operational efficiency, facilitating superior flexible services with fewer buses. The University Transport Department can implement Fixed Route systems in regions with significant population density and substantial demand. Conversely, in areas with a lower population, where Fixed Route systems may be less efficient, the department can opt for DRT systems. Additionally, the findings demonstrate the potential cost-saving benefits of implementing a hybrid system that integrates the university and off-campus student housing. The results indicate that providing fully flexible DRT services to students’ harms efficiency and user experience. A comparative analysis between the Fixed route system and the DRT system reveals that the latter has the potential to offer enhanced service to students, utilizing an equivalent number of vehicles while reducing the number of rides required, all while maintaining a higher degree of flexibility in service provision. According to the recommendation of this study, it is advisable to implement a hybrid fixed route and DRT system. However, to assess the feasibility of such a system in a university setting in the Kingdom of Saudi Arabia (KSA), it is necessary to conduct a comprehensive viability analysis to identify any potential challenges or concerns.

Cloud-Based Demand-Responsive Transportation System Using Forecasting Model

Cloud-Based Demand-Responsive Transportation System Using Forecasting Model

Key Factors Influencing Vehicle Availability Associated with the User Waiting Time of Demand Responsive Transport (DRT) for People with Disabilities

Demand Responsive Transport (DRT) services for the safe and comfortable travel of people with disabilities have long waiting times and significant variations in time and space. Due to these characteristics, user dissatisfaction with DRT services continues to increase. This study aimed to identify factors that affect vehicle availability, which is closely related to waiting time, and to prepare measures to solve problems in waiting time. The data used for the analysis was composed of spatial units, so Moran's I factor was used to test for spatial dependence. After confirming the presence of spatial dependence, spatial regression models optimized for spatial data analysis were estimated. As a result of predicting the model using five independent variables, four variables, Medical Infrastructure Concentration Index (MICI), Disabled Population Concentration Index (DPCI), Depot Size, and Demand Variability Index (DVI), were found to be statistically significant at a 95% confidence level, except for congestion level. The analytical results indicate that the frequency of vehicle operation is low in areas with a low population of the disabled, little medical infrastructure related to the disabled, and irregular DRT demand, which may affect increasing user waiting time. Therefore, supply-oriented policies to increase the number of available vehicles, such as adding more depots or deploying more vehicles, will contribute significantly to reducing user waiting time in these areas.

Defining and implementing a sufficient level of accessibility: What’s stopping us?

Recent transport equity literature has proposed a sufficientarian approach to transport planning, according to which all individuals would be entitled to a minimum level of accessibility deemed adequate or sufficient. The implementation of this approach would require the adoption of an accessibility standard as a key performance indicator guiding transport investments, land use planning and service provision. While accessibility measures are increasingly operationalised in professional practice, the adoption of actual accessibility standards is rare. In this paper, we explore the barriers for adopting explicit accessibility standards and identify conditions within which such standards could be acceptable to practitioners and policymakers. The paper draws on interviews with professionals in three city-regions in Sweden, complemented with interviews with practitioners from the Flanders region in Belgium and from the UK. We find that authorities are hesitant to define and measure accessibility and that where definitions and performance indicators exist, there is a lack of agreement within and across authorities. The prospect of introducing a standard across the board without attaching any conditions comprises a further reason for shying away from standard-setting. The (dis)integration of transport and land use and complicated administrative and governance structures are described as a further barrier, while demand responsive transport is in some cases considered a panacea to all accessibility problems, making it possible to avoid setting standards. Our findings suggest that standards for minimum accessibility could gain political support if their reach is clearly circumscribed, and their benefits are clearly understood.

Assessing spatial characteristics to predict DRT demand in rural Switzerland

The niche market segment of demand responsive transport (DRT) services is meant to overcome structural economic problems of currently cost ineffective public transport (PT) services in rural areas. Simulation studies for mainly urban DRT services showed that demand for DRT trips is correlated with spatial characteristics. More knowledge of spatial characteristics of rural settings and their influence on DRT trips is necessary.In this study, trip data of a rural DRT service called mybuxi is used. Machine learning is applied for a better understanding of spatial characteristics of DRT demand in two different rural settings of the mybuxi service. Here in, the transferability from one mybuxi setting to the other is then tested.Results show that the number of inhabitants is the most important spatial characteristic for the prediction of DRT demand, followed by the distance to a train station and the presence of a restaurant in a given zone. The quality indicator of PT had low or no predictive power. The study shows that both DRT service areas experienced an increase in accessibility. For future transport planning, the increase in accessibility by DRT services in different rural areas must be taken as a legitimation for these services to be implemented instead of line-bound PT services.

The Role of DRT in European Urban Public Transport Systems—A Comparison between Tampere, Braunschweig and Genoa

Demand-Responsive Transport (DRT) is one of the most valid solutions to tackle the problems affecting public transport today, both in urban and rural areas. Despite its undoubted advantages, it still remains underdeveloped compared to its great potential. The purpose of this paper is to understand the role that on-demand transport plays in the strategic choices of public transport authorities (PTAs): to this end, this study examined the DRT services of three geographically distant European cities, in order to test different social, cultural and regulatory backgrounds, examining their main characteristics. Tampere, Braunschweig and Genoa were selected for the purposes of this work; data and information were collected by viewing the official websites of public transport companies and by direct contact via mail/telephone with the managers responsible for on-call transport. The data collected were then analyzed based on specific Key Performance Indicators (KPIs) identified in academic literature. The results of this paper show that the role of on-call service in the strategic decisions of PTAs depends on the cultural context of reference; some cities focus more on urban services, others on rural transport. In all three case studies examined, on-demand transport is an important aspect of local mobility and with wide room for growth.

Adaptive transit design: Optimizing fixed and demand responsive multi-modal transportation via continuous approximation

Adaptive transit design: Optimizing fixed and demand responsive multi-modal transportation via continuous approximation

From School Buses to Carpooling: A Multifaceted Approach to Solving Vehicle Routing Problems in People Transportation

This paper delves into the complex realm of vehicle routing problems (VRPs) with a specific focus on the transportation of people, highlighting the nuanced challenges and optimization opportunities distinct from those associated with goods transportation. Among these, the Dial-a-Ride Problem (DARP) is emphasized as a pivotal area of study. DARP caters to providing personalized, accessible transportation services, particularly for individuals unable to use standard transit options, such as the elderly and handicapped. This research meticulously explores the mathematical formulation of DARP, and operational challenges and extends the discourse to encompass related VRPs in people transportation, thereby broadening the scope of investigation. Operational intricacies of DARP include managing time windows for pickups and deliveries, adhering to vehicle capacity limits, and ensuring tailored transportation solutions that optimally satisfy both operational costs and customer convenience. The paper reviews a wide spectrum of heuristic and metaheuristic solution methods developed over the years, tracing the evolution of these algorithms from their inception to the sophisticated techniques currently employed to address DARP's dynamic, static, and stochastic variants. Additionally, the research extends to related problems such as the School Bus Routing Problem (SBRP), which emphasizes the efficient and timely transportation of students, and the Carpooling Problem, focusing on organizing shared rides to reduce vehicle kilometers and enhance mobility. Demand Responsive Transportation (DRT) problems are also discussed, highlighting their importance in areas where fixed-route services are inefficient. Conclusively, the paper discusses the future scope of research in this domain, underscoring the necessity for novel solution concepts to address the growing complexity and scale of transportation demands. The integration of intermodal aspects, combining public transportation with demand-responsive services, and the advancement of hybrid algorithms are identified as key areas for future exploration. This comprehensive study not only contributes to the academic discourse on optimizing vehicle routing for people transportation but also aims to inform the development of more efficient, accessible, and customer-oriented transportation systems.

Comparing passengers’ satisfaction with fixed-route and demand-responsive transport services: Empirical evidence from public light bus services in Hong Kong

Conventional public transport services are usually highly regulated with fixed-route and fixed-schedule, which are considered less flexible and efficient to serve low-density and dispersed settled areas. Demand-responsive transport is possibly a more economically and operationally viable solution, which offers dynamically allocated routes and schedules and serve the widespread passenger demand. There have been numerous simulation studies comparing the effectiveness of these two types of transport services in different settings, but which type is more favorable to passengers and what service aspects play the key role in shaping the overall satisfaction with the service quality from the passengers’ point of view are largely unknown. Using fixed-route and demand-responsive public light buses in Hong Kong as a case study, this research conducted an on-street questionnaire survey with 547 samples regarding the passengers’ perception of the performance of ten service aspects and the overall performance. An ordered logit model was accordingly developed to identify the relative importance and contribution of these service aspects to the overall service quality. An importance-performance analysis was further carried out to visualize the ratings of importance and performance of the service aspects, and to prioritize the improvement areas. The findings reveal that the passengers were less satisfied with the demand-responsive public light bus services in general. Among all the service aspects, we find that the in-vehicle environment, waiting time, driver’s attitude, and safety hold a higher improvement priority. Policy implications for improving and regulating both fixed-route and demand-responsive public light bus services are suggested.

Introduction of emerging mobility services in rural areas through the use of mobile network data combined with activity‐based travel demand modelling

AbstractWhilst urban areas are thriving in trialling new mobility services (NMS), rural environments, often perceived as areas of low demand for travel, struggle to attract investments for creating more mobility solutions alongside traditional public transport (PT) services, making residents more reliant on private cars.This paper describes how policy interventions for introducing NMS in rural areas should be guided by big data to capture real and accurate travel behaviours, therefore avoiding perceived biases and potentially underestimating demand.In the UK, the provision of transport in rural areas is solely linked to population density and does not consider differences between places and residents’ travel habits. The proposed data‐driven decision‐making process used trip‐chains from mobile network data (MND) to derive recent and accurate travel patterns from residents and provide the right mix of on‐demand mobility services alongside existing fixed scheduled public transport (PT).The manuscript describes the steps carried out to study three rural areas at low, medium and high population density in the UK: a data landscape to select study areas; the development of an activity‐based model, which uses anonymised mobile network data (MND) aggregated at trip‐chains level to derive travel patterns; and the development of an on‐line questionnaire and focus groups with rural communities to co‐designing solutions based on attitudes towards NMS.Results demonstrated that a data‐driven decision making process to introduce NMS is a viable solution for updating demand for travel in rural areas, offering a broad understanding of mobility needs and the relationship of interdependency with nearby areas, therefore allowing policy makers to create users‐centric transport solutions.The study concludes by drawing recommendations for NMS for passengers and goods for the NMS proposed for a rural areas [Demand Responsive Transport (DRT), Micro‐mobility and delivery drones].