Demand Responsive Transport Systems Research Articles

Exploring Willingness to Pay across Different Passenger Traits

In recent years, the transportation landscape has seen a notable shift towards shared mobility, driven by its advantages over traditional systems fraught with inefficiencies. This shift has ushered in demand-responsive transport (DRT) systems, enabled by mobile technology. DRT offers a promising solution for the sustainability of public transport, also for rural Slovakia; however, higher individual journey costs and the necessity for online booking create adoption barriers for this new form. This paper conducts a thorough willingness-to-pay analysis in seven rural Slovak settlements, with the goal of understanding variations and comparing the findings with the existing research. Location, household size, age, car and train usage, and previous experiences with bus transport significantly impact the willingness to pay. Consequently, tailored DRT strategies are necessary for different target groups. To maximize the efficiency of this service, integrating DRT into the regional or national public transportation network is recommended. Insights from this study hold significant implications for policymakers tasked with transforming regional transportation, particularly by integrating DRT into fixed-route bus systems.

Configurations and features of demand responsive transports

The concept of Demand Responsive Transport (DRT) has been around for more than 40 years and is a promising mobility alternative when traditional public transport proves inadequate in terms of its effectiveness or efficiency, as is the case of low-density areas. DRT systems have a wide range of operational configurations, being highly adaptable to different contexts and environments. Therefore, the design of a DRT mobility solution can become a quite complex and challenging problem. To assist in the design of DRTs, this paper aims to present a comprehensive classification of DRT features and to identify some common design choices in different operational scenarios. The proposed classification is based on a review of reports from available literature and previous European DRT projects. In addition, an analysis of the most usual configurations for different purposes and scenarios is presented. In this research, the operational, demand, and administrative characteristics of DRTs are addressed. Demand aspects encompass features that directly influence trip demand, such as service areas, target passengers, and hours of operation. Operational features include characteristics that will affect daily operations as the type of stops, frequency of the operation, booking methodology, vehicle route, pick-up and drop-off locations, and the vehicle type used. Administrative characteristics address the relationship between consumers and the system, such as the purpose of the system, fares, visual identification of stops, and booking methods. Regarding the usual design choices, our survey shows that rural DRTs are primarily oriented to serve populations in need in low-density areas and to complement existing PT gaps, while urban DRTs are mainly viewed as a mobility alternative to fill existing PT gaps. Defining design patterns for peri-urban and multi-area DRTs presents challenges due to their transitional nature, thus combining attributes of both rural and urban systems.

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.

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.

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

Comparison of Operational Costs for Fixed-Route Bus Service and Demand Responsive Transport Systems. The Case of Kosice Region - Slovakia

The issue of sustainability of public transport is constantly receiving attention from both government and research. One possible solution, demand responsive transport (DRT), can increase accessibility in rural areas, improve the quality of service as well as reduce the costs. This paper estimates the operational costs for different types of vehicles in DRT in person-kilometers and compares it to the current costs of standard bus transport for year 2021 and analyses the capacity, occupancy and ticket prices of fixed-route bus transport. As the results indicate, in many cases the costs of DRT are higher compared to standard bus transport, but by increasing the occupancy of vehicles the DRT can provide savings up to 66 %. The use of cars, as well as car-sharing, show higher costs, which is mainly related to a low transport capacity. As the most appropriate vehicles of DRT have been identified micro buses and minibuses.

Optimization of demand-responsive transport: The rolling horizon approach

Demand-responsive Transport (DRT) is a popular topic in the field of transportation. The rolling horizon approach can be used to achieve an efficient operation of the DRT system in the context of trip pre-booking. In this study, a rolling horizon optimizer is implemented and used in an agent-based transport simulation framework. A series of experiments are performed to study the performance of the rolling horizon approach. The results of the experiments provide general guidelines on how to set up the rolling horizon optimizer for a DRT system. With a suitable setup, the rolling horizon approach demonstrates a clear advantage over the other approaches available in the simulation framework.

Demand responsive transport: New insights from peri-urban experiences

Despite great differentials between urban, peri-urban and rural experiences, little research on demand responsive transport (DRT) has been conducted in peri-urban settings. This paper explores the influence of peri-urban area (PUA) conditions on the design and the operation of DRT and the resulting demand patterns and modal shifts. It uses a combination of a trip dataset and a survey of users and non-users. Key findings suggest that the provision of public transport services within the PUA and to nearby towns and cities, the high car ownership rate and the low demand have a significant influence in designing the DRT scheme. An integrated DRT and public transport (PT) system has potentials to be successful in a context of PUA. Our empirical evidence indicates that such a DRT service design can improve the accessibility and generate a stable demand while reducing the risk of substituting PT. However, there is a danger of the unwanted substitution of walking and cycling. We provide recommendations for DRT planners and operators in developing future schemes in PUA settings.

Simulation of Demand Responsive Transport using a dynamic scheduling tool with SUMO

Demand responsive transport (DRT) has been increasingly tested and applied in recent years as a new form of transportation that seeks to address mobility problems in cities and rural areas. The planning of DRT systems is a challenging task for transport planners since the performance of the service depends significantly on the demand, how the scheduling is made, and how the routes are computed. Transport simulations are a useful option to evaluate these systems. The paper presents a Python tool, which aims to simulate diverse DRT services using the software package for microscopic simulations Eclipse SUMO (Simulation of Urban MObility) as a framework. The fleet and requests of the DRT are handled dynamically by the scheduling module of the tool. This module is also responsible for calling a solver algorithm for the Dial-a-Ride-Problem (DARP), processing its results, and dispatching the DRT vehicles according to them. The tool also enables easier implementation of other methods to solve the DARP. To demonstrate the use of the tool, a DRT service operating in two central neighborhoods of the city of Brunswick (Germany) is presented. The tool is called drtOnline.py and is included in SUMO since version 1.9.0.

Simulation of a Demand Responsive Transport feeder system: A case study of Brunswick

Public transport systems in rural and peri-urban areas are in many cases characterized by long travel times, low frequencies and irregular services. Because of this, motorized private transport is often the only practicable mode of mobility in these regions. The use of Demand Responsive Transport (DRT) as feeder systems to mass public transport modes presents a great potential for improvement. This paper investigates the potential of such a system applied to a case-study of a peri-urban area of Brunswick, Germany. For that, the current bus line was replaced by a Bus Rapid Transit (BRT) line with DRT as feeder systems. In order to evaluate the performance of the proposed system and provide a benchmark against the current public transport o er, multiple trips to the city center with the different transport modes were simulated. The agent-based microscopic simulation Eclipse SUMO (Simulation of Urban MObility) was used as a framework. The scenario of the DRT systems was simulated by SUMO coupled to a developed dispatching algorithm. The results show the potential of the proposed system due to the lower travel times, higher frequency and greater service area. Travel times were even comparable with the travel times of private car-based modes, which could lead to a potential increase in demand.

A chance-constrained dial-a-ride problem with utility-maximising demand and multiple pricing structures

The classic Dial-A-Ride Problem (DARP) aims at designing the minimum-cost routing that accommodates a set of user requests under constraints at an operations planning level, where users’ preferences and revenue management are often overlooked. In this paper, we present a mechanism for accepting/rejecting user requests in a Demand Responsive Transportation (DRT) context based on the representative utilities of alternative transportation modes. We consider utility-maximising users and propose a mixed-integer programming formulation for a Chance Constrained DARP (CC-DARP), that captures users’ preferences via a Logit model. We further introduce class-based user groups and consider various pricing structures for DRT services. A customised local search based heuristic and a matheuristic are developed to solve the proposed CC-DARP. We report numerical results for both DARP benchmarking instances and a realistic case study based on New York City yellow taxi trip data. Computational experiments performed on 105 benchmarking instances with up to 96 nodes yield average profit gaps of 2.59% and 0.17% using the proposed local search heuristic and matheuristic, respectively. The results obtained on the realistic case study reveal that a zonal fare structure is the best strategy in terms of optimising revenue and ridership. The proposed CC-DARP formulation provides a new decision-support tool to inform on revenue and fleet management for DRT systems on a strategic planning level.

A demand responsive public transport for a spatially scattered population in a developing country

Rural areas in developing countries suffer from substandard public transit services. The authorities find it difficult to provide quality transport primarily due to budget constraints pertaining to transport infrastructure development, which accommodates spatially heterogonous demand. A questionnaire survey based study conducted in a sparsely populated rural region in Sri Lanka revealed that economically deprived and dependent population tended to choose public transit more over private. The key factors identified in this study that determine the choice of transit were age, gender, education, motorized vehicle ownership, income, travel frequency and transit accessibility. This study further examined the commuter’s willingness towards switching to Demand Responsive Transport system (DRT). Given that DRT was introduced, the commuters responded strongly to pay additional fare whereas moderate agreement was observed in expected comfort level and cashless ticketing. On average, the respondents consented to pay additional fare of SLR 10.75 (0.054 USD) and to wait for 11.65 min to access DRT service. The willingness towards switching to DRT was relatively high in present private transit users than that of in present public transit users. The high level of mobile phone penetration in the study region indicated the feasibility of incorporating state-of-the-art computing and communication technologies to administer DRT system. Authors, therefore recommend transport agencies to assess the financial benefits of introducing DRT service by optimizing the existing resources based on the identified influential parameters.

The attitude of potentially less mobile people towards demand responsive transport in a rural area in central Germany

Demand Responsive Transport (DRT) systems are often discussed to expand public transport in rural areas, where conventional buses are often used below capacity. DRT systems can particularly improve the mobility situation for less mobile people or other people who depend on public transport and ultimately prevent them from social exclusion. This paper examines whether people who show characteristics that indicate a mobility deficit are more willing to access the DRT system EcoBus in a rural area of Germany. Using survey data from 156 respondents from households in the EcoBus service area and utilizing linear regression analysis, this study confirms that car availability harms the intended use of DRT and that physical impairment has a positive effect, as identified several times in the literature. Furthermore, the influence of age on the intended EcoBus use depends on the residence place's city size and hence on its offer of daily public services. While residents of a sub-centre of the region are significantly less willing to use the EcoBus with increasing age, there is an opposite tendency for small villages. Thus, in small inaccessible localities, the likelihood of using EcoBus increases with age, suggesting that DRT systems benefit the doubly constrained population, namely the elderly population in localities with few public services.

The effects of gift vouchers and environmental certificates on the demand for a collective DRT system

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.

Optimal fleet size for a shared demand-responsive transport system with human-driven vs automated vehicles: A total cost minimization approach

Vehicle automation is expected to reduce the cost of shared demand-responsive transport (DRT) services. In this context, questions regarding the conditions under which fixed-route public transport can be replaced with shared on-demand services have emerged. The expected increase in competitiveness between fixed-route and on-demand services requires the development of frameworks that enable the analysis of transportation costs of alternative modes. In this research, we develop a total cost minimization model for demand-responsive door-to-door shared transportation services, including operator and user costs. Optimization variables are vehicle size and fleet size for operation with human-driven and automated vehicles. A hybrid approach is used in which the relevant variables are analytically and numerically modeled, using data from a large-scale agent-based simulation applied to the city of Munich. We compare the case in which all trip requests must be served with the case in which request rejections are allowed, based on waiting and travel times. Different demand levels and alternative scenarios for vehicle automation are analyzed. The results indicate that the performance of door-to-door on-demand shared systems depends on the operational scheme selected. For the DRT setup and vehicle assignment strategy studied, we find that if the system is forced to have no trip rejections, economies of scale are not present, and the high user costs hinder the system’s competitiveness even under the assumption of automated vehicles. In contrast, in a system that allows for trip rejections, economies of scale are present, and vehicle automation can especially reduce operator costs, increasing the system’s competitiveness against other transportation modes. Therefore, in our setting, the efficiency of the demand-responsive service depends on the ability to reject customers, which is against the spirit of a truly public transportation service. On scenario analysis, we show that a theoretical improvement in the performance of the real-time vehicle assignment strategy can significantly reduce total cost, with economies of scale under no-rejection operation. Future research needs to address whether the actual application of more complex vehicle assignment strategies can indeed make DRT systems more cost competitive while serving all trip requests.

Mobility service design via joint optimization of transit networks and demand-responsive services

This paper proposes a modeling framework to design an integrated mobility service system that is composed of a local demand-responsive transportation (DRT) component and a fixed-route transit network component. The region is partitioned into disjoint local zones, and a trip is characterized into an intra- or inter-zonal one based on whether its origin and destination belong to the same zone. The transit network provides backbone line-haul service to inter-zonal trips, while the DRT system targets intra-zonal trips as well as the first-mile and last-mile legs of inter-zonal trips. The system components can be broadly defined, and this paper considers, as examples, conventional non-shared taxi or ride-sharing for the DRT service, and regular bus, bus rapid transit (BRT), or metro for the backbone network. For quantitative analysis of the DRT services, new aspatial queuing network models are developed to capture various DRT operations for serving trips with randomly distributed origins and destinations (i.e., intra-zonal trips) and those with origins or destinations concentrated at a set of fixed transit stations (i.e., first- or last-mile trip legs) at the same time. Each queuing model is integrated with the transit network design model, through proper service region partition, to derive closed-form formulas for the agency and passenger costs. Then, we formulate constrained non-linear programs that simultaneously optimize the zone partition, the fleet size and repositioning operation for the local DRT service, as well as the spacing and headway of a grid transit network. We apply the proposed models to a variety of transit technologies and application scenarios, so as to demonstrate applicability of the models, and to show promising performance of the proposed systems.

Design and Implementation of Zone-to-Zone Demand Responsive Transportation Systems

Conventional fixed-structure transit service is unable to satisfy the increasingly personalized passenger demand. Shared mobility companies enable the transformation of conventional transit with advanced technology. This paper proposes a framework to design an application-based demand responsive transit (DRT) system to serve zone-to-zone passenger requests. The proposed DRT service operates between zone pairs to satisfy “door-to-door” and “reservation-based” requests. A two-phase problem is formulated, including (i) conceptual planning phase and (ii) discrete route design phase. In the conceptual planning phase, a continuous approximation model is proposed to optimize operational efficiency by deciding the resource requirements and operational features with given service area and demand density. In the route design phase, a customized bus routing model is established to generate profitable routes, by adopting a combined solution approach with adapted savings and simulated annealing (SA) method. The theoretical framework is applied in a pilot area at Huangdao College Town in Qingdao, China. An implementable design including the layout plan, candidate stops, and operation headways is developed from the conceptual plan model. Groups of sample data sets are used to demonstrate the applicability of the proposed design framework. Results show that the proposed DRT system is promising in relation to providing better service than the previous first-come-first-serve bus pooling service.