Demand Responsive Transport Research Articles

Public Transit Planning and Operation in the Era of Automation, Electrification, and Personalization

The advent of Connected and Autonomous Vehicles (CAVs) and Mobile Internet technologies is reshaping the public transport sector. Autonomous buses are equipped with varying advanced sensors, and hold great promises to enhancing the responsiveness and flexibility of public transit system. In the context of CAVs, transit operators can not only optimize service headway but also adjust bus capacity to meet the time-varying passenger demand. Anticipated benefits of introducing autonomous buses to the existing transit systems include safety improvement, driver cost reduction, and optimal routing. Bus electrification is another global trend to replace traditional diesel buses for energy savings. Electric buses are advantageous to both operators and passengers due to low greenhouse gas emission, maintenance cost, as well as noise pollution. In recent years, demand responsive public transport (DRPT) services (e.g. customized bus, microtransit) receive huge success thanks to the development of Mobile Internet. Unlike traditional bus services or the fixed-route transit service that relies on passive recipients, fixed stops, and schedules, DRPT can provide personalized service for specific clients through interactive information platform (Internet or smartphone). The aforementioned new types of public transit services significantly improve service quality, reduce energy consumption, and ultimately attract more ridership. To fully explore the benefits of personalized, electric and autonomous transit systems, new analytical models and data-driven methods for transit planning and operation are needed. The authors have selected 15 articles for review in this special issue. A summary of these articles is outlined below.

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.

Taxi vs. demand responsive shared transport systems: An agent-based simulation approach

Public transport in urban and suburban areas is not always able to meet population's need of accessibility to jobs, education, health and other opportunities in terms of routes and frequencies; therefore, those who do not own a private vehicle, or who cannot afford individual public transport (e.g. taxis), are often in a condition of social exclusion. Taking advantages of new ICT tools and facilities, Demand Responsive Shared Transport (DRST) services can provide “on demand” transport gathering ride bookings of different users and routing a fleet of vehicles to satisfy passengers' needs while minimizing the cost for the operator.In this paper, different DRST service configurations are compared to taxi services to investigate their economic attractiveness and sustainability. This is done by using an agent-based simulation model applied to the case of Ragusa (Italy), a city with poor public transport supply, where an innovative DRST service has already been experimented. A set of 50 different scenarios has been simulated, by varying the numbers of vehicles and seat capacity, and considering different demand rates and route choice strategies of the vehicles. Results are analyzed according to different key performance indicators, mainly showing that the DRST system is more advantageous than taxis when dealing with higher demand rates. On the other hand, the efficiency of the DRST system is rather limited compared to taxis in the case of low transport demand and fleets with a small number of vehicles. Between high and low demand there is a balance between the taxi and the DRST systems, where one should deepen the analysis to identify optimal operational parameters. These results pave the way for further analyses to help the planning and design of intermediate transport services like DRST, which are able to bridge the gap between collective and individual transport in urban and suburban areas.

Developing Sustainable and Flexible Rural–Urban Connectivity through Complementary Mobility Services

Transport can play a key role in mitigating climate change, through reducing traffic, emissions and dependency on private vehicles. Transport is also crucial to connect remote areas to central or urban areas. Yet, sustainable and flexible transport is among the greatest challenges for rural areas and rural–urban regions. Innovative transport concepts and approaches are urgently needed to foster sustainable and integrated regional development. This article addresses challenges of sustainability, accessibility, and connectivity through examining complementary systems to existing public transport, including demand-responsive transport and multimodal mobility. We draw upon case studies from the Metropolitan Area of Styria, Ljubljana Urban Region and rural Wales (GUSTmobil, REGIOtim, EURBAN, Bicikelj, Bwcabus, Grass Routes). In-depth analysis through a mixed-methods case study design captures the complexity behind these chosen examples, which form a basis for analysing the effects of services on accessibility for different groups, connectivity to public transport and usability as a “first and last mile” feeder. We further explore the weaknesses of complementary transport systems, including legal, organisational and financial barriers, and offer potential solutions to structure and communicate complementary transport systems to improve access and use. Looking ahead, we use the case studies to anticipate innovative, sustainable “mobility as a service” (MaaS) solutions within and between urban and rural areas and consider how future public policy orientations and arrangements can enable positive change. A main concern of our article and the contribution to scientific literature is through exploring the benefit of well-established multi-level governance arrangements when introducing smaller-scale mobility solutions to improve rural–urban accessibility. It becomes clear that not a one-size-fits-all model but placed-based and tailored approaches lead to successful and sustainable concepts.

Integrating Demand Responsive Services Into Public Transport Disruption Management

High-capacity public transport services such as metro and commuter trains are efficient during normal operations but are vulnerable to disruptions. To manage disruptions, bridging buses are commonly called in to replace the rail-based service along the disrupted lines. These often take significant time to arrive and are costly to keep stand-by. Demand-responsive transport such as taxi can respond to demand almost immediately but is costly and must usually be arranged by the individual travelers. This study examines the integration and potential role of demand-responsive transport in disruption management. The analysis considers the impacts of limiting the serving area, varying the number of available vehicles, pursuing ride-sharing, as well as a system-of-systems approach with collaboration between taxis and bridging buses. Results of computational experiments on the case study of Stockholm, Sweden reveal that integration of demand-responsive transport in the disruption management can bring large positive benefits in terms of average and maximum waiting times for travelers. This is especially the case for strategies including ride-sharing. It is also shown that appropriate trade-offs between desired waiting times and costs can be achieved by collaboration of both bridging buses and demand-responsive transport. Additionally, more robust public transport with increased reliability during disruptions can increase sustainability as more people may choose public transport instead of private cars.

Travelers’ Attitudes Toward Mobile Application–Based Public Transport Services in Lahore

Many cities in developing countries are facing challenges of providing quality public transport facilities to the public. The demand-responsive transport (DRT) initiatives in some cities have helped in providing transportation alternatives to the travelers, and in filling the gap between demand and supply. Recently introduced DRT initiatives in Lahore included the mobile app-based Airlift and Swvl bus services. This article is aimed at evaluating the travelers’ attitudes toward mobile application (app)–based DRT services in Lahore with the help of a questionnaire survey. A questionnaire was designed consisting of travelers’ personal and travel information and their perceptions on selected attributes of Airlift and Swvl bus services. A total of 440 samples were collected through interviews. An exploratory factor analysis (EFA) revealed three factors of service quality, that is, Accessibility and Scheduling Attributes (ASA), Instrumental Attributes (IA), and Service Attraction Attributes (SAA). The results of Structural Equation Modeling (SEM) showed that the ASA, IA, and SAA are significant determinants of travelers’ attitudes toward the existence of Airlift and Swvl bus services in Lahore. These factors have strong correlations with travelers’ intentions to use Airlift and Swvl services in the future. The waiting time at a stop, travelers’ income, vehicle ownership, trip purpose, and profession are also significant in determining the travelers’ attitudes and preferences with app-based public transport services. These findings would be helpful for the service providers and transport planners for making appropriate policies to improve the quality of these services.

A multi objective approach for DRT service using tabu search

Urban population is increasing fast. This is creating new challenges to public transport systems since some groups of citizens as elderly people may have sensory, cognitive or motor impairments that need to be addressed. This work explores the potential of a Demand Responsive Transport (DRT) system for people with reduced mobility in an urban environment. For this purpose, the Dial-A-Ride Problem (DARP) was implemented using a multivariable minimisation approach. In this approach, an Assigning Request to Vehicles (ARV) algorithm is used to obtain an initial solution. Then a Multi-Objective Tabu Search Algorithm (MOTSA) is applied to the initial solution to search for the non-dominated solution (optimisation phase). In this optimisation phase, the total travelled distance, the deadheading distance and the number of vehicles were minimised. The performance of the model was computed combining different parameters’ values of the number of requests, boarding time for each user, the number of seats in each vehicle, vehicle’s speed, the total number of iterations, and candidate threshold number (the algorithm’s parameter). The computational results found a strong positive correlation between the number of requests and the: total travelled distance (rs = 0.977, p-value<0.001) and the number of vehicles (rs =0.883, p-value<0.001); and a low positive correlation between the number of requests and the optimised total travelled distance (rs =0.331, p-value<0.001) and the optimised number of vehicles (rs =0.340, p-value<0.001).

Impact assessment of autonomous demand responsive transport as a link between urban and rural areas

Disruptive developments in automated driving systems, new powertrain concepts and digital mobility are shaping changes in the way people move in rural and urban areas. In combination with these technical potentials, novel mobility concepts as for instance demand responsive transportation (DRT) can improve the everyday mobility of people in terms of both cost-efficiency and sustainability. Moreover, challenges related to demographic transitions and urbanisation can be addressed and negative developments mitigated. One potential application of DRT might be the connection of rural areas with the urban core.The following paper aims to evaluate the viability and feasibility of DRT systems in the interplay of rural and urban areas. The city of Bremerhaven and the immediate surrounding are selected as area of investigation and the agent-based modelling framework MATSim is used to simulate the inhabitant mobility behaviour. On this basis, the global operational costs are calculated for different scenarios, e.g. fully automated vehicles and various powertrain types. The results imply that automated DRT systems are applicable to reduce the economic and environmental costs of transportation when applied in the interplay of rural and urban areas.

Online clustering reduction based on parametric and non-parametric correlation for a many-objective vehicle routing problem with demand responsive transport

In this paper, we address an online dimensionality reduction approach to deal with a many-objective formulation of a Vehicle Routing Problem with a Demand Responsive Transport (VRPDRT). The problem relates to a mode of transport similar to available carpooling services in which passengers are transported from their origin to their destination sharing the same vehicle. The goal is to reduce the operating/riding costs while meeting passenger needs and providing high-quality service. Due to the complexity and conflicting characteristics of the problem, an evolutionary approach based on a dimensionality reduction technique is applied to solve the VRPDRT in which eight different objective functions are used. The performance of the proposed approaches – OnCLτ-MOEA/D and OnCLρ-MOEA/D – are compared to an a priori cluster dimensionality reduction with Pearson’s and τ of Kendall correlation coefficients using a realistic data set containing distances and travel time for Belo Horizonte, Brazil. The online and offline versions of the algorithms are also compared with a baseline approach, a classic version of MOEA/D. Results show that the online cluster-based approach achieves a better spread of solutions, when compared to its a priori versions. Moreover, there is no difference between the results obtained from the online Cluster-based approach and the original MOEA/D. It shows that the proposed dimensionality reduction is an effective technique presenting a positive effect on the search efficiency, computational cost, and in the application of usual visualization techniques.

Mobility-as-a-Service and Demand-Responsive Transport: Practical Implementation in Traditional Forecasting Models

The increasing effect of Transport Network Companies (TNCs) in major US cities, allied to the expectation that connected and autonomous vehicles (CAVs) will become the prevailing type of automobile on the streets in the coming decades, requires such a trend to be reflected in our forecasting models. Yet, most of the efforts undertaken in the United States and elsewhere are largely focused on understanding the demand for such types of transportation and have left aside the analysis of crucial differences in envisaged systems, such as pooled versus single-occupancy vehicles, use of CAVs as access modes to mass transit, and the cost corresponding to different levels of service in citywide systems. In this paper we introduce a new algorithm for modeling pooled CAVs and a framework for integrating this into traditional forecasting models. We also present the preliminary results of an application of the proposed methodology to the metropolitan region of Vancouver, British Columbia. The results are promising, although a few implementation choices made for this study have resulted in poor computational performance.

Will Autonomous Vehicles address impediments to the mobility of ageing populations?

Background/Aims&#x0D; Autonomous Vehicles (AVs) have been touted as a ‘mobility panacea’ for ageing populations. The hopes invested in such technocentric solutions can be understood with reference to the spatial-temporal context of the Global Demographic Transition. The geography of ageing culminates in growing levels of social isolation of older populations in rural, regional and suburban areas. This spatial trend is superimposed on a temporal landscape of recurring economic crises, creating fiscal constraints impeding the efficacy of conventional solutions including scheduled and demand-responsive transport. To what extent can AVs respond to the mobility needs of older people at a time of fiscal crisis?&#x0D; Methods&#x0D; To address this knowledge gap, I undertook a systematic literature review with two academic colleagues from Curtin University in 2019. We reviewed the AV related papers and the wider transportation planning and gerontological research inclusive of factors known to influence the mobility of older people. The research informed a critical perspective exploring possible impacts, inclusive of risks and opportunities through the methodology of scenario analysis.&#x0D; Results&#x0D; We found the technology had the capability to address some aged mobility needs such as those resulting from declining driving ability, and might provide a framework supportive of ‘ageing in place’ solutions.&#x0D; Conclusions&#x0D; The ability to realise the full potential of this ‘socio-technical transition’ and effectively manage unintended impacts, will be informed by society’s institutional capacity inclusive of the State’s ability to implement timely interventions in mobility markets and provide an integrated approach to transport and land use planning.

Acceptable Automobility through Automated Driving. Insights into the Requirements for Different Mobility Configurations and an Evaluation of Suitable Use Cases

It is hoped that Automated Driving (AD) will make alternatives to the private car more attractive and facilitate the transition to sustainable transport. However, this expectation may underestimate both the resistance of private automobility and the unintended consequences of automated driving. Whether AD will contribute to sustainable mobility depends largely on its implementation and how its risks are prevented. This paper provides empirical insights into the design of acceptable forms of AD by investigating specific use cases with respect to the requirements of different mobility configurations. We pay special attention to people who travel with children. Our use cases comprise three probable types, covering the spectrum from demand-responsive transport (DRT) to private vehicles. Our results include the identification of mobility configurations and an analysis of AD use cases considering several empirically derived criteria: improved accessibility, ease of daily life and well-being, and improvement of the traffic situation and the transport system. Our analysis is based on a qualitative study in the Berlin area, Germany. The discussion focuses on the usefulness of AD against the background of different user perspectives, sustainability, and societal requirements, as well as an evaluation of AD in terms of its acceptability. We conclude that automated mobility use cases should meet the requirements of different mobility configurations to promote the transformation from private to shared automobility and, eventually, less automobility overall.

Evaluation methods and governance practices of new flexible passenger transport projects

The emergence of new flexible passenger transport services enabled by technological advancements can have substantial impacts on efficiency and sustainability of public transport systems. Socio-economic appraisal methods of transport investments have developed during last decades, and especially CBA is proven to provide robust method for ranking alternative large conventional transport investments such as rail and road projects. However, there is much more uncertainty with potential impacts of new flexible passenger transport serves such as the automated demand responsive transport services, which can be seen as disruptive technologies on the transport markets. For addressing this uncertainty, we studied governance practices for using CBA and other economic appraisal methods in public decision making in the European Union with a special focus on Germany. We identified and analysed the most uncertain and challenging impacts of the new flexible transport services, which require better consideration in current evaluation methods and practices. The results point out challenges and opportunities for reaching the gap between current appraisal practices and the latest knowledge on the potential impacts of new flexible passenger transport services.

How much flexibility does rural public transport need? – Implications from a fully flexible DRT system

Rural regions in industrialised countries are facing problems in public transport (PT) provision against the backdrop of demographic change, urbanisation and austerity policies. However, innovative mobility concepts evolve under technological developments. Demand responsive transport (DRT) has been identified in research to meet the challenges and efficiently improve mobility through the concept of ride-pooling. Still, most of these DRT services are being investigated in urban settings with high mobility demand and population density. Research on low-demand regions, such as the Oberharz in Germany, is rarely considered. Moreover, the applied DRT services come with several restrictions regarding stop locations, customer target groups or spatial restrictions. Therefore, this paper fills this gap through spatial and temporal analysis of a real-life, fully flexible and true door-to-door DRT experiment. Over a 6-months period around 38,000 trips took place in the Oberharz. The analysis of these trips shows that an unrestricted DRT service between three main centres (Goslar, Clausthal-Zellerfeld and Osterode) results in main travel axes between these cities while the more remote areas forfeit mobility to these centres of public service provision. Consequently, a feeder-trunk system should be favoured for future DRT services in low-demand areas to sustainably improve mobility in remote regions. The complementary extension of the existing PT through such a DRT service should then meet mobility needs of rural areas to redeem car dependency and improve mobility for all population groups.

The combination of e-bike-sharing and demand-responsive transport systems in rural areas: A case study of Velenje

An analysis of the operational characteristics of the transit system serving the town of Velenje (Slovenia) revealed poor performance and the need for improvements. This paper describes the potential integration of an electric bike-sharing system and a semi-flexible demand-responsive transport system to effectively solve this issue. Additionally, general guidance is provided for transit systems with low travel demand. Appropriate transport system schedules are proposed to facilitate customers' use and thus to move demand shares away from private motorized transport. Focus group interviews, implemented to directly involve local stakeholders, revealed an overall positive perception of the proposed transport system. Furthermore, the cost analysis demonstrated that the costs of the new system would not be much higher for the municipality than those currently incurred, making it an important performance improvement achieved at low cost.

On the role of frameworks and smart mobility in addressing the rural mobility problem

Mobility is fundamentally important in enabling people to access services, which can deliver substantial benefits to people's quality of life. This is particularly important in rural areas where the range and extent of public transport services are, in general, significantly lower than in urban areas, and, indeed, below the level required to provide a level of service that is sufficiently high to enable people in rural areas without private cars to access these services. This paper looks at the role of governments in institutional, organisational, regulatory and financial frameworks in supporting rural transport services at a level that enables this access. A cluster analysis is performed to identify distinct classes of framework types across Europe. In addition, the paper gives examples of good practice and innovation in rural transport from across Europe incorporating a variety of themes: the use of Information and Communications Technology, intermodal service coordination, demand-responsive transport, shared mobility and good governance. Key success factors for introducing, sustaining and transferring these forms of good practice are then discussed.

How Can Smart Mobility Innovations Alleviate Transportation Disadvantage? Assembling a Conceptual Framework through a Systematic Review

Transportation disadvantage is about the difficulty accessing mobility services required to complete activities associated with employment, shopping, business, essential needs, and recreation. Technological innovations in the field of smart mobility have been identified as a potential solution to help individuals overcome issues associated with transportation disadvantage. This paper aims to provide a consolidated understanding on how smart mobility innovations can contribute to alleviate transportation disadvantage. A systematic literature review is completed, and a conceptual framework is developed to provide the required information to address transportation disadvantage. The results are categorized under the physical, economic, spatial, temporal, psychological, information, and institutional dimensions of transportation disadvantage. The study findings reveal that: (a) Primary smart mobility innovations identified in the literature are demand responsive transportation, shared transportation, intelligent transportation systems, electric mobility, autonomous vehicles, and Mobility-as-a-Services. (b) Smart mobility innovations could benefit urban areas by improving accessibility, efficiency, coverage, flexibility, safety, and the overall integration of the transportation system. (c) Smart mobility innovations have the potential to contribute to the alleviation of transportation disadvantage. (d) Mobility-as-a-Service has high potential to alleviate transportation disadvantage primarily due to its ability to integrate a wide-range of services.

Travel Mode Choice Under Unlimited-Ride Scheme of Fixed Route Bus and Demand-Responsive Transport

Travel Mode Choice Under Unlimited-Ride Scheme of Fixed Route Bus and Demand-Responsive Transport

Impact assessment of rural PPP MaaS pilots

The purpose of this paper is to present the impact assessment results of Mobility as a Service pilots based on public-private collaboration. In the pilots, companies and local and regional stakeholders joined their expertise to experiment with different ways of organizing mobility services in rural areas. The pilots included demand-responsive transport and integrated transport of different user groups and combining trips that include customers paying themselves and those being publicly subsidized. In addition to the call centre service, a smartphone application was introduced. The impact assessment of these pilots spans individual/user, business/organizational and societal levels. The main findings include improved accessibility of transport services in rural areas and resource efficiency in terms of improved occupancy rates of vehicles, reduced driven kilometres and emissions, and cost savings for the public sector.

Impacts of replacing a fixed public transport line by a demand responsive transport system: Case study of a rural area in Amsterdam

The diffusion of the smartphone and the urban sprawl is pushing both private and public actors to revisit the concept of demand-responsive transport (DRT). This paper provides a historical overview of DRT experiences, understanding their pros and cons. In addition, it presents the case study of Mokumflex, a 12-month DRT pilot program that replaced the regular bus service in low-density areas of Amsterdam, the Netherlands. Based on a close collaboration with the private enterprise that operated the service and also with the local bus operator, we performed an empirical before and after comparison. These insights help to understand the impacts of DRT systems and support (future) design of DRT and public transport. A set of indicators was chosen for the intermodal comparison: travel distances, ridership, costs, Greenhouse Gases (GHG), emissions and population's perception. Ridership dropped from 78.1 passengers/day to 15.9 passengers/day, however, for being “demand-tailored”, passenger-km reduced even more, going from 1252.8 km/day to 136.6 km/day, hence reducing the costs and GHG emissions per passenger. In regards to population's perception, the system enjoyed a good evaluation.