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Decision Support Tool for Demand Responsive Transport Through Simulation
Malmö University, Faculty of Technology and Society (TS), Department of Computer Science and Media Technology (DVMT). Malmö University, Internet of Things and People (IOTAP).ORCID iD: 0000-0002-1401-3510
Malmö University, Internet of Things and People (IOTAP). Malmö University, Faculty of Technology and Society (TS), Department of Computer Science and Media Technology (DVMT).ORCID iD: 0000-0003-0998-6585
Malmö University, Internet of Things and People (IOTAP). Malmö University, Faculty of Technology and Society (TS), Department of Computer Science and Media Technology (DVMT).
Malmö University, Internet of Things and People (IOTAP). Malmö University, Faculty of Technology and Society (TS), Department of Computer Science and Media Technology (DVMT).ORCID iD: 0000-0002-9471-8405
2018 (English)In: Proceedings of the 2018 Winter Simulation Conference, IEEE, 2018, p. 4188-4189Conference paper, Poster (with or without abstract) (Other academic)
Abstract [en]

Demand Responsive Transport (DRT) is seen as a means to providing mobility for passengers living in lowdensity population areas and impaired passengers with a reasonable cost. Conventional public transport istoo expensive to provide a desired level of mobility for these categories of passengers. Hence DRT hasbeen introduced in order to replace or supplement existing transportation schemes. However, multiple DRTschemes were discontinued due to a high cost or poor patronage. In this work we argue that a simulationtool is required to analyze DRT applicability in given conditions before implementing it. As a first steptowards this tool, we describe the requirements that DRT impose on a simulator.

Place, publisher, year, edition, pages
IEEE, 2018. p. 4188-4189
National Category
Natural Sciences
Identifiers
URN: urn:nbn:se:mau:diva-16783Local ID: 27174OAI: oai:DiVA.org:mau-16783DiVA, id: diva2:1420297
Conference
Winter Simulation Conference, Göteborg, Sweden (2018-12-09 - 2018-12-12)
Available from: 2020-03-30 Created: 2020-03-30 Last updated: 2023-12-27Bibliographically approved
In thesis
1. Modelling and Simulating Demand-Responsive Transport
Open this publication in new window or tab >>Modelling and Simulating Demand-Responsive Transport
2023 (English)Licentiate thesis, comprehensive summary (Other academic)
Abstract [en]

Public transport is an efficient way to transport large volumes of travellers. However, there are systemic issues that make it hard for conventional public transport to provide efficient service on finer levels, like first- and last-mile problems or low-demand areas. One of the potential solutions that has been getting a lot of attention recently in research and real practice is Demand-Responsive Transport(DRT). The main difference between demand-responsive services and conventional public transport is the need for explicit requests for a trip from the travellers. The service then adapts the routes of the vehicles to satisfy the requests as efficiently as possible. One of the aims of such transport services is to combine the flexibility and accessibility of travel modes like taxis and private cars with the efficiency of buses achieved through ride-sharing.DRT has the potential to improve public transport in, for example, low population density areas or for people with mobility limitations who could request a trip directly to a home door. Historically DRT has been extensively used for special transportation while the recent trend in research and practice explores the possibility of using this service type for the general population.The history of DRT shows a large degree of discontinued trials and services together with low utilisation of vehicles and limited efficiency levels. In practice, this leads to measures restricting the trip destination, times when service is available, or eligibility to use the service at all in case of special transport DRT. Due to the limited use of DRT services, there is little data collected on the efficiency of the service and transport agencies exploring the possibility of introducing this new service type face difficulties in estimating its potential.The main goal of this thesis is to contribute towards developing a decisionsupport method for transport analysts, planners, or decision-makers who want to evaluate the systemic effect of a DRT service such as costs, emissions and effecton society. Decision-makers should be able to evaluate and compare a large variety of DRT design choices like booking time restrictions, vehicle fleet type, target trip quality level, or stop allocation pattern. Using a design science, we develop a simulation approach which is evaluated with two simulation experiments. The simulation experiments themselves provide valuable insight into the potential of DRT services, explore the niche where DRT could provide the most benefits and advocate taking into account the sustainability perspective for a comprehensive comparison of transport modes.

The findings from the simulation experiments indicate that DRT, even in its extreme forms like fully autonomous shared taxis, does not show the level of efficiency that could result in a revolution in transportation — it is hard to compete inefficiency with conventional public transport in urban zones. However, in scenarios with lower demand levels, it could be more efficient to replace conventional buses with a DRT service when considering costs and emissions. We also show that, when integrated with conventional public transport, DRT could help alleviate the last-mile problem by improving accessibility to long-distance lines. Additionally, if car users are attracted to public transport with the help of DRT, there is a potential to significantly reduce the total level of emissions.

The simulation results indicate that the proposed simulation method can be applied for the evaluation of DRT. The implementation of trip planning combining DRT and conventional public transport is a major contribution of this thesis. We show that the integration between services may be important for the efficiency of the service, especially when considering the sustainability aspects.

Finally, this thesis indicates the direction for further research. The proposed simulation approach is suitable for the estimation of the potential of DRT but lacks the ability to make a prediction of the demand for DRT. Integration of a realistic mode choice model and day-to-day simulations are important for making predictions. We also note the complexity of the DRT routing for large-scale problems which prohibits a realistic estimation with simulation and the efficient operation of the service.

Place, publisher, year, edition, pages
Malmö: Malmö University Press, 2023. p. 191
Series
Studies in Computer Science ; 25
Keywords
On-Demand Mobility, Demand Responsive Transport, Modelling and Simulation, Sustainability
National Category
Computer Sciences Transport Systems and Logistics
Identifiers
urn:nbn:se:mau:diva-62403 (URN)10.24834/isbn.97891787766 (DOI)978-91-7877-415-9 (ISBN)978-91-7877-416-6 (ISBN)
Presentation
2023-11-08, B2 Niagara, Nordenskiöldsgatan 1, 13:15 (English)
Opponent
Supervisors
Available from: 2023-09-13 Created: 2023-09-08 Last updated: 2023-11-17Bibliographically approved

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Dytckov, SergeiDavidsson, PaulHolmgren, JohanPersson, Jan A.

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