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An Individual-Based Simulation Approach to Demand Responsive Transport
Malmö universitet, Fakulteten för teknik och samhälle (TS), Institutionen för datavetenskap och medieteknik (DVMT). Malmö universitet, Internet of Things and People (IOTAP).ORCID-id: 0000-0002-1401-3510
Malmö universitet, Fakulteten för teknik och samhälle (TS), Institutionen för datavetenskap och medieteknik (DVMT). Malmö universitet, Internet of Things and People (IOTAP).ORCID-id: 0000-0002-8209-0921
Malmö universitet, Internet of Things and People (IOTAP). Malmö universitet, Fakulteten för teknik och samhälle (TS), Institutionen för datavetenskap och medieteknik (DVMT).
Malmö universitet, Fakulteten för teknik och samhälle (TS), Institutionen för datavetenskap och medieteknik (DVMT). Malmö universitet, Internet of Things and People (IOTAP).ORCID-id: 0000-0003-0998-6585
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2021 (Engelska)Ingår i: Intelligent Transport Systems, From Research and Development to the Market Uptake, Springer, 2021, s. 72-89Konferensbidrag, Publicerat paper (Refereegranskat)
Abstract [en]

This article demonstrates an approach to the simulation of Demand Responsive Transport (DRT) – a flexible transport mode that typically operates as a combination of taxi and bus modes. Travellers request individual trips and DRT is capable of adjusting its routes or schedule to the needs of travellers. It has been seen as a part of the public transport network, which has the potential to reduce operational costs of public transport services, to provide better service quality for population groups with limited mobility and to improve transport fairness. However, a DRT service needs to be thoroughly planned to target the intended user groups, attract a sufficient demand level and maintain reasonable operational costs. As the demand for DRT is dynamic and heterogeneous, it is difficult to simulate it with a macro approach. To address this problem, we develop and evaluate an individual-based simulation comprising models of traveller behaviour for both supply and demand sides. Travellers choose a trip alternative with a mode choice model and DRT vehicle routing utilises a model of travellers’ mode choice behaviour to optimise routes. This allows capturing supply-side operational costs and demand-side service quality for every individual, what allows for designing a personalised service that can prioritise needy groups of travellers improving transport fairness. By simulating different setups of DRT services, the simulator can be used as a decision support tool.

Ort, förlag, år, upplaga, sidor
Springer, 2021. s. 72-89
Serie
Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, ISSN 1867-8211, E-ISSN 1867-822X ; 364
Nationell ämneskategori
Transportteknik och logistik Datavetenskap (datalogi)
Forskningsämne
Transportstudier
Identifikatorer
URN: urn:nbn:se:mau:diva-41490DOI: 10.1007/978-3-030-71454-3_5Scopus ID: 2-s2.0-85104409614ISBN: 978-3-030-71454-3 (digital)ISBN: 978-3-030-71453-6 (tryckt)OAI: oai:DiVA.org:mau-41490DiVA, id: diva2:1540774
Konferens
4th International Conference on Intelligent Transport Systems, Virtual Event, December 3, 2020
Tillgänglig från: 2021-03-30 Skapad: 2021-03-30 Senast uppdaterad: 2024-02-05Bibliografiskt granskad
Ingår i avhandling
1. Modelling and Simulating Demand-Responsive Transport
Öppna denna publikation i ny flik eller fönster >>Modelling and Simulating Demand-Responsive Transport
2023 (Engelska)Licentiatavhandling, sammanläggning (Övrigt vetenskapligt)
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.

Ort, förlag, år, upplaga, sidor
Malmö: Malmö University Press, 2023. s. 191
Serie
Studies in Computer Science ; 25
Nyckelord
On-Demand Mobility, Demand Responsive Transport, Modelling and Simulation, Sustainability
Nationell ämneskategori
Datavetenskap (datalogi) Transportteknik och logistik
Identifikatorer
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 (Engelska)
Opponent
Handledare
Tillgänglig från: 2023-09-13 Skapad: 2023-09-08 Senast uppdaterad: 2023-11-17Bibliografiskt granskad

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Dytckov, SergeiLorig, FabianHolmgren, JohanDavidsson, PaulPersson, Jan A.

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Institutionen för datavetenskap och medieteknik (DVMT)Internet of Things and People (IOTAP)
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