Multi-agent simulation for planning and designing new shared mobility services

Inturri, Giuseppe; Pira, Michela Le; Giuffrida, Nadia; Ignaccolo, Matteo; Pluchino, Alessandro; Rapisarda, Andrea; D’Angelo, Riccardo

doi:10.1016/j.retrec.2018.11.009

Cited by 55 publications

(30 citation statements)

References 25 publications

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“…Moreover, it is expected that a distributed computational solution, such as the multi-agent architecture, will outperform centralized modeling systems owing to its autonomy and flexibility [32]. Multi-agent computing was applied to overcome several transport challenges, including urban traffic control [33][34][35][36], fleet management [37,38], and route planning and guidance [39,40]. Different agent-based frameworks were used in these applications to implement multi-agent environments, e.g., MATsim [41].…”

Section: State-of-the-art Intelligent Transport Management Systemsmentioning

confidence: 99%

An Eco-Friendly Multimodal Route Guidance System for Urban Areas Using Multi-Agent Technology

et al. 2021

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The use and coordination of multiple modes of travel efficiently, although beneficial, remains an overarching challenge for urban cities. This paper implements a distributed architecture of an eco-friendly transport guidance system by employing the agent-based paradigm. The paradigm uses software agents to model and represent the complex transport infrastructure of urban environments, including roads, buses, trolleybuses, metros, trams, bicycles, and walking. The system exploits live traffic data (e.g., traffic flow, density, and CO2 emissions) collected from multiple data sources (e.g., road sensors and SCOOT) to provide multimodal route recommendations for travelers through a dedicated application. Moreover, the proposed system empowers the transport management authorities to monitor the traffic flow and conditions of a city in real-time through a dedicated web visualization. We exhibit the advantages of using different types of agents to represent the versatile nature of transport networks and realize the concept of smart transportation. Commuters are supplied with multimodal routes that endeavor to reduce travel times and transport carbon footprint. A technical simulation was executed using various parameters to demonstrate the scalability of our multimodal traffic management architecture. Subsequently, two real user trials were carried out in Nottingham (United Kingdom) and Sofia (Bulgaria) to show the practicality and ease of use of our multimodal travel information system in providing eco-friendly route guidance. Our validation results demonstrate the effectiveness of personalized multimodal route guidance in inducing a positive travel behavior change and the ability of the agent-based route planning system to scale to satisfy the requirements of traffic infrastructure in diverse urban environments.

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Section: State-of-the-art Intelligent Transport Management Systemsmentioning

confidence: 99%

An Eco-Friendly Multimodal Route Guidance System for Urban Areas Using Multi-Agent Technology

et al. 2021

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“…In addition to analysing the integration of on-demand mobility services into public transport offers and the ecological effects of these services, we are interested in the role of the spatial context (rural vs. urban). Since on-demand mobility services offer high flexibility to their users, the authors of [41] suggest that these services are especially useful in low-density urban areas or small urban centres. However, there are only a few academic articles on the influence of space (urban vs. rural) and density on on-demand mobility services.…”

Section: Literature Reviewmentioning

confidence: 99%

The Impact of On-Demand Collective Transport Services on Sustainability: A Comparison of Various Service Options in a Rural and an Urban Area of Switzerland

2021

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This study examines the effects of on-demand mobility services on sustainability in terms of emissions and traffic volume. According to our simulations, implementing on-demand mobility services is recommendable only as a supplement to public transport in both urban and rural regions since there are positive effects in terms of CO2 emissions. However, in urban areas, there is a negative impact on the traffic volume in terms of additional vehicle kilometres since the bundled public transport demand is replaced by less bundled on-demand vehicles. In rural areas, the increase in vehicle kilometres plays less of a role due to generally low demand. The negative effects per vehicle kilometre are slightly higher in rural areas due to higher empty kilometres and lower bundling rates, but the negative effects per km2 in dense cities are much more serious. Authorities need to consider these effects according to the spatial context when implementing such services.

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“…The wide spatio-temporal availability of these services, made possible by mobile applications that easily match real time demand and supply, favors the use of micromobility in combination with other modes of transport, such as fixed and demand-responsive transit. Thus fostering a shift from a car dependent mobility model towards a Mobility as a Service (MaaS) approach, implying multimodal and seamless door-to-door trips [3][4][5][6]. Integrating micromobility with public transport could also enlarge its catchment area, increase its accessibility, and reduce congestion phenomena and pollution, thus making cities more liveable [7].…”

Section: Introductionmentioning

confidence: 99%

Planning Suitable Transport Networks for E-Scooters to Foster Micromobility Spreading

et al. 2021

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Micromobility has a high potential to change mobility habits towards the use of sustainable transport modes. The shared mobility paradigm encourages the development of new mobility services, such as bike and e-scooter sharing, potentially reducing the need of car ownership, enlarging the accessibility of public transport and enriching the transport options needed to exploit Mobility as a Service solutions. While bike-sharing services have been used in urban areas for many years, shared e-scooter services (and private e-scooters) have been spreading only in the last few years. Due to the novelty of this mode, few attempts have been made for proper micromobility network planning. This paper proposes a multicriteria GIS-based analysis aimed at planning priority networks for e-scooters, focusing on safety, transport and land use characteristics. The case study is Catania, a medium-sized city in southern Italy, which suffers from a lack of adequate infrastructures for such sustainable modes of transport. By applying the methodology, it is possible to prioritise the road network elements that better fit the needs of e-scooters, thus paving the way for suitable infrastructures and network planning.

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Multi-agent simulation for planning and designing new shared mobility services

Cited by 55 publications

References 25 publications

An Eco-Friendly Multimodal Route Guidance System for Urban Areas Using Multi-Agent Technology

An Eco-Friendly Multimodal Route Guidance System for Urban Areas Using Multi-Agent Technology

The Impact of On-Demand Collective Transport Services on Sustainability: A Comparison of Various Service Options in a Rural and an Urban Area of Switzerland

Planning Suitable Transport Networks for E-Scooters to Foster Micromobility Spreading

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