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Abstract

Limiting private cars’ use while promoting sustainable modes of transport is one of the main challenges of urban transport planning. In this context, characterized by scarce resources and increasing demand for mobility, Demand Responsive Shared Transport (DRST) services can bridge the gap between shared low-quality public transport and unsustainable individual private transport. Taking advantage of Information and Communication Technologies (ICT), they can supply transport solutions ranging from flexible transit to ride sharing services, providing real-time “on demand” mobility through fleets of vehicles shared by different passengers. The optimal design of a DRST service requires a trade-off among efficiency (from the operators’ point of view), service quality (from the users’ point of view) and sustainability (from the community's point of view). In this paper, an agent-based model (ABM) fed with GIS data is used to explore different system configurations of a specific type of DRST service, i.e. flexible transit, and to estimate the transport demand and supply variables that make the service feasible and convenient. The model reproduces a mixed fixed/flexible route transit service with different fleet size and vehicle capacity in the city of Ragusa (Italy) with the aim to: (i) make a first test of the ABM model with GIS-based demand and road network models; (ii) explore different vehicle dispatching strategies; (iii) find appropriate indicators to monitor the service quality and efficiency. Simulation results show the impact of fleet composition and route choice strategy on the system performance. In particular, they show an optimal range of operating vehicles that minimizes a total unit cost indicator, accounting both for passenger travel time and vehicle operation cost. By reproducing the microinteraction between demand and supply agents (i.e. passengers and vehicles), it is possible to monitor the macroscopic behaviour of the system, and derive useful suggestions for the correct planning, management and optimization of DRST services.

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... Nine papers constitute the special issue, showing various perspectives from different parts of the world, i.e.: Italy (Gatta et al., 2019a;Inturri et al., 2019), Spain (Rahmani & Loureiro, 2019), France (Souche-Le Corvec, Mercier, Ovtracht, & Chevallier, 2019), the Netherlands (Wiercx, van Kalmthout, & Wiegmans, 2019), Sweden (Langbroek et al., 2019), United Kingdom (Percoco, 2019), South Korea (Kang & Lee, 2019) and Japan (Tanaka & Okada, 2019). ...
... The topics addressed are: (1) transport policies aimed at limiting private cars' use and promoting sustainable modes of transport (Souche-Le Corvec et al., 2019); (2) methods and models to quantify the impact of transport on the environment (Percoco, 2019;Tanaka & Okada, 2019;Wiercx et al., 2019); (3) new technologies to limit the impact of transport on the environment, in particular electric mobility (Langbroek et al., 2019;Kang & Lee, 2019;Rahmani & Loureiro, 2019) and ICT-enabled new shared mobility services (Inturri et al., 2019); (4) market-based measures to modify the present trends and pro-actively respond to sustainability challenges (Tanaka & Okada, 2019); (5) policy-making processes based on stakeholder involvement methodologies and participatory decision-support methods and models (Gatta et al., 2019a). ...
... The Authors conclude from their analysis that policy packages based on urban road toll and electric vehicles could become the "winning ticket" for Lyon in the future. Inturri et al. (2019) explore the potential of new mobility services able to induce a modal shift from individual to shared transport. The Authors focus on ICT-enabled Demand Responsive Shared Transport (DRST) services, which are particularly suitable to bridge the gap between shared low-quality public transport and unsustainable individual private transport. ...
... The trip rate TR ij generated from an origin i to a destination j is proportional to density population with a gravitationally distributed probability that depends on the number of employees and distance between any pairs of zones. More details on the formulation can be found in Inturri et al. (2019). ...
... If there are waiting passengers or on-board passengers' destinations along the flexible route, a vehicle can shift to it at a diversion node. More details on the dynamics can be found in Inturri et al. (2019) and Giuffrida et al. (2020b). Taxis are randomly generated and travel along the entire road network always using the shortest path, but only if there is a request; otherwise, they stand still, waiting for the next request. ...
... The set of performance indicators reported in Inturri et al. (2019) is monitored during the simulations, both to test the impact of different vehicle RCS on the service efficiency and effectiveness, and to compare the two transport services; indicators allow to evaluate the quality of service both from supply and demand side, and of the overall system as well. ...
Article
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 public individual transport (e.g. taxis), often find themselves in a condition of social exclusion and disadvantage. Taking advantages from new ICT tools and facilities, Demand Responsive Shared Transport (DRST) services can provide “on demand” transport services gathering ride bookings of different users and routing a fleet of vehicles to satisfy passengers’ need while minimizing the cost for the operator. In this paper, different DRST service configurations are compared to taxi services to investigate their convenience 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 offer 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 the 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.
... However, they considered neither the integration with PT nor a comparison with other forms of PT. In 2019, Inturri et al. [41] developed an ABM to compare the performance of a shared DRT with that of a taxi service [42] both for lowdemand areas and for fast-growing cities [43]. e results showed that DRT shared services are convenient under specific demand patterns for the analysed case studies. ...
... If no feasible match can be found, the user assumes the status "rejected" and walks directly to the destination. In this way, the penalty due to the rejection is not an arbitrary fixed value, as done, for example, in [41], but is directly related to the walking time from the origin to the destination, under the simplification that the rejected user does not have any other modal choices. ...
... e model results can be assessed through different output indicators [41] to compare the two feeder services: FRF and DRF as shown in Tables 1 and 2. ...
Article
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Feeder transport services are fundamental as first and last-mile connectors of mass rapid transit (MRT). They are especially beneficial in low-demand areas where private transport is usually the main transport mode. Besides, the rapid spread of new technologies such as vehicle automation and the shared mobility paradigm gave rise to new mobility-on-demand modes that can dynamically match demand with service supply. In this context, the new generation of real-time demand-responsive transport services can act as on-demand feeders of MRT, but their performance needs to be compared with conventional fixed-route fixed-schedule feeders. This article aims at presenting an agent-based model able to simulate different feeder services and explore the conditions that make a demand-responsive feeder (DRF) service more or less attractive than a fixed-route fixed-schedule feeder (FRF). The parametric simulation environment creates realistic constraints and parameters that are usually not included in analytical models because of high computational complexity. First, we identified the critical demand density representing a switching point between the two services. Once the demand density is fixed, exploratory scenarios are tested by changing the demand spatial distribution and patterns, service area, and service configurations. Main results suggest that the DRF is to be preferred when the demand is spatially concentrated close to the MRT station (e.g., in a TOD-like land-use area) or when station spacing is quite high (e.g., a regional railway service), whereas the FRF performs better when the demand is mainly originated at the MRT station to any other destinations in the service area (e.g., during peak hours). Besides, automated vehicles could play a role in reducing the operator cost if the service is performed with many small vehicles rather than higher-capacity vehicles, even if this would not imply a major benefit gain for the users.
... Flexible transport systems are useful to cover a performance gap between individual transport (private car or taxi) and conventional line transport (buses), especially in lowdensity urban areas, characterized by irregular demand, and in small urban centres. Following the shared mobility approach, rides (and costs) can be shared by users, thus enhancing the service efficiency and equity by providing a more extended and frequent public transport, flexible mobility schemes and feeder services (Inturri et al., 2019a) (see Fig. 1). Fig. 1 The flexibility-sustainability-shareability-cost graph of motorized transport services (Inturri et al., 2019a) DRST services can perform different functions, i.e.: (i) service with origin/destination (OD) dispersed in an extended area (e.g. ...
... Following the shared mobility approach, rides (and costs) can be shared by users, thus enhancing the service efficiency and equity by providing a more extended and frequent public transport, flexible mobility schemes and feeder services (Inturri et al., 2019a) (see Fig. 1). Fig. 1 The flexibility-sustainability-shareability-cost graph of motorized transport services (Inturri et al., 2019a) DRST services can perform different functions, i.e.: (i) service with origin/destination (OD) dispersed in an extended area (e.g. taxi sharing); (ii) service on a fixed route with deviations (e.g. ...
... They allow to locate users and vehicles in the network, assign the most suitable vehicle to serve one or more users with travel needs similar to those already scheduled and compatible with the vehicles' residual capacity, select the most suitable route to accomplish the requested service, and perform an electronic payment of the service. In this respect, different studies reproduced DRST services via simulation models, such as agent-based models (ABM), showing how this service can be suitable to satisfy different ranges of weak-demand, also compared to similar services (Inturri et al., 2019a;Inturri et al, 2019b) A further aspect is that web-based technologies enhance the recording and collection of large amount of data, e.g. OD data, number of users boarding/alighting at the different stops, vehicle coverage, cancellations, no-shows, punctuality, and speed. ...
Article
This paper presents a spatial approach to support the design of new on-demand flexible transport services in urban areas, characterized by inefficient public transport and modal imbalance in favour of private cars. These services, enabled by technologies and inspired by the shared mobility paradigm, can complement and improve conventional public transport and reduce car use. The methodology was applied to Acireale, a small town in Southern Italy. A redesign of the existing bus network and its integration with a flexible service was formulated. A scenario analysis was carried out by the evaluation of a simple accessibility measure; the computation of the Gini coefficient was performed to measure the social equity of different scenarios. Results show an increase in equity with a lower coverage of traditional lines and the introduction of on-demand service. This approach based on easy-to-understand indicators can help the strategic planning of such services, which have the potential to find a trade-off between ridership and coverage as both desirable and conflicting goals in public transport planning.
... Recently, Di Maria et al. [9] proposed a modular simulation framework for autonomous mobility on demand and focused on the important issue of optimization strategies using the Manhattan Grid case as a testbed. Inturri et al. [10] present a multi-agent simulation to reproduce a mixed fixed/flexible route transit service with different fleet size and vehicle capacity in the city of Ragusa (Italy), showing an optimal range of operating vehicles that minimizes a total unit cost indicator, accounting both for passenger travel time and operation cost. Giuffrida et al. [11] extend the results of the previous model, studying the effects of different vehicle assignment and route strategies and comparing its performance with a ride-sharing service provided via lowcapacity vehicles. ...
... This paper contributes to filling this gap by presenting a new ABM to simulate flexible/fixed feeder services with different vehicle fleets and demand patterns, to help solve the last-mile problem of mass rapid transit. We build on the works of Inturri et al. [10] by allowing for different levels of flexibility, Scheltes and Correia [11] for the passenger and vehicle dynamics, while allowing for ride sharing; we extended the model of Calabrò et al. [7] by reproducing the operation of a feeder service with optimally designed routes. The model also allows for a more detailed spatial representation of the demand compared to the previous ones, since requests are geocoded to the building scale. ...
... A users' group trip request is generated according to a gravitationally distributed probability from an origin (O) building to the metro station and from the metro station to a destination (D) building, following a M-to-1 demand pattern. The demand model is based on [10] and it has been improved through the introduction of an index of attractiveness of the transit mode versus the walking mode to reach the terminal station. Given a set of n buildings, the trip rate TRij (where i or j corresponds to the terminal station) is calculated with equation (1), where TRi is the generation trip rate from (and to) the building i, proportional to population density and an average trip rate per trip direction (ATR) (simulation variable), calculated with equation (2), and ijis the transit index of the attractiveness of the transit mode, which assumes values between 0 and 1, determined for each building i through the exponential function shown in equation (3). ...
... In the last two decades, DRT services have gained a broader audience with opportunities increased by information and communication technology (ICT). While initial DRT implementations lacked flexibility due to the need for advanced booking, intelligent software systems can now match supply and demand effectively, enabling travellers to request real-time rides [41][42][43]. Examples include shared taxis and 'call-a-bus' services, which provide first and last mile feeder connections to public transport interchanges or direct transport to regional service centres on low-demand routes. These services can provide mobility in accordance with passenger needs and present a feasible response to gaps in existing public transport systems [34]. ...
... Shared Mobility is a further step towards complementing existing services to enable different access needs (such as time, distance or user preference). It is part of the growing Sharing Economy, and involves the organised sharing of mobility services and vehicles [42,45]. Many shared mobility services are organised via a contract between operator and user, enabling provided vehicles (commonly e-cars, bicycles or scooters) or infrastructures, such as parking spaces, to be used independently. ...
... GrassRoutes has long been established, but like EURBAN, it is mostly used by people who depend on it. Therefore, as broadly discussed in the literature [41][42][43], the application of intelligent software systems is indispensable to increase user satisfaction and the number of riders. The better and more flexible the service, the more attractive it becomes to different user groups. ...
Article
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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.
... Hyland and Mahmassani (2020) conducted a variety of agent-based simulations to manifest the potential benefits of SAVs that provide ride-sharing and car-sharing services. Similar studies that simultaneously investigate ridesharing and car-sharing all relied on agent-based simulation methods (Alazzawi et al., 2018;Fagnant and Kockelman, 2018;Gurumurthy et al., 2019;Inturri et al., 2019;Martinez and Viegas, 2017;Vosooghi et al., 2019;Zhang et al., 2015b). The exact approaches for modeling ride-sharing and car-sharing are virtually in a blank state. ...
... In addition, existing studies were based on the vehicle travel demands extracted from personal trip survey (Martinez and Viegas, 2017), mobile phone data (Alazzawi et al., 2018), demand modeling (Vosooghi et al., 2019), and gravity model (Inturri et al., 2019). The present study leverages the road-side LPR data to reconstruct vehicle travel information, which provides a novel way to investigate the shared mobility in the era of autonomous driving. ...
Article
Shared mobility is a promising travel mode in the era of autonomous driving. Travelers may no longer own a vehicle, but use shared autonomous vehicle (SAV) services. This study investigates the effects and feasibility of SAV-based shared mobility, which includes ride-sharing and car-sharing strategies, by using a data-driven modeling approach. Ride-sharing indicates that two trips with similar origin–destination information can be combined into a new one, whereas car-sharing indicates that trips can be fulfilled by a single vehicle consecutively. On the basis of license plate recognition data of Langfang, China, this study extracts the urban-scale vehicle travel demand information. Models for ride-sharing and car-sharing are formulated to generate SAV assignment strategies for fulfilling travel demands. This study reveals the prospects and potential problems of SAV-supported shared mobility at different development stages by setting a variety of scenarios with different participation levels of ride-sharing and car-sharing. The minimum fleet size to fulfil the vehicle travel demand in the road network and the total vehicle stock in the urban area are compared under different scenarios, and the effects of shared mobility on vehicle kilometers traveled (VKT) and parking demand are evaluated. This study also reveals the impacts of SAVs in a practical scenario, which is constructed based on an online survey. Results show that ride-sharing and car-sharing with high participation will lead to considerable benefits, i.e., reductions in fleet size, vehicle stock, and parking demand. Under the shared mobility scenario with 100% ride-sharing and car-sharing participation levels, one SAV can potentially replace 3.80 private conventional vehicles in the road network. However, ride-sharing and car-sharing exhibit opposite effects on VKT. Car-sharing alone increases VKT whereas car-sharing and ride-sharing together have the potential to decrease VKT. This study provides insights for understanding the development of shared mobility and facilitating the efficient utilization of SAVs.
... The framework allows to calculate operational costs and greenhouse gas emissions for various scenarios. Inturri et al. (2019) used agent based modelling via the platform NetLogo to explore the efficiency of shared DRT schemes inspired by an Italian city's traffic system. Consistent to Scheltes and de Almeida Correia (2017), their findings suggest a trade-off between operational costs and customer satisfaction that is mainly channelled by the fleet size and vehicle capacity. ...
... Relating to similar studies, the suggested potential of DRT schemes to increase service quality is not yet analysed in the light of expected operational or environmental costs. Giuffrida et al. (2020) utilised the framework presented in Inturri et al. (2019) and reproduced in a simulation an existing fleet of shared DRT vehicles in city districts of Dubai. Their findings emphasise the sensitivity of DRT systems acceptance with regard to their service quality and reliability. ...
Article
Full-text available
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.
... Actually there are several studies that present analysis of different aspects of provision of public transport system. In general, they can be divided into two groups: works based on use of agents [1][2][3][4] and works based on system dynamics [5][6][7]. In this context the relevance of this study consists in missing exploration of the integration of simulation techniques to analyse macroscopically and microscopically the measurement of variables that indicate the quality of service provided by PPTS system, such as comfort and speed of service. ...
Chapter
Performing macro and microscopic analysis of a complex system, as in the case of measuring variables of quality of service provided by system of public passenger transport, is a problem, even more, if it is about integration of information produced in a minimum period of time that should serve as an input for realization of macroscopic analysis of this information for a longer period of time. The main goal of this paper is describe integration of two paradigms of simulation, one based on intelligent agents for microscopic analysis of the behaviour of selected system of urban public transport in one day of its activity, and another, based on system dynamics, to perform a macroscopic analysis, initially taking into account information from one day of system’s operation. Results of pilot study show that data obtained from the simulation with agents are the starting point for realization of wider analysis by allowing simulation of the system in a period of 180 days.
... However, the required service configurations of these AMOD minibus services to accommodate demand, and their performance in real networks is still unknown and warrants systematic investigation. A few studies have examined such services, albeit in a limited perspective using simplistic simulation models [23], demand models and networks, while some studies have examined their feasibility under different operating practices [30], vehicle dispatching strategies [31], and first/last-mile strategies [32] [33]. Finally, a recent review study examines various aspects related to the deployment of autonomous buses [34]. ...
Article
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Recent advancements in automated vehicle technology and the concurrent emergence of ride-hailing services have focused increasing attention on Automated Mobility-on-Demand (AMOD; a system of shared driverless taxis) as a potential solution for sustainable future urban mobility. However, the impacts of an unrestricted deployment of AMOD are as yet uncertain and likely to be contextspecific; evidence with existing on-demand services suggests that they may lead to the cannibalization of mass-transit and increased traffic congestion. In this context, automated demand-responsive transit (also termed microtransit), which provides similar on-demand services (stop-to-stop or curbside) through higher capacity vehicles, may prove to be a promising substitute and/or complement. In this study, we evaluate the performance of such an automated demand response transit system (hereafter AMOD minibus) through agent-based simulations of the Singapore network. Towards this end, we extend SimMobility (an agentand activity-based microsimulation laboratory) with the capability of modeling an AMOD minibus service including demand, supply and their interactions. On the demand side, we use an activity-based model system that draws on data from a stated-preferences survey conducted in Singapore. On the supply side, an insertion heuristic is applied to dynamically perform both the assignment of requests to vehicles and vehicle routing. Scenario simulations on the Singapore network (with an area-wide deployment of the AMOD services) indicate the potential benefits of an automated demand responsive transit service for local circulation, which can result in a reduction of Vehicle Kilometres Traveled of up to 50% (compared to the AMOD shared taxis) whilst satisfying the same demand, with a modest increase in average travel times.
... ABM as an important tool has become more and more popular for the simulation of complex transport systems (Lemoine et al., 2016;Jing et al., 2018;Baqueri et al., 2019;Korpinen et al., 2019). These models enable the simulation of detailed interactions between agents and the environment (Yang et al., 2011;Dosi et al., 2013;Lemoine et al., 2016;Inturri et al., 2019), and can shed light on the actual decision-making processes within a system (Aziz et al., 2018;Baqueri et al., 2019;Bucovetchi et al., 2019). ABMs have been used in many transportation science problems, such as: commodity transport (Liedtke, 2009;Alho et al., 2017;Giulioni, 2019), parking studies (Khaliq et al., 2018;, destination choice (Horni et al., 2011;Vitins et al., 2016;Fournier and Christofa, 2017;Alvarez and Brida, 2019), integrated traffic simulation and air pollution estimation (Hülsmann et al., 2014;Forehead and Huynh, Nomenclature E Environmental economic benefits of unit pollutant (here referred to as CO 2 ) (10 4 CNY) EF the CO 2 emission factor for the travel mode (kg/ (people$ km)) K equivalent value of pollutants, the equivalent value of CO 2 is 20 L trip distance for each mode (10,000 people$km) P unit price levied on emission equivalent (CNY/t) Q the total of the CO 2 emission (10 4 t/y) QR the amount of transport CO 2 emission reduction under various control measures (10 4 t/a) Gurram et al., 2019), and policy implementation and optimization (Ma et al., 2016;Xiong et al., 2018;Akhter et al., 2019;Simoni et al., 2019). ...
Article
Transportation is a major source of greenhouse gas (GHG) emissions in cities. Multiple strategies including transport management, urban planning and behavioral changes are required to reduce GHG emissions. Considering the urgent need to improve to urban jobs-housing relationship and reduce transport carbon dioxide (CO2) emissions, we propose a complex system model that couples multi-agent based models (ABM) and system dynamics (SD) models to simulate the impact of jobs-housing relationship adjustment policies on CO2 emissions from urban transport. Through simulation of the jobs-housing relationship and comprehensive intelligent simulation of multi-scenario policy schemes, the best optimal combination of schemes is investigated. Results show that the implementation of a single policy and measure can reduce some transport CO2 emissions, but they still rise, and do not reach a peak. To address possible future development of Beijing, three scenarios for transport CO2 emissions reduction were designed, which include Business as usual scenario (BAU), Plan scenario (PS) and Integrated scenario (IS), respectively. Under the IS, carbon intensity could be reduced by 25%-55% compared with 2005, and the environmental economic benefits of each combination scheme were higher than the single measure. Further, we investigated the effects of a reduction in carbon intensity of 65% in 2050 compared to 2005, by simulating 3 different integrated schemes (Combination Scheme Six (CSSI), Combination Scheme Seven (CSSE) and Combination Scheme Eight (CSEI)). This approach showed that CO2 emissions reduction and environmental economic benefits of the CSEI scheme were greater than either of the other two schemes. Therefore, the CSEI scheme is the best optimal development path in an integrated scenario from the long-term goal, and the research results provide decision-making reference and research support for Beijing to achieve low-carbon transportation.
... Generally, optimization models are formulated in relation to specific objectives, but they lack in evidencing interactions among system components [56]. To address this issue, several studies acknowledge agent-based models (ABM) as powerful tools, especially for their capacity to deal with large datasets [56][57][58]. Moreover, ABMs have the substantial advantage of being able to highlight interactions among a significant number of agents and between each agent and the environment, thus orientating any decision-making process at the urban scale [59,60]. ...
Article
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Complexity is a widely acknowledged feature of urban areas. Among the different levels to which this definition applies, the energy sector is one of the most representative of this way of conceiving cities. An evidence of this complexity can be detected in the growing impact of prosumers. Prosumers produce energy to meet their own demands, distribute it directly to neighbors and, eventually, store the energy neither consumed nor distributed. The modelling of distribution networks is a challenging task that requires ad hoc models to simulate the mutual energy exchanges occurring among prosumers. To serve at this scope, this paper proposes an agent-based model aiming at determining which operating conditions enhance the energy distribution among prosumers and diminish the supply from traditional power plants. An application of the model within a residential territory is then presented and simulations are conducted under two scenarios: the first investigating the distribution among prosumers equipped with photovoltaics (PV) systems, the second integrating energy storage systems to PV panels. Both scenarios are studied at varying the installed PV capacity within the territory, the allowed distance of connection among prosumers, as well as the rate of utilization of the links of the network. Results from the simulated case study reveal that the energy distribution among prosumers can be enhanced by providing short-range links for the electricity exchange. Similar advantages can be achieved by integrating storage systems to PV, along with a significant reduction in the electricity requested to the centralized grid.
... In [22], a toll-based policy for air pollution reduction is evaluated, and the long-term user reactions are discussed. The work described in [23] proposes an agent-based model that considers individual characteristics and collective group behaviours in the evaluation of demand responsive shared transport services from the perspective of passengers. In [24], authors describe an articial urban transit system as an instance of artificial transportation systems (ATS) for public transport. ...
Conference Paper
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Traffic congestion is an issue regarding the vitality of cities and the welfare of citizens. Transportation systems are using various technologies to allow users to adapt and make different decisions towards transportation modes. Modification and improvement of these systems affect the commuters' perspective and social welfare. In this study, the effect of road flow equilibrium on commuters' utilities with different types of transportation modes will be discussed. A simple network with two modes of transportation will be illustrated and three different cost policies were considered to test the efficiency of reinforcement learning in commuters' daily trip decision-making regarding time and mode. The artificial society of agents is simulated to analyse the results.
... A more general view can be found in the work proposed in [9], where an agentbased model simulates flexible demand responsive shared transport services. The goal is to obtain a platform to simulate strategic planning in a real context. ...
Chapter
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With the number of people that live in cities increasing every year, the complexity of urban traffic increased as well, making it more necessary than ever to find solutions that are good for the citizens, energy-efficient, and environmentally friendly. One of the systems that are becoming more popular is carsharing, specifically free-floating carsharing: fleets of cars that are parked around a city that can be temporarily booked for private use within the borders of the city by the system users. In this work, we implement one of these systems over SimFleet, an agent-based fleet simulator. We present how the original SimFleet agents are adapted to our system and how they interact with each other, as well as the strategies they follow to address the urban traffic problem efficiently. Our implementation for the simulation of free-floating carsharing scenarios is crucial for companies or municipalities to make the necessary tests before deploying the systems in real life.
... Planning in cities is becoming more and more challenging due to the changes induced by new information and communication technologies (ICT), following the concept of smart and sustainable cities (Bibri, 2019). This is even truer for some sectors like transport, where demand is continuously evolving, habits are changing, and supply is adapting via innovative services able to respond to demand in real time (Inturri et al., 2019). In particular, urban freight transport (UFT) represents an interesting and fertile ground for innovations, as testified by several initiatives and researches (e.g. ...
Article
E-grocery is the fastest growing e-commerce segment, while still a niche market. Notwithstanding the channel choice when buying groceries might have relevant transport and environmental implications, little attention is paid to demand analysis. The paper fills this research gap, by using stated preferences to estimate market shares for e-grocery, distinguishing between home deliveries and click&pick, using the in-store option as a reference, and by considering a case study in Norway. It investigates the role of various purchase characteristics (i.e. product price, service cost, lead-time, time window, travel time and product range) when choosing which purchase channel to use. Results suggest that the most important characteristics for consumers are related to price, in particular product price, but there is also significant heterogeneity in preferences within the sample. Scenario simulations allow estimating transport and environmental impacts deriving from channel market share changes. This information can be useful for developing both managerial strategies to increase e-grocery market share and public policy interventions to minimize negative externalities.
... Cities are facing important changes related to their transport systems (Kane and Whitehead, 2017). This can be ascribed to different factors, like the growing city population, the pervasive diffusion and use of new technologies enabling new shared mobility services (Inturri et al., 2019;Giuffrida et al., 2020) and concepts like "Mobility as a Service" (MaaS) (Jittapirom et al., 2017) that are progressively changing the way mobility is conceived. ...
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Crowdshipping, i.e. delivering goods via the crowd, aims at combining passenger with freight trips. This concept is particularly useful, especially in urban contexts, since it allows using the spare capacity of vehicles and reducing the negative impacts of urban freight transport. While attractive in principle, a crowdshipping service needs to be appropriately conceived to be effective. In this respect, matching passenger with freight transport demand is one of the main issues to consider. Besides, it is important to promote a sustainable crowdshipping, i.e. perfomed via sustainable transport modes. This paper presents a GIS-based approach to evaluate the spatial feasibility of crowdshipping services using public transport or active modes in the context of a University community. The case study analyzed focuses on e-commerce deliveries and takes into account a campus with venues located in different zones in the city of Catania (Italy). The methodology is designed according to spatial considerations related to the proximity of delivery points and home addresses, students’ flows between origins and destinations and main mode of transport used. Results are useful to design the service in a well-established community, which could be considered more inclined to be involved.
... One of the possibilities are pooled on-demand trips-as opposed to private trips-where passengers with a similar trajectory and departure time are combined and travel with the same vehicle, increasing vehicle occupancy and reducing VMT (Henao and Marshall 2018). Developing the necessary sharing algorithms and showcasing the benefits is a central topic of many papers in the field (Alonso-Mora et al. 2017;Bischoff et al. 2018;Inturri et al. 2019;Kucharski and Cats 2020;Lokhandwala and Cai 2018;OECD 2015;Ota et al. 2015;Sayarshad and Oliver Gao 2018). ...
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On-demand mobility services are promising to revolutionise urban travel, but preliminary studies are showing they may actually increase total vehicle miles travelled, worsening road congestion in cities. In this study, we assess the demand for on-demand mobility services in urban areas, using a stated preference survey, to understand the potential impact of introducing on-demand services on the current modal split. The survey was carried out in the Netherlands and offered respondents a choice between bike, car, public transport and on-demand services. 1,063 valid responses are analysed with a multinomial logit and a latent class choice model. By means of the latter, we uncover four distinctive groups of travellers based on the observed choice behaviour. The majority of the sample, the Sharing-ready cyclists (55%), are avid cyclists and do not see on-demand mobility as an alternative for making urban trips. Two classes, Tech-ready individuals (27%) and Flex-ready individuals (9%) would potentially use on-demand services: the former is fairly time-sensitive and would thus use on-demand service if they were sufficiently fast. The latter is highly cost-sensitive, and would therefore use the service primarily if it is cheap. The fourth class, Flex-sceptic individuals (9%) shows very limited potential for using on-demand services.
... 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]. ...
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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.
... In the second case, the advantage is in the simplification of the problem and the speed of calculation, yet this allows only for a suboptimal rather than optimal solution. Among the heuristics, the agent-based approach [39] is quite interesting because it allows evaluation of the interactions among agents in order to model agent behaviour in the context of decisions, especially in the case of high-dimension problems with a large number of interactions. The specific approach used here is based on integer linear programming (ILP) because the number of variables and parameters is not so high. ...
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Abstract Nowadays, goods are relocated daily among urban fashion stores by van or truck. This relocation activity generates externalities in urban areas that cause deterioration in the quality of life of their citizens. Innovative strategies based on a sharing approach promise solutions to reduce the use of heavy, polluting vehicles and therefore the related externalities in urban areas. The authors aim to optimise the relocation activity of city fashion stores through a customer‐involved incentive mechanism. The method provides store shopping vouchers to loyal customers as a reward for package delivery from one shop to another. If no customers agree to participate in the delivery game, company relocation staff will perform the delivery service. The benefit of the proposed delivery game is twofold—it increases customer loyalty and reduces the externalities produced by heavy vehicles moving through the city. To this end, two integer linear programming problems are formalised to optimise goods relocation activity with package deliveries (1) by company staff only and (2) by loyal customers in an incentive game. A simulation case study is presented to show the application of the methodology in fashion stores.
... One of the possibilities are pooled on-demand trips -as opposed to private trips -where passengers with a similar trajectory and departure time are combined and travel with the same vehicle, increasing vehicle occupancy and reducing VMT (Henao & Marshall, 2018). Developing the necessary sharing algorithms and showcasing the benefits is a central topic of many papers in the field (Alonso-Mora, Samaranayake, Wallar, Frazzoli, & Rus, 2017;Bischoff, Kaddoura, Maciejewski, & Nagel, 2018;Inturri et al., 2019;Kucharski & Cats, 2020;Lokhandwala & Cai, 2018;OECD, 2015;Ota, Vo, Silva, & Freire, 2015;Sayarshad & Oliver Gao, 2018). ...
Preprint
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On-demand mobility services are promising to revolutionise urban travel, but preliminary studies are showing that they may actually increase the total vehicle miles travelled, thereby worsening road congestion in cities. In this study, we assess the demand for on-demand mobility services in urban areas, using a stated preference survey, to understand the potential impact of introducing on-demand services on the current modal split. The survey was carried out in the Netherlands and offered respondents a choice between bike, car, public transport and on-demand services. 1,063 valid responses are analysed with a multinomial logit and a latent class choice model. By means of the latter, we uncover four distinctive groups of travellers based on the observed choice behaviour. The majority of the sample (55%) are avid cyclists and do not see on-demand mobility as an alternative for making urban trips. Two classes (27% and 9% of the sample) would potentially use on-demand services: the former is fairly time-sensitive and would thus use on-demand service if they were sufficiently fast. The latter class however is highly cost-sensitive, and would therefore use on-demand mobility primarily if it is cheap. The fourth class (9%) shows very limited potential for using on-demand services.
... Igualmente, os editais não preveem operações de transporte responsivo em linhas específicas, 12 dificultando a flexibilização do sistema à necessidade do usuário. O conceito de transporte responsivo à demanda (demand-responsive transport -DRT) aplicado ao ônibus é uma abordagem recente e voltada ao usuário que vem sendo discutida tanto no cenário internacional (Inturri et al., 2019;Viergutz e Brinkmann, 2019) como em cidades brasileiras como Goiânia e Brasília. ...
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... Different dispatching strategies have been developed and tested for operation with and without the pooling of passengers. The dispatching strategies' efficiency has been shown to directly influence average waiting times and occupancy rates , Alonso-Mora et al. 2018, Hörl et al. 2019b, Inturri et al. 2019, Tsao et al. 2019, Wang et al. 2019. ...
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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.
... The wide spatiotemporal 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]. ...
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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.
... Agent-based modeling is a powerful technique that has seen a number of applications in the literature for simulating transportation systems. Authors in paper (Inturri et al. 2019) have been presented an ad-hoc agent-based model using geographic data to explore different system configurations of demand-responsive shared transport service. The simulation results have analyzed, then, the impact of fleet composition and route selection strategy on system performance. ...
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Simulation and computer modeling have a key role in understanding transportation systems. Focusing on the main system, real-time retrieval of outputs based on mutual interactions of the whole autonomous entities makes the agent-based simulation very promising. This paper deals with an agent-based simulation to investigate and evaluate the potential impacts of implementing Shared Public Transports (SPT) in urban areas. Such a system is intended to integrate the two flows of passengers and containerized freights in Public Transportation (PT) patterns towards more sustainable, efficient, and socially suitable mobility. The proposed model is coupled with a stochastic process in order to provide a range of real-world data of Casablanca city (Morocco) based on institutional surveys. In this respect, two urban transportation systems of freight are tested: (1) the conventional transportation system, (2) the SPT system with heterogeneous fleets. In an effort to sustain efficient and safe movements, this paper examines SPT performances according to a set of key evaluation metrics. Results show that PT stopping remains the most relevant factor when evaluating metrics of the number of waiting containers and waiting time of demand by rates of 82.440% and 62.580%, respectively. Such a waiting containers metric is significantly affected by the volume of demand to transport per time slot by a rate of 78.140%. Under SPT, traffic congestion is the main factor to consider in managing PT with a rate of 65.690% in order to reduce potential accidents. However, demand volume could increase the on-street illegal parking metric by 90.070%. More details are provided below.
... The simulation of shared autonomous vehicles has been already performed in MATSim Bösch, 2018), SimMobility (Meng et al., 2020), POLARIS (Gurumurthy et al., 2020), while in JANUS, car-pooling operations have been modelled by Galland et al. (2014). Inturri et al. (2019) followed an alternative approach to plan and design Demand Responsive Shared Transport services in Ragusa Italy, as it utilized a NetLogo GIS Extension. According to Li et al. (2021), MATSim simulation platform has been selected in the 46% of the research studies, which dealt with shared autonomous vehicles and urban logistics. ...
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E-scooter sharing services have grown exponentially in many cities of the world within the last 10 years, mainly with the goal to serve first/last mile trips. Compared to other shared mobility modes (e.g., autonomous buses and electric taxis), for which Agent-based Models (ABMs) have been applied in many cases, just a few studies attempted to simulate e-scooter trips. This study aims to bridge the gap between ABMs and e-scooter sharing services by reviewing the existing ABMs and conducting a qualitative assessment. Initially, existing ABMs are described based on ten descriptors. To test suitability of each model for simulating e-scooter sharing services, we developed an evaluation checklist based on empirical findings. The ten criteria refer to the capabilities of each model to (a) adjust in new challenges via an open-source code, (b) model shared mobility modes, (c) perform large scale simulation, (d) describe spatiotemporal variation of demand, (e) simulate bicycle, (f) pedestrian, and (g) mixed traffic (h) consider socio-demographic characteristics, (i) integrate new choice models, and (j) model multimodal trips. Our results reveal the advantages and disadvantages of each model in simulating flexible transport modes and services. We end up with a dilemma or a scalability problem: to model e-scooter riding behavior in link level or e-scooter services in network level. It is concluded that the dual behavior of e-scooter users (pedestrian or vehicle) poses new challenges that can be met through the development of new extensions or hybrid simulation models.
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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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Demand responsive transit (DRT) can provide an alternative to private cars and complement existing public transport services. However, the successful implementation of DRT services remains a challenge as both researchers and policy makers can struggle to determine what sorts of places or cities are suitable for it. Research into car-dependent cities with poor transit accessibility is sparse. This study addresses this problem, investigating the potential of DRT service in Wayne County, U.S.A., whose dominant travel mode is private car. Using an agent-based approach, DRT is simulated as a new mobility option for this region, thereby providing insights into its impact on operational, user, and system-level performance indicators. DRT scenarios are tested for different fleet sizes, vehicle occupancy, and cost policies. The results show that a DRT service in Wayne County has a certain potential, especially to increase the mobility of lower-income individuals. However, introducing the service may slightly increase the overall vehicle kilometers traveled. Specific changes in service characteristics, like service area, pricing structure, or preemptive relocation of vehicles, might be needed to fully realize the potential of pooling riders in the proposed DRT service. The authors hope that this study serves as a starting point for understanding the impacts and potential benefits of DRT in Wayne County and similar low-density and car-dependent urban areas, as well as the service parameters needed for its successful implementation.
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Increasing interest and investment in connected, automated, and electric vehicles as well as mobility-as-a-service (MaaS) concepts are paving the way for the next major transformation in transportation through automated and shared mobility. The initial excitement toward rapid deployment and adoption of automated vehicles (AVs) has subsided, and low-speed automated shuttles are emerging as a more pragmatic pathway for introducing automated mobility in geofenced districts. Such shuttles hold the promise to provide a viable alternative for serving short trips in urban districts with high travel densities. As interest in low-speed automated shuttle systems (to improve urban mobility) increases, the need for tools that can inform communities in relation to benefits or disadvantages of automated shuttle deployments is imminent. However, most of the existing transportation planning and simulation tools are not capable of handling emerging shared automated mobility options. This paper presents a microscopic simulation toolkit that can be used by cities and communities to plan for the deployment of low-speed automated shuttles systems, as well as other shared mobility options. Labeled as the Automated Mobility District modeling and simulation toolkit, the proposed decision support tool intends to help cities evaluate the mobility and sustainability impacts of deploying shared automated vehicles (SAVs) in geofenced regions. This paper describes the toolkit, as well as a sample scenario analysis for the deployment of low-speed automated shuttles in Greenville, South Carolina, U.S. Results from the scenario study demonstrate the effectiveness of the proposed simulation toolkit in planning for advanced mobility systems.
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Increase in city population and size leads to growing transport demand and heterogeneous mobility habits. In turn, this may result in economic and social inequalities within the context of rapid economic growth. Provision of flexible transit in fast-growing cities is a promising strategy to overcome the limits of conventional public transport and avoid the use of private cars, towards better accessibility and social inclusion. This paper presents the case of Dubai (UAE), where a demand responsive transit service called MVMANT (a company based in Italy) has been tested in some low demand districts. The contribution of this work relies on the use of an agent-based model calibrated with Geographic Information System (GIS) real data to reproduce the service and find optimal configurations from both the perspective of the transport operator and the community. Different scenarios were simulated, by changing the vehicle assignment strategy and capacity, and comparing MVMANT with a ride-sharing service with smaller vehicles. Results suggest that route choice strategy is important to find a balance between operator and user costs, and that these types of flexible transit can satisfy transport demand with limited total costs compared to other shared mobility services. They can also be effective in satisfying fluctuating demand by adopting heterogeneous fleets of vehicles. Finally, appropriate planning and evaluation of these services are needed to fully explore their potential in covering the gap between low-quality fixed public transport and unsustainable private transport.
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Thesis
The mobility system is one of the urban systems that support urban livability. New demands are emerging emphasizing the importance of the integrity of natural, economic, and social systems, requiring adequate and integrated governance. Considering this panorama, we propose discussions based on the concepts of the quintuple helix (5H) and responsible innovation (RI). This thesis aims to identify and discuss the critical factors to support the development of a responsible urban mobility system as a component of smart and sustainable cities.By addressing a community context, we propose an application in university campuses (Brazil and France). However, the discussions developed can support projects in other contexts, such as cities.The critical success factors identified are proposed to support the development of a governance that is integrative (stakeholders), prospective, responsive, aware of the impacts for future generations, and able to create, capture and assimilate values from the dynamic scenario of innovations.
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This paper examines the changes that might result from the large-scale uptake of a shared and self-driving fleet of vehicles in a mid-sized European city. The work explores two different self-driving vehicle concepts – a ridesharing system (Shared Taxi), which emulates a taxi-like system where customers accept small detours from their original direct path and share part of their ride with others and a dynamic bus-like service with minibuses (Taxi-Bus), where customers pre-book their service at least 30 minutes in advance (permanent bookings for regular trips should represent most requests) and walk short distances to a designated stop. Under the premise that the “upgraded” system should as much as possible deliver the same trips as today in terms of origin, destination and timing, and that it should also replace all car and bus trips, it looks at impacts on car fleet size, volume of travel and parking requirements. Mobility output and CO2 emissions are also detailed in two different time scales (24 hr. average and peak-hour only). The obtained results suggest that a full implementation scenario where the existing metro service is kept and private car, bus and taxi mobility would be replaced by shared modes would significantly reduce travelled vehicle.kilometres and CO2 emissions.
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Ecological Modelling j o u r n a l h o m e p a g e : w w w . e l s e v i e r . c o m / l o c a t e / e c o l m o d e l a b s t r a c t The 'ODD' (Overview, Design concepts, and Details) protocol was published in 2006 to standardize the published descriptions of individual-based and agent-based models (ABMs). The primary objectives of ODD are to make model descriptions more understandable and complete, thereby making ABMs less subject to criticism for being irreproducible. We have systematically evaluated existing uses of the ODD protocol and identified, as expected, parts of ODD needing improvement and clarification. Accordingly, we revise the definition of ODD to clarify aspects of the original version and thereby facilitate future standardization of ABM descriptions. We discuss frequently raised critiques in ODD but also two emerg-ing, and unanticipated, benefits: ODD improves the rigorous formulation of models and helps make the theoretical foundations of large models more visible. Although the protocol was designed for ABMs, it can help with documenting any large, complex model, alleviating some general objections against such models.
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The operation of a demand responsive transport service usually involves the management of dynamic requests. The underlying algorithms are mainly adaptations of procedures carefully designed to solve static versions of the problem, in which all the requests are known in advance. However there is no guarantee that the effectiveness of an algorithm stays unchanged when it is manipulated to work in a dynamic environment. On the other hand, the way the input is revealed to the algorithm has a decisive role on the schedule quality. We analyze three characteristics of the information flow (percentage of real-time requests, interval between call-in and requested pickup time and length of the computational cycle time), assessing their influence on the effectiveness of the scheduling process.
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Taxi service is an important mode of public transportation in most metropolitan areas since it provides door-to-door convenience in the public domain. Unfortunately, despite all the convenience taxis bring, taxi fleets are also extremely inefficient to the point that over 50% of its operation time could be spent in idling state. Improving taxi fleet operation is an extremely challenging problem, not just because of its scale, but also due to fact that taxi drivers are self-interested agents that cannot be controlled centrally. To facilitate the study of such complex and decentralized system, we propose to construct a multiagent simulation platform that would allow researchers to investigate interactions among taxis and to evaluate the impact of implementing certain management policies. The major contribution of our work is the incorporation of our analysis on the real-world driver's behaviors. Despite the fact that taxi drivers are selfish and unpredictable, by analyzing a huge GPS dataset collected from a major taxi fleet operator, we are able to clearly demonstrate that driver's movements are closely related to the relative attractiveness of neighboring regions. By applying this insight, we are able to design a background agent movement strategy that generates aggregate performance patterns that are very similar to the real-world ones. Finally, we demonstrate the value of such system with a real-world case study.
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In this paper we study the impact on productivity of specific operating practices currently used by demand responsive transit (DRT) providers. We investigate the effect of using a zoning vs. a no-zoning strategy and time-window settings on performance measures such as total trip miles, deadhead miles and fleet size. It is difficult to establish closed-form expressions to assess the impact on the performance measures of a specific zoning practice or time-window setting for a real transportation network. Thus, we conduct this study through a simulation model of the operations of DRT providers on a network based on data for DRT service in Los Angeles County. However, the methodology is quite general and applicable to any other service area. Our results suggest the existence of linear relationships between operating practices and performance measures. In particular we observe that for each minute increase in time-window size the service saves approximately 2 vehicles and 260 miles driven and that a no-zoning strategy is able to satisfy the same demand by employing 60 less vehicles and driving 10,000 less total miles with respect to the current zoning strategy.
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In the late sixties the Canadian psychologist Laurence J. Peter advanced an apparently paradoxical principle, named since then after him, which can be summarized as follows: {\it 'Every new member in a hierarchical organization climbs the hierarchy until he/she reaches his/her level of maximum incompetence'}. Despite its apparent unreasonableness, such a principle would realistically act in any organization where the mechanism of promotion rewards the best members and where the mechanism at their new level in the hierarchical structure does not depend on the competence they had at the previous level, usually because the tasks of the levels are very different to each other. Here we show, by means of agent based simulations, that if the latter two features actually hold in a given model of an organization with a hierarchical structure, then not only is the Peter principle unavoidable, but also it yields in turn a significant reduction of the global efficiency of the organization. Within a game theory-like approach, we explore different promotion strategies and we find, counterintuitively, that in order to avoid such an effect the best ways for improving the efficiency of a given organization are either to promote each time an agent at random or to promote randomly the best and the worst members in terms of competence. Comment: final version published on Physica A, 10 pages, 4 figures, 1 table (for on-line supplementary material see the link: http://www.ct.infn.it/cactus/peter-links.html)
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The LITRES-2 modelling system provides a framework for investigating the performance of urban passenger transport systems, with particular attention to demand-responsive transport modes and traveller information technologies. The modes covered include conventional timetabled services (buses, trains etc.), taxis (both single- and multiple-hire), and other demand-responsive services. Tables of estimated aggregate demand are disaggregated so as to produce a stream of fully-articulated travel-requests. Individual requests are resolved as single- or multiple-leg journeys, through the use of request-broking and journey-planning modules that seek to minimise travellers' generalised costs. Journey-legs allocated to demand-responsive modes are handled by a fleet-scheduling module which includes provision for “instantaneous” as well as advance-notice bookings, and for contingent situations such as breakdowns and passenger no-shows. The fleet-scheduling and journey-planning modules are designed as embedded control systems and are intended for use in real-time as well as modelling applications. The paper describes the main analytical and procedural components of LITRES-2, and assesses some methodological issues arising from experience in recent planning studies. The system appears to be well suited for use in modelling situations where the critical issues are concerned with the supply rather than demand side of transportation activity.
Demand responsive transport services: Towards the flexible mobility agency. ENEA. Italian National Agency for New Technologies
  • G Ambrosino
  • J D Nelson
  • M Romanazzo
Ambrosino, G., Nelson, J. D., & Romanazzo, M. (2003). Demand responsive transport services: Towards the flexible mobility agency. ENEA. Italian National Agency for New Technologies, Energy and the Environment88-8286-043-4.
Fully agent-based simulation model of multimodal mobility in european cities. Models and Technologies for intelligent transportation systems
  • M Čertický
  • M Jakob
  • R Píbil
Čertický, M., Jakob, M., & Píbil, R. (2015). Fully agent-based simulation model of multimodal mobility in european cities. Models and Technologies for intelligent transportation systems (MT-ITS).
Simulation testbed for autonomic demandresponsive mobility systems
  • M Čertický
  • M Jakob
  • R Píbil
Čertický, M., Jakob, M., & Píbil, R. (2016). Simulation testbed for autonomic demandresponsive mobility systems. Autonomic Road Transport Support Systems, 147-164.
Department of economic and social affairs, population division. The world's cities in 2016 -data booklet
United Nations (2016). Department of economic and social affairs, population division. The world's cities in 2016 -data booklet. ST/ESA/SER.A/392.