Article

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

Authors:
To read the full-text of this research, you can request a copy directly from the authors.

## 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.

## No full-text available

... 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
Full-text available
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
Full-text available
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
Full-text available
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
Full-text available
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
Full-text available
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
Full-text available
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. ...
Article
Full-text available
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). ...
Article
Full-text available
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]. ...
Article
Full-text available
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. ...
Article
Full-text available
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
Full-text available
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. ...
Article
A segurança energética tem sido um tópico pouco abordado no país, mas representa uma grave vulnerabilidade. A variação dos preços internacionais de combustíveis importados dificulta o planejamento energético nacional e onera as empresas e os usuários dependentes de tecnologias convencionais. Um dos efeitos dessa dependência é a instabilidade social e econômica, evidenciada, por exemplo, na greve dos caminhoneiros em 2018, na qual cerca de 2 milhões de caminhoneiros protestaram contra o aumento do preço do diesel. Tal evento interrompeu o abastecimento de combustíveis, medicamentos, transporte público etc., impactando o desenvolvimento econômico do país (BCB, 2018). O diesel mineral corresponde a 42% da energia consumida pelo setor de transportes brasileiro (gráfico 1). Considerando apenas o transporte de passageiros por ônibus, a participação do diesel mineral em mistura com biodiesel atinge quase 100% do uso de energia, com poucos experimentos locais que demandam outras fontes como eletricidade, gás natural veicular (GNV), biodiesel (B100) e etanol hidratado.
... 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. ...
Article
Full-text available
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]. ...
Article
Full-text available
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. ...
Article
Full-text available
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. ...
Article
Full-text available
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.
Article
Full-text available
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.
Article
Full-text available
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.
Article
Full-text available
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.
Article
With the world population highly increasing, efficient methods of transportation are more necessary than ever. On the other hand, the sharing economy must be explored and applied where possible, aiming to palliate the effects of human development on the environment. In this paper we explore demand-responsive shared transportation as a system with the potential to serve its users’ displacement needs while being less polluting. In contrast with previous works, we focus on a distributed proposal that allows each vehicle to retain its private information. Our work describes a partially dynamic system in which the vehicles are self-interested: they decide which users to serve according to the benefit it reports them. With our modelling, the system can be adapted to mobility platforms of autonomous drivers and even simulate the competition among different companies.
Article
Full-text available
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.
Article
Full-text available
In rural areas with low demand, demand responsive transport (DRT) can provide an alternative to the regular public transport bus lines, which are expensive to operate in such conditions. With simulation, we explore the potential effects of introducing a DRT service that replaces existing bus lines in Lolland municipality in Denmark, assuming that the existing demand remains unchanged. We set up the DRT service in such a way that its service quality (in terms of waiting time and in-vehicle time) is comparable to the replaced buses. The results show that a DRT service can be more cost efficient than regular buses and can produce significantly less CO2 emissions when the demand level is low. Additionally, we analyse the demand density at which regular buses become more cost efficient and explore how the target service quality of a DRT service can affect operational characteristics. Overall, we argue that DRT could be a more sustainable mode of public transport in low demand areas.
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.
Article
Full-text available
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.
Article
Full-text available
The last mile in a public transport trip is known to bring a large disutility for passengers, because the conventional transport modes for this stage of the trip can, in many cases, be rather slow, inflexible and not being able to provide a seamless experience to passengers. Fully automated vehicles (AVs), that is, those which do not need a driver, could act as a first mile/last mile connection to mass public transport modes. In this paper, we study a system that we call Automated Last-Mile Transport (ALMT), which consists of a fleet of small, fully automated, electric vehicles to improve the last mile performance of a trip done in a train. An agent-based simulation model was proposed for the ALMT whereby a dispatching algorithm distributes travel requests amongst the available vehicles using a FIFO sequence and selects a vehicle based on a set of specified control conditions (e.g. travel time to reach a requesting passenger). The model was applied to the case-study of the connection between the train station Delft Zuid and the Technological Innovation Campus (Delft, The Netherlands) in order to test the methodology and understand the performance of the system in function of several operational parameters and demand scenarios. The most important conclusion from the baseline scenario was that the ALMT system was only able to compete with the walking mode and that additional measures were needed to increase the performance of the ALMT system in order to be competitive with cycling. Relocating empty vehicles or allowing pre-booking of vehicles led to a significant reduction in average waiting time, whilst allowing passengers to drive at a higher speed led to a large reduction in average travel time, whilst simultaneously reducing system capacity as energy use is increased.
Conference Paper
Full-text available
Including an active participation of citizens and stakeholders from the beginning of transport decision-making processes is widely recognized as a precondition to avoid the failure of projects/policies/plans as a consequence of a lack of con-sensus. Appropriate methods and tools are needed to support participation pro-cesses towards well-thought and shared solutions. In this paper quantitative methods, stakeholder interaction and simulation models are used to guide and reproduce a participatory experiment aimed at consensus building about mobili-ty management strategies. Analytic Hierarchy Process (AHP) has been used to elicit stakeholder preferences, different voting methods have been used to ag-gregate the individual preferences, group interaction has been performed via a facilitated dialogue to reach a consensus among stakeholders and an agent-based model (ABM) has been used to simulate the same consensus building process. Besides the social network of stakeholders has been analyzed to gain insights on its influence on the consensus formation. The results of this integrated procedure, applied in a pilot experiment with University students as stakeholders, provide useful suggestions on how to use different methods and guide effective and efficient participation processes aimed at consensus building.
Article
Full-text available
Sharing rides could drastically improve the efficiency of car and taxi transportation. Unleashing such potential, however, requires understanding how urban parameters affect the fraction of individual trips that can be shared, a quantity that we call shareability. Using data on millions of taxi trips in New York City, San Francisco, Singapore, and Vienna, we compute the shareability curves for each city, and find that a natural rescaling collapses them onto a single, universal curve. We explain this scaling law theoretically with a simple model that predicts the potential for ride sharing in any city, using a few basic urban quantities and no adjustable parameters. Accurate extrapolations of this type will help planners, transportation companies, and society at large to shape a sustainable path for urban growth.
Article
Full-text available
Two important claims for carsharing systems are their increased flexibility and potential contribution to reducing transport externalities such as pollution. Carsharing typically involves a fleet of vehicles in stations around a city that clients may use on an hourly-payment basis. Classical round-trip systems address a niche market of shopping and errand trips. However, a growing market is now arising providing one-way trips to clients. Great uncertainty remains on the economic viability of this type of carsharing given the complex relation between supply and demand, and how this may influence the level of service provided. Realistic modeling tools that include both supply and demand characterization and allow testing several carsharing operational parameters are scarce. In this sense, a detailed agent-based model was developed to simulate one-way carsharing systems. The simulation incorporates a stochastic demand model discretized in time and space and a detailed environment characterization with realistic travel times. The operation includes maintenance operations, relocations and reservations. The model was applied to the case-study city of Lisbon. Our results show that comparing to other modes, carsharing performs worse than private cars both in terms of time and cost. Nevertheless, it clearly outperforms taxis in terms of cost, and outperforms buses, metro and walking in terms of travel time. The competitiveness of carsharing is highly determined by trip length, becoming more competitive than other modes (travel-time wise) as trips become longer. The operational policies as car-fleet relocation and car reservation showed significant effects in enhancing profit while preserving good customers' satisfaction.
Article
Full-text available
This paper provides a critical review of research on Agent-Based Models (ABMs) focusing on urban mobility, dealing either with passengers or with freight transport. The work concentrates on urban areas where public policies aiming at improving the sustainability of city systems necessarily affect both passengers and freight dimensions. Traffic in towns is responsible for a high share of congestion and pollution and consequently, it contributes to the climate change problems. The following conclusions can be derived. ABMs present important advantages for analysing urban transport and its sustainability but more efforts are needed in order to test and improve their use. In the literature, there is still a gap in urban transport AB modelling. The number of developed models is limited and they are often applied in broader geographical areas than urban ones. Only some of the works includes the estimation of environmental impacts as a result of certain types of agents' behaviour. Despite their potential effectiveness to represent the impacts of different public policies on agent behaviour and on the environment, none of the ABMs have been implemented in the real word by the researchers and there is no evidence of application of any model by policy-makers.
Article
Full-text available
In transport planning several actors with conflicting objectives are involved in the decision-making process. Though public participation is fundamental to legitimate a transport plan, some inconsistencies may arise when individual preferences are aggregated into a collective decision. In this work, we reproduce the process of collective preference ranking among plan alternatives using agent-based simulations of the opinion dynamics on groups of stakeholders linked in typical social networks. The results show the efficacy of interaction and the relevance of the network topology to find a transitive and shared collective preference ranking.
Article
Full-text available
The increasing use of automobiles has had significant negative impacts on urban life: pollution, excessive energy use and time lost in traffic. The quick rise of auto externalities has policy makers facing the hard challenge of balancing demand for mobility on the one hand, and assuring sustainable urban life on the other. One strategy that can aid reducing these externalities is carsharing. Carsharing typically involves a fleet of vehicles in stations around a city, which clients may use on an hourly payment basis. Classical round-trip systems only address a niche market of urban trips such as shopping and errands, and few companies have risked the one-way carsharing option in the past due to vehicle stocks imbalance. Currently these systems are gaining new attention with important car builders investing in providing the one-way market in many cities in Europe and the United States. Nevertheless, there is still great uncertainty on the financial and economic viability of this type of carsharing. This results from a lack of realistic modeling tools that allow testing several operational parameters of this transportation alternative. In this paper we present a very detailed and realistic model to assess the potential of one way carsharing systems done through the use of agent based simulation. The simulation incorporates a stochastic demand model discretized in time and space and a detailed road network. It aims to assess the economic performance of the system both from the users’ perspective and the carsharing operator. The performance is a function of several planning and operational decisions which are included in the model: fleet size; station or free parking areas location decision; pricing policies. Some lower level configurations are also analyzed, such as an information system, vehicle reservation and maintenance operations scheduling. This paper focuses on the analysis of the spatial distribution and fleet size impacts on the demand for this transport option. This model was developed for the city of Lisbon, but its flexible architecture allows it to be adapted to different cities. Therefore this may become a tool that government authorities can use to rigorously estimate carsharing impacts and at the same time help private companies to manage their systems better.
Article
Full-text available
Widespread adoption of smartphones and ubiquitous internet connectivity gives rise to new markets for personalized and efficient on-demand mobility services. To rigorously analyze new control mechanisms for these services, we introduce an open-source agent-based simulation testbed that allows evaluating the performance of demand-responsive transport schemes. In particular, our testbed provides a framework to compare both centralized and decentralized, static and dynamic passenger allocation and vehicle routing mechanisms under various conditions; including varying vehicle fleets, road network topologies and passenger demands. The testbed supports all stages of the experimental process; from the implementation of control mechanisms and the definition of experiment scenarios, through to simulation execution, analysis, and interpretation of results. Ultimately, our testbed accelerates the development of control mechanisms for emerging on-demand mobility services and facilitates their comparison with well-defined benchmarks. We illustrate our approach on an example simulation study of standard taxi and taxi sharing services in the area of Sydney, Australia.
Article
Full-text available
Various studies have advocated the potential for Demand Responsive Transport (DRT) services to deliver sustainable local public transport. This paper investigates the sustainability credentials of DRT services using evidence from UK-based research. More specifically, six potential DRT market niches were identified, including those which offer potential commercial opportunities (e.g. airport surface access) and those that meet social needs (e.g. non-emergency hospital trips). Mode share of these DRT services, against car or bus travel, was simulated from mixed logit models within a panel data modelling framework estimated from survey data. The survey was conducted of over 400 respondents in urban (Rochdale, Manchester) and rural (Melton Mowbray, Leicestershire) areas.Experience shows that it is particularly difficult to make DRT services financially viable. Of the DRT services investigated, those targeting airline or train passengers offer potential. However, they are in direct competition with the car, and so their success depends on the cost and availability of parking spaces. Some of the DRT schemes explored meet social needs, such as to access shopping facilities or hospitals, but they face cost challenges. In addition, institutional barriers for new DRT schemes need to be overcome in order to develop a sustainable local public transport system.
Article
Full-text available
The realization of innovative transport services, require increasingly greater flexibility and inexpensiveness of the service. In many cases the solution is to realize a demand responsive transportation system, in which there are two main goals: minimize costs and maximize flexibility. In this work, we address a Demand Responsive Transport System capable of managing incoming transport demand using a solution based on an insertion heuristics to solve an On-Line dynamic DaRP instance. The solutions provided by the heuristics are simulated dynamically in a discrete events environment in which it is possible to reproduce the movement of the vehicles, the passengers’ arrival to the stops, the delays due to the traffic congestion and possible anomalies in the behavior of the passengers. Finally, at the end of the simulation, a set of performance indicators summarize the solution planned by the heuristics.
Article
Full-text available
Taxi services are a vital part of urban transportation, and a major contributor to traffic congestion and air pollution causing substantial adverse effects on human health. Sharing taxi trips is a possible way of reducing the negative impact of taxi services on cities, but this comes at the expense of passenger discomfort in terms of a longer travel time. Due to computational challenges, taxi sharing has traditionally been approached on small scales, such as within airport perimeters, or with dynamical ad-hoc heuristics. However, a mathematical framework for the systematic understanding of the tradeoff between collective benefits of sharing and individual passenger discomfort is lacking. Here we introduce the notion of shareability network which allows us to model the collective benefits of sharing as a function of passenger inconvenience, and to efficiently compute optimal sharing strategies on massive datasets. We apply this framework to a dataset of millions of taxi trips taken in New York City, showing that the cumulative trip length can be cut by 40%, leading to similar reductions in service cost, traffic, and emissions. This benefit comes with split fares and minimal passenger discomfort quantifiable as an additional travel time of up to five minutes, hinting towards a wide passenger acceptance of such a shared service. Simulation of a realistic online dispatch system demonstrates the feasibility of a shareable taxi service in New York City. Shareability as a function of trip density saturates fast, suggesting effectiveness of the taxi sharing system also in cities with much sparser taxi fleets. We anticipate our methodology to be a starting point to the development and assessment of other ride sharing scenarios and to a wide class of social sharing problems where spatio-temporal conditions for sharing, the incurred discomfort for individual participants, and the collective benefits of sharing, can be formally defined.
Article
Full-text available
Building on similarities between earthquakes and extreme financial events, we use a self-organized criticality-generating model to study herding and avalanches dynamics in financial markets. We consider a community of interacting investors, distributed on a small world network, who bet on the bullish (increasing) or bearish (decreasing) behavior of the market compared to the day before, following the S&P500 historical time series. Remarkably, we find that the size of herding-related avalanches in the community can be strongly reduced by the presence of a relatively small percentage of trader s, randomly distributed inside the network, who adopt a random investment strategy. These results suggest a promising strategy to limit the size of financial bubbles and crashes. We also find that the final wealth distribution of all traders corresponds to the well-known Pareto power law, while that one of random traders only is exponential. In other words, for technical traders, the risk of losses is much greater than the probability of gains compared to those of random traders.
Conference Paper
Full-text available
Modern societies rely on efficient transportation systems for sustainable mobility. In this paper, we perform a large-scale and empirical evaluation of a dynamic and distributed taxi-sharing system. The novel system takes advantage of nowadays widespread availability of communication and computation to convey a cost-efficient, door-to-door and flexible system, offering a quality of service similar to traditional taxis. The shared taxi service is assessed in a real-city scenario using a highly realistic simulation platform. Simulation results have shown the system's advantages for both passengers and taxi drivers, and that trade-offs need to be considered. Compared with the current taxi operation model, results show a increase of 48% on the average occupancy per traveled kilometer with a full deployment of the taxi-sharing system.
Conference Paper
Full-text available
When considering the need for an intelligent transportation mode based upon the fact that car travel is still the consumer's first choice, we decided to explore the idea of collective taxis. More precisely, we are seeking to provide an autonomous high quality door-to-door service, affordable by almost everyone, covering the entire urban area, simply by allocating in an optimal way more than one passenger to each vehicle and using the latest available information regarding traffic conditions, etc. Because this system is far less unconstrained than most public transportation systems, it has high potentialities in terms of performance and flexibility, but it is consequently very difficult to manage and to design optimally. Therefore, we present a discrete event simulation tool and show how it can be used to conceive, optimise and compare decision algorithms, achieve sound trade-off between conflicting performance indicators and assess the efficiency of the system in various contexts.
Article
Full-text available
Simulation models that describe autonomous individual organisms (individual based models, IBM) or agents (agent-based models, ABM) have become a widely used tool, not only in ecology, but also in many other disciplines dealing with complex systems made up of autonomous entities. However, there is no standard protocol for describing such simulation models, which can make them difficult to understand and to duplicate. This paper presents a proposed standard protocol, ODD, for describing IBMs and ABMs, developed and tested by 28 modellers who cover a wide range of fields within ecology. This protocol consists of three blocks (Overview, Design concepts, and Details), which are subdivided into seven elements: Purpose, State variables and scales, Process overview and scheduling, Design concepts, Initialization, Input, and Submodels. We explain which aspects of a model should be described in each element, and we present an example to illustrate the protocol in use. In addition, 19 examples are available in an Online Appendix. We consider ODD as a first step for establishing a more detailed common format of the description of IBMs and ABMs. Once initiated, the protocol will hopefully evolve as it becomes used by a sufficiently large proportion of modellers.
Conference Paper
Full-text available
Dial-a-ride systems are attracting attention as a new style of transportation systems for urban areas. While it has been reported that such systems improve the usability of bus systems when applied in a small town or area, it is not obvious how and under what conditions the systems are effective in comparison to traditional fixed-route bus systems. We conducted two computer simulations of dial-a-ride and fixed-route systems in order to compare the usability and profitability of both systems. Simulation results indicated that: (1) The usability of the dial-a-ride system with a fixed number of buses drops very quickly when the number of requests(demands) increases. (2) When we increase the number of buses proportionally to the number of demand, the usability of the dial-a-ride system is improved more significantly than that of the fixed-route system. (3) When frequency of demands is sufficiently, the dial-a-ride system is a reasonable solution from the both usability and profitability perspectives.
Article
Full-text available
We study a prototypical model of a Parliament with two Parties or two Political Coalitions and we show how the introduction of a variable percentage of randomly selected independent legislators can increase the global efficiency of a Legislature, in terms of both the number of laws passed and the average social welfare obtained. We also analytically find an "efficiency golden rule" which allows to fix the optimal number of legislators to be selected at random after that regular elections have established the relative proportion of the two Parties or Coalitions. These results are in line with both the ancient Greek democratic system and the recent discovery that the adoption of random strategies can improve the efficiency of hierarchical organizations.
Article
Demand Responsive Shared Transport DRST services take advantage of Information and Communication Technologies ICT, to provide on demand transport services booking in real time a ride on a shared vehicle. In this paper, an agent-based model ABM is presented to test different the feasibility of different service configurations in a real context. First results show the impact of route choice strategy on the system performance.
Article
Abstract This paper proposes a novel approach to support participatory decision-making processes in the context of urban freight transport through the integration of discrete choice modeling and agent-based modeling. The methodology is based on an innovative multilayer network and opinion dynamics models and applied to the case study of Rome’s limited traffic zone. Simulation results produce a ranking of plausible policies that maximize consensus building while minimizing utility losses due to the negotiation process. These results can be used to support real participatory decision-making processes on freight-related policies accounting both for stakeholders’ heterogeneous preferences and their interaction effects.
Article
This paper explores the potential contribution that the public transport Agency can make to the emerging Mobility as a Service (MaaS) paradigm through the integration of regular collective transport services with complementary flexible transport schemes and other forms of shared-use transport. The latest ICT developments provide new opportunities to organise and offer collective and individual mobility services. In the evolving scenario of the service sharing economy we see this with a number of new mobility schemes–e.g. vehicle sharing and dynamic ride sharing schemes like Car2Go, DriveNow, BlaBlaCar, Uber, Lyft. We define a Flexible and Shared Use Mobility (FSUM) Agency; a single co-ordination centre of different flexible services and shared mobility schemes, which requires co-ordination and co-operation among different service providers, the integration of data and platforms, technical services and systems. The fundamental enabling technologies and standards are illustrated and the supporting ICT architecture outlined. Finally, the organisational aspects related to the operation of the Agency are discussed and illustrated with reference to the EC-funded PERHT project.
Article
Article
Abstract In this paper a land use and transport model is presented to calculate an indicator of “Transport Energy Dependence” (TED) in order to support the delivery of sustainable urban and transport plans. The model is based on a mathematical description of the transport system, where transport mode choice follows ideal simple rules based on distance from origin to destination and transit network accessibility. For each transport mode unit energy consumption, capacity and load factor are considered. Flows of trips are optimally assigned between origin and destination zones in such a way that transport energy is minimised. Energy ideally required for home-to-school/university travel is assessed as these journeys contribute a significant number of daily trips within a city. In particular, the model was applied to the urban area of Catania, a medium-sized town in Italy, for different scenarios, including improvements in the transit system and in pedestrian/cycling accessibility. The methodology proved to be suitable to evaluate the potential impact of land use and transport policies in terms of transport energy dependence, separating it from behavioural considerations.
Conference Paper
Traditional transit is often unable to effectively service areas of low ridership and low population density. To alleviate this problem, a method of combining traditional transit with demand-responsive transportation is proposed. This system, known as the network-inspired transportation system (NITS), uses demand-responsive transportation to handle the first and last miles of each passenger's trip. The effectiveness of the NITS is tested in simulations run in a fictional gridded street city as well as the city of Atlanta, GA. Simulation results show that the NITS provides a higher quality of service than transit in low density urban areas where traditional transit is not effective.
Article
Carsharing programs that operate as short-term vehicle rentals (often for one-way trips before ending the rental) like Car2Go and ZipCar have quickly expanded, with the number of US users doubling every 1–2 years over the past decade. Such programs seek to shift personal transportation choices from an owned asset to a service used on demand. The advent of autonomous or fully self-driving vehicles will address many current carsharing barriers, including users’ travel to access available vehicles.This work describes the design of an agent-based model for shared autonomous vehicle (SAV) operations, the results of many case-study applications using this model, and the estimated environmental benefits of such settings, versus conventional vehicle ownership and use. The model operates by generating trips throughout a grid-based urban area, with each trip assigned an origin, destination and departure time, to mimic realistic travel profiles. A preliminary model run estimates the SAV fleet size required to reasonably service all trips, also using a variety of vehicle relocation strategies that seek to minimize future traveler wait times. Next, the model is run over one-hundred days, with driverless vehicles ferrying travelers from one destination to the next. During each 5-min interval, some unused SAVs relocate, attempting to shorten wait times for next-period travelers.Case studies vary trip generation rates, trip distribution patterns, network congestion levels, service area size, vehicle relocation strategies, and fleet size. Preliminary results indicate that each SAV can replace around eleven conventional vehicles, but adds up to 10% more travel distance than comparable non-SAV trips, resulting in overall beneficial emissions impacts, once fleet-efficiency changes and embodied versus in-use emissions are assessed.
Article
Numerous variations of the vehicle routing and scheduling problem are discussed, and a taxonomy is provided for these problems. Current solution strategies for vehicle routing are classified. A hierarchy of scheduling or problems, moving from the very simple to the extremely complex is demonstrated. Three of the many possible combined routing and scheduling problems are described.
Article
An analytic investigation into the fundamental aspects of scheduling ″Dial-a-Ride″ transportation systems is conducted. Based upon simple mathematical models that focus on the combinatorial nature of the problem, a class of algorithms is derived for which performance can be measured in a precise asymptotic probabilistic sense. It is concluded that the approach yields many qualitative insights and the resulting transportation schemes have modest computational requirements, are decentralized, and are easy to visualize and implement.
Article
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.
Article
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.
Conference Paper
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.
Article
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.
Article
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)
Article
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.