Agent-based Simulation Model for Long-term Carpooling: Effect of Activity Planning Constraints

AbstractIn order to commute by carpooling, individuals need to communicate, negotiate and coordinate, and in most cases adapt their daily schedule to enable cooperation. Through negotiation, agents (individuals) can reach complex agreements in an iterative way, which meets the criteria for the successful negotiation. The procedure of negotiation and trip execution in the long-term carpooling consists of a number of steps namely; (i) decision to carpool, (ii) exploration and communication, (iii) negotiation, (iv) coordination and schedule adaptation, (v) long term trip execution (carpooling), (vi) negotiation during carpooling and (vii) carpool termination and exploration for new carpool. This paper presents a conceptual design of an agent-based model (ABM) of a set of candidate carpoolers. A proof of concept implementation is presented. The proposed model is used for simulating the interactions between autonomous agents. The model enables communication to trigger the negotiation process; it measures the effect of pick-drop and shopping activities on the carpooling trips. Carpooling for commuting is simulated: we consider a set of two intermediate trips (home-to-work and work-to-home) for the long-term carpooling. Schedule adaptation during negotiation depends on personal preferences. Trip timing and duration are crucial factors. We carried out a validation study of our results with real data (partial) collected in Flanders, Belgium. Simulation results show the effect of constraining activities on the carpooling trips. The future research will mainly focus on enhancing the mechanisms for communication and negotiation between agents

Multi-Agent Systems

This Special Issue ""Multi-Agent Systems"" gathers original research articles reporting results on the steadily growing area of agent-oriented computing and multi-agent systems technologies. After more than 20 years of academic research on multi-agent systems (MASs), in fact, agent-oriented models and technologies have been promoted as the most suitable candidates for the design and development of distributed and intelligent applications in complex and dynamic environments. With respect to both their quality and range, the papers in this Special Issue already represent a meaningful sample of the most recent advancements in the field of agent-oriented models and technologies. In particular, the 17 contributions cover agent-based modeling and simulation, situated multi-agent systems, socio-technical multi-agent systems, and semantic technologies applied to multi-agent systems. In fact, it is surprising to witness how such a limited portion of MAS research already highlights the most relevant usage of agent-based models and technologies, as well as their most appreciated characteristics. We are thus confident that the readers of Applied Sciences will be able to appreciate the growing role that MASs will play in the design and development of the next generation of complex intelligent systems. This Special Issue has been converted into a yearly series, for which a new call for papers is already available at the Applied Sciences journal’s website: https://www.mdpi.com/journal/applsci/special_issues/Multi-Agent_Systems_2019

Special Issue ``Multi-Agent Systems'': Editorial

Multi-agent systems (MAS) allow and promote the development of distributed and intelligent applications in complex and dynamic environments. Applications of this kind have a crucial role in our everyday life, as witnessed by the broad range of domains they are deployed to---such as manufacturing, management sciences, e-commerce, biotechnology, etc. Despite heterogeneity, those domains share common requirements such as autonomy, structured interaction, mobility, and openness---which are well suited for MAS. Therein, in fact, goal-oriented processes can enter and leave the system dynamically and interact with each other according to structured protocols. This special issue gathers 17 contributions spanning from agent-based modelling and simulation to applications of MAS in situated and socio-technical systems

Diagnosing Sharing Anxiety

Numerous studies indicate that the potential of autonomous vehicles (AVs) to reduce greenhouse gas emissions, reduce traffic congestion, and increase mobility access can only be fully realized through fleets of vehicles being used for shared rides, also known as dynamic ridepooling. This has the potential for transforming the public transport industry, as well as how transportation functions in urban and rural contexts.In order for shared AVs (SAVs) to be a feasible service, users need to be willing to share a driverless space with strangers. However, most of the research in the field has focused on traffic impact studies or in technological acceptance, not social acceptance of the driverless space an AV represents. In contemporary dynamic ridepooling or on-demand transport, users are often motivated through lower fares to share their ride in a human-driven vehicle, yet pooled rides are not a given service by many companies.Understanding how potential users feel about sharing a driverless space with strangers, is critical in order to develop strategies for increasing acceptance and adoption of a new mobility behavior, especially when planning for shared autonomous transport. What are the factors that would motivate users to make this choice? If given the option of a driverless vehicle, would users of these services be motivated by the same factors? That is what Study 1 of this licentiate thesis sought to answer.Using qualitative research methods, the study comprised of four focus groups held in New South Wales, Australia, with active users of either the trialled on-demand transport service or commercial ridepooling. Through thematic analysis of the focus group conversations, confirmed factors of cost, comfort, convenience, safety, community culture, and trust in authority emerged. However, the results showed that when presented with driverless scenarios, the focus group participants’ willingness-to-share dropped significantly, due to strong concerns about the unknown behaviour of their co-passengers. This revealed ”sharing anxiety” in even extremely motivated users of dynamic ridepooling, and a potential barrier to the deployment of SAVs.Thus Study 2 turned to transportation stakeholders in New South Wales, to understand their perspectives on how to mitigate this problem. Study 2 is a policy-focused investigation with experts from the state’s transport authority, autonomous vehicle operators, public transport operators, and academics. Again, qualitative methods were used, this time one-on-one interviews. The results revealed a relative lack of awareness about the existence and impact of sharing anxiety, which in turn raises concerns about the preparedness of governments and transport operators to introduce SAV services.The combined confirmation of sharing anxiety as a complex barrier, as well as the lack of awareness from transportation stakeholders, indicates a potential challenge to the widespread adoption of SAVs and shared autonomous public transport (SAPT), one that would require building strategies for increasing willingness-to-share at the community or societal level. This licentiate begins the foundational work towards the development of a descriptive and prescriptive framework, the Societal Readiness Index for Shared Autonomy

Environmental Attitudes and Behaviors: An Examination of the Antecedents of Behavior among Air Force Members at Work

A questionnaire was randomly distributed to members of the United States Air Force at Wright Patterson AFB, OH, with 307 returned. The survey was designed to test the theory of planned behavior (TPB) model developed by Icek Ajzen, and the organizational theory of planned behavior (OTPB) model explored in this research effort. Validation and measurement of the TPB in relation to an organizational setting was accomplished, with the organizational theory of planned behavior (OTPB) developed. The behaviors and intentions individuals have towards recycling, energy conservation, and carpooling were examined, with the demographic variables of gender, age, and education also investigated. Regression analysis revealed that the TPB is supported by this research, while the OTPB is not well supported. However, the organizational commitment component of the OTPB does account for significant variance, and seems to support a portion of the OTPB. The demographic variables of gender, age, and education provide useful insight into the organization. Women show a greater tendency to carpool to work than men, and are more likely to participate in the behavior. Also, having some college education influences energy conservation behavior, energy conservation intention, and carpooling behavior at work. It was also shown that those who are older have a greater tendency to conserve energy at work, and are more likely to participate in the behavior

Publicly funded research, development and demonstration projects on electric and plug-in vehicles in Europe - update

The previous report on the publicly funded research and development and demonstration projects included ongoing and recently concluded projects with the information available in 2011-2012. The aim of the current work was to update the collection of the on-going or recently concluded research, development and demonstration projects on electric and plug-in hybrid vehicles, which received EU and national public funding with the total budget of more than 500000 Euro, in order to update the EV-Radar tool with new projects. Altogether 158 R&D and demonstration projects have been found and analysed in this report from EU member states and EFTA countries.JRC.F.6-Energy Technology Policy Outloo

SOCIAL NETWORK INFLUENCE ON RIDESHARING, DISASTER COMMUNICATIONS, AND COMMUNITY INTERACTIONS

The complex topology of real networks allows network agents to change their functional behavior. Conceptual and methodological developments in network analysis have furthered our understanding of the effects of interpersonal environment on normative social influence and social engagement. Social influence occurs when network agents change behavior being influenced by others in the social network and this takes place in a multitude of varying disciplines. The overarching goal of this thesis is to provide a holistic understanding and develop novel techniques to explore how individuals are socially influenced, both on-line and off-line, while making shared-trips, communicating risk during extreme weather, and interacting in respective communities. The notion of influence is captured by quantifying the network effects on such decision-making and characterizing how information is exchanged between network agents. The methodologies and findings presented in this thesis will benefit different stakeholders and practitioners to determine and implement targeted policies for various user groups in regular, special, and extreme events based on their social network characteristics, properties, activities, and interactions

Growing Artificial Societies to Support Demand Modelling in Mobility-as-a-Service Solutions

Tráfego intenso, congestionamentos e tempos de deslocamento mais longos são consequência doaumento da população, da continuação da posse de carro próprio e do fim do transporte público derota fixa. Embora esta situação tenha criado alguma pressão sobre as autoridades governamentaispara lidar com as questões acima mencionadas, isso também pode provar ser uma oportunidadepara numa nova abordagem ao conceito de mobilidade.Uma possível solução passaria pela Mobilidade como serviço (MaaS), um conceito relativa-mente novo no paradigma de mobilidade, que promete mudar em termos do que é mobilidade ecomo ela é entregue aos usuários finais. Fazendo uso das atuais infraestruturas físicas e meios detransporte, e combinando-as com tecnologias da informação e comunicação (TICs), o MaaS temcomo principal objetivo entregar a mobilidade aos usuários finais como um serviço que é consum-ido através de uma plataforma. Essas plataformas são baseadas em modelos de mercado, onde umregulador é responsável pelo equilíbrio entre oferta e demanda.As Sociedades Artificiais (AS) pretendem ser uma forma de simular sociedades reais, atravésde um modelo artificial de agentes proativos e dinâmicos, capazes de interagir entre eles. Essesagentes são capazes de se comunicar entre eles através de uma rede social, onde várias regras sãousadas para disciplinar e normalizar os agentes e o ambiente onde eles estão contidos.A modelação da demanda (DM) é um conceito que permite prever com precisão a demandapor algum mercado, dependendo do equilíbrio entre oferta e demanda. Além disso, tendo em contaa presença do regulador, responsável pela manutenção e implementação de políticas de regulação,o DM facilita a modelação de toda essa dinâmica.A análise dos melhores modelos de serviços, pode ser muito benéfica para o MaaS, uma vezque a modelação de metodologias novas e mais precisas poderia melhorar os processos de decisãopresentes nos vários modelos de mercado do MaaS.Este trabalho tem como objetivo desenvolver um metamodelo cognitivo de sistema multi-agente capaz de descrever a dinâmica do conceito de MaaS. O metamodelo desenvolvido deveser capaz de suportar diferentes estratégias deliberativas e de tomada de decisão em ambientes demercado de serviços abertos, com aplicações de mobilidade em Cidades Inteligentes. O objetivo édesenvolver uma plataforma de apoio à decisão para apoiar a análise e implementação de políticasde incentivo que promovam o desenvolvimento do conceito de MaaS. Esta plataforma fará uso detécnicas de modelagem e simulação de sistemas complexos recorrendo às metáforas de sociedadesartificiais e sistemas multiagentes.Huge traffic, congestion, longer commute times, are a consequence of the increase in population,continuation of universal car ownership and demise of fixed route public transport. While thissituation have been creating some pressure on the governmental authorities to tackle the afore-mentioned issues, this could also prove to be an opportunity to try a different approach regardingthe concept of mobility.One particular solution could be Mobility-as-a-Service (MaaS), a relatively new concept in amobility paradigm that promises a big shift in terms of what is mobility and how it is deliveredto the end-users. Making use the current physical infrastructures and transport means, and com-bining them with information and communications technologies (ICTs), MaaS has the main goalto delivery the mobility to the end-users as a service that is consumed through a platform. Theseplatforms are based on market models, where there a regulator that is responsible for the balancethe balance between supply and demand.Artificial Societies (AS) aims to be a way to simulate real societies, through an artificial modelof proactive and dynamic agents, able to interact between them. These agents are able to commu-nicate between them through a social network, where several rules are used to discipline and normboth agents and the environment where they are contained.Demand modelling (DM) is a concept that allows accurately to forecast the demand regardingsome market, depending of the balance between supply and demand. Moreover, taken into accountthe presence of the regulator, which is responsible for the maintenance and implementation ofpolicies, DM facilitates the modelling of all this dynamic.The analysis of the best service models, could prove greatly beneficial for MaaS, as modelingnew and more accurate methodologies could better the decision processes present in the variousmarket models of MaaS.This work aims to develop a cognitive multi-agent system meta-model able to describe thedynamic of MaaS concept. The developed meta-model should be able to support different de-liberative and decision making strategies in open service market environments, with mobility ap-plications in Smart Cities. The purpose is to develop a decision support platform to support theanalysis and implementation of incentive policies that promote the development of the concept ofMaaS. This platform will make use of techniques of modeling and simulation of complex systemsresorting to the metaphors of artificial societies and multi-agent systems