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It has been almost half a century since the first interest in autonomous robots was shown, and research is still continuing to improve their ability to make perfectly conscious decisions from a user safety point of view. These autonomous robots are now at a fairly advanced level, which means that their adoption rate in social environments is also increasing. This article reviews the current state of development of this technology and highlights the evolution of interest in it. We analyze and discuss specific areas of its use, for example, its functionality and current level of development. Finally, challenges related to the current level of research and new methods that are still being developed for the wider adoption of these autonomous robots are highlighted. [ABSTRACT FROM AUTHOR]

Social and economic change in the built environment is increasingly driven by processes of datafication. These often find expression through smart phone apps and private platforms that seek to upset the status quo by mediating consumer and producer interactions, and by monetising the data these produce. This paper uses the practice-oriented concept of 'disruptive data' to draw attention away from specific technologies and towards the broader political economic logics that underlie them. In so doing, disruption is reframed as a capitalist strategy for creating and capitalising on uncertainty. The rapid change to Dublin's taxi industry over the past decade illustrates these dynamics. By following how ride-hailing apps, most notably Hailo, were introduced into and effected the city, the importance of regulatory context but also wider flows of data and capital are stressed. Data disruptions occur not at the level of the app or platform, but at the economic relations in which they are embedded. By paying attention to the historical details of data disruption, the specificities of change processes are revealed without losing track of their broader economic function. [ABSTRACT FROM AUTHOR]

The increasing number of private vehicles has caused severe traffic congestion and air pollution. As an innovative transportation mode, mobility services such as ridesharing have been considered as an alternative. However, it has been evidenced that most private vehicle owners would not switch from driving to using ridesharing because such options only attract those who never intend to own a car. Therefore, it is more meaningful for private vehicle owners to provide ridesharing services, also known as Hitch, which can improve urban traffic efficiency on the service supply side. This study outlines an empirical study which is conducted to assess drivers as a group, to examine the factors which influence their intention of ridesharing. A sample of 597 private vehicle owners in Tianjin, China, completed a questionnaire. Structural equation modeling (SEM) is implemented to analyze the proposed model, specially explore the mediating role of trust and habit. The results indicate that habit is the most important factor, which is mainly influenced by extrinsic motivation (i.e., instrumental motive). Furthermore, habit can increase trust in ridesharing, another important factor, which is mainly affected by intrinsic motivation (i.e., affective motive and responsibility). Therefore, this shows the relationship between intrinsic motivation and extrinsic motivation. The findings in this paper have strong implications for both governments and platform developers, to promote the transition from solo driving to ridesharing to improve traffic condition and environmental pollution. • We test the factors leading private vehicle owners to share a ride, on the service supply side. • This study analyzes trust and habit as mediators bridging motivations. • Motivation theory and material possession theory (MPT) are used. [ABSTRACT FROM AUTHOR]

The state-of-the-art of mobility services among large-scale agent-based travel demand models has focused predominantly on the demand side, whereas complexities of the supply side have been given much less attention. Conventional definitions must be revisited to establish solid foundations for model implementations. First, several mobility services are characterized from abstract attributes, by all agents involved, and by operational tasks involved in service provision. Then, a high-level generic service provision process is developed to allow instantiation of various services. Extensions for conventional travel demand model systems are also developed, including: a mobility services component containing service provider agentsand their operational tasks integrated logically into service provision processes; a fleet component containing vehicle agents of each service and a driver activity model when human-driven; a MaaS component containing mobility provider agents that coordinate and integrate mobility services. Generic modeling issues are also discussed, including treatment of time, data structures, and computational efficiency. [ABSTRACT FROM AUTHOR]

Digitalisation in transport services offers many benefits for travellers. However, not everyone is willing or able to follow the new, more or less formal requirements digitalisation has brought along. Existing reviews on the intersection between Information and Communication Technologies (ICTs) and mobility cover a range of vantage points, but the perspective of how various levels of engagement with digital technologies affect access and navigation of transport services has not been addressed yet. In communication science, studying disparities in terms of ICT appropriation and their consequences is known as digital inequality research. This review paper aims at shedding light on what digital inequality in the context of transport services consists of and what its consequences are. To do so, we define and use a conceptual framework for the analysis of digital inequality in transport services. The review of the twenty-five papers, as selected in our systematic literature search, shows that there is a burgeoning interest in this topic. Vulnerability to digitalisation in transport services exists along dimensions of age, income, education, ethnicity, gender and geographical region. We find that motivations and material access get more attention than digital skills and effective usage. Nevertheless, literature acknowledges that having material access to technology does not mean that people benefit from what technology has to offer. Furthermore, the characteristics of ICTs impact one's possibilities to access digital technologies, such as how user-friendly a technology is. Data-driven and algorithm-based decision-making present a particularly pernicious form of digital exclusion from transport services. As digital technologies are progressively becoming indispensable to navigate the world of transport services, low levels of digital engagement may create a new layer of transport disadvantage, possibly on top of existing ones. Although digitalisation can be part of the solution to transport disadvantage, it can also be part of the problem. With network effects at play, what might start as a relative disadvantage may turn into an absolute disadvantage. Given the nascent state of research on digital inequality in transport services, much remains to be understood. Suggested research avenues include mechanisms of digital exclusion from transport services, the contribution of digital inequality to transport disadvantage, and importantly, solutions to mitigate its impacts. [ABSTRACT FROM AUTHOR]

This paper proposes a holistic, within-day ridehailing service provision modelling approach, focusing on large-scale services with human-driven fleets. The model is powered by a full, two-year record of ridehailing trips in Toronto. Canada. Despite the abundant data, operations and fleet-related data still lacks, and uncertainty still exists concerning actual service provision deployment. Hence, a novel approach dealing with limited data availability is developed, which extracts implicit supply levels from trip-based demand data. The model is time-step driven, agent-based, and uses list-based data structures. It focuses on three key components: matching mechanisms, time intervals, and (several features of) driver activity. After testing various component combinations, a Hungarian matching algorithm, a normal distribution of driver work hours, and 5-minute time intervals allow close replication of observed wait time distributions and unique drivers per hour. Emergent model outputs also include VKT by vehicle states (idling, en-route, in-service), vehicle shifts and trip chains. [ABSTRACT FROM AUTHOR]

This study aims to evaluate and quantify the impact of demand forecast spatial resolution on the operational performance of a shared-use automated vehicle (AV) mobility service (SAMS) fleet. To perform the evaluation, this study employs an agent-based modeling framework that includes user requests, AVs, and an SAMS fleet controller. In the simulation, an SAMS fleet controller dynamically assigns AVs to on-demand user requests and repositions empty AVs throughout the service region to serve expected future demand requests. The fleet controller uses an offline demand forecast model and an online optimization model that jointly assigns AVs to users and repositioning trips. Results indicate that despite demand forecast quality decreasing at higher spatial resolutions, the operational efficiency of the SAMS fleet increases with higher spatial resolution forecasts (i.e. smaller subareas). Results also indicate that there is a significant operational value associated with improving short-term demand forecasts at high spatial resolutions. [ABSTRACT FROM AUTHOR]

This paper presents a comprehensive literature review focused on the supply side of mobility services, providing relevant insights at the conceptual, operational, and modelling levels. Definitions are first drawn from the Mobility as a Service paradigm due to its predominance in the literature. This is followed by an assessment of the operational features of a range of mobility services, including carsharing, bikesharing, ridehailing, and demand responsive transit. To conclude the review, the state-of-the-art in modelling approaches for mobility services is reported, at different levels of complexity and integration. Three of the most important findings and arguments from this paper suggest that a high degree of generality exists for operational features of mobility services; that it is essential to make a distinction between Mobility as a Service and a mobility service in isolation; along with the argument that human agency should be carefully considered in modelling efforts, both for user agent and driver agent decision-making processes. Finally, key considerations are proposed for the future development of a conceptual framework for modelling the supply side of mobility services, which would have a generic service provider model as its core component. [ABSTRACT FROM AUTHOR]

The advent of automated vehicles could be transformative to the existing transportation system; however, the ways in which changes could happen are uncertain. This research was aimed at contributing to the literature of acceptance of self-driving vehicles and the role of ride-hailing in this decision-making process. An online survey was implemented to collect information for two distinct segments of the population: ride-hailing users and non-ride-hailing users. The data were examined through bivariate descriptive analysis and multivariate models. The results provided several insights. The overall intent to use was found to be higher among users of ride-hailing services than among non-users of such services. The results highlighted significant association of several variables with intent to use, including demographics, residential characteristics, technology and shared mobility use factors, and attitudes and perceptions. The results of this research could inform several important policy issues at the intersection of emerging technology and mobility options. [ABSTRACT FROM AUTHOR]

Parking Benefit Districts (PBDs) are a parking measure where revenues from on-street parking charges are returned to the area where they are charged, and stakeholders in the area participate in prioritizing how the revenues are to be spent. The purpose of this article is to analyse whether and how a PBD programme can be transferred to a European context, and whether it can contribute to reduced car dependency. The first part of the article provides an overview of some salient features of PBD programmes in the USA through a literature survey. This is followed by results from interviews and from a focus group with civil servants and a deputy mayor in Stockholm. The results are used to analyse the conditions for implementing a PBD programme in Stockholm, as well as for analysing how such a programme can be designed to reduce car dependency. A main conclusion is that there are no legal barriers that render a PBD programme impossible in Stockholm, even though there are some legal restrictions. We also conclude that a PBD programme might contribute to reduced car dependency in two different ways, either by increasing acceptance for parking charges or by improving the alternatives to private cars. There seem to be several aspects in a PBD programme that can contribute to increased acceptance for parking charges. However, there is no tradition of working with these principles in Sweden and the programme’s redistributional effects need to be taken into account when designing the programme. [ABSTRACT FROM AUTHOR]

This paper assesses the demand for a flexible, demand-adaptive transit service, using the Chicago region as an example. We designed and implemented a stated-preference survey in order to (1) identify potential users of flexible transit, and (2) inform the service design of the flexible transit mode. Multinomial logit, mixed-logit, and panel mixed-logit choice models were estimated using the data obtained from the survey. The survey instrument employed a d p -efficient design and the Google Maps API to capture precise origins and destinations in order to create realistic choice scenarios. The stated-preference experiments offered respondents a choice between traditional transit, car, and a hypothetical flexible transit mode. Wait time, access time, travel time, service frequency, cost, and number of transfers varied across the choice scenarios. The choice model results indicate mode-specific values of in-vehicle travel time ranging between $16.3 per hour (car) and $21.1 per hour (flexible transit). The estimated value of walking time to transit is $25.9 per hour. The estimated value of waiting time at one’s point of origin for a flexible transit vehicle is $11.3 per hour; this value is significantly lower than the disutility typically associated with waiting at a transit stop/station indicating that the ‘at-home’ pick-up option of flexible transit is a highly desirable feature. The choice model results also indicate that respondents who use active-transport modes or public transit for their current commute trip, or are bikeshare members, were significantly more likely to choose flexible and traditional transit than car commuters in the choice experiments. The implications of these and other relevant model results for the design and delivery of flexible, technology-enabled services are discussed. [ABSTRACT FROM AUTHOR]

Carsharing has become an important addition to existing mobility services over the last years. Today, several different systems are operating in many big cities. For an efficient and economic operation of any carsharing system, the identification of customer demand is essential. This demand is investigated within the presented research by analyzing booking data of a German free-floating carsharing system. The objectives of this paper are to describe carsharing usage and to identify factors that have an influence on the demand for carsharing. Therefore, the booking data are analyzed for temporal aspects, showing recurring patterns of varying lengths. The spatial distribution of bookings is investigated using a geographic information system and indicates a relationship between city structure and areas with high demand for carsharing. The temporal and spatial facets are then combined by applying a cluster analysis to identify groups of days with similar spatial booking patterns and show asymmetries in the spatiotemporal distribution of vehicle supply and demand. Influences on demand can be either short-term or long-term. The paper shows that changes in the weather conditions are a short-term influence as users of free-floating carsharing react to those. Furthermore, the application of a linear regression analysis reveals that socio-demographic data are suitable for making long-term demand predictions since booking numbers show quite a strong correlation with socio-demography, even in a simple model. [ABSTRACT FROM AUTHOR]

Mobility currently evolves far beyond owning a car or using public transit services. Passenger transport can be managed by mobility providers by combining and extending various mobility services either directly or by using available mobility service platforms. This paper evaluates the capabilities and technical features of existing mobility service platforms with a special focus on electric mobility. Based upon this evaluation, criteria are presented which future platforms should address. As part of this work, a marketplace approach is developed which addresses the identified criteria. Potential marketplace architectures are presented which are deemed to establish marketplace interconnectivity. The developed marketplace approach and the proposed architectures contribute to the vision of an interconnected service ecosystem for mobility services. [ABSTRACT FROM AUTHOR]

Sustainable mobility is a relevant challenge addressed today by policy-makers, public managers and researchers worldwide. In addition to engineering and infrastructural issues, the problem is also generating increasing interest in the service management field. This article aims to present a framework useful to support the design of more sustainable mobility systems within territorial communities. A review of extant literature, ongoing projects and research initiatives is used to derive a six-component integrative framework aimed to improve a mobility system by introducing new services, evaluating trade-offs, and assessing or promoting the use of services already in place. Two cases are presented as illustrative examples of application. The proposed framework can support further investigations aimed to define new ways to face the sustainable mobility challenge through a service innovation perspective. The framework can also support the design of interdisciplinary curricula for competence development in the mobility field. The work investigates the challenge of sustainable mobility through complementary socio-technical and service management perspectives, and provides a contribution of potential value to conceive more effective solutions to mobility management. [ABSTRACT FROM AUTHOR]

This paper examines two cases of technological innovation in individual mobility that are driven by purely entrepreneurial spirit. They entail the introduction into commerce of innovative, low-impact vehicles in the US: Sparrow, produced by Corbin Motors, and Gizmo, produced by NEVCO. Both are three-wheeled electric vehicles with seating capacity for one adult. They were first produced as experiments and then moved to a small commercial scale. Drawing on a larger set of actors could be accomplished by engaging: local governments concerned with the matters of transportation, technology, energy and spatial planning; citizen groups; universities; NGOs; and various businesses. These stakeholders should be encouraged to study the fate of Gizmo and Sparrow in the marketplace, adopt the vehicles on an experimental basis, and to include them as well as other such mobility solutions into long-term planning. Designing a programme for mapping out and interpreting the learning processes would also be constructive. A promising approach would be to introduce a system for obtaining systematic feedback from the purchasers of the vehicles and other stakeholders. Notably, the above changes would also facilitate the market diffusion of these innovations. In short, the business and social agendas would reinforce each other. [ABSTRACT FROM AUTHOR]

The goal of this paper is to develop a modeling framework that captures the inter-decision dynamics between mobility service providers (MSPs) and travelers that can be used to optimize and analyze policies/regulations related to MSPs. To meet this goal, the paper proposes a tri-level mathematical programming model with a public-sector decision maker (i.e. a policymaker/regulator) at the highest level, the MSP in the middle level, and travelers at the lowest level. The public-sector decision maker aims to maximize social welfare via implementing regulations, policies, plans, transit service designs, etc. The MSP aims to maximize profit by adjusting its service designs. Travelers aim to maximize utility by changing their modes and routes. The travelers' decisions depend on the regulator and MSP's decisions while the MSP decisions themselves depend on the regulator's decisions. To solve the tri-level mathematical program, the study employs Bayesian optimization (BO) within a simulation–optimization solution approach. At the lowest level, the solution approach includes an agent-based transportation system simulation model to capture travelers' behavior subject to specific decisions made by the regulator and MSP. At the middle and highest levels, the solution approach employs BO for the MSP to maximize profit and for the regulator to maximize social welfare. The agent-based transportation simulation model includes a mode choice model, a road network, a transit network, and an MSP providing automated mobility-on-demand (AMOD) service with shared rides. The modeling and solution approaches are applied to Munich, Germany in order to validate the model. The case study investigates the tolls and parking costs the city administration should set, as well as changes in the public transport budget and a limitation of the AMOD fleet size. Best policy settings are derived for two social welfare definitions, in both of which the AMOD fleet size is not regulated as the shared-ride AMOD service provides significant value to travelers in Munich. • Optimization of regulatory measures for autonomous mobility on-demand systems. • Hierarchical decision-making of regulator, mobility service provider and travelers. • Solution approach using multi-level, multi-objective Bayesian optimization. • Agent-based model including ridepooling, private vehicles and public transport. • Fleet size should not be regulated; toll and parking fees depend on scenario. [ABSTRACT FROM AUTHOR]