Preparing a nation for autonomous vehicles: opportunities,barriers and policy recommendations

Autonomous vehicles (AVs) represent a potentially disruptive yet beneficial change to our transportation system. This new technology has the potential to impact vehicle safety, congestion, and travel behavior. All told, major social AV impacts in the form of crash savings, travel time reduction, fuel efficiency and parking benefits are estimated to approach $2000 to per year per AV, and may eventually approach nearly $4000 when comprehensive crash costs are accounted for. Yet barriers to implementation and mass-market penetration remain. Initial costs will likely be unaffordable. Licensing and testing standards in the U.S. are being developed at the state level, rather than nationally, which may lead to inconsistencies across states. Liability details remain undefined, security concerns linger, and without new privacy standards, a default lack of privacy for personal travel may become the norm. The impacts and interactions with other components of the transportation system, as well as implementation details, remain uncertain. To address these concerns, the federal government should expand research in these areas and create a nationally recognized licensing framework for AVs, determining appropriate standards for liability, security, and data privacy.     

Autonomous vehicles: who will use them,and will they share?

ABSTRACT

The advent of road transport automation is suggested to be one of four key technological transitions that could amount to a major transformation in mobility practices. Specifically, fully Automated Vehicles (AVs) might replace the current private car owner user model with fleets of on-demand synchronously-shared automated taxis. However, significant barriers to this vision becoming the norm remain. This paper examines two critical user-acceptance aspects of the transition: willingness to adopt AVs, and willingness to share an AV with others, particularly strangers. Our novel survey (n?=?899) included a choice experiment featuring four future full automation transport services (private, synchronously/asynchronously shared, and public). Cluster analysis examined respondents' preferences and their demographic and psycho-social characteristics. We uncover significant uncertainty about willingness to adopt automation and sharing, and important differences between clusters within our sample. For example, under 50% of participants report willingness to use an AV over their normal mode, or would prefer an automated option to a current human-driven option. Our findings raise critical questions for policymakers and transport authorities. Not least, how can AV technologies help realise the environmental and social benefits of widespread vehicle sharing in a context of a travelling public that still prefers its privacy on-the-move?     

Parents’ perspectives on using autonomous vehicles to enhance children’s mobility

Prior research has estimated the impact of an autonomous vehicle (AV) environment on the mobility of underserved populations such as adult non-drivers. What is currently unknown is the impact of AVs on enhancing the mobility of children who are also mobility disadvantaged, as child passengers are likely part of AV ridership scenarios in the perceivable future. To address this question, our study collected perceived benefits and concerns of AVs from a US convenience sample of parents whose children relied on them for mobility. We found that parents’ intentions to travel in AV and their technology readiness as well as parent (sex, residence area) and child (age, restraint system) demographic profiles were important determinants of potential AV acceptance and impact. In addition, two groups of potential AV users emerged from the data: the curious and the practical. This study addresses a gap in the literature by assessing parents’ perspectives on using AVs to transport children. The results have great potentials to guide the design of mobility features, safety evaluations, and implementation policies, as a decline in public interest in AVs has been recently documented.     

Automated vehicles: exploring possible consequences of government (non)intervention for congestion and accessibility

ABSTRACT

Academic research on automated vehicles (AVs) has to date been dominated by the fields of engineering and computer science. Questions of how this potentially transformative technology should be governed remain under-researched and tend to concentrate on governing the technology’s early development. We respond in this paper by exploring the possible longer-term effect of government (lack of) intervention.

The paper tests the hypothesis that a “laissez-faire” governance approach is likely to produce less desirable outcomes in a scenario of mass uptake of AVs than would a well-planned set of government interventions. This is done using two prominent themes in transport policy – traffic flow and accessibility – in a scenario of high market penetration of Level-5 automated vehicles in capitalist market economies. The evidence used is drawn from a literature review and from the findings of a set of workshops with stakeholders.

We suggest that a laissez-faire approach will lead to an increase in traffic volume as a result of a growing population of “drivers” and a probable increase in kilometres driven per passenger. At the same time, the hoped-for increases in network efficiency commonly claimed are not guaranteed to come about without appropriate government intervention. The likely consequence is an increase in congestion. And, with respect to accessibility, it is likely that the benefits of AVs will be enjoyed by wealthier individuals and that the wider impacts of AV use (including sprawl) may lead to a deterioration in accessibility for those who depend on walking, cycling or collective transport.

We consider the range of possible government intervention in five categories: Planning/land-use; Regulation/policy; Infrastructure/technology; Service provision; and Economic instruments. For each category, we set out a series of interventions that might be used by governments (at city, region or state level) to manage congestion or protect accessibility in the AV scenario described. Many of these (e.g. road pricing) are already part of the policy mix but some (e.g. ban empty running of AVs) would be new. We find that all interventions applicable to the management of traffic flow would also be expected to contribute to the management of accessibility; we define a small number of additional interventions aimed at protecting the accessibility of priority groups.

Our general finding is that the adoption of a package of these interventions could be expected to lead to better performance against generic traffic-flow and accessibility objectives than would a laissez-faire approach, though questions of extent of application remain.

In our conclusions, we contrast laissez-faire with both anticipatory governance and “precautionary” governance and acknowledge the political difficulty associated with acting in the context of uncertainty. We point out that AVs do not represent the first emerging technology to offer both opportunities and risks and challenge governments at all levels to acknowledge the extent of their potential influence and, in particular, to examine methodically the options available to them and the potential consequences of pursuing them.     

Discussing the “positive utilities” of autonomous vehicles: will travellers really use their time productively?

ABSTRACT

Autonomous vehicles (AVs) are expected to reshape travel behaviour and demand in part by enabling productive uses of travel time—a primary component of the “positive utility of travel” concept—thus reducing subjective values of travel time savings (VOT). Many studies from industry and academia have assumed significant increases in travel time use and reductions in VOT for AVs. In this position paper, I argue that AVs’ VOT impacts may be more modest than anticipated and derive from a different source. Vehicle designs and operations may limit activity engagement during travel, with AV users feeling more like car passengers than train riders. Furthermore, shared AVs may attenuate travel time use benefits, and productivity gains could be limited to long-distance trips. Although AV riders will likely have greater activity participation during travel, many in-vehicle activities today may be more about coping with commuting burdens than productively using travel time. Instead, VOT reductions may be more likely to arise from a different “positive utility”—subjective well-being improvements through reduced stresses of driving or the ability to relax and mentally transition. Given high uncertainty, further empirical research on the experiential, time use, and VOT impacts of AVs is needed.     

Dynamic autonomous vehicle fleet operations: Optimization-based strategies to assign AVs to immediate traveler demand requests

Motivated by the growth of ridesourcing services and the expected advent of fully-autonomous vehicles (AVs), this paper defines, models, and compares assignment strategies for a shared-use AV mobility service (SAMS). Specifically, the paper presents the on-demand SAMS with no shared rides, defined as a fleet of AVs, controlled by a central operator, that provides direct origin-to-destination service to travelers who request rides via a mobile application and expect to be picked up within a few minutes. The underlying operational problem associated with the on-demand SAMS with no shared rides is a sequential (i.e. dynamic or time-dependent) stochastic control problem. The AV fleet operator must assign AVs to open traveler requests in real-time as traveler requests enter the system dynamically and stochastically. As there is likely no optimal policy for this sequential stochastic control problem, this paper presents and compares six AV-traveler assignment strategies (i.e. control policies). An agent-based simulation tool is employed to model the dynamic system of AVs, travelers, and the intelligent SAMS fleet operator, as well as, to compare assignment strategies across various scenarios. The results show that optimization-based AV-traveler assignment strategies, strategies that allow en-route pickup AVs to be diverted to new traveler requests, and strategies that incorporate en-route drop-off AVs in the assignment problem, reduce fleet miles and decrease traveler wait times. The more-sophisticated AV-traveler assignment strategies significantly improve operational efficiency when fleet utilization is high (e.g. during the morning or evening peak); conversely, when fleet utilization is low, simply assigning traveler requests sequentially to the nearest idle AV is comparable to more-advanced strategies. Simulation results also indicate that the spatial distribution of traveler requests significantly impacts the empty fleet miles generated by the on-demand SAMS.     

Agricultural vehicles and sustainable safe road traffic: solving conflicts on arterial highways

Addressing the issues of traffic safety in rural areas presents a constant challenge. The mix of light and heavy vehicles and the considerable differences in speed among these traffic participants result in high risks and delays for the faster vehicles. Agricultural vehicles (AVs) in particular have such an impact on traffic, especially when using arterial highways. This paper reviews the problems of safety and delays that AVs cause on arterial highways, and the appropriate mitigation. The concept of 'sustainable safety' in The Netherlands focuses on these problems, because of the proposed construction of parallel roads alongside all arterial highways. However, Dutch accident statistics cannot justify the high costs for the construction of parallel roads alongside 7000 km of arterial highways. Delays experienced by fast traffic are another reason for separating AVs from other road users with parallel roads. Alternative measures alongside the arterial highway, such as passing bays, restricting AVs to travelling at off-peak only and improving the conspicuity of the AVs, may be more cost-effective ways of reducing delays and/or improving traffic safety on arterial highways. Another solution may be to eliminate the need for AVs to use the arterial highway by altering their routes. For this purpose, land reallocation projects (as practised in Holland) can provide a useful tool.     

Planning the driverless city

ABSTRACT

AV technologies have the potential to transform urban landscapes and existing transport systems and networks. Yet, the utopian imaginary of reduced automobile ownership and a new shared economic future sits in tension with suggestions that car dependency, urban sprawl and transport inaccessibility will be exacerbated. The issues are situated in a complex governance landscape involving an influential private sector who are increasingly setting the agenda. The public sector may be forced into reacting to the new innovations by information technology and automobile companies as they are introduced into existing built environments. Drawing on an extensive literature base and interviews with public sector planners, this paper reveals the conceptual gaps in the framing of AV technology – the prospects and limits – and how these are conceived. The paper raises questions about the role urban planning can play in the rollout of AVs in order to anticipate and mediate unwanted built environment and socio-spatial impacts, as well as reconciling the ambition of transport innovation with the public purpose of planning.     

Location privacy preferences: A survey-based analysis of consumer awareness,trade-off and decision-making

With the advent and rapid dissemination of location-sensing information technology, the issue of location information privacy is receiving growing attention. Perhaps of greatest concern is ensuring that potential users of mobile Information and Communications Technologies (e.g., Location-Based Services and Intelligent Transportation Systems) are comfortable with the levels of privacy protection afforded them, as well as with the benefits they will receive in return for providing private location information. This paper explores the concepts of privacy risks, benefits, willingness to trade, and compensation in relationship to mobile and locational technologies using a stated preference survey to ascertain areas of interest in determining the trade-offs that consumers will be willing to make in return for mobility enhancements. Analysis of the survey leads to findings that while respondents believe that sharing data in the mobile environment may pose privacy risks, they do not generally take steps necessary to address these risks; that privacy preferences are impacted by a range of factors, including both personal and contextual considerations (such as factors arising from their specific situation at the time of information seeking); and that willingness to trade private location data is dependent upon a number of factors related to context, personal characteristics, expected benefits and degree of trust in the collecting organization.     

A statistical analysis of consumer perceptions towards automated vehicles and their intended adoption

ABSTRACT

While automated vehicle (AV) development continues to progress rapidly, how the public will accept and adopt automated vehicles remains an open question. Using extensive survey data, we apply cluster analysis to better understand consumer perceptions toward potential benefits and concerns related to AVs with regard to factors influencing their AV adoption likelihood. Four market segments are identified – ‘benefits-dominated,’ ‘concerns-dominated,’ ‘uncertain,’ and ‘well-informed.’ A random parameters multinomial logit model is then estimated to identify factors influencing the probability of respondents belonging to one of these four market segments. Among other influences (such as socio-economic and current travel characteristics), it is found that ‘Millennials’ have a higher probability of belonging to the well-informed market segment, ‘Gen-Xers’ with a lower probability to the uncertain market segment, and ‘Baby Boomers’ with a higher probability to the concerns-dominated market (relative to the ‘Great Generation’). We also study the individuals’ expressed likelihood of AV adoption using separate random parameters ordered probit estimations for each of the four market segments. The substantial and statistically significant differences across each AV consumer market segment underscore the potentially large impact that different consumer demographics may have on AV adoption and the need for targeted marketing to achieve better market-penetration outcomes.     

Modeling adoption timing of autonomous vehicles: innovation diffusion approach

Autonomous vehicles (AVs) are expected to act as an economically-disruptive transportation technology offering several benefits to the society and causing significant changes in travel behavior and network performance. However, one of the critical issues that policymakers are facing is the absence of a sound estimation of their market penetration. This study is an effort to quantify the effect of different drivers on the adoption timing of AVs. To this end, we develop an innovation diffusion model in which individuals’ propensities to adopt a new technology such as AVs takes influence from a desire to innovate and a need to imitate the rest of the society. It also captures various sources of inter-personal heterogeneity. We found that conditional on our assumptions regarding the changes in market price of AVs over time, their market penetration in our study region (Chicago metropolitan area) will eventually reach 71.3%. Further, model estimation results show that a wide range of socio-demographic factors, travel pattern indicators, technology awareness, and perceptions of AVs are influential in people’s AV adoption timing decision. For instance, frequent long-distance travelers are found to make the adoption decision more innovatively while those who have experienced an accident in their lifetime are found to be more influenced by word of mouth.     

Will autonomous vehicles change residential location and vehicle ownership? Glimpses from Georgia

Many studies have begun investigating possible transportation landscapes in the autonomous vehicle (AV) era, but empirical results on longer-term decisions are limited. We address this gap using data collected from a survey designed and implemented for Georgia residents in 2017–2018. Focusing on a hypothetical all-AV future, this section of the survey included questions regarding advantages/disadvantages of AVs, short-term mode choice impacts, medium-term impacts on activity patterns, and long-term behavioral changes – specifically, whether/how AVs will influence individuals to change residential location and the number of cars in the household. We hypothesize that AVs could act in concert with attitudinal preferences to stimulate changes in these long-term decisions, and that some medium-term activity changes triggered by AVs could motivate people to relocate their residence or shed household vehicles. We applied exploratory factor analysis to measure the perceived likelihood that AVs would prompt various medium-term changes. We then included some of those measures, among other variables, in a cross-nested logit (CNL) model of the choice of the residential location/vehicle ownership bundle. Although more than half of respondents expected “no change” in their bundle, we found that younger, lower income, pro-suburban, and pro-non-car-mode individuals were more likely to anticipate changing their selections. In addition, some expected medium-term impacts of AVs influenced changes in these longer-term choices. We further applied the CNL model to two population segments (Atlanta and non-Atlanta-region residents). We found notable improvement in goodness of fit and different effects of factors across segments, signifying the existence of geography-related taste heterogeneity.     

Autonomous vehicle perception: The technology of today and tomorrow

Perception system design is a vital step in the development of an autonomous vehicle (AV). With the vast selection of available off-the-shelf schemes and seemingly endless options of sensor systems implemented in research and commercial vehicles, it can be difficult to identify the optimal system for one’s AV application. This article presents a comprehensive review of the state-of-the-art AV perception technology available today. It provides up-to-date information about the advantages, disadvantages, limits, and ideal applications of specific AV sensors; the most prevalent sensors in current research and commercial AVs; autonomous features currently on the market; and localization and mapping methods currently implemented in AV research. This information is useful for newcomers to the AV field to gain a greater understanding of the current AV solution landscape and to guide experienced researchers towards research areas requiring further development. Furthermore, this paper highlights future research areas and draws conclusions about the most effective methods for AV perception and its effect on localization and mapping. Topics discussed in the Perception and Automotive Sensors section focus on the sensors themselves, whereas topics discussed in the Localization and Mapping section focus on how the vehicle perceives where it is on the road, providing context for the use of the automotive sensors. By improving on current state-of-the-art perception systems, AVs will become more robust, reliable, safe, and accessible, ultimately providing greater efficiency, mobility, and safety benefits to the public.     

Shared versus private mobility: Modeling public interest in autonomous vehicles accounting for latent attitudes

Emerging autonomous vehicles (AVs) and shared mobility systems per se will transform urban passenger transportation. Coupled together, shared AVs (SAVs) can facilitate widespread use of shared mobility services by providing flexible public travel modes comparable to private AV. Hence, it may be conjectured that future urban mobility is likely an on-demand service and AV private ownership is unappealing. Nonetheless, it is still unclear what observable and latent factors will drive public interest in (S)AVs, the answer to which will have important implications on transportation system performance. This paper aims to jointly model public interest in private AVs and multiple SAV configurations (carsharing, ridesourcing, ridesharing, and access/egress mode) in daily and commute travels with explicit treatment of the correlations across the (S)AV types. To this end, multivariate ordered outcome models with latent variables are employed, whereby latent attitudes and preferences describing traveler safety concern about AV, green travel pattern, and mobility-on-demand savviness are accounted for using structural and measurement equations. Drawing from a stated preference survey in the State of Washington, important insights are gained into the potential user groups based on the socio-economic, built environment, and daily/commute travel behavior attributes. Key policies are also offered to promote public interest in (S)AVs by scrutinizing the marginal effects of the latent variables.     

Integrated models of land use and transportation for the autonomous vehicle revolution

ABSTRACT

The advent of the autonomous vehicle (AV) will affect not only the transportation system, but also future patterns of land development. Integrated land use and transportation models will be critical tools in assessing the path forward with this technology. Key questions with respect to land use impacts of AVs arise from potential changes in sensitivity to travel and reduced demand for parking. It is an open question whether AVs will induce urban sprawl, or whether spatial economies of agglomeration will mitigate any reductions in travel time sensitivity. The deployment of shared fleets of AVs would likely reduce parking demand, producing yet to be explored impacts on property development within existing urban footprints. We perform a critical assessment of currently operational models and their ability to represent the adoption of AVs. We identify the representation of time in such models as a vital component requiring additional development to model this new technology. Existing model applications have focused on the discrete addition of new infrastructure or policy at a fixed point in time, whereas AV adoption will occur incrementally through time. Stated adaptation surveys are recommended as tools to quantify preferences and develop relevant model inputs. It is argued that existing models that assume comparatively static equilibrium have been convenient in the past, but are insufficient to model technology adoption. In contrast, dynamic model frameworks lack sufficient structure to maintain reasonability under large perturbations from base conditions. The ongoing advancement of computing has allowed models to move away from being mechanistic aggregate tools, towards behaviourally rich depictions of individual persons and firms. However, much work remains to move from projections of existing conditions into the future, to the evolution of the spatial economy as it evolves through time in response to new technologies and exogenous stresses. Principles from complex and evolutionary systems theory will be important in the development of models with the capacity to consider such dynamics.     

Autonomous vehicles: scientometric and bibliometric review*

ABSTRACT

This paper presents a scientometric and bibliometric review of the research on autonomous vehicles (AVs) to identify its main characteristics, evolution, and potential trends for future studies. Relevant articles were searched on WoS, yielding a research corpus of 10,580 papers, and the software CiteSpace was subsequently used for analysis. The results showed that AV research is heterogeneous and registered a growing demand over time. Multidisciplinarity is present, with 96 science fields being identified. As in any other sector, it is necessary to understand broader aspects of this industry such as the market factors surrounding it, as well as other economic and managerial issues. In this sense, we observed a migration of the research field from multidisciplinarity to pluridisciplinarity with a greater number of studies focusing on the latter. We understand that terminology standardisation contributes to achieving pluridisciplinarity. As such, it is important to highlight that sustainability, public policies, liability, and safety, as well as business issues such as performance and business models are some of the tendencies in the field of AVs. For future studies, we suggest a more in-depth analysis of publications in terms of individual search terms, as well as the sub-areas identified as trends in this paper.     

Optimal deployment of autonomous vehicle lanes with endogenous market penetration

This paper develops a mathematical approach to optimize a time-dependent deployment plan of autonomous vehicle (AV) lanes on a transportation network with heterogeneous traffic stream consisting of both conventional vehicles (CVs) and AVs, so as to minimize the social cost and promote the adoption of AVs. Specifically, AV lanes are exclusive lanes that can only be utilized by AVs, and the deployment plan specifies when, where, and how many AV lanes to be deployed. We first present a multi-class network equilibrium model to describe the flow distributions of both CVs and AVs, given the presence of AV lanes in the network. Considering that the net benefit (e.g., reduced travel cost) derived from the deployment of AV lanes will further promote the AV adoption, we proceed to apply a diffusion model to forecast the evolution of AV market penetration. With the equilibrium model and diffusion model, a time-dependent deployment model is then formulated, which can be solved by an efficient solution algorithm. Lastly, numerical examples based on the south Florida network are presented to demonstrate the proposed models.     

Estimating the trip generation impacts of autonomous vehicles on car travel in Victoria,Australia

Autonomous vehicles (AVs) potentially increase vehicle travel by reducing travel and parking costs and by providing improved mobility to those who are too young to drive or older people. The increase in vehicle travel could be generated by both trip diversion from other modes and entirely new trips. Existing studies however tend to overlook AVs’ impacts on entirely new trips. There is a need to develop a methodology for estimating possible impacts of AVs on entirely new trips across all age groups. This paper explores the impacts of AVs on car trips using a case study of Victoria, Australia. A new methodology for estimating entirely new trips associated with AVs is proposed by measuring gaps in travel need at different life stages. Results show that AVs would increase daily trips by 4.14% on average. The 76+ age group would have the largest increase of 18.5%, followed by the 18–24 age group and the 12–17 age group with 14.6 and 11.1% respectively. If car occupancy remains constant in AV scenarios, entirely new trips and trip diversions from public transport and active modes would lead to a 7.31% increase in car trips. However increases in car travel are substantially magnified by reduced car occupancy rates, a trend evidenced throughout the world. Car occupancy would need to increase by at least 5.3–7.3% to keep car trips unchanged in AV scenarios.     

Designing optimal autonomous vehicle sharing and reservation systems: A linear programming approach

Autonomous vehicle (AV) technology holds great promise for improving the efficiency of traditional vehicle sharing systems. In this paper, we investigate a new vehicle sharing system using AVs, referred to as autonomous vehicle sharing and reservation (AVSR). In such a system, travelers can request AV trips ahead of time and the AVSR system operator will optimally arrange AV pickup and delivery schedules and AV trip chains based on these requests. A linear programming model is proposed to efficiently solve for optimal solutions for AV trip chains and required fleet size through constructed AVSR networks. Case studies show that AVSR can significantly increase vehicle use rate (VUR) and consequentially reduce vehicle ownership significantly. In the meantime, it is found that the actual vehicle miles traveled (VMT) in AVSR systems is not significantly more than that of conventional taxis, despite inevitable empty hauls for vehicle relocation in AVSR systems. The results imply huge potential benefits from AVSR systems on improving mobility and sustainability of our current transportation systems.     

Roads in transition: Integrated modeling of a manufacturer-traveler-infrastructure system in a mixed autonomous/human driving environment

This paper develops an integrated model to characterize the market penetration of autonomous vehicles (AVs) in urban transportation networks. The model explicitly accounts for the interplay among the AV manufacturer, travelers with heterogeneous values of travel time (VOTT), and road infrastructure capacity. By making in-vehicle time use more leisurely or productive, AVs reduce travelers’ VOTT. In addition, AVs can move closer together than human-driven vehicles because of shorter safe reaction time, which leads to increased road capacity. On the other hand, the use of AV technologies means added manufacturing cost and higher price. Thus, traveler adoption of AVs will trade VOTT savings with additional out-of-pocket cost. The model is structured as a leader (AV manufacturer)-follower (traveler) game. Given the cost of producing AVs, the AV manufacturer sets AV price to maximize profit while anticipating AV market penetration. Given an AV price, the vehicle and routing choice of heterogeneous travelers are modeled by combining a multinomial logit model with multi-modal multi-class user equilibrium (UE). The overall problem is formulated as a mathematical program with complementarity constraints (MPCC), which is challenging to solve. We propose a solution approach based on piecewise linearization of the MPCC as a mixed-integer linear program (MILP) and solving the MILP to global optimality. Non-uniform distribution of breakpoints that delimit piecewise intervals and feasibility-based domain reduction are further employed to reduce the approximation error brought by linearization. The model is implemented in a simplified Singapore network with extensive sensitivity analyses and the Sioux Falls network. Computational results demonstrate the effectiveness and efficiency of the solution approach and yield valuable insights about transportation system performance in a mixed autonomous/human driving environment.