Road Vehicle Automation 3

In 2014, the Japanese government initiated a research and development project on automated driving systems. Background, scope, focuses and expected outcome of the project are described in this paper. Deployment of the Intelligent Transport Systems has been actively promoted by the Japanese government in the past 20 years. Technological and operational platforms essential for automated driving systems were formulated as a result of collaboration among public agencies, industries and academia. Application of automated driving technologies is expected to contribute to overcome societal challenges, such as aging society, in addition to road traffic safety, efficiency and enhanced mobility.

The Accessible Transportation Technologies Research Initiative (ATTRI) leverages emerging innovations to identify, develop, and deploy new transformative technologies, applications, or systems, along with supporting policies and institutional guidance, to address mobility challenges of all travelers, in particular, travelers with disabilities. ATTRI research focuses on the needs of three stakeholder groups: people with disabilities, veterans with disabilities, and older adults. ATTRI will also develop technological solutions to lower or remove barriers to transportation according to four functional disabilities within these stakeholder groups: visual, hearing, cognitive, and mobility. The technologies potentially leveraged by ATTRI provide almost ubiquitous access to a wealth of real-time situational data sources, including data specific to transportation, municipalities, points of interest, accessibility, and crowd-sourced information.

New paradigms emerging in transportation and information and communication technology create opportunities to better understand and leverage the interactions between travelers, vehicles, and the built environment to reduce greenhouse gas emissions and save energy. The U.S. Department of Energy’s SMART (Systems and Modeling for Accelerated Research in Transportation) Mobility Initiative recognizes and harnesses these megatrends by elevating DOE’s traditional transportation energy focus beyond the vehicle component technology level to transportation-as-a-system analysis, modeling and simulation, and applied research and development in 5 interrelated topics: connected and automated vehicles, mobility decision science, urban science, vehicles and infrastructure, and multi-modal.

This chapter summarizes a longer policy paper, How Governments Can Promote Automated Driving, which details steps that state and local governments can take now to encourage the development, deployment, and use of automated road vehicles. The chapter has four main parts. Context emphasizes the need to think broadly about relevant technologies, impacts, and laws. Administrative Strategies identifies steps that governments can take in the course of their ordinary operations. Legal Strategies recommends a careful legal audit and provides guidance on the legal changes or clarifications that may flow from such an audit. Community Strategies focuses on ways that communities can prepare for and even attract truly driverless systems that are responsive to local needs and opportunities.

Autonomous vehicles have the potential to change all aspects of mobility—from driver safety and insurance liability to car ownership and how Americans commute. It has the potential to disrupt both public and private transportation as we know it. As Google, Uber, the automobile industry, and other organizations continue to make rapid technological advances, it is vital that federal, state, and local governments establish policies, laws and regulations that account for these disruptions. Of utmost importance is finding a balance between guarding public safety while regulating insurance/liability and still encouraging investment in research and development of autonomous vehicles. Most research papers and news reports regarding autonomous vehicles focus on the technological advancement or implications for society (e.g., improved safety and greater mobility for the elderly and disabled people). Many articles cite the importance of government regulation; however, very few provide targeted guidance on how government agencies should respond. The intent of this paper is to outline the role of government in autonomous vehicles and present information local and regional governments need to inform planning and decision-making—both now and in the future.

This article takes seriously how discourses of automated driving shape the world we are designing and the public’s perception of it. The metaphors which organize our thought and scaffold our conceptual frameworks betray our point of view: legacy, engineering-based or user-centered. Valeo’s Intuitive Driving strategy centers on the user experience and therefore on the evolving relationship between user and technology. Relationships are built on trust. Automated Driving involves an evolution of agency in a high stakes context with new implications for trust generation. It also entails a shift which has a huge impact both on industry and user: from horsepower to data-power. This shift fundamentally alters the nature of the relationship between human and vehicle. In the design of this relationship anthropomorphism is a central issue. Building a trusting human-machine relationship in automated driving inevitably means dealing with social robotics and affective computing where anthropomorphism in technology has been explored for many years. But the specificity of the automatic driving moment must be attended to: this is the only robot with an interior private mobile space. This new being will need a specific behavior designed for it, and already, a new discourse to speak of it.

This chapter addresses the testing and evaluation of the virtual truck driver. While the primary focus of the discussion is on verification and validation in model-based systems engineering it also touches upon testing for certification, establishing regulations, public investment, and research and development. A reference architecture for automated driving coordinates designs at the vehicle and system levels for increased interoperability among components and improved efficiency. A model-based systems engineering approach exploits automated vehicle systems domain models as a primary means of information exchange to help manage the complexity and provide analytical support for efficient architecting, design, verification, and validation. These models support the testing and evaluation process for functional safety design and certification. Finally, demonstration pilots, operational testing, and natural use testing, combined with system design artifacts, are critical to public and regulatory acceptance of the virtual driver. Although safety must be assured, the primary challenge is how to make such assurances without relying on a human driver and vouching for the virtual driver under all allowable driving situations and conditions. This chapter provides some ideas on how all of this might come together and help bring fully automated vehicles to the market.

As automated driving technology advances, the driver’s role continues to shift from active vehicle control to passive monitoring of the automated driving system and environment. This study comprised three experiments on controlled test tracks in mixed traffic that investigated driver interactions with prototype Level 2 and Level 3 partially automated driving systems. The study investigated which human-machine interface (HMI) characteristics are most effective at issuing a Take-Over Request (TOR) during the operation of a Level 2 automated driving system, how to prompt drivers to attend to the road when distracted during the operation of a Level 2 automated driving system (and whether these prompts are effective over time), and which HMI characteristics are most effective at issuing a TOR during the operation of a Level 3 automated driving system. In addition, participants’ trust in the automated driving system they experienced was gauged through multiple Likert-type surveys and an after-experience interview.

Automation disuse and associated loss of automation benefits may occur if users of automated vehicles experience motion sickness. Compared to conventional vehicles, motion sickness will be of greater concern due to the absence of vehicle control and the anticipated engagement in non-driving tasks. Furthermore, future users are expected to be less tolerant to the occurrence of motion sickness in automated vehicles compared to other means of transport. The risk of motion sickness may be manageable if we understand underlying causes and design our vehicles and driver-vehicle interactions appropriately. Guided by three fundamental principles, an initial set of design considerations are provided reflecting the incorporation of basic perceptual mechanisms.

Recent research on automated vehicle technologies points to the need to consider drivers’ interactions with road vehicle automation, and to apply Human Factors (HF) principles and guidelines to support timely and safe transfer of control to and from automation. This chapter elaborates on a Human Factors breakout session at the 2015 “Automated Vehicles Symposium” that addressed issues on how humans will interact with automated technologies, particularly considering that a wide variety of designs are either under development or already deployed. A number of key human factors design challenges are outlined including that automation is a cost-benefit trade-off where reduced human performance is a cost; that there are different transfer of control concerns for different levels of automation; that the driver may not provide suitable fallback performance of the dynamic driving task; that the better the automation, the less attention drivers will pay to traffic and the system, and the less capable they will be to resume control; and that the driver may be “out-of-the-loop”—may not monitor the driving environment or be aware of the status of automation. Two suggestions to solve the human factors issues are proposed: (1) to work within given constraints, to design the best we can, according to the given definitions of levels 2 and 3 vehicle automation, or (2) to advise against developing level 3 automation and instead advocate two levels of automation: shared driving wherein the driver understands his/her role to be responsible and in control for driving, and delegated driving in which there is no expectation that the driver will be a fallback for performing the dynamic driving task.

Autonomous vehicles offer great promise for unprecedented improvements in mobility and safety. However, self-driving vehicles may also significantly alter behavior because they can make driving easier and safer. This may lead connected autonomous vehicles to have large unintended consequences in terms of additional energy use and greenhouse gas emissions, as well as causing decreases in the density of urban areas and may impact congestion. This paper uses consensus estimates from the literature on the cost of driving and the value of travel time to evaluate automation’s ability to reduce the costs of travel time. Policy solutions to address the induced driving include charging for miles driven taking into account when and where vehicles are used.

This document aims at assessing and fine tuning alternative scenarios concerning road automated transport, based on the contribution of research, industry and public stakeholders convened at the CityMobil2 Workshops organised in La Rochelle on 30–31st March 2015. Two different paradigms—with and without a shift to shared mobility—were debated and a number of potential socio-economic impacts were identified. Road automation scenarios are devised for different urban typologies—large metropolitan areas, polycentric city networks, small-medium towns, rural/tourist areas. Impacts are assessed in a qualitative fashion—with the support of an online DELPHI survey followed by the workshop debates—in relation to a number of variables. These include: job disruption and creation; personal trips costs; public budget effects; insurance costs; accessibility to remote areas; road capacity and its use; journey comfort and convenience; energy and emissions; land saving for new public space uses; social impacts in terms of safety, personal security, health and active travel (trade-offs in automated rides vs. walking or cycling) and different perception/value of time spent travelling in automated vehicles.

The combination of connectivity and automation with the electrification of road vehicles offers a multitude of synergies in both performance of the technical systems and added values for users and businesses. These synergies become manifest in e.g. a higher energy efficiency and a more convenient operation. Furthermore they may define new products and services in the automotive domain. Therefore, they are an interesting subject of innovation analysis. This paper summarizes the activities of an international working group dealing with connectivity, automation, and electrification in road vehicles which was formed under the umbrella of the International Energy Agency (IEA). These activitites include the analysis of potential synergies, an information exchange about relevant research and development activities, and discussions on future trends in innovation, business development and deployment.

Commercial trucking is an industry ripe for connected and automated vehicles. The operations of the trucks combined with the highly analytical nature of the customers makes for the possibility of very rapid adoption. By combining partial automation with vehicle-to-vehicle and vehicle-to-cloud communication, these fleets can see massive fuels savings and safety improvements in the near term.

Ubiquitous, commercial deployment of automated road vehicles is desirable in order to realize their potential benefits such as crash avoidance, congestion mitigation, reduced environment impact, reduced driver stress, and increased driver productivity. A rigorous application of systems engineering, which includes validation and verification as crucial elements of assurance, is needed for the design and development of automated road vehicles. We discuss, without implying any form of joint recommendation, several areas of relevance to a common understanding of validation and verification of automated vehicles, namely customer expectations for vehicle response, industry standards for terms and definitions, industry standards for how measurement should be done, deeper knowledge of driving behavior today to serve as a reference, and standardized processes that encompass minimum performance requirements.

Three basic enablers for connected and automated vehicles (CAVs) are wireless networking, sensing, and control. Tightly coupled with the physical process of wireless signal propagation, vehicle movement, and environment, however, CAV wireless networking, sensing, and control are subject to complex cyber-physical uncertainties. To address the challenges, we propose an integrated, cross-layer framework for taming cyber-physical uncertainties, within which we develop novel algorithms and methodologies for addressing the interdependencies between networking, sensing, control, and physical processes. To enable high-fidelity evaluation and thus the deployment and adoption of new CAV technologies, we develop a software-defined CAV infrastructure for conducting CAV experiments using vehicles in real-world traffic so that properties of V2X communication, vehicles, traffic, road, and environment are captured at high-fidelity.

Vehicle automation relies heavily on technologies such as sensing, wireless communications, localization, mapping, human factors, and several others. Applications planned within the USDOT’s automation research roadmap depend on the understanding and applicability of these technologies. Thus it is important to be aware of the state of these technologies, and more importantly to stay ahead of the curve. The value of this task is not in accurately predicting the future of these technologies for USDOT’s automation program, but to minimize surprises. A four step process was followed to better understand advances in positioning, navigation and timing (PNT), mapping, communications, sensing and human factors. The first step identified the needs, second tracked high-level trends and based on these findings, the third step identified gaps. Finally, these insights were used to develop potential next steps for USDOT consideration. Paper presents a high-level overview of the research process, findings from the study and insights on next steps.

Currently different research activities on automated driving are conducted around the globe. The European flagship research project on automated driving functions is the research project “AdaptIVe” (Automated Driving Applications and Technologies for Intelligent Vehicles). Besides the development of automated driving functions, the project deals with general research on legal aspects, human factors and evaluation. The evaluation and impact assessment of automated driving functions faces different challenges considering the complexity of the technology. In this context, this paper describes the evaluation approaches that are taken in the project for the technical evaluation and impact assessment.

With the emergence of connected and automated vehicle (CAV) technologies, research on traffic flow modeling and analysis will play a very important role in improving our understanding of the fundamental characteristics of traffic flow. The frontier of studies on CAV systems have examined the impacts of CAVs on freeway bottleneck capacity, and macroscopic traffic flow, CAV applications on optimization of individual vehicle trajectories, potentials of CAV in traffic signal control, and applications of CAV in network routing. For current and future research initiatives, the greatest challenge lies in the potential inconsistencies between user, operator, and manufacturer goals. Specific research needs were identified on data collection and analysis on CAV behavior and applications. This paper summarizes the presentations and discussions during the Automated Vehicles Symposium 2015 (AVS15) held in Ypsilanti, Michigan, on July 20–23, 2015.

It is commonly accepted that Automated Transit will still be as relevant as it is now, if not more so, even when fully-automated vehicles become a reality. We need to develop a consensus on how vehicle automation will transform and perhaps disrupt the traditional transit systems, what new and different types of market-driven and publicly-run frameworks will emerge, and how we should invest our limited public resources. The two day session on Automated Transit and Shared Mobility Track (ATSM) during the 2015 Automated Vehicle Symposium (AVS) explored implications for the changing roles of transit and shared mobility as vehicle automation progresses. This chapter not only documents the main ideas presented during the symposium, but also supplements certain ideas with further discussions and clarifications after the conference.

For the first time in 2015, the Automated Vehicle Symposium featured a breakout session explicitly devoted to vulnerable road users (VRUs) and their use of and interactions with automated vehicles. A number of stakeholders, experts, and researchers from a variety of fields presented and discussed the state of current research and thought concerning the potential relationship of vulnerable road users and automated vehicles and how to maximize the benefits this novel technology might bring to these individuals. The topics included the role of design, various technological solutions, policies, and programs that could advance the safe mobility of VRUs in a future with an integrated fleet of automated vehicle systems. Through expert-led small group discussion, the breakout group produced a list of possible definitions for VRUs including pedestrians, cyclists, seniors (pedestrians as well as drivers), and identified key research gaps within the context of this multifaceted segment of the population. Some of these gaps related to motorcycle interactions, how different groups of VRUs will accept emerging AV technologies, and goals and solutions when considering how best to share limited roadway space across all road user constituencies.

The substantial uncertainty associated with the capabilities and deployment time lines of automated vehicle (AV) technologies makes it difficult to consider AVs in the long range transportation planning process. At the same time, given current and anticipated resource constraints, the consideration of AV technology could be critical for developing efficient and sustainable transportation systems. This paper documents findings from a workshop of modelers, planners, and researchers on (1) potential uncertainties associates with AV technology and adoption, (2) its implications for the transportation planning process, and (3) possible approaches (including immediate steps) that can help address planning under uncertainty. The workshop was held in the context of the Automated Vehicle Symposium 2015.