Automated driving systems (ADS) have the potential to revolutionize transportation. Through the automation of driver functions in the application of advanced technology within the vehicle, significant improvements can be made to safety, efficiency, user experience, and the preservation of the environment. According to the US Department of Transportation [1], there are more than 1,400 cars, trucks, buses, and other vehicles being tested by more than 80 companies across the USA. Implementation of ADS technology is well advanced, with many sites across the USA incorporating automated vehicles (AVs) into wider programs to apply advanced technology to transportation. Discussions with the public sector’s implementing agencies suggest that one of the barriers to faster progress lies in the lack of consistent and standardized field-testing protocols. This report looks at the state of the art of field testing for ADS and identifies areas for improved consistency and standardization. It will define the problem to be addressed by AVs and the challenges associated with the introduction of such vehicles and open-road situations. In particular, the report will look at the possibilities for big data and analytics to enable the sharing of lessons learned and convergence on standard field-testing approaches. NOTE: SAE EDGE™ Research Reports are intended to identify and illuminate key issues in emerging, but still unsettled, technologies of interest to the mobility industry. The goal of SAE EDGE™ Research Reports is to stimulate discussion and work in the hope of promoting and speeding resolution of identified issues. SAE EDGE™ Research Reports are not intended to resolve the issues they identify or close any topic to further scrutiny. Click here to access the full SAE EDGETM Research Report portfolio. https://doi.org/10.4271/EPR2019009

With over 100 years of operation, the current automobile industry has settled into an equilibrium with the development of methodologies, regulations, and processes for improving safety. In addition, a nearly $2-trillion market operates in the automotive ecosystem with connections into fields ranging from insurance to advertising. Enabling this ecosystem is a well-honed, tiered supply chain and an established development environment. Autonomous vehicle (AV) technology is a leap forward for the existing automotive industry; now the automobile is expected to manage perception and decision-making tasks. The safety technologies associated with these tasks were presented in an earlier SAE EDGE™ Research Report, “Unsettled Technology Areas in Autonomous Vehicle Test and Validation.” In a later SAE EDGE™ Research Report, “Unsettled Topics Concerning Automated Driving Systems and the Transportation Ecosystem,” senior executives from the automotive ecosystem explored the impact of AV technology as they faced the prospect of this disruptive technology entering their marketplace. Interestingly, stable use-models and market penetration were all gated primarily by the demonstration of AV safety. Building on these previous verification and validation (V&V)-related reports, “Unsettled Topics Concerning Automated Driving Systems and the Development Ecosystem” explores the open issues in the shift of the development and supplier environment toward a new AV-enabled future. NOTE: SAE EDGE™ Research Reports are intended to identify and illuminate key issues in emerging, but still unsettled, technologies of interest to the mobility industry. The goal of SAE EDGE™ Research Reports is to stimulate discussion and work in the hope of promoting and speeding resolution of identified issues. SAE EDGE™ Research Reports are not intended to resolve the challenges they identify or close any topic to further scrutiny. Click here to access the full SAE EDGETM Research Report portfolio. https://doi.org/10.4271/EPR2020004

Over the last 100 years, the automobile has become integrated in a fundamental way into the broader economy. A broad and deep ecosystem has emerged, and critical components of this ecosystem include insurance, after-market services, automobile retail sales, automobile lending, energy suppliers (e.g., gas stations), medical services, advertising, lawyers, banking, public planners, and law enforcement. These components - which together represent almost $2 trillion of the U.S. economy - are in equilibrium based on the current capabilities of automotive technology. However, the advent of autonomous vehicles (AVs) and technologies like electrification have the potential to significantly disrupt the automotive ecosystem. The critical cog governing the rate and pace of this shift is the management of the test and verification of AVs. In this SAE EDGE™ report, six senior industry leaders in the impacted ecosystems essay articles which describe sectors of the current automotive ecosystem and the manner in which AV technology can potentially reshape them - providing a mosaic of the massive infrastructure shifts which will be required to absorb AV technologies. NOTE: SAE EDGE™ Research Reports are intended to identify and illuminate key issues in emerging, but still unsettled, technologies of interest to the mobility industry. The goal of SAE EDGE™ Research Reports is to stimulate discussion and work in the hope of promoting and speeding resolution of identified issues. SAE EDGE™ Research Reports are not intended to resolve the issues they identify or close any topic to further scrutiny. Click here to access the full SAE EDGETM Research Report portfolio. https://doi.org/10.4271/EPR2019005

This SAE EDGE™ Research Report identifies key unsettled issues of interest to the automotive industry regarding the new generation of sensors designed for vehicles capable of automated driving. Four main issues are outlined that merit immediate interest: First, specifying a standardized terminology and taxonomy to be used for discussing the sensors required by automated vehicles. Second, generating standardized tests and procedures for verifying, simulating, and calibrating automated driving sensors. Third, creating a standardized set of tools and methods to ensure the security, robustness, and integrity of data collected by such sensors. The fourth issue, regarding the ownership and privacy of data collected by automated vehicle sensors, is considered only briefly here since its scope far exceeds the technical issues that are the primary focus of the present report. SAE EDGE™ Research Reports are preliminary investigations of new technologies. The three technical issues identified in this report need to be discussed in greater depth with the aims of, first, clarifying the scope of the industry-wide alignment needed, second, prioritizing the issues requiring resolution, and, third, creating a plan to generate the necessary frameworks, practices, and protocols. Click here to access the full SAE EDGETM Research Report portfolio. https://doi.org/10.4271/EPR2018001

Unsettled Topics in Automated Vehicle Data Sharing for Verification and Validation Purposesdiscusses the unsettled issue of sharing the terabytes of driving data generated by Automated Vehicles (AVs) on a daily basis. Perception engineers use these large datasets to analyze and model the automated driving systems (ADS) that will eventually be integrated into future "self-driving" vehicles. However, the current industry practices of collecting data by driving on public roads to understand real-world scenarios is not practical and will be unlikely to lead to safe deployment of this technology anytime soon. Estimates show that it could take 400 years for a fleet of 100 AVs to drive enough miles to prove that they are as safe as human drivers. Yet, data-sharing can be developed - as a technology, culture, and business - and allow for rapid generation and testing of the billions of possible scenarios that are needed to prove practicality and safety of an ADS - resulting in lower research and development costs to the industry. Unsettled Topics in Automated Vehicle Data Sharing for Verification and Validation Purposes explores how this could lead to better regulation, insurance, public acceptance - and finally, shorter technology development cycles. Finding a business case and changing to an open data culture are not going to be easy tasks, but data sharing is the only way forward for the whole industry to move to the next phase of deployment after nearly a decade of intense research.