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Technical Paper

Safe Operations at Roadway Junctions - Design Principles from Automated Guideway Transit

This paper describes a system-level view of a fully automated transit system comprising a fleet of automated vehicles (AVs) in driverless operation, each with an SAE level 4 Automated Driving System, along with its related safety infrastructure and other system equipment. This AV system-level control is compared to the automatic train control system used in automated guideway transit technology, particularly that of communications-based train control (CBTC). Drawing from the safety principles, analysis methods, and risk assessments of CBTC systems, comparable functional subsystem definitions are proposed for AV fleets in driverless operation. With the prospect of multiple AV fleets operating within a single automated mobility district, the criticality of protecting roadway junctions requires an approach like that of automated fixed-guideway transit systems, in which a guideway switch zone “interlocking” at each junction location deconflicts railway traffic, affirming safe passage.
Technical Paper

It Takes a Village: A Case Study of Business Development and Innovation in a UAS/AUS Ecosystem to Address Critical Industry Challenges

Entrepreneurial innovation that spurs economic development requires a collaborative cluster of cooperative effort, across a diverse ecosystem of partners. Literature provides resounding evidence to support the notion that an innovative, entrepreneurial ecosystem is critical to both successful economic development and industry sector growth. The UAS/AUS industry sector is a fast-growing sector across the United States, with regional leadership demonstrated in North Dakota, California, North Carolina, New York, Oklahoma, Texas and New Mexico. This case study is focused on investigating how the North Dakota autonomous systems ecosystem continues to evolves and develop mechanisms and partnerships to address industry pain points, facilitate cutting edge research, ensure high-quality UAS/AUS testing, and support an adaptive business development pipeline across the entrepreneurial life cycle.
Research Report

Unsettled Issues Regarding Autonomous Vehicles and Open-source Software

Unsettled Issues Regarding Autonomous Vehicles and Open-source Software introduces the impact of software in advanced automotive applications, the role of open-source communities in accelerating innovation, and the important topic of safety and cybersecurity. As electronic functionality is captured in software and a bigger percentage of that software is open-source code, some critical challenges arise concerning security and validation.
Technical Paper

Vehicular Visual Sensor Blinding Detection by Integrating Variational Autoencoders with SVM

The advancements of autonomous vehicles or advanced driver assistance systems in terms of safety, driving experience, and comfort against manual driving results in extensive adoption of them across the modern automotive sector. The autonomous vehicles are equipped with numerous sensing and actuating components both inside as well as outside the vehicles to perceive the environment, perform path planning, and intelligently control the autonomous vehicles. The perception mechanism includes fused information of multiple sensors such as camera, RADAR, and LiDAR to effectively understand all the dynamic driving environments. Some of the intentional and unintentional mechanisms such as cyber-attacks and natural variations of the environment, etc., across the sensor's external interface with the environment cause the degradation of the perception mechanism.
Technical Paper

Implementation Methodologies for Simulation as a Service (SaaS) to Develop ADAS Applications

Over the years, the complexity of autonomous vehicle development (and concurrently the verification and validation) has grown tremendously in terms of component-, subsystem- and system-level interactions between autonomy and the human users. Simulation-based testing holds significant promise in helping to identify both problematic interactions between component-, subsystem-, and system-levels as well as overcoming delays typically introduced by the default full-scale on-road testing. Software in Loop (SiL) simulation is utilized as an intermediate step towards software deployment for autonomous vehicles (AV) to make them reliable. SiL efforts can help reduce the resources required for successful deployment by helping to validate the software for millions of road miles. A key enabler for accelerating SiL processes is the ability to use Simulation as a Service (SaaS) rather than just isolated instances of software.
Technical Paper

Adopting Aviation Safety Knowledge into the Discussions of Safe Implementation of Connected and Autonomous Road Vehicles

The development of connected and autonomous vehicles (CAVs) is progressing fast. Yet, safety and standardization-related discussions are limited due to the recent nature of the sector. Despite the effort that is initiated to kick-start the study, awareness among practitioners is still low. Hence, further effort is required to stimulate this discussion. Among the available works on CAV safety, some of them take inspiration from the aviation sector that has strict safety regulations. The underlying reason is the experience that has been gained over the decades. However, the literature still lacks a thorough association between automation in aviation and the CAV from the safety perspective. As such, this paper motivates the adoption of safe-automation knowledge from aviation to facilitate safer CAV systems.
Technical Paper

Technical Trends of the Intelligent Connected Vehicle and Development Stage Division for Freeway Traffic Control

It is deemed that currently the intelligent connected vehicle (ICV) is in its early stage of development, and it will go through multiple development stages in the future to realize its final goal—autonomous driving. Based on the existing ICV researches, this paper believes that ICV can be used to improve the efficiency and safety of freeway. The current research of ICV has two main directions: one focuses on the traffic flow characteristics of vehicles with different attributes, the other is concerned with using ICV to reduce congestion. From the policies issued by countries around the world and the development plans promoted by major vehicle manufacturers, the future development trends and challenges of ICV are analyzed. ICV must overcome all the shortcomings to achieve its final goal, including insufficient hardware capabilities or excessive cost, and the degree of intelligence that needs to be improved.
Technical Paper

Service Analysis of Autonomous Driving

Autonomous driving represents the ultimate goal of future automobile development. As a collaborative application that integrates vehicles, road infrastructure, network and cloud, autonomous driving business requires a high-degree dynamic cooperation among multiple resources such as data, computing and communications that are distributed throughout the system. In order to meet the anticipated high demand for resources and performance requirements of autonomous driving, and to ensure the safety and comfort of the vehicle users and pedestrians, a top concern of autonomous driving is to understand the system requirements for resources and conduct an in-depth analysis of the autonomous driving business. In this context, this paper presents a comprehensive analysis of the typical business for autonomous driving and establishes an analysis model for five common capabilities, i.e. collection, transmission, intelligent computing, human-machine interaction (HMI), and security.
Research Report

Unsettled Topics Concerning Human and Autonomous Vehicle Interaction

This report examines the current interaction points between humans and autonomous systems, with a particular focus on advanced driver assistance systems (ADAS), the requirements for human-machine interfaces as imposed by human perception, and finally, the progress being made to close the gap. Autonomous technology has the potential to benefit personal transportation, last-mile delivery, logistics, and many other mobility applications enormously. In many of these applications, the mobility infrastructure is a shared resource in which all the players must cooperate. In fact, the driving task has been described as a “tango” where we—as humans—cooperate naturally to enable a robust transportation system. Can autonomous systems participate in this tango? Does that even make sense? And if so, how do we make it happen? Click here to access the full SAE EDGETM Research Report portfolio.
Research Report

Unsettled Topics Concerning Autonomous Public Transportation Systems

With billions of dollars of investment and events like DARPA’s Grand Challenges automated driving technology has been making its way toward commercialization. While the enabling technology for SAE Level 4 and 5 automated vehicles (AV) has not yet matured, specific restricted-use models such as “robo-taxis” and automated truck convoying show great promise. Now, cities are across the world are looking to AVs to solve their public transportation issues. With low speeds and fixed route, public transportation is an ideal application for AVs. From a business angle, AVs could leverage existing public transport models and infrastructure while providing superior quality of service for disadvantaged communities. Yet, dense urban environments—which would benefit from automated transportation the most—present unique challenges and public sector requirements. This SAE EDGE™ Research Report by Dr.
Journal Article

A Novel Assessment and Administration Method of Autonomous Vehicle

As a promising strategic industry group that is rapidly evolving around the world, autonomous vehicle is entering a critical phase of commercialization from demonstration to end markets. The global automotive industry and governments are facing new common topics and challenges brought by autonomous vehicle, such as how to test, assess, and administrate the autonomous vehicle to ensure their safe running in real traffic situations and proper interactions with other road users. Starting from the facts that the way to autonomous driving is the process of a robot or a machine taking over driving tasks from a human. This paper summarizes the main characteristics of autonomous vehicle which are different from traditional one, then demonstrates the limitations of the existing certification mechanism and related testing methods when applied to autonomous vehicle.
Technical Paper

Secure Vehicular Communication Using Blockchain Technology

Also, all the existing methods for vehicular communication rely on a centralized server which itself invite massive cyber-security threats. These threats and challenges can be addressed by using the Blockchain (BC) technology, where each transaction is logged in a decentralized immutable BC ledger.
Technical Paper

A Safety and Security Testbed for Assured Autonomy in Vehicles

Connectivity and autonomy in vehicles promise improved efficiency, safety and comfort. The increasing use of embedded systems and the cyber element bring with them many challenges regarding cyberattacks which can seriously compromise driver and passenger safety. Beyond penetration testing, assessment of the security vulnerabilities of a component must be done through the design phase of its life cycle. This paper describes the development of a benchtop testbed which allows for the assurance of safety and security of components with all capabilities from Model-in-loop to Software-in-loop to Hardware-in-loop testing. Environment simulation is obtained using the AV simulator, CARLA which provides realistic scenarios and sensor information such as Radar, Lidar etc. MATLAB runs the vehicle, powertrain and control models of the vehicle allowing for the implementation and testing of customized models and algorithms.
Research Report

Unsettled Topics Concerning Automated Driving Systems and the Development Ecosystem

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.”
Research Report

Unsettled Impacts of Integrating Automated Electric Vehicles into a Mobility-as-a-Service Ecosystem and Effects on Traditional Transportation and Ownership

The current business model of the automotive industry is based on individual car ownership, yet new ridesharing companies such as Uber and Lyft are well capitalized to invest in large, commercially operated, on-demand mobility service vehicle fleets. Car manufacturers like Tesla want to incorporate personal car owners into part-time fleet operation by utilizing the company’s fleet service. These robotaxi fleets can be operated profitably when the technology works in a reliable manner and regulators allow driverless operation. Although Mobility-as-a-Service (MaaS) models of private and commercial vehicle fleets can complement public transportation models, they may contribute to lower public transportation ridership and thus higher subsidies per ride. This can lead to inefficiencies in the utilization of existing public transportation infrastructure.
Research Report

Unsettled Topics Concerning Automated Driving Systems and the Transportation Ecosystem

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.
Research Report

Unsettled Technology Areas in Autonomous Vehicle Test and Validation

Automated driving system (ADS) technology and ADS-enabled/operated vehicles - commonly referred to as automated vehicles and autonomous vehicles (AVs) - have the potential to impact the world as significantly as the internal combustion engine. Successful ADS technologies could fundamentally transform the automotive industry, civil planning, the energy sector, and more. Rapid progress is being made in artificial intelligence (AI), which sits at the core of and forms the basis of ADS platforms. Consequently, autonomous capabilities such as those afforded by advanced driver assistance systems (ADAS) and other automation solutions are increasingly becoming available in the marketplace. To achieve highly or fully automated or autonomous capabilities, a major leap forward in the validation of these ADS technologies is required. Without this critical cog, helping to ensure the safety and reliability of these systems and platforms, the full capabilities of ADS technology will not be realized.
Technical Paper

Intelligent Vehicle Monitoring for Safety and Security

The caveat to these additional capabilities is issues like cybersecurity, complexity, etc. This paper is an exploration into FuSa and CAVs and will present a systematic approach to understand challenges and propose potential framework, Intelligent Vehicle Monitoring for Safety and Security (IVMSS) to handle faults/malfunctions in CAVs, and specifically autonomous systems.