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Registration - WCX™ World Congress Experience

2024-07-14
Count on SAE International®—the global leader in technical learning for mobility professionals—to deliver emerging research, consumer metrics, regulatory standards and the latest innovations to advance mobility at the WCX World Congress event.
Event

Digital Summit - WCX™ World Congress Experience

2024-07-14
If you are not able to attend WCX 2022 in-person, you will have the opportunity to join a selected number of live technical and executive discussions online that will advance your skill set in propulsion, connectivity security and safety as well as the business of technology.

SAE EDGE™ Research Reports - Publications

2024-07-14
SAE EDGE Research Reports provide examinations significant topics facing mobility industry today including Connected Automated Vehicle Technologies Electrification Advanced Manufacturing
Training / Education

The Nature of Automated Vehicle Safety Will SAE Level 5 Ever Be Achieved?

The automated vehicle industry has been busy designing, developing, and deploying several self driving vehicles and services in the last few years. However, much of the outcomes and the overall outlook of the vehicle and services, such as robotaxis, are not great. Customers and stakeholders complain that the level of automation is low, mostly SAE Levels 1, 2, and very little of Level 3. It appears that Level 4 is far out in the horizon and many wonder if Level 5 is actually achievable.
Student

AutoDrive Challenge

2024-07-14
SAE International and General Motors have partnered to headline sponsor AutoDrive Challenge™, the latest of SAE International’s Collegiate Design Series.
Technical Paper

Securing Connected Vehicles End to End

2014-04-01
2014-01-0300
As vehicles become increasingly connected with the external world, they face a growing range of security vulnerabilities. Researchers, hobbyists, and hackers have compromised security keys used by vehicles' electronic control units (ECUs), modified ECU software, and hacked wireless transmissions from vehicle key fobs and tire monitoring sensors. Malware can infect vehicles through Internet connectivity, onboard diagnostic interfaces, devices tethered wirelessly or physically to the vehicle, malware-infected aftermarket devices or spare parts, and onboard Wi-Fi hotspot. Once vehicles are interconnected, compromised vehicles can also be used to attack the connected transportation system and other vehicles. Securing connected vehicles impose a range of unique new challenges. This paper describes some of these unique challenges and presents an end-to-end cloud-assisted connected vehicle security framework that can address these challenges.
Journal Article

Exploiting Channel Distortion for Transmitter Identification for In-Vehicle Network Security

2020-08-18
Abstract Cyberattacks on financial and government institutions, critical infrastructure, voting systems, businesses, modern vehicles, and so on are on the rise. Fully connected autonomous vehicles are more vulnerable than ever to hacking and data theft. This is due to the fact that the industry still relies on controller area network (CAN) protocol for in-vehicle control networks. The CAN protocol lacks basic security features such as message authentication, which makes it vulnerable to a wide range of attacks including spoofing attacks. This article presents a novel method to protect CAN protocol against packet spoofing, replay, and denial of service (DoS) attacks. The proposed method exploits physical uncolonable attributes in the physical channel between transmitting and destination nodes and uses them for linking the received packet to the source.
Technical Paper

Trust-Based Control and Scheduling for UGV Platoon under Cyber Attacks

2019-04-02
2019-01-1077
Unmanned ground vehicles (UGVs) may encounter difficulties accommodating environmental uncertainties and system degradations during harsh conditions. However, human experience and onboard intelligence can may help mitigate such cases. Unfortunately, human operators have cognition limits when directly supervising multiple UGVs. Ideally, an automated decision aid can be designed that empowers the human operator to supervise the UGVs. In this paper, we consider a connected UGV platoon under cyber attacks that may disrupt safety and degrade performance. An observer-based resilient control strategy is designed to mitigate the effects of vehicle-to-vehicle (V2V) cyber attacks. In addition, each UGV generates both internal and external evaluations based on the platoons performance metrics. A cloud-based trust-based information management system collects these evaluations to detect abnormal UGV platoon behaviors.
Journal Article

Cyberattacks and Countermeasures for Intelligent and Connected Vehicles

2019-10-14
Abstract ICVs are expected to make the transportation safer, cleaner, and more comfortable in the near future. However, the trend of connectivity has greatly increased the attack surfaces of vehicles, which makes in-vehicle networks more vulnerable to cyberattacks which then causes serious security and safety issues. In this article, we therefore systematically analyzed cyberattacks and corresponding countermeasures for in-vehicle networks of intelligent and connected vehicles (ICVs). Firstly, we analyzed the security risk of ICVs and proposed an in-vehicle network model from a hierarchical point of view. Then, we discussed possible cyberattacks at each layer of proposed network model.
Journal Article

A Novel Assessment and Administration Method of Autonomous Vehicle

2020-04-14
2020-01-0708
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.
Magazine

Autonomous Vehicle Engineering: July 2020

2020-07-02
Editorial High noon for high-level autonomy The Navigator A fork in the road for the AV business The Electric, Autonomous Revolution Lifts Off Engineering the new generation of electric and hybrid vertical-take-off-and-landing vehicles at Wisk and Elroy Air. New SAE Standard for Automated-Driving Developers Developed in less than a year, SAE's new J3216 standard will impact traffic management, operations and safety for automated mobility. Making Data Logging, Replay and Prototyping More Efficient High levels of continuity and compatibility are vital to avoid interruptions in the development process - and reduce cost. Radar Death Star ELunewave's 3D-printed spherical antenna makes for fast, 360-degree single-snapshot readings that are claimed to beat the slower sweeps of conventional radar. The Case for FOTA in AV Data Security Firmware over-the-air data transmission helps OEMs drive secure vehicle autonomy.
Technical Paper

Integrating Fuzz Testing into a CI Pipeline for Automotive Systems

2022-03-29
2022-01-0117
With the rapid development of connected and autonomous vehicles, more sophisticated automotive systems running large portions of software and implementing a variety of communication interfaces are being developed. The ever-expanding codebase increases the risk for software vulnerabilities, while at the same time the large number of communication interfaces make the systems more susceptible to be targeted by attackers. As such, it is of utmost importance for automotive organizations to identify potential vulnerabilities early and continuously in the development lifecycle in an automated manner. In this paper, we suggest a practical approach for integrating fuzz testing into a Continuous Integration (CI) pipeline for automotive systems. As a first step, we have performed a Threat Analysis and Risk Assessment (TARA) of a general E/E architecture to identify high-risk interfaces and functions.
Technical Paper

Access Control Requirements for Autonomous Robotic Fleets

2023-04-11
2023-01-0104
Access control enforces security policies for controlling critical resources. For V2X (Vehicle to Everything) autonomous military vehicle fleets, network middleware systems such as ROS (Robotic Operating System) expose system resources through networked publisher/subscriber and client/server paradigms. Without proper access control, these systems are vulnerable to attacks from compromised network nodes, which may perform data poisoning attacks, flood packets on a network, or attempt to gain lateral control of other resources. Access control for robotic middleware systems has been investigated in both ROS1 and ROS2. Still, these implementations do not have mechanisms for evaluating a policy's consistency and completeness or writing expressive policies for distributed fleets. We explore an RBAC (Role-Based Access Control) mechanism layered onto ROS environments that uses local permission caches with precomputed truth tables for fast policy evaluation.
Technical Paper

Evaluating Trajectory Privacy in Autonomous Vehicular Communications

2019-04-02
2019-01-0487
Autonomous vehicles might one day be able to implement privacy preserving driving patterns which humans may find too difficult to implement. In order to measure the difference between location privacy achieved by humans versus location privacy achieved by autonomous vehicles, this paper measures privacy as trajectory anonymity, as opposed to single location privacy or continuous privacy. This paper evaluates how trajectory privacy for randomized driving patterns could be twice as effective for autonomous vehicles using diverted paths compared to Google Map API generated shortest paths. The result shows vehicles mobility patterns could impact trajectory and location privacy. Moreover, the results show that the proposed metric outperforms both K-anonymity and KDT-anonymity.
Technical Paper

Service Analysis of Autonomous Driving

2020-12-30
2020-01-5194
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 Legal Issues Facing Data in Autonomous, Connected, Electric, and Shared Vehicles

2021-09-13
EPR2021019
Modern automobiles collect around 25 gigabytes of data per hour and autonomous vehicles are expected to generate more than 100 times that number. In comparison, the Apollo Guidance Computer assisting in the moon launches had only a 32-kilobtye hard disk. Without question, the breadth of in-vehicle data has opened new possibilities and challenges. The potential for accessing this data has led many entrepreneurs to claim that data is more valuable than even the vehicle itself. These intrepid data-miners seek to explore business opportunities in predictive maintenance, pay-as-you-drive features, and infrastructure services. Yet, the use of data comes with inherent challenges: accessibility, ownership, security, and privacy. Unsettled Legal Issues Facing Data in Autonomous, Connected, Electric, and Shared Vehicles examines some of the pressing questions on the minds of both industry and consumers. Who owns the data and how can it be used?
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