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While some players’ valuations collapsed, 2022 overall wasn’t all bad as some companies expanded their driverless enterprises.

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.

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.

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.

Do you know what personal protective equipment (PPE), tools, and instruments are needed to keep you safe around high voltage (HV) vehicles? Are you aware of how to protect yourself or your employees when working around high voltage systems and platforms? Safety is paramount when working around any type of high voltage. As electric vehicles (EV) and EV fleets become more prevalent, the critical need for OEMs, suppliers, companies, and organizations to provide comprehensive safety training for teams working with or around xEV systems and platforms increases.

SAE International and General Motors have partnered to headline sponsor AutoDrive Challenge™, the latest of SAE International’s Collegiate Design Series.

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.

On-road vehicles equipped with driving automation features—where a human might not be needed for operation on-board—are entering the mainstream public space. However, questions like “How safe is safe enough?” and “What to do if the system fails?” persist. This is where remote operation comes in, which is an additional layer to the automated driving system where a human remotely assists the so-called “driverless” vehicle in certain situations. Such remote-operation solutions introduce additional challenges and potential risks as the entire vehicle-network-human now needs to work together safely, effectively, and practically. Unsettled Issues in Remote Operation for On-road Driving Automation highlights technical questions (e.g., network latency, bandwidth, cyber security) and human aspects (e.g., workload, attentiveness, situational awareness) of remote operation and introduces evolving solutions.

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.

Ransomware is not a new method of malware infection. This historically had been experienced in the enterprise in nearly every industry. This has been especially problematic in the medical and manufacturing fields. As the attackers saturate the specifically targeted industries, the attackers will expand their target industries. One of these which has not been significantly explored by the ransomware groups are the embedded systems and automobile environment. This set of targets is massive and provides for a vast attack potential. While this has not experienced this attack methodology at length, the research and efforts are creeping towards this as a natural extension of the business. The research focusses on the history of ransomware, uses in the enterprise, possible attack vectors with ground vehicles, and defenses to be explored and implemented to secure automobiles, fleets, and the industries.

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.

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.

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.

With the rapid development of vehicle intelligent and networking technology, the IT security of automotive systems becomes an important area of research. In addition to the basic vehicle control, intelligent advanced driver assistance systems, infotainment systems will all exchange data with in-vehicle network. Unfortunately, current communication network protocols, including Controller Area Network (CAN), FlexRay, MOST, and LIN have no security services, such as authentication or encryption, etc. Therefore, the vehicle are unprotected against malicious attacks. Since CAN bus is actually the most widely used field bus for in-vehicle communications in current automobiles, the security aspects of CAN bus is focused on. Based on the analysis of the current research status of CAN bus network security, this paper summarizes the CAN bus potential security vulnerabilities and the attack means.

This paper is the second in the series of documents designed to record the progress of a series of SAE documents - SAE J2836™, J2847, J2931, & J2953 - within the Plug-In Electric Vehicle (PEV) Communication Task Force. This follows the initial paper number 2010-01-0837, and continues with the test and modeling of the various PLC types for utility programs described in J2836/1™ & J2847/1. This also extends the communication to an off-board charger, described in J2836/2™ & J2847/2 and includes reverse energy flow described in J2836/3™ and J2847/3. The initial versions of J2836/1™ and J2847/1 were published early 2010. J2847/1 has now been re-opened to include updates from comments from the National Institute of Standards Technology (NIST) Smart Grid Interoperability Panel (SGIP), Smart Grid Architectural Committee (SGAC) and Cyber Security Working Group committee (SCWG).

Facial recognition software (FRS) is a form of biometric security that detects a face, analyzes it, converts it to data, and then matches it with images in a database. This technology is currently being used in vehicles for safety and convenience features, such as detecting driver fatigue, ensuring ride share drivers are wearing a face covering, or unlocking the vehicle. Public transportation hubs can also use FRS to identify missing persons, intercept domestic terrorism, deter theft, and achieve other security initiatives. However, biometric data is sensitive and there are numerous remaining questions about how to implement and regulate FRS in a way that maximizes its safety and security potential while simultaneously ensuring individual’s right to privacy, data security, and technology-based equality.