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Technical Paper

A Safety and Security Testbed for Assured Autonomy in Vehicles

2020-04-14
2020-01-1291
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.
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

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

2021-04-06
2021-01-0116
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.
Journal Article

Improvement of the Resilience of a Cyber-Physical Remote Diagnostic Communication System against Cyber Attacks

2019-04-02
2019-01-0112
In the near future, vehicles will operate autonomously and communicate with their environment. This communication includes Vehicle-to-Vehicle (V2V), Vehicle-to-Infrastructure (V2I) communication, and comunication with cloud-based servers (V2C). To improve the resilience of remote diagnostic communication between a vehicle and external test equipment against cyberattacks, it is imperative to understand and analyze the functionality and vulnerability of each communication system component, including the wired and wireless communication channels. This paper serves as a continuation of the SAE Journal publication on measures to prevent unauthorized access to the in-vehicle E/E system [9], explains the components of a cyber-physical system (CPS) for remote diagnostic communication, analyzes their vulnerability against cyberattacks and explains measures to improve the resiliance.
Technical Paper

Streamlined Process for Cloud Based Diagnostics Using Amazon Web Services

2021-04-06
2021-01-0159
In the age of 5G, the cloud constitutes a massive computational resource. Such capability is greatly underutilized, especially for the purpose of vehicle diagnostics and prognostics. Diagnostics and prognostics run mostly in the limited and cost sensitive electronic module of the vehicle. Utilizing vehicle connectivity, along with the massive capability of the cloud would allow the deployment of smarter algorithms that provide improved vehicle performance and operation management. In this paper, a streamlined process to develop and deploy off-board diagnostics is presented. The process included developing multiphysics digital twins and running the diagnostics off-board. It was demonstrated on a fleet of virtual Hybrid Electric Vehicles (HEV). The Digital Twin replica was created using Simulink® and Simscape®. The microcontroller used to demonstrate the diagnostic is a Raspberry Pi hardware running in real time.
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