Analysis and Simulation of PNT Threats and Risks to HATS
Highly automated vehicles (HAVs), whether ground, aerial, or maritime, rely on a steady stream of signals and information from external sources: signals that localize the vehicle and provide information about the road network, other nearby vehicles, larger-scale traffic, and state of the infrastructure and the environment. Currently, many deployed systems either trust the information implicitly, or at best perform basic sanity and consistency checks leading to little more than enabling or disabling the entire system. This includes a heavy reliance on PNT as location and timing information is central to many HAV operations. The potential impacts of radio frequency (RF) jamming and spoofing, interference with PNT sensor data, or interference with PNT augmentation or correction communications, on HAV functions are not thoroughly investigated, but they could wreak havoc in HAVs or result in passenger fatalities. ++++++++++ In this project, thorough risk identification, threat assessment, and risk analysis studies will be conducted at the component, subsystem, and system level to understand the impact of interference on HAVs using risk and failure analysis methodologies and modeling and simulation tools. Initially, an approach like Attack Trees and Attack Modes and Effect Analysis will be adopted for qualitative analysis of different PNT threats for HAV operations. Later, the quantification of threats and risks will be done by integrating the simulation models of PNT features with HAV functionalities. These functionalities include maneuvers limited to individual or multiple HAVs where V2X may play an important role. Academically available simulation tools will be used to evaluate the PNT concerns in HAV operation. This effort would involve PNT modeling for the PVT information required. An evaluation of safety and functional impacts will be conducted for intentional and unintentional PNT interference. ++++++++++ (Task 2.1) Analysis and Simulation of Initial PNT Threats and Risks: Redmill ---- The study team has selected several PNT threat scenarios for initial analysis: (i) GPS spoofing, (ii) multi-sensor fusion, (iii) sensor based obstacle localization, (iv) faulty PNT information from other connected HAVs, and (v) false map update. The team will perform a risk and threat analysis to HAV functions for each threat, including simulation results and analysis of the level of risk and the effectiveness of identified HAV mitigation strategies. ++++++++++ (Task 2.2) Analysis and Simulation of Initial Motivating Scenarios: Redmill ---- The study team has selected several HAV operational scenarios for initial analysis: (i) passing behavior on rural highways; (ii) intersection safety; and (iii) multi unmanned aerial vehicle (UAV) takeoff, formation flying, and landing. The team will outline the identified PNT threats, risk methodology and threat assessment, and simulation analysis and results of the level of risk and the effectiveness of identified HAV mitigation strategies. ++++++++++ (Task 2.3) Scenario and Threat Risk Analysis based on Literature Review: Bhat ---- The results of the literature review of Project 1, along with simulation results and stakeholder feedback, will be used to select additional threats and scenarios for analysis. The study team will perform a risk and threat analysis to HAV functions for each threat, including simulation results and analysis of the level of risk and the effectiveness of identified HAV mitigation strategies. The team will outline the identified PNT threats, risk methodology and threat assessment, and simulation analysis and results of the level of risk and the effectiveness of identified HAV mitigation strategies. ++++++++++ (Task 4.3) PNT Cyber Security in HAVs: Ahmed ---- A standalone receiver is normally resistant against cyberattacks, but the moment it connects to a device, a local or remote computer in an HAV, the receiver and the information coming in to the receiver are exposed to vulnerability. Newer receivers may be interfaced with vehicular network protocol for over-the-air firmware update, log retrieval, or data access, and thus can be hijacked through the various levels of attack vectors targeting HAVs. To address the depth of these concerns, Threat Assessment and Risk Analysis (TARA) will be done using Attack Trees, Attacks Modes, and Effect Analysis. These methods can help to qualitatively analyze vulnerabilities. Next, simulation tools will be developed with integrated receiver, PNT, and HAV features to quantify the risk associated with each vulnerability. The simulation framework will be further used to generate recommendations for validation tests.
Language
- English
Project
- Status: Active
- Funding: $404250
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Contract Numbers:
69A3552047138
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Sponsor Organizations:
Office of the Assistant Secretary for Research and Technology
University Transportation Centers Program
Department of Transportation
Washington, DC United States 20590 -
Managing Organizations:
Center for Automated Vehicle Research with Multimodal AssurEd Navigation
Ohio State University
Columbus, OH United States 43210 -
Project Managers:
Dunn, Denise
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Performing Organizations:
Ohio State University Center for Automotive Research
930 Kinnear Road
Columbus, OH United States 43212 Austin, Texas United States Cincinatti, OH United States 45221 Irvine, CA United States -
Principal Investigators:
Redmill, Keith
Ahmed, Qadeer
Bhat, Chandra
Cohen, Kelly
Ozguner, Umit
Chen, Alfred
- Start Date: 20201101
- Expected Completion Date: 0
- Actual Completion Date: 0
- USDOT Program: University Transportation Centers
Subject/Index Terms
- TRT Terms: Autonomous vehicles; Computer security; Global Positioning System; Risk analysis; Satellite navigation systems; Trucks
- Subject Areas: Data and Information Technology; Highways; Safety and Human Factors; Vehicles and Equipment;
Filing Info
- Accession Number: 01850654
- Record Type: Research project
- Source Agency: Center for Automated Vehicle Research with Multimodal AssurEd Navigation
- Contract Numbers: 69A3552047138
- Files: UTC, RIP
- Created Date: Jun 29 2022 2:56PM