Multimodal In-Vehicle Sensor Fusion for Cyber-Secured Autonomous Navigation

Successful navigation of autonomous vehicles relies on positioning, navigation, and timing (PNT) services. Global Navigation Satellite Systems (GNSS), such as Global Positioning System (GPS) (USA), BeiDou/BDS (China), Galileo (Europe), GLONASS (Russia), IRNSS/NavIC (India), and QZSS (Japan), provide PNT services. However, GNSS signals are vulnerable to unintentional interference (e.g., jamming caused by walls and ceilings in garages and tunnels, and multipath issues due to high-rise buildings in urban areas) and deliberate cyber threats (e.g., jamming and spoofing of GNSS signals). Prior research shows that the use of multi-sensor fusion systems—i.e., GNSS with inertial measurement unit (IMU) and perception sensors (PS) (e.g., camera, LiDAR, RADAR)— could complement each other and correct the individual sensor output and determine reliable navigation solution under deliberate threats and GNSS-denied environments (e.g., GNSS outage and/or INS error accumulation issue and/or PS view obstruction). However, IMU and PS can only provide relative positioning and rely on GNSS for absolute positioning. Even advanced INS (GNSS+IMU) provide cm level accuracy; however, during GNSS outage, it could accumulate position error up to 3.80 meters in just 1 minute due to error accumulation of inertial sensors. Thus, the major research gap is to comprehensively identify and understand GNSS vulnerabilities in autonomous vehicles, investigate realistic attack modeling, detection, and develop cyber-resilient navigation solutions for GNSS-based navigation. The overarching research goal of this project is to understand the vulnerabilities of GNSS-based navigation, develop intelligent slow-drifting cyber-attacks, develop corresponding attack detection models, and devise cyber-resilient navigation solutions to enhance the GNSS-based navigation system. The research goal will be achieved through the following research objectives: (1) investigate and develop intelligent slow-drifting GNSS spoofing attacks by manipulating GNSS signal’s navigation data; (2) investigate and develop GNSS cyber-attack detection algorithms for slow-drifting GNSS spoofing attacks; and (3) develop a secure in-vehicle sensor fusion-based navigation module using deep fusion algorithms during a GNSS-denied environment. The outcomes of this project will be to implement and validate intelligent slow-drifting GNSS spoofing attack models using a GNSS receiver in both laboratory and real-world environments, evaluate GNSS cyber-attack detection algorithms against intelligent slow-drifting GNSS spoofing attacks through field testing, and demonstrate proof-of-concept of an in-vehicle sensor fusion-based cyber-resilient navigation solution in a controlled, real-world environment.

Language

  • English

Project

  • Status: Active
  • Funding: $236516
  • Contract Numbers:

    69A3552344812

    69A3552348317

  • Sponsor Organizations:

    Office of the Assistant Secretary for Research and Technology

    University Transportation Centers Program
    Department of Transportation
    Washington, DC  United States  20590

    University of Alabama, Tuscaloosa

    Department of Civil, Construction and Environmental Engineering
    P.O. Box 870205
    Tuscaloosa, AL  United States  35487-0205

    Clemson University

    College of Engineering and Science
    109 Riggs Hall, Box 340901
    Clemson, SC  United States  29631-0901
  • Managing Organizations:

    National Center for Transportation Cybersecurity and Resiliency (TraCR)

    Clemson University
    Clemson, SC  United States 

    University of Alabama, Tuscaloosa

    Department of Civil, Construction and Environmental Engineering
    P.O. Box 870205
    Tuscaloosa, AL  United States  35487-0205
  • Project Managers:

    Chowdhury, Mashrur

  • Performing Organizations:

    University of Alabama, Tuscaloosa

    Department of Civil, Construction and Environmental Engineering
    P.O. Box 870205
    Tuscaloosa, AL  United States  35487-0205

    Clemson University

    College of Engineering and Science
    109 Riggs Hall, Box 340901
    Clemson, SC  United States  29631-0901
  • Principal Investigators:

    Rahman, Mizanur

    Chowdhury, Mashrur

    Cheng, Long

  • Start Date: 20240101
  • Expected Completion Date: 20241231
  • Actual Completion Date: 0
  • USDOT Program: University Transportation Centers

Subject/Index Terms

Filing Info

  • Accession Number: 01907738
  • Record Type: Research project
  • Source Agency: National Center for Transportation Cybersecurity and Resiliency (TraCR)
  • Contract Numbers: 69A3552344812, 69A3552348317
  • Files: UTC, RIP
  • Created Date: Feb 9 2024 7:41PM