Enhancing Pavement-Encoded Signages for Precise Driving Automation [Supporting Dataset]

Details

• Creators:
  Sakulneya, Apidej ; Liu, Pengyuan ; Hsiao, Chun-Chien ; Talebpour, Alireza ; Roesler, Jeffery
• Corporate Creators:
  Illinois Center for Transportation
• Corporate Contributors:
  Center for Connected and Automated Transportation (CCAT) ; United States. Department of Transportation. University Transportation Centers (UTC) Program ; United States. Department of Transportation. Office of the Assistant Secretary for Research and Technology
• Subject/TRT Terms:
  Autonomous Vehicles Construction Sites Data Intelligent Vehicles Pavement Management Systems Road Marking Materials Rural Areas Testing Weather Work Zone Safety
• DOI:
  https://doi.org/10.21949/6728-cv12
• Resource Type:
  Dataset
• Right Statement:
  Public Domain
• Geographical Coverage:
  United States
• Corporate Publisher:
  University of Michigan. Center for Connected and Automated Transportation ; Illinois Center for Transportation
• Abstract:
  A field study was developed combining an automated driving system (ADS) vehicle and magnetometer-based sensing system to test the detectability, repeatability, and reliability of pavement encoded electromagnetic (EM) strips placed on the surface of concrete and asphalt pavement. The objective was to define the EM strips’ patterns, lateral vehicle position, and speed accuracy at several vehicle speeds (15 to 55 mph) and weather conditions on a closed traffic concrete pad and a low-volume rural road. The closed area concrete pad consisted of two test segments that evaluated construction work zone warning patterns, lane shifting, lateral vehicle position, vehicle speed, and unsignalized intersection stop warning pattern with the ADS vehicle testing conducted between 25 and 55 mph. The second test section on a rural road placed 36 longitudinal EM strips spaced at 15 and 20 ft on a tangent and horizontal curve, respectively. The vehicle traversed this section in several weather conditions (normal, snow, ice) and compared its lateral position and speed to a camera-based ground truth measure and GPS speed indicator. The refined signal-processing algorithms enabled reliable and repeatable detection of the EM strips when the minimum signal threshold was set to 30 nT/ms. To minimize the effects of electromagnetic interference from the ADS vehicle, two bandpass filtering configurations were employed successfully with 15–55 Hz for < 35 mph and 20–80 Hz for > 35 mph along with a notch filter at 60Hz to remove adjacent powerline noise. A noise rejection framework was deployed based on top-row sensor coincidence screening, which filtered out disturbances from embedded ferromagnetic elements in or near the pavement. With the V2I EM strips, sensors, and filtering system refined, more than 90% of the EM strips were detected in all weather conditions. For the rural road section, the mean lateral position accuracy varied between 1.3 to 2.6 in. for all weather conditions, while the difference in calculated and GPS speed was < 1 mph. The new signal-processing enhancements and testing at various speeds confirmed the V2I system is detectable, interpretable, and repeatable, which can now lead to additional V2I testing in more complex testing configurations and sites.
• Content Notes:
  This item is made available under the terms of Public Access. Use the following citation: Sakulneya, A, Liu, P., Hsiao, C.-C., Talebpour, A., & Roesler, J. (2026). Enhancing pavement-encoded signages for precise driving automation. Illinois Center for Transportation. https://doi.org/10.21949/6728-cv12
• Format:
  ZIP
• Funding:
  69A3552344812 ; 69A3552348317
• Collection(s):
  US Transportation Collection
• Main Document Checksum:
  urn:sha-512:4beee81c727e1e4a56bd079536f83e353e85c45d025afa45a814f3dcac48b5f496098721b10873920a82a04f41432828e4d470ef52151a5c0588e8f262f87df9
• Download URL:
  https://rosap.ntl.bts.gov/view/dot/92528/dot_92528_DS1.json
• File Type:
  [JSON - 6.17 KB ]