phase I.

Details

• Creators:
  Druta, Cristian ; Alden, Andrew S.
• Corporate Creators:
  Virginia Tech Transportation Institute
• Contributors:
  Guevara, Gabriel
• Corporate Contributors:
  United States. Federal Highway Administration ; United States. Department of Transportation. Intelligent Transportation Systems Joint Program Office
• Subject/TRT Terms:
  Connected Vehicle In Vehicle Sensors Pavement Friction Risk Assessment Rotational Displacement Slipperiness Traction Weather Conditions Wheel Sensor Pulse Wheel Slip Winter Maintenance

  More +
• Publication/ Report Number:
  FHWA-JPO-16-359
• Resource Type:
  Tech Report
• Geographical Coverage:
  United States;Virginia
• Edition:
  Final report
• Corporate Publisher:
  United States. Department of Transportation. Intelligent Transportation Systems Joint Program Office
• Abstract:
  Real-time assessment of road surface conditions can be used to provide valuable safety information to travelers when roads are slippery (e.g.,
  
  contaminated roads, heavy rain, black ice, etc.). Identification of these hazardous surface conditions using onboard vehicle sensors will warn drivers to
  
  proceed with caution on compromised road sections, thus reducing the risks of crashes. This information may also be used to provide data on roadway
  
  deficiencies such as winter weather impacts and wear loss of surface friction to highway agencies resulting in more efficient and less costly
  
  maintenance operations.
  
  The main objective of this study was to establish a real-time relationship between certain variables collected by vehicle onboard sensors and the
  
  roadway surface conditions. It is hypothesized that the relative difference in rotation between the driven and nondriven wheels may be used to assess
  
  pavement surface condition, and thus, traction.
  
  Front- and rear-wheel drive vehicles were tested to determine the relative rotational displacements of driven and nondriven wheels under dry, wet,
  
  snowy/slushy, and icy road surface conditions. These variables, among others, were supplied by the factory-installed wheel-speed sensors utilized by
  
  the vehicle’s Anti-lock Braking System (ABS). The rear-wheel drive vehicle was driven over two pavement sections of different grades and lengths to
  
  compare results. The front-wheel drive vehicle was driven on a single pavement section at the Virginia Tech Transportation Institute’s Smart Road
  
  facility. Both vehicles were driven under controlled conditions of constant speed, minimal steering, no braking, and with monitoring of onboard safety
  
  systems (e.g., ABS, stability control) as potential confounds. Time and position data were collected from a Differential Global Positioning System
  
  (DGPS) installed in the vehicles. All these data were employed to calculate total distances traveled by the vehicles as well as ratios between distances
  
  traveled by driven and nondriven wheels in order to distinguish between different pavement surface conditions.
  
  The results of experimentation with multiple test runs conducted on roads conditions ranging from dry to icy showed a small but statistically discernable
  
  difference in the relative rotational displacement of driven versus nondriven wheels. Changes in the observed rotation ratios were clearly associated
  
  with pavement conditions known to produce poor traction (e.g., icy, slightly wet and dirty). That is, tests performed on slippery roads resulted in an
  
  increased change in the driven versus nondriven wheel rotational rates. Of the surface condition scenarios tested, icy, and slightly wet and dirty, and
  
  certain snow-covered pavement provided the least traction while clean dry, moderately wet, and other snow-covered pavement conditions provided
  
  better traction.
  
  
• Format:
  PDF
• Funding:
  DTFH61-13-P-00017
• Collection(s):
  Federal Highway Administration US Transportation Collection
• Main Document Checksum:
  urn:sha-512:7f6f47da91f3b29b90c924a3718534ac8deb37dd77d84092dd6917b84c91cc52bf4abf0b6a3dc14572a8549aadcbf34e6667b434daa095712229bfbb7f19983a
• Download URL:
  https://rosap.ntl.bts.gov/view/dot/32155/dot_32155_DS1.pdf
• File Type:
  [PDF - 2.25 MB ]