Road grade estimation for on-road vehicle emissions modeling using light detection and ranging data.
Vehicle-specific power (VSP) is useful for explaining a substantial portion of variability in real-world vehicle emissions, such as those measured with portable emissions monitoring systems (PEMS). VSP is a function of vehicle speed, acceleration, and road grade. Road grade is shown to significantly affect estimates of both VSP and of real-world emissions via sensitivity analysis and analysis of empirical data. However, road grade is difficult to measure reliably using PEMS. Therefore, alternative methods for estimating road grade were identified and compared. A preferred method for estimating road grade was explored in more detail based on light detection and ranging (LIDAR) data. The method includes buffering LIDAR data onto roadway maps using a geographic information system tool, defining segments of roadway based on criteria pertaining to vertical curvature, quantification of roadway elevations within the buffered segments, and estimation of road grade and banking by fitting a plane to each segment. Factors influencing errors in road grade estimates are discussed. The method was evaluated by application to selected interstate highways and comparison to design drawing data. The development and application of LIDAR-based road grade data are demonstrated via a case study using PEMS data collected in the Research Triangle Park, NC, area. LIDAR data are shown to be reliable and accurate for road grade estimation for vehicle emissions modeling.
Zhang
Kaishan
K
North Carolina State University, Department of Civil, Construction, and Environmental Engineering, Raleigh, NC 27695, USA. frey@eos.ncsu.edu
Frey
H Christopher
HC
D000393:Air Pollutants / Q000032:analysis*; D002245:Carbon Dioxide / Q000032:analysis; D002248:Carbon Monoxide / Q000032:analysis; D004784:Environmental Monitoring; D005742:Gasoline; D006838:Hydrocarbons / Q000032:analysis; D018986:Motor Vehicles; D009569:Nitric Oxide / Q000032:analysis; D001335:Vehicle Emissions / Q000032:analysis*
D000393:Air Pollutants; D005742:Gasoline; D006838:Hydrocarbons; D001335:Vehicle Emissions; D002245:Carbon Dioxide; D009569:Nitric Oxide; D002248:Carbon Monoxide