Truck travel characteristics as an indicator of system condition and performance : [technical summary].
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Truck travel characteristics as an indicator of system condition and performance : [technical summary].

Filetype[PDF-588.23 KB]


English
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  • Alternative Title:
    Joint Transportation Research Program Technical Report Series : Civil Engineering
  • Creators:
    Sinha, Kumares C.
  • Corporate Creators:
    Purdue University. Joint Transportation Research Program
  • Corporate Contributors:
    Indiana Department of Transportation
  • Subject/TRT Terms:
  • Resource Type:
    Tech Report
  • Geographical Coverage:
    Indiana
  • Edition:
    Technical summary.
  • Corporate Publisher:
    Purdue University. Joint Transportation Research Program
  • Abstract:
    Truck traffic has significantly increased in past decades. The effect of trucks on the level of service is determined by considering passenger car equivalents (PCE) of trucks. The Highway Capacity Manual (HCM) uses a single PCE value for all tucks combined. However, the composition of truck traffic varies from location to location; therefore a single PCE-value for all trucks may not correctly represent the impact of truck traffic at specific locations. Consequently, the Indiana Department of Transportation (INDOT) wanted to develop separate PCE values for single-unit and combination trucks to replace the single value provided by the HCM. Traditionally, equivalent delay and microscopic simulations have been used to estimate PCE values. In order to facilitate the development of site specific PCE values, an alternative PCE-estimation methodology was explored in the present study on the basis of lagging headways measured from real traffic data. Lagging headway, defined as the distance from the rear bumper of a leading vehicle to the rear bumper of the following vehicle, is the actual space a vehicle consumes while in the traffic stream. The study used data from four locations on a single urban freeway and three different rural freeways in Indiana. Three-stage-least-squares (3SLS) regression techniques were used to estimate models that predict lagging headways for passenger cars, single-unit and combination trucks. The models were then expanded to predict lagging headways for each of nine vehicle-following combinations which were used to predict class average lagging headways. After determining lagging headways by vehicle class, the PCE values were calculated as the ratio of the lagging headway of each truck class to that of passenger cars.
  • Format:
    PDF
  • Funding:
    SPR-3229
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