Identification of Operational Design Domain for Autonomous Truck Mounted Attenuator System on Multilane Highways

Qing Tang, Xianbiao Hu, Hong Yang

Research output: Chapter in Book/Report/Conference proceedingChapter

4 Scopus citations

Abstract

The Autonomous Truck Mounted Attenuator (ATMA) vehicle system is a technology that leverages connected and automated vehicle (CAV) capabilities for maintenance of transportation infrastructure. Promoted by FHWA and state departments of transportation (DOTs), it is a niche CAV application in leader–follower style, intended to remove DOT workers from the following maintenance truck, to reduce fatalities in work zones. Because practicable guidance for deployment of this technology is largely missing in MUTCD, state DOTs have been making their own deployment criteria. In this manuscript, we focus on the operational design domain (ODD) problem—under what traffic conditions should ATMA be deployed. Modeling efforts are first focused on the derivation of an effective discharge rate that can be associated with a moving bottleneck caused by slow-moving ATMA vehicles on a multilane highway. Then, based on the demand input and discharge rates, microscopic traffic flow models calculate vehicle delay and density, which the Highway Capacity Manual (HCM) suggests are key indicators of a multilane highway’s level of service (LOS). In this way, the linkage between AADT and LOS is analytically established. NGSIM data is used for the model validation and shows that the developed model correctly captures the effective discharge rate discount caused by moving bottlenecks. The modeling results demonstrate that roadway performance is sensitive to the K factor and D factor, as well as the operating speed of ATMA and, if LOS = C is a desirable design objective, a good AADT threshold to use would be around 40,000 vehicles per day.

Original languageEnglish (US)
Title of host publicationTransportation Research Record
PublisherSAGE Publications Ltd
Pages1-15
Number of pages15
Volume2676
Edition12
DOIs
StatePublished - Dec 2022

All Science Journal Classification (ASJC) codes

  • Civil and Structural Engineering
  • Mechanical Engineering

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