TY - CHAP
T1 - Identification of Operational Design Domain for Autonomous Truck Mounted Attenuator System on Multilane Highways
AU - Tang, Qing
AU - Hu, Xianbiao
AU - Yang, Hong
N1 - Funding Information:
The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This material is based on work supported by the Colorado DOT, and the AMT pool fund under the award number 5380-19-03, as well as U.S. DOT through Mid-America Transportation Center, under the contract number 69A3551747107.
Publisher Copyright:
© SAGE Publications Ltd. All rights reserved.
PY - 2022/12
Y1 - 2022/12
N2 - 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.
AB - 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.
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U2 - 10.1177/03611981211061555
DO - 10.1177/03611981211061555
M3 - Chapter
AN - SCOPUS:85144596535
T3 - Transportation Research Record
SP - 1
EP - 15
BT - Transportation Research Record
PB - SAGE Publications Ltd
ER -