Macroeconomic Impacts of Automated Driving Systems in Long-Haul Trucking

Waschik, Robert; Friedman, Daniel; Taylor, Catherine; Boatner, Jasmine

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Macroeconomic Impacts of Automated Driving Systems in Long-Haul Trucking

2021-01-28
By Waschik, Robert ; Friedman, Daniel ; Taylor, Catherine

File Language:

English

Details

Creators:

Waschik, Robert ; Friedman, Daniel ; Taylor, Catherine ; Boatner, Jasmine
Corporate Creators:

John A. Volpe National Transportation Systems Center (U.S.) ; Victoria University. Centre of Policy Studies
Corporate Contributors:

United States. Department of Transportation. Intelligent Transportation Systems Joint Program Office
Subject/TRT Terms:
Publication/ Report Number:

DOT-VNTSC-FHWA-20-16;FHWA-JPO-21-847
Resource Type:

Tech Report
Geographical Coverage:

United States
Corporate Publisher:

United States. Department of Transportation. Intelligent Transportation Systems Joint Program Office
Abstract:

This report presents an analysis of the potential macroeconomic impacts resulting from the adoption of higher level automated driving systems (ADS) of the long-haul trucking industry in the United States. The analysis uses USAGE-Hwy, a computable general equilibrium (CGE) model of the U.S. economy that includes detail on transportation related industries including for-hire and in-house trucking. Three time profiles for the adoption of automation are explored. The results show that automation of the long-haul trucking industry is expected to bring welfare enhancing productivity enhancements to the economy. Assuming that occupational turnover rates remain as they are, these positive economic impacts would not be accompanied by forced-lay-offs under the slow and medium adoption scenarios. Only under the fast adoption scenario are there short-lived, small magnitude lay-offs.
Format:

PDF
Funding:

693JJ318N300055
Download URL:

https://rosap.ntl.bts.gov/view/dot/54596/dot_54596_DS1.pdf
File Type:

[PDF - 525.34 KB]
Collection(s):

Autonomous Vehicles ; Volpe Center
Main Document Checksum:

urn:sha-512:08b386c207d532222cc8684e508aff2f884e20e3f64ce357400fe773fc38fd273d5fc3a5f1b80ef6ee3c89df48dc66385bbf294e3967754ccaf9df7e749bc457

File Language:

English

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