Paving the Way for Autonomous and Connected Vehicle Technologies in the Motor Carrier and Rail Industries
This research sought to evaluate the broad impacts that automated and connected vehicle technologies can have on both the motor carrier and rail industries. The studies look at potential safety considerations and infrastructure needs that will be required to support the mass adoption of these emerging technologies, as well as the potential costs and benefits as they come into the market. Using large truck crash data from 2013 through 2015 obtained from the Missouri State Highway Patrol, chi-square automatic interaction detection (CHAID) decision trees were estimated to examine the effect of autonomous vehicle (AV) and connected vehicle (CV) technologies on motor carrier crash severity. Results suggest that the greatest contributory predictors of crash severity outcomes are driving too fast for conditions, distracted/inattentive driving, overcorrecting, and driving under the influence of alcohol. If these circumstances are altered by AV and CV technologies, it is suggested that between 117 and 193 severe crashes involving large trucks could be prevented annually in Missouri alone. To render such safety benefits, key vehicle needs include autonomously controlling acceleration and steering, monitoring of the environment, and responding to dynamic driving environments without the need for human intervention. Importantly, the safe operations of a system that can perform such AV and CV tasks require readable lane markings, traffic signals and signs, managed or dedicated lane usage, and dedicated refueling and/or recharging facilities. Further, since the development and adoption of these technologies are likely to be gradual, three phases of adoption were posited and analyzed. Depending on the degree of autonomy that is available, the motor carrier industry could achieve up to a 42.1% reduction in average cost per mile. And if fully autonomous technology was made available for use in the motor carrier industry, it is estimated that the American rail freight industry could see a 19% to 45% drop in demand.
- Record URL:
- Record URL:
- Record URL:
Language
- English
Project
- Status: Completed
- Funding: $25000
-
Contract Numbers:
DTRT-13-G-UTC37
-
Sponsor Organizations:
Iowa State University
2711 S Loop Drive, Suite 4700
Ames, IA United States 50010-8664Office of the Assistant Secretary for Research and Technology
University Transportation Centers Program
Department of Transportation
Washington, DC United States 20590 -
Managing Organizations:
Institute for Transportation
2711 South Loop Drive, Suite 4700
Ames, Iowa United States 50010-8664 -
Performing Organizations:
University of Missouri, St. Louis
1 University Boulevard
St. Louis, MO United States 63121-4400 -
Principal Investigators:
Mundy, Ray
- Start Date: 20160801
- Expected Completion Date: 20180330
- Actual Completion Date: 0
Subject/Index Terms
- TRT Terms: Costs; Forecasting; Freight and passenger services; Investments; Motor carriers; Policy making; Railroad rails; Technological forecasting; Trucking
- Subject Areas: Freight Transportation; Motor Carriers; Operations and Traffic Management; Railroads;
Filing Info
- Accession Number: 01618252
- Record Type: Research project
- Source Agency: Midwest Transportation Center
- Contract Numbers: DTRT-13-G-UTC37
- Files: UTC, RIP
- Created Date: Dec 1 2016 12:47PM