Modeling trucking industry perspective on the adoption of connected and autonomous trucks

Simpson, Jesse; Sharma, Ishant; Mishra, Sabyasachee

doi:10.1016/j.rtbm.2022.100883

Cited by 6 publications

(1 citation statement)

References 72 publications

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“…ATs offer significant benefits, including safety improvements, operational efficiency, reduced labor and fuel costs, and enhanced driving ease [3]. Significant economic advantages come from replacing the driver [4], achieving almost continuous vehicle utilization [5], avoiding traffic by prioritizing nighttime operations, and reducing road damage by operating at night when lower temperatures reduce the impact of load stress [6].…”

Section: Opportunities and Challengesmentioning

confidence: 99%

Route Risk Index for Autonomous Trucks

Jones,

Bridgelall,

Tolliver

2024

Applied Sciences

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The proliferation of autonomous trucking demands a sophisticated understanding of the risks associated with the diverse U.S. interstate system. Traditional risk assessment models, while beneficial, do not adequately address the state and regional variations in factors that significantly impact the safety and efficiency of autonomous freight transport. This study addresses the problem by developing a composite risk index that evaluates the safety of U.S. interstate routes for autonomous trucking, considering both state and regional differences in traffic volumes, road conditions, safety records, and weather patterns. The potential for autonomous trucking to transform the freight industry necessitates a risk assessment model that is as dynamic and multifaceted as the system it aims to navigate. This work contributes a regionally sensitive risk index using GIS methodologies, integrating data from national databases, and applying statistical analysis to normalize risk factors. The findings reveal significant state and regional disparities in risk factors, such as the predominance of precipitation-related risks in the Southeast and traffic in the Far West. This work provides a targeted approach to risk assessment for policymakers and infrastructure planners and offers a strategic tool for logistics companies in optimizing autonomous trucking routes. The long-term benefit is a scalable model that can adapt to evolving data inputs and contribute to the broader application of risk assessment strategies in various domains.

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