Paving the Way for Autonomous and Connected Vehicle Technologies in the Motor Carrier Industry
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Summary
This study investigates the infrastructure requirements and safety implications of adopting autonomous vehicle (AV) and connected vehicle (CV) technologies within the motor carrier industry. Motivated by the potential for these technologies to mitigate driver shortages, reduce fatigue, and enhance safety, the research focuses on identifying the specific infrastructure modifications necessary to support the mass adoption of AVs and CVs, particularly in mixed-traffic environments. The authors aim to quantify the safety benefits of eliminating human-error-related crash circumstances through automation, thereby justifying the associated infrastructure investments. The methodology utilizes large truck crash data from 2013 through 2015 obtained from the Missouri State Highway Patrol’s Statewide Traffic Accident Records System. The dataset comprises 1,083,150 records, with 15,338 crashes attributed to motor carrier driver contributions. The researchers employed Chi-Square Automatic Interaction Detection (CHAID) decision trees to analyze the relationship between contributing crash circumstances and crash severity outcomes. This approach allowed for the identification of key predictors of severe crashes and the estimation of potential reductions in fatal and injury crashes if specific contributing factors were eliminated by AV/CV technologies. The results indicate that the primary predictors of crash severity are driving too fast for conditions, distracted or inattentive driving, overcorrecting, and driving under the influence of alcohol. The analysis suggests that if AV and CV technologies effectively alter these circumstances, between 117 and 193 severe crashes involving large trucks could be prevented annually in Missouri alone. To achieve these safety benefits, the study identifies critical infrastructure needs. For AVs, these include readable lane markings, improved traffic signals and signs, and dedicated refueling or recharging facilities. For CV-enabled truck platooning, the research highlights the need for managed or dedicated lanes to facilitate safe highway merging and exiting, as well as infrastructure that supports vehicle-to-infrastructure communication for autonomous acceleration control. The significance of this work lies in its provision of a safety-based justification for infrastructure investment prior to the mainstream adoption of autonomous freight technologies. The authors conclude that while fiscal burdens exist, the potential safety improvements warrant proactive infrastructure development, potentially through public-private partnerships. The study also notes limitations, including the reliance on Missouri-specific data and the uncertainty surrounding the timeline for widespread technology adoption. Ultimately, the report emphasizes that designing infrastructure around autonomous systems, rather than adapting systems to existing infrastructure, is crucial for ensuring safety and efficiency in the future motor carrier industry.
Key finding
Eliminating driving too fast for conditions, distracted driving, overcorrecting, and alcohol use through autonomous technologies could prevent between 117 and 193 severe large truck crashes annually in Missouri.
Methodology
dataset
Sample size: 15338
Provenance
The full processing record for this entry. Every stage of this paper's journey through the pipeline is logged — what ran, with which tool and model, how many attempts it took, and when it last completed. Discovered via bulk_ingest_rosap on 2026-05-23 (6 acquisition events logged).
| Stage | Outcome | Tool | Model | Prompt | Attempts | Completed |
|---|---|---|---|---|---|---|
| discover | success | rosap | — | — | 2 | 2026-05-23 |
| archive | success | — | — | — | 1 | 2026-05-23 |
| extract | success | cached | — | — | 2 | 2026-06-10 |
| clean | success | — | — | — | 1 | 2026-06-01 |
| chunk | success | — | — | — | 1 | 2026-06-01 |
| embed | success | — | — | — | 1 | 2026-06-02 |
| enrich | success | — | — | — | 1 | 2026-05-23 |
| promote | success | — | — | — | 1 | 2026-05-23 |
| summarize | success | llm | qwen3.6-27b-prismaquant | summ-v5 | 3 | 2026-06-10 |
| tag | success | vector_similarity | — | — | 19 | 2026-06-11 |
| verify | success | — | — | — | 2 | 2026-06-10 |
Summary generated by qwen3.6-27b-prismaquant on 2026-06-10; verification: verified.
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- Empirical Findings: observational prevalence
- Methodological Resource: tool software
- Theoretical Contribution: conceptual framework