Commercial Truck Platooning Demonstration in Texas – Level 2 Automation

Kuhn, Beverly; Lukuc, Mike; Poorsartep, Mo; Wagner, Jason; Balke, Kevin N.; Middleton, Dan; Songchitruksa, Praprut; Wood, Nick; Moran, Maarit · 2017 · ROSA P / Texas Department of Transportation. Research and Technology Implementation Office

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Summary

This report details a comprehensive demonstration of commercial truck platooning in Texas, funded by the Texas Department of Transportation (TxDOT) and conducted by the Texas A&M Transportation Institute. The research addresses the feasibility of deploying automated truck platoons on specific Texas corridors within five to ten years, motivated by critical industry challenges including a projected driver shortage, significant fuel costs, congestion-related economic losses, and safety concerns. The study aims to assess the practicality and return on investment of cooperative adaptive cruise control (CACC) technologies, which allow trucks to travel in tight formations with short following distances using vehicle-to-vehicle (V2V) communication. The methodology involved a multi-phase approach integrating regulatory analysis, scenario development, system engineering, and field testing. Researchers first evaluated federal and state regulations, identifying potential barriers such as Federal Motor Vehicle Safety Standards (FMVSS) and liability issues. They developed and validated four platooning concepts—ad hoc, guided, scheduled, and trip platooning—using simulation tools like TruckSim to assess fuel savings and traffic throughput. The team then integrated hardware from partners including Navistar, Bendix, and ZF-TRW, installing dedicated short-range communication (DSRC) radios, electronic throttle and brake controls, and steering actuators on heavy trucks. This system enabled automated longitudinal and lateral control, with the lead vehicle transmitting acceleration data to follower vehicles at 10 Hz. The project culminated in a Phase 1 proof-of-concept demonstration at the Texas A&M University RELLIS Campus. The demonstration successfully executed key maneuvers, including joining and leaving the platoon, maintaining following distances, changing gaps, and performing lane changes. Data collection focused on vehicle dynamics, GPS positioning, and thermal performance, with instrumentation measuring radiator inlet temperatures and intake air conditions to monitor engine stress during close-following operations. Preliminary simulations indicated potential fuel savings due to reduced aerodynamic drag, with specific ratios dependent on the time spent as a follower versus a leader vehicle. The demonstration confirmed that the integrated hardware and software could maintain stable platooning behavior under controlled conditions. The significance of this work lies in its validation of Level 2 automation for commercial freight, providing a roadmap for future deployment. The report concludes that platooning technology is ready for industrial use in specific roadway and operating conditions, offering substantial benefits in fuel economy, safety, and traffic efficiency. By addressing regulatory frameworks and demonstrating technical feasibility, the study positions TxDOT as a leader in connected and automated vehicle initiatives. The findings suggest that with continued refinement and regulatory adaptation, truck platooning can mitigate driver shortages and reduce the economic impact of congestion, serving as a viable near-term solution for freight mobility.

Key finding

Platooning technology is ready for industrial use and provides value in specific roadway and operating conditions for heavy truck fleet operations.

Methodology

field_study

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).

StageOutcomeToolModelPromptAttemptsCompleted
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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