Cooperative Driving Automation: Research into Automated Port Operations and Automated Commercial Motor Vehicle Operations: Concept of Operations for Enhanced Automated Port Drayage

Sethi, Sonika; Marchese, Matthew; Greenwood, Aaron T.; Leslie, Ed; O’Malley, Steve · 2022 · ROSA P / United States. Department of Transportation. Intelligent Transportation Systems Joint Program Office

archive: archived pipeline: cataloged verified

Get this paper ↗ (full text — opens at the source; we link to it, we don't host it)

Summary

This report presents a Concept of Operations (ConOps) for enhancing automated port drayage through Cooperative Driving Automation (CARMA). Sponsored by the U.S. Department of Transportation, including the Federal Highway Administration (FHWA), Federal Motor Carrier Safety Administration (FMCSA), and Maritime Administration (MARAD), the project addresses significant traffic congestion at marine container terminals. This congestion, caused by trucks queuing at gates and operational bottlenecks, leads to driver productivity losses, increased shipment costs, and environmental degradation. The primary objective is to leverage connected automated vehicles (CAVs) to improve efficiency, safety, and emissions during short-haul drayage operations, which involve moving containers between terminals, rail intermodal yards, and staging areas. The study focuses on the APM Terminal in Mobile, Alabama, selected as a representative stacked-container facility suitable for automation testing. The methodology involves developing a detailed operational concept for SAE Level 2–3 automated Commercial Motor Vehicles (CMVs) equipped with CARMA technology. The report outlines the current drayage landscape, identifying key stakeholders such as terminal operators, trucking firms, and federal agencies, and analyzing existing processes for import and export transactions. It details the necessary technological and operational changes required to integrate automated trucks into terminal infrastructure, including gate passage, inspection points, and container loading/unloading. The proposed system relies on automated control systems and communications to manage vehicle movements within the terminal and on adjacent public roads. The findings define a specific operational workflow for automated drayage, covering routes from rail intermodal yards to terminal entry gates, through container storage yards, past radiation portal monitors, and back to rail terminals. The report establishes that wheel-based terminals are unsuitable for this specific automation concept due to chassis hitching requirements, favoring stacked facilities like APM Mobile where chassis handling occurs off-site. The study identifies high-level requirements for system implementation, including infrastructure modifications and software enhancements to the CARMA Platform, Cloud, and Simulation tools. It also outlines a phased deployment strategy, beginning with a proof of concept on a closed track, followed by a scale-model demonstration using the APM Terminal layout, and potentially leading to full-scale field tests at cooperating port facilities. The significance of this work lies in its provision of a structured framework for deploying cooperative automation in complex maritime environments. By detailing the specific needs and requirements for automated port drayage, the report supports the broader ITS MARAD program’s goal of improving freight network performance. It offers a roadmap for reducing port congestion and enhancing operational efficiency through technology transfer and field operational testing. The document serves as a guide for system developers, port operators, and policymakers interested in implementing connected automated vehicle technologies to address critical challenges in commercial motor vehicle operations and port logistics.

Key finding

The report establishes a conceptual framework for using cooperative driving automation to streamline port drayage operations, targeting reduced congestion and increased efficiency through automated interactions with terminal infrastructure.

Methodology

review

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 24 2026-06-11
verify success 2 2026-06-10

Summary generated by qwen3.6-27b-prismaquant on 2026-06-10; verification: verified.

Topics

Ranked by relevance to this paper. Hover a topic for its definition.