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21st Century Operations Using 21st Century Technologies
Table of Contents

Automated Driving Systems (ADS) Operational Behavior and Traffic Regulations Information – Proof-of-Concept Demonstration Report

CHAPTER 1. INTRODUCTION

BACKGROUND

The advent of automated driving systems (ADS) and anticipated cooperative ADS will transform the way vehicles interact not only with each other and other travelers, but also with transportation infrastructure, communications infrastructure, information systems, and system management and operations strategies. Infrastructure owner-operators (IOO) and their partner agencies across the country have been grappling with the questions of how ADS will interact with the transportation system—and what they should do to prepare. Uncertainty around the timing of ADS technology development and market penetration has made preparing for this transformation a challenge, underscoring the need for practice-ready information and tools that IOOs can use for planning and deploying resources and policies for the integration of ADS. The National Dialogue on Highway Automation1 includes a need for a National vision; increased public awareness and support; agency guidance and education; enhanced planning to include probabilistic and scenario-based planning; and data exchange, standardization, and management.

National automation readiness requires a strategic understanding of the context of automated vehicles (AV) and the National transportation infrastructure among all stakeholders. The Federal Highway Administration (FHWA) has been exploring this context through its work in automated vehicles. This exploration includes assessing information and data needs for AV, the National Dialogue on Highway Automation, and other FHWA leadership and working groups. Needs, insights, and opportunities identified through these efforts, as well as coordination with the Cooperative Automated Transportation (CAT) Coalition and other professional and research organizations, are providing essential input for Federal, State, and local initiatives to guide AV implementation. IOOs need insights and tools for planning, developing, and deploying resources as they prepare their organizations, physical assets, and policies to best facilitate and leverage ADS deployment.

Among the key aspects of ADS planning, deployment, and operations, access to data is a critical enabler of safe, efficient, and accessible integration of AVs into the transportation system. On December 7, 2017, the U.S. Department of Transportation (USDOT) hosted the Roundtable on Data for Automated Vehicle Safety.2 The roundtable demonstrated multimodal alignment around a unified approach to Federal AV policy, and marked the beginning of a new phase of dialogue among public and private-sector stakeholders to accelerate safe deployment of AVs. The following high-priority use cases for data exchange were identified by roundtable participants:

  • Monitoring planned and unplanned work zones.
  • Providing real-time road conditions.
  • Diversifying AV testing scenarios.
  • Improving cybersecurity for AVs.
  • Improving roadway inventories.
  • Developing AV inventories.
  • Assessing AV safety features and performance.

A data system related to traffic laws and regulations will facilitate the development of ADS behavior and roadway adaptations that fulfill the vision of safe and effective ADS operations. The ADS Operational Behavior and Traffic Regulation Database framework is, therefore, an important element for realizing effective, robust digital transportation systems for AV integration. It consists of a comprehensive, structured database of traffic regulations that developers could use to set basic programming standards in ADS regarding traffic regulations.

There are challenges to developing ADS. In order to function effectively, ADS must account for the multitude of static and dynamic traffic regulations, which means agencies must provide the regulatory information to ADS and determine how the system would be implemented across the Nation. Traffic regulation information varies among governmental jurisdictions across the Country in format, structure, and implementation. Without common data exchanges, it is almost impossible to develop ADS software that can ensure optimal ADS performance under varying sets of traffic regulations. In short, ADS development needs the traffic regulation database for testing, and for IOOs to ensure well-tuned ADS operational behavior and transportation system safety.

PURPOSE

This research investigates the challenges of establishing an ADS-ready traffic laws and regulations database, and accessing and exchanging requirements to support the sharing and consumption of the information within the ADS ecosystem. It also identifies the basic requirements for collaboration among State and local traffic code stakeholders, as well as ADS behavior subject matter experts (SME).

For consistency and interoperability, it is necessary to develop a comprehensive database framework to support the incorporation of all traffic regulations that enable ADS behavior development and operation. The ultimate goal is to facilitate a traffic regulation specification that supports the development and subsequent operation of traffic with ADS-equipped vehicles. This project involves: a detailed analysis of the ADS readiness of current traffic laws and regulations databases, development of a concept of use (COU), design of a prototype of the traffic laws and regulation database framework, conduction of a simulated proof-of-concept laboratory testbed-simulated demonstration, and development of a model testing plan for a future collaborative implementation of AV integration with the traffic laws and regulations database framework.

The purpose of this proof-of-concept demonstration report is to describe the prototype ADS regulations database design and the prototype database testing. The design is based on the CoU3 and includes a blockchain database implementation, a traffic regulations data interface, and administrative interface for specifying regulations. The prototype database framework is implemented with sample regulations data from the Uniform Vehicle Code (UVC) and selected jurisdictions for some operational scenarios, as may be applicable in particular operational design domains, and is fully documented in a project GitHub repository. The prototype demonstration uses the data framework and the CARLA4 simulation platform to evaluate use of the regulations data interface for two selected scenarios: intersection right-turn-on-red and freeway left-lane use. The testing simulation scripts, videos, and documentation are stored in the project GitHub repository.5

The organization of this report is as follows:

Chapter 1 introduces the background and purpose of the research project and this report.

Chapter 2 describes the traffic regulations data framework and implementation.

Chapter 3 describes the proof-of-concept demonstration using the ADS regulations data framework interface and simulations.

1 Federal Highway Administration (FHWA), Office of Operations. (n.d.). “National Dialogue on Highway Automation.” https://ops.fhwa.dot.gov/automationdialogue/index.htm, last accessed May 11, 2020. [ Return to Return to Note 1 ]

2 USDOT. 2018. Roundtable on Data for Automated Vehicle Safety Summary Report. https://www.transportation.gov/av/data/roundtable-data-automated-vehicle-safety-summary-report, accessed May 11, 2020. [ Return to Return to Note 2 ]

3 FHWA, Automated Driving Systems (ADS) Operational Behavior and Traffic Regulations Information – Concept of Use, FHWA-HOP-20-041, Washington, DC: FHWA. [ Return to Return to Note 3 ]

4 CARLA Team 2021. 2021. “CARLA Open-source simulator for autonomous driving research.” (website). https://carla.org/, last accessed December 7, 2021. [ Return to Return to Note 4 ]

5 GitHub. 2021. “ads-traffic-regs.” (website). https://github.com/usdot-fhwa-stol/ads-traffic-regs/tree/cherneysp-initial, last accessed December 7, 2021. [ Return to Return to Note 5 ]