State of the Practice Review and Stakeholder Interviews Assessed Infrastructure Information and Mapping Support Needs for Both Human and Automated Driving.
Nationwide, United States
Infrastructure and V2X Mapping Needs Assessment and Development Support: Final Project Report
Summary Information
With the development of automated driving systems, the transportation system will need to support both human drivers and connected, automated vehicles (CAVs). Researchers conducted a state of the practice review and interviewed stakeholders to address uncertainties in business models and standardization for the public and private sectors providing location-based data for CAVs. Location-based data could include a combination of dynamic and static data that depict the driving environment with high precision, accuracy and currency. The focus of the effort centered around how to connect CAV-Path data (a real-time collection of data that allows CAVs to understand the basic road network and the current status of its path) to road network data and to understand public sector roles in data provision. Seventeen industry stakeholders from three key stakeholder groups, including original equipment manufacturers (OEMs), map providers, and Infrastructure Owner-Operators (IOOs) / suppliers, were interviewed, followed by additional stakeholder meetings to validate the interview results. Using work zones as a case study, researchers developed tools to demonstrate how a public agency might create data feeds for use by human and machine drivers, based on existing and emerging standards.
- Code and quantify CAV-Path data consistently at the national level. To develop usable national CAV-Path data that will be easily computable by a CAV, it must be consistent. The data provided by public agencies must be used by and fused with data from many others across the ecosystem. That data should be contributed in a nationally consistent way, as vehicles need to understand the information the same way wherever they travel. Developing standards that are consistent nationally with respect to public sector information is also important to enable automated vehicles.
- Provide data relating to the entire journey, both what is true at any given time and place, and what is coming up. Map content, such as road geometry, road furniture (e.g., sign and traffic signal locations), rules of the road (“legal path”), and recent / temporary changes, are needed for priority applications.
- Monitor, support, and implement location referencing (absolute and / or relative positions) solutions to hold the CAV-Path data set together. Usually a “cross-map” referencing approach is implemented at the required levels of accuracy for automated vehicles. Standards organizations are also developing approaches to location referencing.
- Provide spatial accuracy to 20 centimeters or below. Content quality was a major priority area for stakeholders. To support automated vehicle functions, the data must be highly accurate, complete, and current, and include quality metadata to enable informed judgments. This identified spatial accuracy requirement is a dramatic shift from existing “road level” or “lane level” accuracies to a “within lane” or feature-level focus.
- Expect performance requirements to satisfy automated vehicles to include a tight set of end-to-end latency metrics. “Latency” is measured as the time of change to the time of vehicle awareness of change. This requirement encompasses data collection, processing, communications, and retrieval periods.
- Create a data registry that will house the full suite of standard transportation data elements and their metadata. The registry will enable consistent use and re-use of these elements by developers. Otherwise, it is very difficult to avoid conflicts and unintentional standards overlap.
- Harmonize or translate related / competing standards. There are ongoing efforts to harmonize key standards on a national and global basis. For example, there must be translation between data standards to avoid the need for full harmonization. Outreach efforts can also help to avoid the development of redundant standards.
- Recognize that nationally consistent CAV-Path data requires coordination between all involved parties. The needs and gaps in CAV-Path data standards are not expected to be solved by a single public or private entity. Rather, it requires a coordinated and cooperative approach to ensure that CAVs can be assured of high-quality content suitable for their functions / applications.
