Virtual Assessment to enable safe Automated Driving

Technological innovations in road mobility systems follow each other in rapid succession. Fast advances are made in digitalization which allows for further connecting vehicles and infrastructure, and increased possibilities for cooperative mobility solutions.

In this way, automation solutions become increasingly complex and driving functions become more and more integrated. Currently, systems enter the market in the passenger car domain, that are able to completely take over control of the human driver for part of the trip. A new UN-ECE regulation dealing with ALKS (advanced lane keeping system) under conditions allows drivers to take their hands off the steering wheel and their eyes off the road during such driving phases!

National vehicle authorities (such as RDW) are asked to allow such vehicles onto the public road. However, an appropriate system for type approval of such innovative vehicles is not yet in place. Also consumer organizations such as Euro NCAP, that provide a safety rating to new passenger cars entering the market, have difficulty in providing a proper safety assessment of vehicles because the integration of functions and the increased automation, require an ever increasing number of tests to appropriately cover the operational design domain of these new cars.

Over the last years, TNO has developed a methodology, StreetWise, to build and maintain a real-world scenario database, suitable for testing and validation of CAD systems. Currently, StreetWise provides a solution on how to identify, parameterize and characterize scenarios from object-level in-vehicle sensor data provided from a fleet of vehicles driving on public roads.

In this TKI project, StreetWise+, TNO extends this method to identify and characterize scenarios using roadside based camera systems. Moreover, TNO will integrate the effects of communication signals in the scenario definition, to accommodate assessment of communication-based automated systems, such as C-ACC (platooning), C-AEB (communication enhanced autonomous emergency braking), or Intelligent Speed Adaptation (ISA) functionality. Furthermore, TNO will extend the scenario models to allow multiple interacting actors to be part of the description of complex scenarios.

Siemens DISWwill use Simcenter Prescan and HEEDS to run a large variety of virtual tests resulting from the StreetWise methodology. The aim is to demonstrate virtual testing and safety assessment for the use case of a combined function of Advanced Cruise Control (ACC) and Intelligent Speed Assist (ISA) to relevant stakeholders.

Itility will ensure efficient cloud-based data processing, and will develop a data stream quality check using their expertise in anomaly detection methods. Working closely together with TNO and Siemens DISW data scientists and software engineers, Itility will support the development of the statistical driver models and relevant APIs.

As the research proposed in this project has a good match with the HTSM Automotive Roadmap, the project received TKI funding. The project will run until December 2022.