Real time transmission of external data for Automated Driving vehicles based on TPEG technology is demonstrated for the first time
Developers from TomTom and NNG have demonstrated a live data feed that provides external real-time data specifically tailored for Automated Driving (AD) vehicles, thus increasing safety and ensuring better traffic management. This is possible thanks to the new generation of TPEG3 data feed developed by TISA (Traveller Information Services Association).
TISA members TomTom, the location technology specialist, and NNG have proven the possibility and the benefits of sending real-time data specifically generated to supplement the onboard sensor data of an AD vehicle from an emergency vehicle. The data feed generated by TomTom in Berlin was perfectly received in Budapest by NNG, who processed the data using an autonomous driving simulation. This triggers certain actions, such as forming an emergency lane or informing passengers about deviations of the planned route, as well as preventing non-standard manoeuvres caused by an approaching emergency vehicle that the passengers might not yet be aware of.
“Emergency situations require rapid action to help save lives, so it’s critical that drivers and vehicles can be warned to make way for emergency services. TomTom is always developing new solutions to help make roads safer for everyone and this exciting collaboration has the potential to further enhance the TomTom Hazard Warnings service.” – Ralf-Peter Schäfer, VP Traffic and Travel, TomTom.
“NNG is excited to participate in the development and piloting of future Information for Automated Driving (TPEG3) as it fits perfectly in our technology vision supporting traveller experience in the automated driving era. NNG’s Intelligent Co-Driver concept is able to make use of the TPEG3 specified dynamic data to keep the vehicles and their occupants up-to-date about safety relevant traffic situations. TPEG3-EVA demonstrator therefore is a key milestone for us through. We strengthened the cooperation with other members of the traveller and traffic information ecosystem.” – NNG CTO Martin Pfeifle.
“The results of the demonstration exceeded our expectations on the value that the TPEG3 data could deliver to improve the autonomous driving strategy and tactics in the given context of an approaching emergency vehicle. This was a very promising first demonstration, which paves the way for more use cases to which the TPEG3 data feed will be expanded, so a lot of development and standardization lies ahead of us.” – TISA Executive Director Matthias Unbehaun.
At the base of this demonstration was a completely updated version of the TPEG2 protocol, which is the successor of the globally very successful RDS-TMC and nowadays part of most modern navigation systems. It offers a method for transmitting multimodal traffic and travel information, regardless of client type, location or delivery channel (e.g. mobile networks, DAB, HD radio, etc.). However, to suit the specific needs of AD vehicles concerning flexibility of delivery, as well as richness and granularity of the information, a completely new data model was conceived and combined with state-of-the-art serialization and compression, plus a hybrid request-response / publish-subscribe communication paradigm. The first main objective of TPEG3 is to improve situation awareness by providing an ‘additional sensor’ for AD vehicles, effectively extending the range of onboard sensors whilst being faster than current map updating techniques. The second objective is to support traffic control strategies and policies for the safe and efficient usage of available road infrastructure.
TISA will now start improving the logical data model, adding a large number of new use cases requested by TISA members. TISA will also integrate rich meta-data to describe quality characteristics and the provenance of the source data, as well as to assist the processing and interpretation of the information in the AD vehicle with rich contextual information. TISA will further liaise with other standardization organizations to ensure alignment and interoperability with in-vehicle communication (e.g. ADASIS) and to integrate an uplink channel to feed data from the AD vehicle back to the service provider (e.g. using SENSORIS).