How cars and infrastructure work together in automated city driving

Pedestrians hidden from view by vehicles, cyclists crossing in front of cars, buses suddenly approaching: managing city traffic can be a difficult task. Among all the infrastructure, streetlights could make urban traffic safer and provide automated vehicles with an overview of the situation. This was the focus of the MEC-View research project. The project called for streetlights to be equipped with video and lidar sensors, then use advanced mobile technology to provide vehicles with critical information in real time, allowing them to detect obstacles—whether other cars, bicycles, or pedestrians—quickly and reliably. After more than three years of development, the project is ready to present its results. The project partners, which have received €5.5 million in funding from the German Federal Ministry for Economic Affairs and Energy (BMWi), were Bosch, the consortium leader, Mercedes-Benz, Nokia, Osram, TomTom, IT Designers, and the Universities of Duisburg-Essen and Ulm. The city of Ulm, an associated partner, has been the testing ground for streetlight sensors and connectivity technology for the past three years. The knowledge gained from the project will now be used to further develop automotive, automated driving, and mobile technology. Furthermore, the infrastructure built will be available for future research projects.

Bird’s-eye view beats ant’s-eye view

Reaching up to six meters high, streetlights rise above road traffic. They thus provide a precise bird’s-eye view of what’s happening at busy intersections. This is knowledge that automated vehicles will need in the future. While a vehicle’s sensor systems (cameras, radar, and lidar) provide an accurate 360-degree view, a ground-level view isn’t always sufficient to detect a pedestrian hidden by a truck, a vehicle emerging from a hidden ford, or a cyclist approaching from behind and quickly changing lanes. “Because the vehicle itself can’t see around corners or through walls, we use sensors installed in streetlights to extend the field of view of the vehicle’s sensors,” says Dr. Rüdiger Walter Henn, who leads the MEC-View project at consortium leader Bosch. The project partners have developed the corresponding hardware and software for this purpose; the system processes images and signals from infrastructure sensors, combines them with high-resolution digital maps (HD maps), and transmits them wirelessly to the vehicle. This data is then merged with the vehicle’s own sensor information to create an accurate picture of the situation, including all relevant road users.

Wireless data transmission

Advanced mobile technology enables the transmission of sensor information with extremely low latency. While the MEC-View project used LTE mobile communications technology with a configuration optimized for this purpose, in the new 5G standard, real-time data transmission is a core function. The core task of latency-optimized mobile communications is not only the virtually instantaneous wireless transmission of data, but also the processing of that data as close as possible to the source. This task is performed by special computers, known as Mobile Edge Computing Servers (or MEC servers), which are integrated directly into the mobile network. They combine sensor data located on streetlights with data from vehicle environment sensors and high-precision digital maps. From there, they generate an environment model that includes all available information on the current traffic situation and make it available wirelessly to vehicles. In the future, facilities such as city traffic control centers could be equipped with such servers so they can share data with all vehicles, regardless of manufacturer, and with other road users.

Blending seamlessly into traffic

In Ulm, project partners have been testing the interaction of prototype automated vehicles and infrastructure sensors in real-world traffic conditions since 2018. An intersection in the Lehr district of Ulm is known for its lack of all-round visibility. Now, streetlights are equipped with sensors to help automated vehicles navigate the intersection. Cars approaching the difficult intersection from a side road must merge onto the main road. Thanks to the newly developed technology, the automated car is able to recognize road users from the outset and can adapt its driving strategy accordingly. As a result, the vehicle navigates through gaps in traffic on the main road and merges seamlessly, without the need to stop. Such a development will make urban traffic not only safer but also more fluid. The constructed infrastructure will remain in Ulm, where it will be available for use in subsequent research projects.

Additional information:

Project website with results: www.mec-view.de

Project partners:

Robert Bosch GmbH (consortium leader)

IT Designers GmbH

Mercedes-Benz AG

Nokia Solutions and Networks GmbH & Co. KG

Osram GmbH

TomTom N.V.

University of Duisburg-Essen

University of Ulm

City of Ulm (associated partner)