{"id":3087,"date":"2020-07-21T07:09:52","date_gmt":"2020-07-21T07:09:52","guid":{"rendered":"http:\/\/tomdenton.org\/blog\/?p=3087"},"modified":"2020-07-21T07:09:52","modified_gmt":"2020-07-21T07:09:52","slug":"how-cars-and-infrastructure-work-together-in-urban-automated-driving","status":"publish","type":"post","link":"http:\/\/tomdenton.org\/blog\/?p=3087","title":{"rendered":"How cars and infrastructure work together in urban automated driving"},"content":{"rendered":"

Pedestrians obscured from view by vehicles, cyclists passing in front of the car, buses that suddenly approach: negotiating city traffic can quickly become a difficult task. Of all things, it could be streetlights that make urban traffic safer and provide automated vehicles with an overview of the traffic situation. This was the subject of the MEC-View research project. The project required streetlights to be fitted with video and lidar sensors, which then used advanced cellular technology to provide vehicles with critical information in real time, allowing them to detect obstacles \u2013 whether other cars, bicycles, or pedestrians \u2013 quickly and reliably. After more than three years of development, the project is now ready to present its findings. Partners in the project, which received 5.5 million euros in funding from the German Federal Ministry for Economic Affairs and Energy (BMWi), were Bosch, the consortium leader, together with Mercedes-Benz, Nokia, Osram, TomTom, IT Designers, and the universities of Duisburg-Essen and Ulm. The project\u2019s associated partner was the city of Ulm, which for the past three years has been the testing ground for the sensors on the streetlights and the connectivity technology. The insights gained in the project will now be used to further develop automotive technology, automated driving, and cellular technology. In addition, the infrastructure the project has built up will now be available for further research projects to use.<\/p>\n

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Bird\u2019s-eye beats worm\u2019s eye<\/strong>
\nReaching up to six meters in height, streetlights tower above road traffic. They have a precise bird\u2019s eye view of developments at busy intersections, say \u2013 and it is knowledge like this that automated vehicles will need in the future. While a vehicle\u2019s sensor systems \u2013 cameras, radar, and lidar sensors \u2013 give it precise 360-degree vision, the view from the ground \u2013 from the vehicle alone \u2013 is not always sufficient for it to see a pedestrian currently obscured by a truck, a vehicle emerging from a concealed entrance, or a cyclist approaching from behind and changing lanes quickly. \u201cBecause the vehicle itself cannot see around corners or through walls, we use the streetlight sensors to extend the vehicle sensors\u2019 field of view,\u201d says Dr. R\u00fcdiger Walter Henn, who heads the MEC-View project at the consortium leader Bosch. The project partners have developed the corresponding hardware and software for this purpose; the system processes the images and signals from the infrastructure sensors, combines them with high-resolution digital maps (HD maps), and transmits them to the vehicle over the air. There, the data merges with the vehicle\u2019s own sensor information to create an accurate picture of the situation, including all relevant road users.<\/p>\n

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Wireless data transmission<\/strong>
\nAdvanced cellular technology makes extremely low-latency transmission of sensor information possible. While the MEC-View project used LTE mobile communications technology with an optimized configuration for this purpose, in the new 5G communications standard, real-time data transmission is a basic 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 to the source as possible. This task is performed by special computers, known as mobile edge computing servers (or MEC servers for short), which are integrated directly into the cellular network. They combine the streetlight sensor data with data from a vehicle\u2019s surround sensors and highly accurate digital maps. From this, they generate a model of the surroundings that includes all available information about the current traffic situation, and make this model available to vehicles over the air. In the future, facilities such as the city traffic control centers could be equipped with such servers, so that they can share the data with all vehicles, regardless of manufacturer, and other road users.<\/p>\n

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Seamlessly merging with trafic<\/strong>
\nIn Ulm, the project partners have been testing the interaction of automated vehicle prototypes and infrastructure sensors in real traffic conditions since 2018. One intersection in the Lehr district of Ulm is notorious for its lack of good all-round visibility. The streetlights there were equipped with sensors to help automated vehicles negotiate the intersection. Vehicles approaching the difficult intersection from a side road have to merge onto the main road. Thanks to the newly developed technology, the automated prototype now recognizes road users early on and can adapt its driving strategy accordingly. As a result, the vehicle targets gaps in the traffic on the main road and merges seamlessly, without stopping. Such a development will make urban traffic not only safer, but also more fluid. The infrastructure built up during the project will remain in Ulm, where it will be available for use by subsequent research projects.<\/p>\n

 <\/p>\n

Project website with the findings: www.mec-view.de<\/p>\n","protected":false},"excerpt":{"rendered":"

Pedestrians obscured from view by vehicles, cyclists passing in front of the car, buses that suddenly approach: negotiating city traffic can quickly become a difficult task. Of all things, it could be streetlights that make urban traffic safer and provide automated vehicles with an overview of the traffic situation. This was the subject of the […]<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_jetpack_newsletter_access":"","_jetpack_dont_email_post_to_subs":false,"_jetpack_newsletter_tier_id":0,"_jetpack_memberships_contains_paywalled_content":false,"_jetpack_memberships_contains_paid_content":false,"footnotes":"","jetpack_publicize_message":"","jetpack_publicize_feature_enabled":true,"jetpack_social_post_already_shared":true,"jetpack_social_options":{"image_generator_settings":{"template":"highway","default_image_id":0,"font":"","enabled":false},"version":2},"jetpack_post_was_ever_published":false},"categories":[15,46],"tags":[],"class_list":["post-3087","post","type-post","status-publish","format-standard","hentry","category-automotive","category-connected"],"jetpack_publicize_connections":[],"jetpack_featured_media_url":"","jetpack_sharing_enabled":true,"jetpack_shortlink":"https:\/\/wp.me\/p79TdE-NN","jetpack-related-posts":[{"id":3032,"url":"http:\/\/tomdenton.org\/blog\/?p=3032","url_meta":{"origin":3087,"position":0},"title":"Staying on track despite malfunctions","author":"Tom Denton","date":"April 2, 2020","format":false,"excerpt":"How driverless shuttles get safely from A to B Project 3F presents its results on automated driving at low speed On course: vehicles can continue driving in spite of altered circumstances along theroute and technical failures in the system On board: people and goods transported on test grounds in Renningen\u2026","rel":"","context":"In "Automotive"","block_context":{"text":"Automotive","link":"http:\/\/tomdenton.org\/blog\/?cat=15"},"img":{"alt_text":"","src":"https:\/\/i0.wp.com\/tomdenton.org\/blog\/wp-content\/uploads\/2020\/04\/20190311mst_07305508x3097_img_w1600-768x432.jpg?resize=350%2C200","width":350,"height":200,"srcset":"https:\/\/i0.wp.com\/tomdenton.org\/blog\/wp-content\/uploads\/2020\/04\/20190311mst_07305508x3097_img_w1600-768x432.jpg?resize=350%2C200 1x, https:\/\/i0.wp.com\/tomdenton.org\/blog\/wp-content\/uploads\/2020\/04\/20190311mst_07305508x3097_img_w1600-768x432.jpg?resize=525%2C300 1.5x, https:\/\/i0.wp.com\/tomdenton.org\/blog\/wp-content\/uploads\/2020\/04\/20190311mst_07305508x3097_img_w1600-768x432.jpg?resize=700%2C400 2x"},"classes":[]},{"id":2808,"url":"http:\/\/tomdenton.org\/blog\/?p=2808","url_meta":{"origin":3087,"position":1},"title":"Automated driving in cities","author":"Tom Denton","date":"July 12, 2018","format":false,"excerpt":"Bosch and Daimler select Nvidia AI platform Bosch and Daimler to source Drive Pegasus platform AI processors and software supplied by the U.S. AI computing company Nvidia Systems architectures for fully automated and driverless urban driving must be versatile, redundant, and fail-operational. 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