The Goal
Demonstrate the potential of 5G technology for cooperative driving applications within an EU-wide, inter-corporational project named 5G Carmen.
The Solution
We provided the onboard software and maneuvering algorithms for Cooperative Lane Management (CLM), enabling coordinated actions like autonomous overtaking and lane merging.
The Impact
Identification of further challenges to achieve smooth cross-border cooperative driving. The basis for more targeted research funding in the future has been created.
Leveraging 5G for Autonomous Driving
What are the advantages of 5G for automotive applications? And more specifically: What are the implications of 5G for autonomous driving? These were the overarching questions of our joint Cooperative Lane Management (CLM) project with members of the 5G Carmen consortium.
5G Carmen is an EU-wide project with many participants for a bigger scope. The goal: To demonstrate the potential of 5G technology for automotive applications, seamlessly crossing borders and connecting vehicles on the road with 5G. The objective of the sub-project CLM was to create a system that allows cars to perform autonomous coordinated actions, like overtaking and lane merging. The system had to be scalable to hundreds, even thousands of cars, to enable use cases like efficient traffic control on a large road section.
On A Joint Mission
One of the most interesting, but also challenging aspects of this project, was the level of international and inter-corporational collaboration. To tackle the big scope of the project objective, we teamed up with a broad range of industry experts (Nokia, Qualcomm, BMW, Stellantis, and many more) for approximately one year.
The whole system was made of many components that work together as a data pipeline. Motius provided the crucial parts of the algorithm: the onboard software and the maneuvering service. Meanwhile, other partners provided the infrastructure that enables the transport of data.
A Precise GNSS System & Edge Computing
Now let’s get to the exciting technical stuff! The onboard software runs on each car and collects information about the car: GPS position, speed, and the indicator status. The GPS position is provided by a Motius-developed precision GNSS system that tracks the car with an accuracy of a few centimeters.
Each car sends these informations to the maneuvering service which implements an algorithm to control each car’s speed for the optimal procedure of the maneuver. Now the magic can happen: In case of overtaking, the maneuvering service will open up a gap between two cars and merge the overtaking car in between.
The system is locally using a centralized approach, which means that each car has its own 5G connectivity and sends data to a central maneuvering service. The maneuvering service is deployed on edge computing units called MECs. These MECs are physically located very close to the mobile network stations to minimize network transport times. By design, there are many MECs deployed along the Autobahn, so each MECs only needs to handle the traffic that is close to its location. So far, so good. But does it work?
Testing at the Austrian-German Border
To finish the project, we needed some proper testing. This is why we met up with BMW (one of our 5G Carmen project partners) to see our software working in a real-life scenario. The final demo shows an overtaking scenario on a public road, demonstrating it in a real-world environment. Because of legal reasons, the cars are still required to have real drivers, but the drivers are following the instructions that are being sent by the CLM system.
The goal of the final demo was to show the capability of the system running on public roads in proximity to the German-Austrian border. On each side of the border, there is a MEC deployed that takes over the maneuvering depending on which side of the border the maneuver takes place. The driver or user will not notice the handover of responsibilities. Also, we used this opportunity to record data from the maneuvers that allow us to analyze the advantages of 5G over 4G.
Want to build products of the future?
The Goal
Demonstrate the potential of 5G technology for cooperative driving applications within an EU-wide, inter-corporational project named 5G Carmen.
The Solution
We provided the onboard software and maneuvering algorithms for Cooperative Lane Management (CLM), enabling coordinated actions like autonomous overtaking and lane merging.
The Impact
Identification of further challenges to achieve smooth cross-border cooperative driving. The basis for more targeted research funding in the future has been created.
Leveraging 5G for Autonomous Driving
What are the advantages of 5G for automotive applications? And more specifically: What are the implications of 5G for autonomous driving? These were the overarching questions of our joint Cooperative Lane Management (CLM) project with members of the 5G Carmen consortium.
5G Carmen is an EU-wide project with many participants for a bigger scope. The goal: To demonstrate the potential of 5G technology for automotive applications, seamlessly crossing borders and connecting vehicles on the road with 5G. The objective of the sub-project CLM was to create a system that allows cars to perform autonomous coordinated actions, like overtaking and lane merging. The system had to be scalable to hundreds, even thousands of cars, to enable use cases like efficient traffic control on a large road section.
On A Joint Mission
One of the most interesting, but also challenging aspects of this project, was the level of international and inter-corporational collaboration. To tackle the big scope of the project objective, we teamed up with a broad range of industry experts (Nokia, Qualcomm, BMW, Stellantis, and many more) for approximately one year.
The whole system was made of many components that work together as a data pipeline. Motius provided the crucial parts of the algorithm: the onboard software and the maneuvering service. Meanwhile, other partners provided the infrastructure that enables the transport of data.
A Precise GNSS System & Edge Computing
Now let’s get to the exciting technical stuff! The onboard software runs on each car and collects information about the car: GPS position, speed, and the indicator status. The GPS position is provided by a Motius-developed precision GNSS system that tracks the car with an accuracy of a few centimeters.
Each car sends these informations to the maneuvering service which implements an algorithm to control each car’s speed for the optimal procedure of the maneuver. Now the magic can happen: In case of overtaking, the maneuvering service will open up a gap between two cars and merge the overtaking car in between.
The system is locally using a centralized approach, which means that each car has its own 5G connectivity and sends data to a central maneuvering service. The maneuvering service is deployed on edge computing units called MECs. These MECs are physically located very close to the mobile network stations to minimize network transport times. By design, there are many MECs deployed along the Autobahn, so each MECs only needs to handle the traffic that is close to its location. So far, so good. But does it work?
Testing at the Austrian-German Border
To finish the project, we needed some proper testing. This is why we met up with BMW (one of our 5G Carmen project partners) to see our software working in a real-life scenario. The final demo shows an overtaking scenario on a public road, demonstrating it in a real-world environment. Because of legal reasons, the cars are still required to have real drivers, but the drivers are following the instructions that are being sent by the CLM system.
The goal of the final demo was to show the capability of the system running on public roads in proximity to the German-Austrian border. On each side of the border, there is a MEC deployed that takes over the maneuvering depending on which side of the border the maneuver takes place. The driver or user will not notice the handover of responsibilities. Also, we used this opportunity to record data from the maneuvers that allow us to analyze the advantages of 5G over 4G.
Want to build products of the future?
The Goal
Demonstrate the potential of 5G technology for cooperative driving applications within an EU-wide, inter-corporational project named 5G Carmen.
The Solution
We provided the onboard software and maneuvering algorithms for Cooperative Lane Management (CLM), enabling coordinated actions like autonomous overtaking and lane merging.
The Impact
Identification of further challenges to achieve smooth cross-border cooperative driving. The basis for more targeted research funding in the future has been created.
Leveraging 5G for Autonomous Driving
What are the advantages of 5G for automotive applications? And more specifically: What are the implications of 5G for autonomous driving? These were the overarching questions of our joint Cooperative Lane Management (CLM) project with members of the 5G Carmen consortium.
5G Carmen is an EU-wide project with many participants for a bigger scope. The goal: To demonstrate the potential of 5G technology for automotive applications, seamlessly crossing borders and connecting vehicles on the road with 5G. The objective of the sub-project CLM was to create a system that allows cars to perform autonomous coordinated actions, like overtaking and lane merging. The system had to be scalable to hundreds, even thousands of cars, to enable use cases like efficient traffic control on a large road section.
On A Joint Mission
One of the most interesting, but also challenging aspects of this project, was the level of international and inter-corporational collaboration. To tackle the big scope of the project objective, we teamed up with a broad range of industry experts (Nokia, Qualcomm, BMW, Stellantis, and many more) for approximately one year.
The whole system was made of many components that work together as a data pipeline. Motius provided the crucial parts of the algorithm: the onboard software and the maneuvering service. Meanwhile, other partners provided the infrastructure that enables the transport of data.
A Precise GNSS System & Edge Computing
Now let’s get to the exciting technical stuff! The onboard software runs on each car and collects information about the car: GPS position, speed, and the indicator status. The GPS position is provided by a Motius-developed precision GNSS system that tracks the car with an accuracy of a few centimeters.
Each car sends these informations to the maneuvering service which implements an algorithm to control each car’s speed for the optimal procedure of the maneuver. Now the magic can happen: In case of overtaking, the maneuvering service will open up a gap between two cars and merge the overtaking car in between.
The system is locally using a centralized approach, which means that each car has its own 5G connectivity and sends data to a central maneuvering service. The maneuvering service is deployed on edge computing units called MECs. These MECs are physically located very close to the mobile network stations to minimize network transport times. By design, there are many MECs deployed along the Autobahn, so each MECs only needs to handle the traffic that is close to its location. So far, so good. But does it work?
Testing at the Austrian-German Border
To finish the project, we needed some proper testing. This is why we met up with BMW (one of our 5G Carmen project partners) to see our software working in a real-life scenario. The final demo shows an overtaking scenario on a public road, demonstrating it in a real-world environment. Because of legal reasons, the cars are still required to have real drivers, but the drivers are following the instructions that are being sent by the CLM system.
The goal of the final demo was to show the capability of the system running on public roads in proximity to the German-Austrian border. On each side of the border, there is a MEC deployed that takes over the maneuvering depending on which side of the border the maneuver takes place. The driver or user will not notice the handover of responsibilities. Also, we used this opportunity to record data from the maneuvers that allow us to analyze the advantages of 5G over 4G.
Want to build products of the future?
The Goal
Demonstrate the potential of 5G technology for cooperative driving applications within an EU-wide, inter-corporational project named 5G Carmen.
The Solution
We provided the onboard software and maneuvering algorithms for Cooperative Lane Management (CLM), enabling coordinated actions like autonomous overtaking and lane merging.
The Impact
Identification of further challenges to achieve smooth cross-border cooperative driving. The basis for more targeted research funding in the future has been created.
Leveraging 5G for Autonomous Driving
What are the advantages of 5G for automotive applications? And more specifically: What are the implications of 5G for autonomous driving? These were the overarching questions of our joint Cooperative Lane Management (CLM) project with members of the 5G Carmen consortium.
5G Carmen is an EU-wide project with many participants for a bigger scope. The goal: To demonstrate the potential of 5G technology for automotive applications, seamlessly crossing borders and connecting vehicles on the road with 5G. The objective of the sub-project CLM was to create a system that allows cars to perform autonomous coordinated actions, like overtaking and lane merging. The system had to be scalable to hundreds, even thousands of cars, to enable use cases like efficient traffic control on a large road section.
On A Joint Mission
One of the most interesting, but also challenging aspects of this project, was the level of international and inter-corporational collaboration. To tackle the big scope of the project objective, we teamed up with a broad range of industry experts (Nokia, Qualcomm, BMW, Stellantis, and many more) for approximately one year.
The whole system was made of many components that work together as a data pipeline. Motius provided the crucial parts of the algorithm: the onboard software and the maneuvering service. Meanwhile, other partners provided the infrastructure that enables the transport of data.
A Precise GNSS System & Edge Computing
Now let’s get to the exciting technical stuff! The onboard software runs on each car and collects information about the car: GPS position, speed, and the indicator status. The GPS position is provided by a Motius-developed precision GNSS system that tracks the car with an accuracy of a few centimeters.
Each car sends these informations to the maneuvering service which implements an algorithm to control each car’s speed for the optimal procedure of the maneuver. Now the magic can happen: In case of overtaking, the maneuvering service will open up a gap between two cars and merge the overtaking car in between.
The system is locally using a centralized approach, which means that each car has its own 5G connectivity and sends data to a central maneuvering service. The maneuvering service is deployed on edge computing units called MECs. These MECs are physically located very close to the mobile network stations to minimize network transport times. By design, there are many MECs deployed along the Autobahn, so each MECs only needs to handle the traffic that is close to its location. So far, so good. But does it work?
Testing at the Austrian-German Border
To finish the project, we needed some proper testing. This is why we met up with BMW (one of our 5G Carmen project partners) to see our software working in a real-life scenario. The final demo shows an overtaking scenario on a public road, demonstrating it in a real-world environment. Because of legal reasons, the cars are still required to have real drivers, but the drivers are following the instructions that are being sent by the CLM system.
The goal of the final demo was to show the capability of the system running on public roads in proximity to the German-Austrian border. On each side of the border, there is a MEC deployed that takes over the maneuvering depending on which side of the border the maneuver takes place. The driver or user will not notice the handover of responsibilities. Also, we used this opportunity to record data from the maneuvers that allow us to analyze the advantages of 5G over 4G.