Ultra-Reliable Low Latency Communication (uRLLC) is key to provide communication between autonomous vehicles and 5G cellular networks. Paving the vehicle communication with uRLLC Having good connectivity at the speed of light provided by 5G network enables quick data processing and decision-making ahead of the time. With this, they are able to see few metres ahead of what speed is required to reach the next green light making the driving more efficient. Here cars are more likely to chase the ‘green-wave' in the city. ‘Traffic Light Information’ is a novel Vehicle-to-Infrastructure (V2I) service initiated by Audi in Europe. By the time it reaches the traffic signal, the signal would have turn to green from red signal thus reducing its waiting time on the signal. V2X, Telematics, and 4G/5G connections make it possible for the autonomous cars to see obstacles around corners and beyondĬonnectivity between cars and the traffic infrastructure enables cars to be one step ahead by building awareness like there is a slow-moving traffic and will slow down its speed automatically with information processed through inbuilt Advanced Driver Assistance Systems (ADAS). Evidence suggests manufacturers anticipate difficulties in achieving significant ROI using autonomous technology as remarkable number of consumers in nations like United States (38percent), Japan (31percent), and Germany (50percent) are reluctant to make additional investments for vehicles enabled with this autonomous feature.įollowing are the reasons why we think that 5G low latency data connections are critical for AVs? This rule needs to be amended in countries giving consent to permit level 5 vehicles on the roads.ĭetermining monetization value of sensors used in 5G network self-driving cars is hard as sometimes data aggregated by OEMs is really poor quality or overestimated value. The 1968 Vienna protocol specifies that a human driver should be always in vehicle’s control and is responsible for its behaviour in traffic. Fully autonomous driving in level 5 will require change in national as well as international law and many countries have taken measures to create legislation in order to test autonomous cars on public roads. The inception of 5G autonomous vehicles poses many legal questions, like who is going to be charged in case of an accident? In level 5 vehicles, there is no control of the driver creating liabilities for the automobile manufacturers. It is even complex to predict human error, for instance, when a person indicates a left and then move towards right. Self-driving cars find it hard when it comes to understand the semantics of the situation, the behaviour of other objects on the road and signals like brake lights. In terms of safety, the biggest challenge for autonomous vehicles is that it is unable to predict agent behaviour.
Creating and maintaining the maps across all the roads is difficult and is time intensive process. Self-driving cars rely on maps to navigate that is created by using cameras and lidars to map the territory in detail. However, they are restricted from being used as OEM vehicle sensors due to its limitation in range capacity. These sensors are mainly applied in relatively low speed ADAS modules such as detection of obstacles in traffic congested areas and parking space detection and assistance. Short range sensors also called as ultrasonic sensors (typical ~2m) sends ultrasonic waves to detect echoes from the objects/obstacles using transmitter-receiver pair. However, laser beams do not provide accurate results in weather conditions like snow, smoke, fog or smog and is expensive due to its costs equivalent to ten times the cost of radar and camera sensors.
Lidar is the other sensor that has proved to be quite useful for full driverless capability with much higher resolution in order to detect any object around the car’s surroundings. Radar uses radio waves to detect vehicles/objects and is accurate in all conditions of visibility but is unable to differentiate objects’ type without a human driver due to its longer wavelength. Camera-based sensors are unable to detect objects in foggy areas, rain or in the night. However, each of the sensors have their own limitations. Challenges involved in deploying autonomous vehicles without data connectivity or 5GĪutonomous Vehicles work on four primary sensors camera, ultrasonics, radar and lidar.