Challenge #2: Minimize ‘common cause’ errors and create true redundancy
These three systems – the main planner, fallback planner and supervisor – must be technically separated from one another, each with its own hardware, software and data sources. Otherwise, ‘common cause’ errors can occur because a change is misinterpreted by all three systems.
"So, to achieve true redundancy, it's important not just to copy systems," says Andreas Nagler. For example, the supervisor works with an object list to get a picture of the environment. To do this, the radar sensor scans all detectable nearby vehicles and objects, including the direction of movement. While the supervisor operates with the object list generated by the sensors, the two planners work directly with the raw data, such as point clouds from laser scanners (LiDAR).
The main and fallback planners also take advantage of what’s known as sensor data fusion. If only one sensor reports an object and all other sensors do not, the algorithm may decide that this signal can be ignored. The supervisor, however, considers the sensors in a strictly separated manner. Therefore, the individual systems each form their own impression, which, when combined, ensures safer behavior.
Challenge #3: Calculating the traffic flow
Weighing up potentially dangerous situations requires highly complex software that has to decide within seconds whether to react and, for example, change lanes unnecessarily and over-cautiously. Here, the software acts both directly and indirectly. The supervisor checks the paths calculated by the planners and predicts the path of travel for the next few meters, as well as a few seconds into the future. The second prediction is much more complex. It depends, among other things, on speed, road construction, weather conditions, and of the way in which other road users have driven in the past. The supervisor compares this with the trajectories of the path planners and changes them if the so-called ‘sovereignty zone’ around the vehicle should be violated.
Further challenges: Automated parking
Not only is there plenty of room for innovation on roads; parking is also an essential element in automated driving. For example: Will parking garages themselves take remote control over cars? You can find out more about upcoming possibilities and challenges – like preventing unauthorized access to a vehicle – in this Porsche Newsroom article.