Connected Automated Driving

Abstract

Vehicle automation and vehicle connectivity are among the most fascinating trends in automotive electronics. These trends are considered individually but foremost the potential of their combination is discussed. We investigate which sensor configurations may be sufficient for automated vehicles. We show that cognitive and autonomous vehicles with a few close-to-market sensors are feasible. Vision plays the dominant role in our autonomous vehicle. We completely avoid bulky on-roof mounted sensors. The sensor suite enables the vehicle to perceive its environment and automatically navigate through everyday's traffic. The augmentation of sensor information by prior knowledge from digital maps is elaborated. Real-time automated decision-making and trajectory planning methods are outlined. The potential of cooperative information exchange and distributed decision in traffic is outlined. Extensive experiments are shown in real world scenarios from our AnnieWAY vehicle, the winner of the 2011 and second winner of the 2016 Grand Cooperative Driving Challenge, and from the Bertha vehicle that drove autonomously on the 104 km of the Bertha Benz memorial route from Mannheim to Pforzheim through a highly populated area of Germany.