Armin Joos

Making Bertha Drive?An Autonomous Journey on a Historic Route

125 years after Bertha Benz completed the first overland journey in automotive history, the Mercedes Benz S-Class S 500 INTELLIGENT DRIVE followed the same route from Mannheim to Pforzheim, Germany, in fully autonomous manner. The autonomous vehicle was equipped with close-to-production sensor hardware and relied solely on vision and radar sensors in combination with accurate digital maps to obtain a comprehensive understanding of complex traffic situations. The historic Bertha Benz Memorial Route is particularly challenging for autonomous driving. The course taken by the autonomous vehicle had a length of 103 km and covered rural roads, 23 small villages and major cities (e.g. downtown Mannheim and Heidelberg). The route posed a large variety of difficult traffic scenarios including intersections with and without traffic lights, roundabouts, and narrow passages with oncoming traffic. This paper gives an overview of the autonomous vehicle and presents details on vision and radar-based perception, digital road maps and video-based self-localization, as well as motion planning in complex urban scenarios.

Active Pedestrian Safety by Automatic Braking and Evasive Steering

Active safety systems hold great potential for reducing accident frequency and severity by warning the driver and/or exerting automatic vehicle control ahead of crashes. This paper presents a novel active pedestrian safety system that combines sensing, situation analysis, decision making, and vehicle control. The sensing component is based on stereo vision, and it fuses the following two complementary approaches for added robustness: 1) motion-based object detection and 2) pedestrian recognition. The highlight of the system is its ability to decide, within a split second, whether it will perform automatic braking or evasive steering and reliably execute this maneuver at relatively high vehicle speed (up to 50 km/h). We performed extensive precrash experiments with the system on the test track (22 scenarios with real pedestrians and a dummy). We obtained a significant benefit in detection performance and improved lateral velocity estimation by the fusion of motion-based object detection and pedestrian recognition. On a fully reproducible scenario subset, involving the dummy that laterally enters into the vehicle path from behind an occlusion, the system executed, in more than 40 trials, the intended vehicle action, i.e., automatic braking (if a full stop is still possible) or automatic evasive steering.

Lane keeping based on location technology

Vehicle positioning with an accuracy of 10 cm or less will enable lane-keeping assistance in addition to other safety benefits when an enhanced lane-level digital map is in place. With constantly evolving technology and sensors, a high-precision positioning system that fits into the automotive market can be expected within the next decade. Such a system will incorporate Global Positioning System (GPS) and inertial system (INS) for enhanced positioning performance and availability. In this paper, the technology fields that will have a significant impact on the deployment of a centimeter-level vehicle-positioning system will be discussed. Vision-based lane-recognition (VBLR) systems are relatively mature and have already been introduced to the market for lane-departure warning, etc. However, both systems have some limitations. GPS/INS-based systems may suffer from frequent satellite signal masking or blockage, while vision-based systems do not work well in adverse weather conditions or with poor lane signature. Effectively combining these two technologies can make a robust lane-departure warning system. A precision map was made for the test area near Stuttgart using DaimlerChrysler Research and Technology North America (RTNA)s map-making approach. A Mercedes S-class equipped with both a vision system and a high-precision GPS/INS was used for the test. The positioning map-matching results and the vision offset are compared and the complementary effectiveness is illustrated.

Autonomes Fahren auf der historischen Bertha-Benz-Route

Zusammenfassung Im Jahre 1888 trat Bertha Benz die erste Überlandfahrt in der Geschichte des Automobils an. 125 Jahre später wiederholte die Mercedes Benz S-Klasse S 500 Intelligent Drive diese historische Fahrt von Mannheim nach Pforzheim – selbständig, ohne Fahrereingriff und im realen Verkehr. Die Bertha-Benz-Route ist 103 km lang und zeichnet sich durch eine breite Vielfalt von zu bewältigenden Fahrsituationen aus, die repräsentativ für den heutigen Alltagsverkehr sind. Die Strecke beinhaltet die Innenstädte von Mannheim und Heidelberg sowie die Durchfahrung von 23 Ortschaften und kleineren Städten. Zu den Situationen, die ein autonomes Fahrzeug auf der Bertha-Benz-Route beherrschen muss, gehören z. B. Kreisverkehre, Kreuzungen mit und ohne Ampelanlagen, Zebrastreifen, Überholen von Radfahrern oder enge Ortsdurchfahrten mit entgegenkommendem Verkehr. Eine Besonderheit des vorgestellten Projektes war die ausschließliche Verwendung seriennaher Sensorik. Kameras und Radarsensoren in Verbindung mit einer präzisen digitalen Karte ermöglichten die Erfassung des Fahrzeugumfelds auch in komplexen Situationen. Dieser Artikel liefert eine Systemübersicht des Fahrzeugs. Er beschreibt die kamerabasierte Umgebungswahrnehmung, die verwendeten digitalen Karten und die kartenrelative Selbstlokalisierung sowie die Manöverplanung in komplexen Verkehrsszenarien.