Axel Gern

Advanced lane recognition-fusing vision and radar

One major problem of the common vision-based lane recognition systems is their susceptibility to weather. These problems mainly stem from the fact, that they only look for road structures. From the position of other cars in front, the run of the curve can be estimated. This paper presents our fusion approach, that takes leading vehicles into account which have been detected by radar. The Kalman filter applied here does not only deliver improved measurements of the run of the curve, but also a precise estimate of the lateral position of the observed cars. This information can be used to improve the lane assignment of ACC systems.

Robust vehicle tracking fusing radar and vision

Many driver assistance systems are based on vehicle detection and tracking including adaptive cruise control, collision warning and fully autonomous driving. A large detection range is required, especially while driving at higher speeds on highways. A reliable and precise detection is needed even under adverse weather conditions. In this paper we present a fusion approach combining radar and monocular image processing. The approach enables one to track vehicles up to a distance of 130 m and to assign them reliably to specific lanes.

Vision-based lane recognition under adverse weather conditions using optical flow

Lane recognition is the basis for many driver assistance systems, including lane departure warning (LDW), the assignment of vehicles to specific lanes and fully autonomous driving. A major problem of common vision-based lane recognition systems is their susceptibility to weather. Especially when driving in adverse weather conditions such as rain or snow it is difficult to estimate the road course. The contrast between the white lane markings and the pavement is poor, sometimes the colors of the markings are negated. Furthermore the range of sight is reduced enormously causing a bad prediction of the lane parameters, particularly the curvature. We present a solution which relies not only on finding white markings. Correlating structures parallel to the road over time the horizontal optical flow is calculated. It is then integrated in the lane recognition system estimating the position of the vehicle within the lane and the curvature parameters of the road ahead. The system allows to assign obstacles detected by radar or vision reliably to specific lanes and to drive laterally controlled autonomously even under adverse weather conditions.

CHAUFFEUR Assistant: a driver assistance system for commercial vehicles based on fusion of advanced ACC and lane keeping

This paper presents the integrated approach for environment perception and vehicle control developed for the CHAUFFEUR Assistant application. Using a combination of radar and video sensor, the sensor fusion approach provides the vehicle controllers with valuable data about preceding vehicles and about the lane. These controllers guide the truck to stay in the lane and keep a short but still safe distance to the preceding vehicle.

6 – From door to door — principles and applications of computer vision for driver assistant systems

Publisher Summary In this chapter, the achievements in vision-based driver assistance at DaimlerChrysler are described. The chapter presents the systems that have been developed for both highways and urban traffic, and describe principles that have proven robustness and efficiency for image understanding in traffic scenes. The development of computer vision systems for cars is promoted for three main reasons: safety, convenience, and efficiency. At least three guiding principles have emerged for robust vision-based driver assistant systems: (1) vision in cars is vision over time; (2) stereo vision providing 3D information became a central component of robust vision systems; and (3) object recognition can be considered as a classification problem. Besides continuous improvement of the robustness of the image analysis modules, sensor problems have to be overcome. As other information sources, such as radar, digital maps, and communication become available in modern cars, their utilization will help to raise the performance of vision based environment perception.

Detecting reflection posts - lane recognition on country roads

This paper presents a new approach to the challenging task of lane recognition on general roads. Lane recognition is the basis for many driver assistance systems, including lane departure warning and the assignment of vehicles to specific lanes. Most systems of the past are designed for the well defined highway scenario. They rely on white lane markings with known geometric appearance. Our method is an extension which also works when lane markings are in bad conditions or missing completely. We use reflection posts as a means of estimating the course of the road. In addition we are furthermore able to measure the horizontal and vertical slope of the road surface.

The Comfort Highway Copilot-An Advanced Driving Assistance System

Abstract In this paper the DaimlerChrysler contribution to the project Driving Assistance Strategies which was a part of the German joint research programme MoTiV (Mobility and Transportation within an intermodal traffic) is presented. To support the driver in highway driving tasks an advanced driving assistance system was developed at DaimlerChrysler which combines the longitudinal and lateral vehicle guidance. An experimental vehicle was equipped with image processing and an electronic steering system. To explore the acceptance and handling of this driving assistance system a Man Machine Interface with different user versions was developed. In order to ensure the highest system safety level an extensive safety process was performed. The paper concludes in the main results of the field tests regarding the acceptance of the tested advanced driving assistance systems.

Realzeitfähige Multiagentenarchitektur für autonome Fahrzeuge

Das Aufgabengebiet des Autonomen Fahrens bringt neben Herausforderungen bei der Bildverarbeitung und den HardwareKomponenten auch zahlreiche Anspruche an die Software-Architektur mit sich. Dies gilt umso mehr, je komplexer und umfangreicher diese Systeme aufgebaut sind.