Drivers of heavy goods vehicles are not able to survey the whole surrounding area of their vehicle due to large blind spot regions. This paper shows how catadioptric cameras—a combination of cameras and mirrors—can be used to survey the surrounding area of vehicles. Four such cameras were mounted on a truck–trailer combination, and the images are combined such that obstacles are visible in an image presented to the driver. This image is a bird's eye view of the vehicle. Additionally, corridors indicating the path of motion of the vehicle are overlaid to the resulting image. To compute those corridors, a mathematical description of the path of motion is derived. Such a system does not only support the driver during maneuvering tasks but also increases safety of driving large vehicles.

Omnidirectional cameras are well suited for maneuvering tasks due to to their large field of view. We mounted two catadioptric cameras on a vehicle and provide the driver with a bird's-eye view of the surrounding area behind the vehicle as well as the area on the left and right hand side. In order to enlarge the field of view of the bird's-eye view image, we will show an extension to the bird's-eye view image that provides a larger field of view and thus simplifies challenging maneuvering tasks. An overlay onto the resulting image shows the motion path of the vehicle while reversing. This motion path is connected to the steering angle. The driver can easily see where the vehicle will move when the steering angle is not changed throughout the movement.

Omnidirectional cameras are leaving the scientific labs to be used in market applications. Many such application areas like robotics and automotive need very accurate models of the image formation. When a car or robot motion is controlled by an omnidirectional camera system, the exact control of action depends on a reliable calibration. An unprecise calibration can cause costly or hazardous consequences for man and machine. Therefore, we developed an omnidirectional camera model that can deal with parabolic and hyperbolic mirrors in combination with distorting lenses. It has the adequate complexity to allow both, precision and robustness of the calibration process. We successfully applied this model to our driver assistance systems of future light and heavy trucks.

Maneuvering large vehicles like trucks is a challenging task because their drivers often cannot see the closest surrounding area of the vehicle. This paper presents a system providing the driver with a bird's-eye view of the surrounding area on a single display. This view is constructed by stitching together cutouts from two omnidirectional images acquired by catadioptric cameras, which are placed below the side mirrors. The geometry of the cameras is analyzed with respect to the formation of blind spots. We illustrate how to select the cutouts in order to eliminate completely the blind spots in the bird's-eye view