Towards Reliable Multisensory Perception and Its Automotive Applications

Autonomous driving poses numerous challenging problems, one of which is perceiving and understanding the environment. Since self-driving is safety critical and many actions taken during driving rely on the outcome of various perception algorithms (for instance all traffic participants and infrastructural objects in the vehicle's surroundings must reliably be recognized and localized), thus the perception might be considered as one of the most critical subsystems in an autonomous vehicle. Although the perception itself might further be decomposed into various sub-problems, such as object detection, lane detection, traffic sign detection, environment modeling, etc. In this paper the focus is on fusion models in general (giving support for multisensory data processing) and some related automotive applications such as object detection, traffic sign recognition, end-to-end driving models and an example of taking decisions in multi-criterial traffic situations that are complex for both human drivers and for the self-driving vehicles as well

Design and Analysis of the Trajectory of an Overtaking Maneuver Performed by Autonomous Vehicles Operating with Advanced Driver-Assistance Systems (ADAS) and Driving on a Highway

Overtaking is a maneuver that consists of passing another vehicle traveling on the same trajectory, but at a slower speed. Overtaking is considered one of the most dangerous, delicate and complex maneuvers performed by a vehicle, as it requires a quick assessment of the distance and speed of the vehicle to be overtaken, and also the estimation of the available space for the maneuver. In particular, most drivers have difficulty overtaking a vehicle in the presence of vehicles coming on other trajectories. To solve these overtaking problems, this article proposes a method of performing safe, autonomous-vehicle maneuvers through the PreScan simulation program. In this environment, the overtaking-maneuver scenario (OMS) is composed of highway infrastructure, vehicles and sensors. The proposed OMS is based on the solution of minimizing the risks of collision in the presence of any oncoming vehicle during the overtaking maneuver. It is proven that the overtaking maneuver of an autonomous vehicle is safe to perform through the use of advanced driver-assistance systems (ADAS) such as adaptive cruise control (ACC) and technology-independent sensors (TIS) that detect the driving environment of the maneuver

Jelzőtábla-felismerő rendszerek vizsgálata különös tekintettel a sebességkorlátozásokra = Investigation of traffic sign recognition systems with special regard to speed limits = Untersuchung von Verkehrschild-Erkennungssystemen unter besonderer Berücksichtigung von Geschwindigkeitsbegrenzungen

Napjaink legégetőbb problémái közé tartoznak a közúti közlekedési balesetek, amelyek számos emberéletet követelnek. A közúti balesetek jelentős része valamilyen emberi mulasztás miatt következik be, így ezek elkerülésére, valamint az esetleges bekövetkezett károk mértékének csökkentése érdekében fejlesztették ki az úgynevezett vezetést támogató ADAS rendszereket. A rendszerek által használt szenzorok megkönnyítik a járművezetők tájékozódását, valamint jelentősen csökkentik a már bekövetkezett balesetek súlyosságát