Abstract

Detection and tracking of other vehicles and lane geometry will be required for many future intelligent driver assistance systems. By integrating the estimation of these two features into a single filter, a more optimal utilization of the available information can be achieved. For example, it is possible to improve the lane curvature estimate during bad visibility by studying the motion of other vehicles. This paper derives and evaluates various approximations that are needed in order to deal with the non-linearities that are introduced by such an approach.

Abstract

large number of testing procedures have been developed to ensure vehicle safety in common and extreme driving situations. However, these conventional testing procedures are insufficient for testing autonomous vehicles. They have to handle unexpected scenarios with the same or less risk a human driver would take. Currently, safety related systems are not adequately tested, e.g. in collision avoidance scenarios with pedestrians. Examples are the change of pedestrian behaviour caused by interaction, environmental influences and personal aspects, which cannot be tested in real environments. It is proposed to use Virtual Reality techniques. This method can be seen as a new Pedestrian in the Loop testing procedure. ispartof: 2017 XXVI INTERNATIONAL CONFERENCE ON INFORMATION, COMMUNICATION AND AUTOMATION TECHNOLOGIES (ICAT) vol:2017-December ispartof: ICAT 2017 (International Conference on Information, Communication and Automation Technologies) location:Sarajevo, Bosnia & Herzegovina date:26 Oct - 28 Oct 2017 status: published Document type: Conference object

Abstract

ft need to be separated from other aircraft by either a minimum vertical distance of 1000ft or by a minimum horizontal distance of 5NM to avoid mid-air collisions. Traffic Alert and Collision Avoidance System (TCAS) work well as a tactical safety backups to avoid collision, but cannot perform separation assurance. This paper presents the design aspects of system that would predict separation infringement and provide flight crew with necessary guidance for maintaining separation. This paper discusses formulation of system function based on ADS-B, mathematical models, simulation and results. A system model has been implemented in MATLAB and various encounters with different speed ratios at various conflict angles has been fed as input to system model with a goal of avoidance and recovery to original waypoint. Both Heading and Speed maneuvers are evaluated and results are presented. The required strength of resolution maneuver as a function of conflict geometry is studied and automatic maneuver selection function is implemented in system model and maneuver selection function is evaluated with discussion of results.

Abstract

This paper presents a collision avoidance algorithm to prevent bird strikes for aircraft departing from an airport. By using trajectory-information of aircraft and birds, the algorithm predicts potential collisions. Collision avoidance is performed by delaying departing aircraft until they can follow a collision-free trajectory. An implementation of this concept has the potential to increase aviation safety by preventing bird strikes but might reduce runway capacity due to delaying aircraft. As a precursor to the feasibility, this study investigates the maximum achievable safety effect at minimum delay costs of such a system by assuming a deterministic world. Therefore, no uncertainties regarding bird and aircraft positions were considered to enable the system to prevent all bird strikes for departing traffic while causing the smallest possible delay. The anticipated effects were studied by running fast-time simulations including three air traffic intensities at a single-runway airport and bird movements from all seasons. The results imply a high potential for the increase in safety at a reasonable reduction in runway capacity. An initial cost-estimate even revealed a strong saving potential for the airlines. Based on these results, a feasibility study of implementing a bird strike advisory system including uncertainties in bird movements as well as probabilistic effects will be performed.

Abstract

© 2018 SAE International. All Rights Reserved. A large number of testing procedures have been developed to ensure vehicle safety in common and extreme driving situations. However, these conventional testing procedures are insufficient for testing autonomous vehicles. They have to handle unexpected scenarios with the same or less risk a human driver would take. Currently, safety related systems are not adequately tested, e.g. in collision avoidance scenarios with pedestrians. Examples are the change of pedestrian behaviour caused by interaction, environmental influences and personal aspects, which cannot be tested in real environments. It is proposed to use augmented reality techniques. This method can be seen as a new (Augmented) Pedestrian in the Loop testing procedure. ispartof: SAE Technical Papers vol:2018-April ispartof: WCX™: SAE World Congress Experience location:Detroit, Michigan, United States date:10 Apr - 14 Apr 2018 status: published Document type: Conference object

Abstract

Safety in the operations of UAVs (Unmanned Aerial Vehicles) depends on the current and future reduction of technical barriers and on the improvements related to their autonomous capabilities. Since the early stages, aviation has been based on pilots and Air Traffic Controllers that take decisions to make aircraft follow their routes while avoiding collisions. RPA (Remotely Piloted Aircraft) can still involve pilots as they are UAVs controlled from ground, but need the definition of common rules, of a dedicated Traffic Controller and exit strategies in the case of lack of communication between the Ground Control Station and the aircraft. On the other hand, completely autonomous aircraft are currently banned from civil airspace, but researchers and engineers are spending great effort in developing methodologies and technologies to increase the reliability of fully autonomous flight in view of a safe and efficient integration of UAVs in the civil airspace. This paper deals with the design of a collision avoidance system based on a Distributed Model Predictive Controller (DMPC) for trajectory tracking, where anticollision constraints are defined in accordance with the Right of Way rules, as prescribed by the International Civil Aviation Organization (ICAO) for human piloted flights. To reduce the computational burden, the DMPC is formulated as a Mixed Integer Quadratic Programming optimization problem. Simulation results are shown to prove the effectiveness of the approach, also in the presence of a densely populated airspace.

Abstract

International audience; The main ideas behind the design of CATS were to have a general purpose simulator able to be a stable basis for the development of other modules, representing different levels of Air Traffic Control and Air Traffic Management. The basic framework and hypothesis of the CATS simulator are introduced. Two approaches of automatic conflict resolution are detailed as examples. The first one deals with a centralized control system for high density areas and medium term (10 to 15 minutes ahead) control. The second one deals with an on board reactive short term (3 to 10 minutes ahead) automatic conflict solver. As both solvers use a conflict detection that is robust to uncertainties, a convex modeling of uncertainties is first introduced.

Abstract

International audience; As Air Traffic keeps increasing, many research programs focus on collision avoidance techniques. In this paper, a neural netwok learned by genetic algorithm is introduced to solve conflicts between two aircrafts. The learned NN is then tested on different conflicts and compared to the optimal solution. Results are very promising.