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Most of the existing approaches for flight collision avoidance are concerned with local traffic alone for which the separation is based on the pairwise analysis of aircraft trajectory trends, which is not efficient with regard to some flight path requirements along waypoints. The purpose of this paper is to deal with the global collision avoidance problem which aims at separating aircraft taking into consideration the global traffic in a given area instead of considering them pairwise. It aims to model the concept of global collision avoidance and propose a validated algorithm for the purpose in the framework of free‐flight.

The collision avoidance procedure computes online the appropriate speed and heading for each aircraft, at each sampling time‐instant, to generate a collision‐free flight trajectory along scheduled waypoints. The method accounts for automatic assignment of priority indexes that are updated from one control time horizon to the next. The paper considers here the case of aircraft flying at the same altitude, but the proposed method is easily extendable to the general 3D situation. Owing to the predictive features that are inherent to collision avoidance, the collision‐free trajectories are generated using model predictive control approach. A simulation example is presented in the end and its results show the suitability of the proposed approach.

Since the model predictive control approach is used, the collision avoidance procedure is anticipative; therefore, the avoidance capability depends only on the prediction horizon rather than on the control horizon.

The computation of the trajectory guidance information (speed and heading) at each time‐step is fast, therefore the proposed method is well suited for online processing requirements in real world applications.

The paper provides a flexible modelling framework and a computationally effective algorithm, both based on model predictive control concepts, to cope with global collision avoidance for flight safety enhancement in the framework of free‐flight.

The objective of collision avoidance is to assure the separation of aircraft during flight operations — to avoid the situation occurring where two or more aircraft could occupy the same point in airspace at the same time. The problem centres on how best to avoid such a spatial conflict—through ground‐derived data and air traffic control, by means of air‐derived data and pilot judgment, or by some combination of the two? In the quest for a solution, many kinds of systems have been studied and prototype hardware built and tested. Some provided only partial answers; some might meet the safety needs but create implementation difficulties; several have demonstrated the potential for world‐wide application. It is with the last group that we are concerned here. Any collision avoidance system (CAS) selected must be one that meets international requirements; this implies that protection can be offered to all aircraft, that the CAS is compatible with other existing systems and that costs would not be excessive. It goes without saying that reliability must be very high to achieve international acceptance. Several approaches are in development in the United Kingdom and in the United States that could meet these criteria, according to their proponents. However, a controversy continues over which approach is best — one depending heavily on ground‐computed data, the other on air‐derived data. And, there are associated concerns with the presentation of data in the cockpit and the evasive‐manoeuvre capability offered. Finally, with regard to a developmental system favoured by both the United Kingdom and the United States, there appears to be serious divergence of opinions among critics of the system concept related to the impact of radio‐spectrum utilization on existing ICAO secondary surveillance radar standards. Because there is honest technical disagreement on what the optimum collision avoidance system should be, we have made the following pages available as a forum for discussion of the subject of those representing differing sides of the argument: air traffic control, CAS developers, the airlines, the air transport pilots, general aviation and radio frequency allocation. As is usual in the presentation in ICAO Bulletin, the views expressed herein are those of the authors and do not imply in any way acceptance or rejection of those views by ICAO.

The presentation of in-vehicle warnings information at risky driving scenarios is aimed to improve the collision avoidance ability of drivers. Existing studies have found that driver’s collision avoidance performance is affected by both warning information and driver’s workload. However, whether moderation and mediation effects exist among warning information, driver’s cognition, behavior and risky avoidance performance is unclear.

This purpose of this study is to examine whether the warning information type modifies the relationship between the forward collision risk and collision avoidance behavior. A driving simulator experiment was conducted with waring and command information.

Results of 30 participants indicated that command information improves collision avoidance behavior more than notification warning under the forward collision risky driving scenario. The primary reason for this is that collision avoidance behavior can be negatively affected by the forward collision risk. At the same time, command information can weaken this negative effect. Moreover, improved collision avoidance behavior can be achieved through increasing drivers’ mental workload.

The proposed model provides a comprehensive understanding of the factors influencing collision avoidance behavior, thus contributing to improved in-vehicle information system design.

The significant moderation effects evoke the fact that information types and mental workloads are critical in improving drivers’ collision avoidance ability. Through further calibration with larger sample size, the proposed structural model can be used to predict the effect of in-vehicle warnings in different risky driving scenarios.

Wheeled mobile robots (WMR) are the most widely used robots. Avoiding obstacles in unstructured environments, especially dynamic obstacles such as pedestrians, is a serious challenge for WMR. This paper aims to present a hybrid obstacle avoidance method that combines an informed-rapidly exploring random tree* algorithm with a three-dimensional (3D)-object detection approach and model prediction controller (MPC) to conduct obstacle perception, collision-free path planning and obstacle avoidance for WMR in unstructured environments.

Given a reference orientation and speed, the hybrid method uses parametric ellipses to represent obstacle expansion boundaries based on the 3D target detection results, and a collision-free reference path is planned. Then, the authors build on a model predictive control for tracking the collision-free reference path by incorporating the distance between the robot and obstacles. The proposed framework is a mapless method for WMR.

The authors present experimental results with a mobile robot for obstacle avoidance in indoor environments crowded with obstacles, such as chairs and pedestrians. The results show that the proposed hybrid obstacle avoidance method can satisfy the application requirements of mobile robots in unstructured environments.

In this study, the parameter ellipse is used to represent the area occupied by the obstacle, which takes the velocity as the parameter. Therefore, the motion direction and position of dynamic obstacles can be considered in the planning stage, which enhances the success rate of obstacle avoidance. In addition, the distance between the obstacle and robot is increased in the MPC optimization function to ensure a safe distance between the robot and the obstacle.

The purpose of this paper is to realize a smooth and secure brake assistance system to avoid rear‐end collision of automobiles.

It is important to judge necessity of deceleration assistance as early as possible and initiate the assistance naturally in order to reduce rear‐end crashes. However, it easily results in driver's discomfort. In addition, deceleration profile of the automatic braking is also important to realize smooth collision avoidance. In this paper, a deceleration assistance control for collision avoidance will be proposed based on the formulated braking behavior models of expert drivers to realize smooth, secure brake assistance.

The proposed brake assistance system can realize smooth deceleration profile and appropriate final status of the two vehicles for various approaching conditions. In addition, experimental results using a driving simulator will show validity of the proposed system based on subjective evaluation. It is also shown that the system realizes smooth deceleration control even under existence of the interaction between human driver and the system.

This paper does not deal with effect of the deceleration method on change of drivers' behavior, including driver's trust on the system. Over‐trust should be eliminated if any.

The originality of the paper is to derive smooth secure collision avoidance system based on the driver's perceptual risk model. This method can realize smooth collision avoidance behavior for the various approaching conditions with a unified simple algorithm.

The purpose of this paper is to present an algorithm for performing collision avoidance with robotic manipulators.

The method does not require any a priori knowledge of the motion of other objects in its environment. Moreover, it is computationally efficient enough to be implemented in real time. This is achieved by constructing limitations on the motion of a manipulator in terms of its allowable instantaneous velocity. Potential collisions and joint limits are formulated as linear inequality constraints. Selection of the optimal velocity is formulated as a convex optimization and is solved using an interior point method.

Experimental results with two industrial arms verify the effectiveness of the method and illustrate its ability to easily handle many simultaneous potential collisions.

The resulting algorithm allows arbitrary motions commanded to the robot to be modified on‐line in order to guarantee optimal real‐time collision avoidance behaviors.

CONCERN about the development and implementation of collision avoidance systems has occupied companies and authorities for many years in various parts of the world and particularly in the USA where the density of all kinds of air traffic has increased substantially and will continue to do so into the foreseeable future. Although increases of density occur worldwide, the vast amount of private and business flying in North America makes it essential that any workable scheme of collision avoidance must have mandatory general aviation participation. The necessity for such a system has been underlined by mid‐air collisions which have happened over a considerable period of time and growing pressure has meant that the FAA in 1987 issued a Notice of Provisional Rulemaking (NPRM) in which comments about its contents were to have been received before the end of 1987.

Teleoperations in hazardous environments are often hampered by the lack of available information regarding the state of the remote robotic device. Typically, ideal camera placements are not possible, and an operator is left with the problem of performing complex manoeuvres in the presence of severe blind‐spots. To address this dilemma, we have been investigating the use of a haptic interface, which not only allows an operator to communicate motion commands to a robot, but also allows the robot to communicate to the operator its motion when performing autonomous collision avoidance. This haptic interface provides total operator control, plus vital information that can be used to decide if and how a robot's autonomous operation should be overridden. This paper details our work in this area and presents the results we have obtained from operator/task performance experimentation with this new haptic communication approach.

The purpose of this paper was to present the process of building hardware and software for a collision avoidance system of a quadrotor capable of an indoor autonomous flight.

The system development was carried out in two steps. First, the quadrotor system was designed to mount mission equipments for an indoor flight. The prediction error minimization (PEM) method was used for system identification of the quadrotor, and the linear quadratic regulator (LQR) control method was used for the attitude control. Second, a collision detection system was realized by using a Kinect sensor, an embedded board and a ground control system (GCS). A Kinect sensor with embedded board can send the 3D depth information to GCS and then the GCS displays the 3D depth information with a warning message.

As the controller design requires a linear model, the PEM method was used in system identification. The LQR was used in controller design. It was found that the use of the PEM method for system identification was effective for developing a linear model required for a practical control system using LQR. As 3D depth information from a Kinect sensor is quite accurate in an indoor environment, a collision detection system with Kinect was successfully developed.

The step-by-step approach presented in this paper can be used to develop an autonomous aerial vehicle capable of navigating in an indoor environment with obstacles.

The primary contribution of the paper is the presentation of a practical method for developing a low-cost collision avoidance system for a quadrotor vehicle.