Envelopes and waves: safe multivehicle collision avoidance for horizontal non-deterministic turns

Real-time Collision Avoidance for Pedestrian and Bicyclist Simulation: A Smooth and Predictive Approach

BackgroundCollision avoidance between two walkers involves a mutual adaptation to speed and orientation in order to successfully avoid a collision. Minimum Predicted Distance (MPD) is the distance at which two walkers would collide if their speed and path trajectory were maintained at first sight of one another. MPD has been used to describe the risk of collision and its evolution over time between two adult walkers when on a collision course. Middle-aged children have been shown to have poor perception-action coupling during static and dynamic collision avoidance tasks. Research has yet to examine whether perception-action coupling deficits persist in a dynamic collision avoidance task involving a child and another walker. Research questionCan the metric MPD(t) be used to examine collision avoidance strategies between children and adults? MethodsEighteen children (age: 10 ± 1.5 years) and eighteen adults (34 ± 9.6 years) walked along a 12.6 m pathway while avoiding another participant (child or adult). Groups of three children and three adults were recruited per session. Trials were randomized equally such that each adult interacted with another adult 20 times, each child interacted with another child 20 times, and each adult interacted with a child 21 times, for a total of 141 trials. 3D kinematic data of each participant’s head was recorded using the Vicon system. ResultsThe results demonstrated: (1) MPD(t) can be used to predict future collisions in children, (2) MPD(t) is an absolute measure that is consistently lower when a child is involved compared to two adult walkers, (3) the individual passing second, even when it is a child, contributes more to MPD(t) than the walker passing first. SignificanceIt appears children have developed adult-like strategies during a collision avoidance task involving two walkers. Body anthropometrics should be considered when determining collision avoidance strategies between children and adults.

65 pp., 33 fig., 2 tab., 1982. Pb. DM 49.-. Ralph-Michael Böhmer Flow Cytometry and Cell Proliferation Kinetics Progress in Histochemistry and Cytochemistry Vol. 14, No 4 VI 1982 Gustav Fischer Verlag Stuttgart - New York VI

<div class="htmlview paragraph">Since 1955 the aviation community has been investigating the feasibility of an airborne collision avoidance system. These studies have included analytical and engineering design efforts as well as flight simulation tests and actual flight tests. The majority of the effort expended during these investigations has been devoted to the engineering aspects of the systems. Of equal importance in meeting the overall objective of collision avoidance is the transmission of system information to the crew in a form that can be used effectively in the operational environment. The Boeing Commercial Airplane Company fulfilled a contract for the FAA, using simulation to help determine flight deck display requirements and operational procedures for the traffic alert and collision avoidance system (TCAS II) in commercial transport aircraft.</div> <div class="htmlview paragraph">Using the experience gained from these studies, this paper describes the type of efforts required to develop pilot factor characteristics for future collision avoidance systems it addresses man-machine interface requirements to ensure that the system is compatible with the overall aircraft system. It presents some of the functional requirements that the display and control components of the system must meet to accomplish separation assurance. Some of the subjects that are discussed include: a) the impact of the collision avoidance system utilization philosophy on the display requirements; b) the importance of designing the collision avoidance display system so that it can be integrated into the flight deck environment; c) techniques for incorporating realistic human performance estimates into the system performance assumptions; d) the effect on system performance of using natural response patterns; e) techniques that can be used to generate pilot response time commensurate with the situational requirements; f) the role of simulation in the design process; and g) consideration for certification during the development of a collision avoidance system.</div>

Ship collision avoidance behaviour recognition and analysis based on AIS data

In-vehicle multiplexing and networking, including sharing information and control between different in-vehicle data buses and between the vehicle and the infrastructure, provides both opportunities and challenges for safety system designers. This paper provides an overview of in-vehicle networking and discuses trends that affect the application of in-vehicle networking to future collision avoidance systems. An overview of the classification of vehicle networking developed by the Society of Automotive Engineers (SAE) as well as descriptions of several emerging in-vehicle network standards provides background information necessary to understand the potential use of in-vehicle data buses. While most existing collision avoidance warning systems use only dedicated wiring, some emerging safety systems are beginning to employ in-vehicle networking to enhance their performance. Because use of in-vehicle networks requires careful design, the paper presents simulation results of network performance when supporting safety systems including collision avoidance systems. These results not only indicate the types of systems that can be supported by the various data bus standards, but also identify key design parameters. In addition, the paper discusses key trends such as internetworking between multiple in-vehicle data buses.

Efforts to increase airport capacity include studies of aircraft systems that would enable simultaneous approaches to closely spaced parallel runways in Instrument Meteorological Conditions (IMC). The time-critical nature of a parallel approach results in key design issues for current and future collision avoidance systems. These issues are being studied in two ways. First, a part-task flight simulator study has examined the procedural and display issues inherent in such a time-critical task. Second, a prototype collision avoidance logic capable of generating this maneuver guidance has been designed using a recently developed methodology.

In this work we present a novel and generic framework for reactive collision avoidance in bipedal locomotion, which is formulated as an optimization problem considering the constraints of collision avoidance as well as others (e.g. joint limits) to simultaneously satisfy both Cartesian and joint space objectives. To realize the reactive behaviors, several task space motions, such as the translational motion of the swing foot and the vertical position of the support foot, could be relaxed in presence of obstacles. Therefore, the swing foot trajectory is modulated with respect to the references in real-time for preventing future collisions between the legs, or legs and obstacles in the environment. External obstacle negotiation in the proposed framework can also be addressed generically by treating the obstacle as an extended segment of the support foot. The allowable deviation of the relaxed degrees of freedom from their references could be further utilized to modify the foot placement to regenerate a reactive walking pattern. The validation and the performance of the proposed method are fully evaluated and demonstrated in physics based simulations of the compliant humanoid robot COMAN.

This paper presents a synthesis of an optimal control solution for cooperative collision avoidance strategies for aircraft (ships) with unequal turn capabilities in a close proximity coplanar encounter. The analytic expressions for the extremals are presented and their properties are analyzed. Simple algorithms for the synthesis of optimal control are developed. The structure of the synthesis is analyzed and its behavior with a change in the nondimensional turn rate ratio is studied. It is shown that Merz’s solution for identical aircraft (see Merz in Proc. Joint Automatic Control Conf., Paper 15-3, pp. 449–454, 1973; Navigation 20(2):144–152, 1973; Tarnopolskaya and Fulton in J. Optim. Theory Appl. 140(2):355–375, 2009) is a degenerate case of this more general solution. The results of this paper are useful for benchmarking and validating automated proximity management and collision avoidance systems.

Unmanned Aerial Vehicles (UAV) have become more popular for usage due to the low cost of deployment and maintenance. Single UAV employment allows remote area monitoring and transferring different payloads to inaccessible or dangerous zones for human. In order to deal with flight tasks that are more complex, UAV swarms are applied. The main challenge of UAV swarm formation and flight control is to avoid vehicle collisions. In this case, artificial intelligence is responsible for flight performance in the airspace in such way that collision is avoided. The main requirements to the method, which will provide conflict-free maneuvers, are safety (collision avoidance), liveness (decentralized control, destination area reachability) and flyability (UAV flight performance constraints are satisfied). Artificial force field method fulfills all of these demands. It allows to detect a potential conflict between multiple UAVs in a swarm and other static or moving obstacles found in airspace, to provide collision resolution by changing UAVs flight parameters through maintaining minimum separation distance, including cases when manned vehicles are found in the same airspace. There can be distinguished by a wide range of obstacles: static (buildings, restricted areas and bed weather conditions) and dynamic ones (other UAVs, manned aircraft). Method allows keeping UAV swarm shape on the flight path, taking into account ground speed and turn bank angle values restrictions according to UAV’s flight performance characteristics.

Unmanned Aerial Vehicles (UAVs) are now becoming increasingly accessible to amateur and commercial users alike. Several types of airspace structures have been proposed in recent research, which include several structured free flight concepts. In this paper, for simplicity, distributed coordination of the motions of cooperative multicopters in structured airspace concepts is focused on. This is formulated as a free flight problem, including convergence to destination lines/planes and inter-agent collision avoidance. The destination line of each multicopter is known a priori. Further, Lyapunov-like functions are designed elaborately, while formal analysis and proofs of the proposed distributed control are given to show that the free flight control problem can be solved. What is more, by the proposed controller, a multicopter can keep away from another as soon as possible once it enters the safety area of another one. Simulations and experiments are given to show the effectiveness of the proposed method.

We present a decentralized minimum-time trajectory optimization scheme based on learning model predictive control for multi-agent systems with nonlinear decoupled dynamics and coupled state constraints. By performing the same task iteratively, data from previous task executions is used to construct and improve local time-varying safe sets and an approximate value function. These are used in a decoupled MPC problem as terminal sets and terminal cost functions. Our framework results in a decentralized controller, which requires no communication between agents over each iteration of task execution, and guarantees persistent feasibility, finite-time closed-loop convergence, and non-decreasing performance of the global system over task iterations. Numerical experiments of a multi-vehicle collision avoidance scenario demonstrate the effectiveness of the proposed scheme.

An improved ant colony optimization approach for multi-aircraft escape maneuvers in the horizontal plane was proposed in this paper. An ant colony algorithm is a typical cluster algorithm, which is a new application in aircraft traffic collision avoidance system. A multi-aircraft horizontal maneuver model based on ant colony algorithm was proposed.

This paper investigates the long-term effects of satellite breakup on the evolutionary growth of debris in the Low Earth Orbit (LEO) environment. We use a set of stochastic simulations of source-sink models to explore how collisional cascade can happen (or not) due to debris objects from meter scales down to 1 mm. We model two distinct effects from two classes of debris: (1) lethal debris cause catastrophic breakup of satellites upon collisions, and (2) marginally lethal debris do not cause catastrophic breakup, but can turn active maneuverable satellites into derelict ones. We show that the future environment sensitively depends on the relative proportion of the two classes of debris produced by each breakup event. In particular, a large amount of marginally lethal debris can introduce a large number of mission-ending collisions, creating a large population of derelict satellites that ultimately become a source of catastrophic collisions. We can dramatically decrease future collisions by lowering the observable length scale of debris below the length scale characteristic of debris that causes lethal collisions, ℓLethal, and allowing active satellites to maneuver and perform collision avoidance.

Future collision avoidance systems, which are capable of fully controlling the vehicle, have to make critical decisions in a very short time. To do this, they need to check constantly if their own vehicle's occupancy collides with the other traffic participants' occupancy. Those collision checks consume a substantial amount of time and consequently, the collision avoidance systems could fail to intervene in complex scenarios. We propose a new approach to reduce the computation time for collision checks significantly. Instead of using geometric methods, we store finitely many possible collision scenarios between two objects in a table and thus collision checks become a matter of lookup table queries. To ensure that the finite number of configurations cover all possible scenarios, we use a novel abstraction technique which guarantees that every collision will be detected. The approach works for arbitrarily many traffic participants by applying the approach pairwise (own vehicle and other object) to each traffic participant. Randomly generated scenarios show that the new approach can be several times faster than geometric intersection techniques thanks to the trade-off between memory consumption and computation time.