Probabilistic verification and synthesis of the next generation airborne collision avoidance system

The next generation airborne collision avoidance system, ACAS X, departs from the traditional deterministic model on which the current system, TCAS, is based. To increase robustness, ACAS X relies on probabilistic models to represent the various sources of uncertainty. The work reported in this paper identifies verification challenges for ACAS X, and studies the applicability of probabilistic verification and synthesis techniques in addressing these challenges. Due to shortcomings of off-the-shelf probabilistic analysis tools, we developed a new framework, named VeriCA (Verification for Collision Avoidance). VeriCA is a combined probabilistic synthesis and verification framework that is custom designed for ACAS X and systems with similar characteristics. VeriCA supports Java as a modeling language, is memory efficient, employs parallelization, and provides an interactive simulator that displays aircraft encounters and the corresponding ACAS X behavior. We describe the application of our framework to ACAS X, together with the results and recommendations that our analysis produced.     

Fuzzy collision avoidance system for ships

The paper discusses the problem of maritime traffic control. A model of the relative motion of two vessels is considered. An algorithm for the generation of alarms of various types in accordance with the verbal ship–ship danger level is considered. Navigation situations are separated into levels based on the ship’s maneuvering intensity and time to collision. A fuzzy decision-making system about the motion’s danger level that combines Mamdani and Sugeno fuzzy inference systems is proposed. The results of the numerical experiment that demonstrates the system’s operation under standard conditions and the results of the system’s field tests based on real ship traffic data in the waters adjacent to the port of Vladivostok are given.     

A formally verified blockchain-based decentralised authentication scheme for the internet of things

The Journal of Supercomputing - With the proliferation of intelligent devices in the Internet of Things (IoT), the security of IoT devices is becoming a major concern as an attacker can exploit...     

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

International Journal on Software Tools for Technology Transfer - We present an approach to analyze the safety of asynchronous, independent, non-deterministic, turn-to-bearing horizontal maneuvers...     

Decision support system for collision avoidance of vessels

Although there are many advanced systems to assist vessels with passing through narrow waterways, it continues to be a serious problem because of disturbance factors and geographic structure. By taking Istanbul Strait as a model for this study, we aimed to develop a decision support system and/or a guidance method to assist reciprocally passing vessels. The main purpose is to develop an Artificial Neural Network (ANN) that uses the data of manually controlled vessels to generate predictions about the future locations of those vessels. If there is any possibility of collision, this system is aimed to warn the operators in the Vessel Traffic Services (VTS) centre and to guide the personnel of the vessels. In this study, manually controlled and reciprocally passing vessels’ data were used (including coordinates, speed, and environmental conditions), neural networks were trained, and predictions were made about the locations of vessels three minutes after the initial point of evaluation (this duration was determined by considering the conditions of Istanbul Strait). With this purpose, we used data gathered from vessels and proved the success of the system, especially concerning predictions made during turnings, by determining the possibility of collision between two vessels three minutes after the data was gathered.     

A formally verified application-level framework for real-time scheduling on POSIX real-time operating systems

We present a framework, called meta scheduler, for implementing real-time scheduling algorithms. The meta scheduler is a portable middleware layer component designed for implementations over POSIX-compliant operating systems. It accommodates pluggable real-time scheduling algorithms while offering the flexibility of platform independence - the singular underlying OS requirement is the now nearly ubiquitous POSIX compliance. The versatility of pluggable schedulers positions the meta scheduler for deployment in an interoperable heterogeneous real-time environment. We present the design of the meta scheduler and outline its implementation. Furthermore, we present a mechanized correctness verification using the UPPAAL model checker. Prototype implementation of the meta scheduler over QNX Neutrino real-time operating system demonstrates high performance and a small footprint.     

A fuzzy aid rear-end collision warning/avoidance system

To decrease traffic accidents is a declared target of Intelligent Transportation Systems (ITS). Among them, rear-end collisions are one of the most common and constitute one of the as yet unsolved topics in the automotive sector. This paper presents an approach to the avoidance of rear-end collisions in congested traffic situations. To this end, two fuzzy controllers, a Collision Warning System (CWS) and a Collision Avoidance System (CAS), have been developed. The former is in charge of alerting the driver in case of an impending rear-end collision to prevent or mitigate the crash. The latter is in charge of generating an output control signal for the steering wheel in order to avoid the collision. Both CWS and CAS have been tested with real cars using vehicle-to-infrastructure (V2I) communications to acquire data of vehicles. A system installed in the infrastructure capable of assessing road traffic conditions in real time is responsible for transmitting the data of the vehicles in the surrounding area. The systems have been tested at the Center for Automation and Robotics (CAR)’s facilities with two mass-produced cars.     

A collision avoidance scheme for the synchronized broadcast packets in a multi-AP Wi-Fi broadcasting system

A Wi-Fi broadcasting system is a kind of Mobile-TV system that transmits multimedia content over Wi-Fi networks. The specialty of the system is that it takes advantage of broadcast packets for streaming to be scalable to the number of users. However, the loss rate of broadcast packets is much higher than that of unicast ones because MAC layer retransmission is not applied on broadcast packets. To recover lost packets, a packet level Forward Error Correction (FEC) scheme is usually used in Wi-Fi broadcasting systems. But it introduces additional transmission overhead, which is usually proportional to the packet loss rate. So it is important to reduce the packet loss rate to build an efficient and reliable Wi-Fi broadcasting system. While past studies have considered only single-AP systems, our study focuses on a multi-AP system which is designed to cover a much larger area. We found a specific packet collision problem that increases packet loss rate significantly in a multi-AP system. It is caused by the simultaneous arrival and transmission of a broadcast packet at and by APs. We identify two scenarios of the collision that depend on the channel state at the time of packet arrival. We propose two collision avoidance methods to handle these scenarios: Broadcast Packet Scheduling Method (BPSM) and Adaptive Contention Window-Sizing Method(ACWSM). We implement both methods in our multi-AP Wi-Fi broadcasting system and verify their effectiveness through experiments.     

An efficient system for combined route traversal and collision avoidance

Here we consider the problem of a robot that must follow a previously designated path outdoors. While the nominal path, a series of closely spaced via points, is provided with an assurance that it will lead to the destination, we can’t be guaranteed that it will be obstacle free. We present an efficient system capable of both following the path as well as being perceptive and agile enough to avoid obstacles in its way. We present a system that detects obstacles using laser ranging, as well as a layered system that continuously tracks the path, avoiding obstacles and replanning the route when necessary. The distinction of this system is that compared to the state of the art, it is minimal in sensing and computation while achieving high speeds. In this paper, we present an algorithm that is based on models of obstacle avoidance by humans and show variations of the model to deal with practical considerations. We show how the parameters of this model are automatically learned from observation of human operation and discuss limitations of the model. We then show how these models can be extended by adding online route planning and a formulation that allows for operation at varying speeds. We present experimental results from an autonomous vehicle that has operated several hundred kilometers to validate the methodology.

基于范例推理的船舶避碰决策支持系统

根据船舶避碰的特点,将范例推理（Case-based Reasoning,CBR）方法引入到船舶避碰决策支持系统的设计中．为提高决策系统的性能,优化范例表示方法;并在分析阶段先对碰撞局面进行分类;再通过搜索树进行范例匹配;最后,讨论该方法的可行性．     

A constraint-based approach for human–robot collision avoidance

In this paper, we present a software-based approach for collision avoidance that can be applied in human–robot collaboration scenarios. One of the contributions is a method for converting clustered 3D sensor data into computationally efficient convex hull representations used for robot-obstacle distance computation. Based on the computed distance vectors, we generate collision avoidance motions using a potential field approach and integrate them with other simultaneously running robot tasks in a constraint-based control framework. In order to improve control performance, we apply evolutionary techniques for parameter optimization within this framework based on selected quality criteria. Experiments are performed on a dual-arm robotic system equipped with several depth cameras. The approach is able to generate task-compliant avoidance motions in dynamic environments with high performance.     

一种基于效益的多机器人避碰协调策略

多移动机器人系统在完成同时定位和地图构建SLAM任务时,机器人之间常常存在相互碰撞的问题,而这种碰撞的避免又不同于一般的避障,因为避障问题中的障碍物一般是不动的。为了解决机器人之间的避碰问题,提出了一种基于效益的多机器人避碰协调策略。该策略以提高多机器人系统探索效率为主,确定机器人通过交叉路口的顺序。同时考虑了动态协调避碰的情况,给出了确定机器人通过交叉路口顺序的算法。通过机器人在交叉路口实现避碰协调算法的仿真示例,对该方法的避碰协调过程进行了说明,并对仿真结果进行了分析,同时对仿真中机器人和目标位置的空间关系给出了合理的假设。     

基于LPC2210的汽车防撞装置的设计

随着私家车的增多,给日常生活带来了方便,同时也给交通带来极大压力.汽车的安全问题变得尤其重要.本文介绍基于LPC2210的汽车防撞系统.此系统采用了两种测距方法:调频连续渡雷达测距和超声波测距.提示部分采用了语音播报和LCD显示两种方式.本文阐述了信号的发射接收、语音集成芯片、LCD显示这三部分与核心控制芯片的硬件连接及整个系统的软件流程图.     

碰撞防护系统分析及铁路应用设计

在分析既有碰撞防护系统的基础上,首次提出适用于轨道交通领域的列车碰撞防护系统概念,设计了列车碰撞系统的功能架构并定义了各子系统的功能,对比分析了列车碰撞防护系统的两种工作模式.作为列车控制系统的安全叠加系统,列车碰撞防护系统可有效提升铁路运输安全性能.     

空中自动防撞系统最优逃避机动的确定

采用最优控制理论对空中自动防撞系统确定其最优的逃避机动.首先将空中自动防撞系统逃避机动的确定问题抽象为一个具有复合性能指标的可变终端时刻的最优控制问题,然后采用二次曲线拟合的方法,求出两架飞机最靠近的终端时刻.最后根据极大值原理和飞机的状态方程,推算出为使两架飞机在最靠近时,实现最大距离的逃避机动所应采用的最优滚转角速度和法向过载,并给出了最优解的解析表达式.     

车载雷达防追尾预警系统中的目标跟踪研究

考虑毫米波雷达测量的误差和噪声的存在,为了提高毫米波雷达汽车防追尾预警系统的可靠性,设计了一个多模型算法实现对机动车辆的准确跟踪。针对汽车在高速公路上最常见的匀速、匀加速及转弯运动模型进行仿真实验,结果表明该算法能够有效地跟踪前方行驶车辆,探知自车与前车之间距离信息、速度信息等,从而降低雷达虚警率。     

On-line collision avoidance system for two PTP command-based manipulators with distributed controller

This research aims to solve online collision avoidance problem of two manipulators with independent controller. Since industrial robot controller is a closed commercial system, trajectory generation part of robot controlling is always proprietary or unknown. Thus, this paper proposes a collision avoidance system of two manipulators which are controlled by point-to-point (PTP) commands, in condition that the internal of robot controller is unknown and unchangeable. Based on this condition, collision avoidance is supposed to be realized by online scheduling of these PTP controlling commands. This paper proposes the collision avoidance method that assumes the three-dimensional common workspace between two manipulators can be partitioned into many subregion elements. And with managing these subregion elements, which are occupied by robot motion, PTP commands are scheduled to adjust execution timing for collision avoidance. A deadlock problem caused by the partition of the workspace is also taken into consideration in the method. And the effectiveness and efficiency of the method have been verified by simulations and experiments.     

汽车纵向主动避撞系统的研究现状与展望

针对现代交通安全问题,提出了一种辅助驾驶员行车安全的方法,即纵向主动避撞,主要围绕汽车纵向主动避撞系统中的行车信息感知与处理、安全距离模型、车辆动力学系统建模、车辆动力学控制四个关键技术进行叙述.各种先进的控制技术为研究汽车纵向主动避撞系统提供了新的机遇,它所衍生出的新功能新系统对汽车的安全性、舒适性及经济性等方面都有...