Time Collision Avoidance Research Articles

Research on Autonomous Collision Avoidance of USV Based on Improved APF Algorithm

Abstract Aiming at the problem of Unmanned Surface Vessel (USV) avoiding dynamic vessels on the sea surface, an Artificial Potential Field method based on Velocity Obstacle Method (VO-APF) was studied. Under the premise of complying with the Convention on the International Regulations for Preventing Collisions at Sea (COLREGs), the overlapping of ship domains is minimized. The Quaternion ship domain was introduced into VO to make it more suitable for collision avoidance judgment in the ship domain, and the collision avoidance time of the ship was predicted, and the reasonable obstacle avoidance point was finally obtained. The attraction function of the obstacle avoidance target point and the repulsion function of the ship domain based on the APF are set, and the USV is subjected to the repulsion force and attraction in the APF, and finally completes the whole dynamic ship collision avoidance task. In the simulation environment, VO, APF and VO-APF were compared in three different encounter situations. The results show that VO-APF can help USV to complete the collision avoidance task under the premise of complying with COLREGs, and the overlap time between USV’s own ship domain and the other ship domain is the shortest, and the safety degree is the highest.

Space–time collision avoidance and train dynamics constraints-driven optimal control for heterogeneous heavy-haul trains platoon operation considering air brake delay

The potential of heavy-haul train platoon operation technology in improving railway freight capacity is increasingly recognised, with extensive trial research currently underway. This study firstly utilising longitudinal train dynamics devised a space–time collaborative collision avoidance model for trainsets, accounting for air brake delay. Secondly, an air brake application strategy was proposed, focusing on collision avoidance and managing speeds on steep ramps. Subsequently, a constraint-driven optimal control scheme tailored for heavy-haul train platooning operations within an open railway environment was developed, which simulates train platooning amidst real-world dynamic traffic flow scenarios, offering a global perspective on railway network operations. Finally, we comprehensively evaluate the impact of line conditions on key platoon control parameters based on realistic railway operation scenarios. Findings show that constraint-driven optimal control, integrating train dynamics and space–time collaborative collision avoidance, effectively replicates the dynamic traits of train platoons. The consideration of air braking delays is crucial due to heterogeneous train formations and steep ramps, which can easily cause collisions. Moreover, on real-world railway lines, the average headway of heavy-haul trains weighing 10,000 tons and below can be compressed to 99.82 s when operating in platoons, significantly enhancing transportation capacity compared to existing semi-automatic blocking systems.

Collision Avoidance Decision Method for Unmanned Surface Vehicle Based on an Improved Velocity Obstacle Algorithm

To ensure navigation safety, unmanned surface vehicles (USVs) need to have autonomous collision avoidance capability. A large number of studies on ship collision avoidance are available, and most of these papers assume that the target ships keep straight or follows the International Regulations for Preventing Collisions at Sea (COLREGS). However, in the actual navigation process, the target ship may temporarily turn. Based on the above reasons, this paper proposes a multi-ship collision avoidance decision method for USVs based on the improved velocity obstacle algorithm. In the basic dynamic ship domain model, a collision risk model is constructed to improve the accuracy of the risk assessment between the USV and target ships. The velocity obstacle algorithm is combined with the dynamic ship domain, and the collision avoidance timing and method are judged according to the collision risk. The simulation results show that the decision method can handle the situation that the target ship temporarily turns and has an emergency collision avoidance capability. Compared with the traditional VO algorithm, the collision avoidance time of the method is shorter, and the number of course changes is less.

Statistical Model Checking for Stochastic and Hybrid Autonomous Driving Based on Spatio-Clock Constraints

Autonomous driving vehicles are a kind of typical cyber-physical systems integrating complex interactions between hardware and software components such as collaborative computation, distributed communication, and spatio-clock synchronous control with surrounding traffic environment. They can percept the environment, communicate with surroundings, and react fast enough to control independently. The purpose of autonomous driving emergence is to improve driving safety, reduce environmental pollution, and ease the traffic congestion. However, new features with surrounding open and dynamic environment make systems design and verification becoming more and more complex than ever, such as stochastic communication delay, hardware spontaneous failure distribution, and natively hybrid behaviors described by ordinary differential equations. Spatial and time collision avoidance remains crucial obstacles on the path to becoming ubiquitous and dependable. In this paper, we adopt statistical model checking (SMC) to enlighten possible hazards affected by stochastic and hybrid features in the design phase of autonomous driving systems. In order to provide safety and accountability, we first propose a dedicated multi-lane spatio-clock stochastic specification language (MLSCL) to describe safety invariants and guards in domain-specific autonomous driving systems. Then, we present the semantic mapping rules between MLSCL and UPPAAL SMC models, and design the spatio-clock stochastic and hybrid automata based on MLSCL in order to model inherently stochastic and hybrid behaviors. Finally, we present an illustrative lane-change case study to verify spatio-clock stochastic and hybrid-related properties adopting SMC, and demonstrate the effectiveness of our proposed approach.

An accident prediction architecture based on spatio‐clock stochastic and hybrid model for autonomous driving safety

SummaryCollaborative and autonomous driving vehicles combine hardware and software complex processes, also are heavily dependent on and influenced by the world of physical and cyber interactions. They have enabled many new features and advanced functionalities, such as stochastic and hybrid natures, mobile spatial topologies, and time‐critical dependability. However, the existing modeling and verification techniques have not established faith in proving correctness and safety. Spatial and time collision avoidance remains crucial obstacles on the path to becoming ubiquitous and dependable. In order to ensure safety, we first design an accident prediction architecture in system design‐time and run‐time stages. We apply it on collaborative and autonomous overtaking systems involving spatial‐ and time‐critical accident predictions. Then, we develop a novel and dedicated spatio‐clock stochastic specification language (SCSSL) to describe safety invariants and guards in domain‐specific autonomous driving systems. Next, we create the spatio‐clock stochastic and hybrid automata models based on SCSSL in order to model inherently stochastic and hybrid behaviors. To illustrate the effectiveness of spatio‐clock consistency stochastic specification and verification, we adopt statistical model checking natively to provide reliable predictions for the incoming collision instants and positions. Finally, we present an illustrative overtaking case study to verify spatio‐clock stochastic and hybrid related properties and ensure correct modeling, and demonstrate the significance of our proposed approach.

A Practical and Effective Layout for a Safe Human-Robot Collaborative Assembly Task

This work describes a layout to carry out a demonstrative assembly task, during which a collaborative robot performs pick-and-place tasks to supply an operator the parts that he/she has to assemble. In this scenario, the robot and operator share the workspace and a real time collision avoidance algorithm is implemented to modify the planned trajectories of the robot avoiding any collision with the human worker. The movements of the operator are tracked by two Microsoft Kinect v2 sensors to overcome problems related with occlusions and poor perception of a single camera. The data obtained by the two Kinect sensors are combined and then given as input to the collision avoidance algorithm. The experimental results show the effectiveness of the collision avoidance algorithm and the significant gain in terms of task times that the highest level of human-robot collaboration can bring.

A Safety Collision Avoidance Algorithm Based on Comprehensive Characteristics

Aiming at the requirements of vehicle safety collision avoidance system, a safety collision avoidance algorithm based on environmental characteristics and driver characteristics is proposed. By analyzing the relationship between collision avoidance time and the environment, a safety time model is established. In the established safety time model, parameters based on driver characteristics are added, which increases the flexibility of the algorithm. The algorithm can adapt to more different driving conditions and give appropriate warning thresholds. After simulation and comparison with other algorithms, the algorithm proposed in this paper can satisfied the requirements of reducing vehicle collision risk. The effectiveness and feasibility of the algorithm are verified, and the safety of vehicle driving can be improved.

A Real Time Simulation Optimization Framework for Vessel Collision Avoidance and the Case of Singapore Strait

Safety is a primary concern for the various transport means. For sea transport, this includes various aspects like human safety at sea and at port, and also environmental safety and sustainability. In heavy-traffic regions where the waters are congested and vessels sail very closely together, ensuring these safety needs can be challenging. In this paper, we leverage on the rich information transmitted through the automatic identification system (AIS) and propose, for the first time, an integrated simulation-optimization approach for real time collision avoidance. This enables capturing of stochastic dynamic behavior of vessels for better prediction and fast trajectory optimization for application in real time. Specifically, a realistic agent-based model is developed based on behavioral learning in a real-environment, and incorporated into a fast collision avoidance optimization model in real time to provide robust collision avoidance that is able to account for future stochastic consequences of the actions taken. To achieve this, we develop: 1) a vessel pattern recognition method that mines the rich AIS data to produce realistic trajectory models; 2) an agent-based simulation model to enhance future trajectory prediction; and 3) a fast surrogate-based sampling technique to generate collision avoidance maneuvers for vessel captains in real time. To illustrate the feasibility of the approach, we use the case of the Singapore strait, one of the busiest straits in the world.

A constant guidance law-based collision avoidance for unmanned aerial vehicles

A method of automatic collision avoidance based on constant guidance law is proposed to solve the problem that the collision avoidance time is difficult to be estimated accurately during the collision avoidance process. The guidance command of the collision avoidance method is constant, and the lower bound of the constant guidance command satisfying the safe collision avoidance requirement is given by geometric method. Then, a collision avoidance time estimation method based on particle swarm optimization is proposed. In addition, the attitude control loop adopts the nonlinear proportional-integral-derivative based on tracking-differentiator, and the sufficient conditions for the system stability are given using the T-passive method. The simulation results show that the collision avoidance time estimation error is small and the maneuvering range of collision avoidance is smaller than the collision avoidance method based on proportional guidance and nonlinear dynamic inverse guidance. This method can achieve collision avoidance under the influence of wind disturbance and safety distance abrupt change.

SRM plume: A candidate as space debris braking system for Just-In-Time Collision avoidance maneuver

A possible system suited for Just-In Time Collision Avoidance (JCA) is a cloud injected in a sub-orbital trajectory by a sounding rocket that will drag down the passing object because of the local higher density. The sudden deceleration experienced by the debris will after a few revolutions ensure a consistent deviation from its nominal trajectory and therefore will permit a safe reduction of any collision risk with other objects. This article first introduces a feasibility study of such a system, using as baseline an SRM and then enlarges the study to an enhanced system.

Design of emergency braking algorithm for pedestrian protection based on multi-sensor fusion

Globally, safety has become an increasingly important issue in the automotive industry. In an attempt to reduce traffic fatalities, UNECE launched a new EU Road Safety Program which aims to decrease the number of road deaths by half by 2020. AEB (Autonomous Emergency Braking) is a very effective active safety system intended to reduce fatalities. This study involves the design of a multi-sensor data fusion strategy and decision-making algorithm for AEB pedestrian. Possible collision avoidance scenarios according to the EuroNCAP protocol are analyzed and a robust pedestrian tracking strategy is proposed. The performance of the AEB system is enhanced by using a braking model to predict the collision avoidance time and by designing the system activation zone according to the relative speed and possible distance required to stop for pedestrians. The AEB activation threshold requires careful consideration. The test results confirm the advantages of the proposed algorithm, the performance of which is described in this paper.

自律全方位移動ロボットの並進と回転の同時制御によるロボットサイズを考慮した障害物回避(機械力学,計測,自動制御)

This paper presents a real time collision avoidance method considering robot's size for an autonomous omni-directional mobile robot by simultaneous control of translational and rotational motions. This method enables the robot, which the size of width is not equal to that of length, to avoid unknown obstacles safely and efficiently in real time. To consider the difference between the width and length of the robot, the Capsule Case is newly introduced. In order to achieve the simultaneous control, this method employs an omni-directional platform. As an example of design method of the proposed method, novel control method based on the Fuzzy Potential Method is proposed. To verify the effectiveness of the proposed method, several numerical simulations and experiments are carried out.

A Real Time Collision Avoidance Algorithm for Mobile Robot based on Elastic Force

This present paper proposes the modified Elastic Strip method for mobile robot to avoid obstacles with a real time system in an uncertain environment. The method deals with the problem of robot in driving from an initial position to a target position based on elastic force and potential field force. To avoid the obstacles, the robot has to modify the trajectory based on signal received from the sensor system in the sampling times. It was evident that with the combination of Modification Elastic strip and Pseudomedian filter to process the nonlinear data from sensor uncertainties in the data received from the sensor system can be reduced. The simulations and experiments of these methods were carried out. The algorithm for avoiding the collision proposed in the paper can make robot create a safety path to reach the target of using Modification Elastic Strips. This method based on the nearest points; one on the left and one on the right. Also, the application of Pseudomedian filter in data processing with the nonlinear data received from sensor system of robot was proposed. The simulation and experiments of these studies were carried out to illustrate the effectiveness of the proposed approach.