Active Collision Avoidance System Research Articles

Design and application of automatic driving emergency collision avoidance control algorithm based on artificial intelligence technology

The topic of car intelligence has seen a surge in research interest in automobile active collision avoidance systems in recent years. When there is an obstruction in front of the vehicle, active braking or active steering can be used to prevent a collision, which effectively increases driving safety. Research on intelligent automotive active collision avoidance technology is valuable both academically and practically. This paper aims to enhance the adaptability of active collision avoidance systems to various working conditions. To this end, we propose a design scheme that synchronizes the steering and braking collision avoidance strategies. Additionally, we derive a risk assessment model that takes into account both vehicle dynamics instability factors and vehicle collision factors at the same time. This approach effectively addresses the challenge of effectively assessing the risk of self-driving cars in emergency situations and helps to quantify the risk associated with them. Lastly, a simulation and experimental analysis are conducted on the active collision avoidance strategy that is suggested in this study. The findings demonstrate that the active collision avoidance control system for intelligent vehicles, both longitudinal and transverse, developed in this paper can accurately assess collision risk, make decisions, and manage the collision avoidance process. It can also further decrease the frequency of collision accidents.

Research on robustness of intelligent vehicle longitudinal active collision avoidance system based on equivalent external interference

The rate of fatal traffic accidents caused by sudden risks such as pedestrians crossing the road in violation of regulations and goods falling in front of the vehicles has remained high under the complex dynamic environment. The appearance of sudden obstacles/pedestrians will indirectly trigger sudden changes in sensor signals and control signals, and cause the drivers’ improper driving behaviors. At the same time, the parameter perturbation of the vehicle itself and the sensor noise and other direct disturbances will also put forward high requirements for the robust performance of the vehicle braking system controller. Traditional control methods are difficult to ensure the robust stability required by the vehicle braking system in the actual driving process under sudden emergency conditions. In order to improve the braking control performance and robust performance of the active collision avoidance system under sudden emergency conditions under the influence of its own parameter perturbation, sensor perturbation and other perturbations, this manuscript analyzes the accident risk characteristics of sudden emergency conditions, and establishes an equivalent virtual external force interference model [Formula: see text]. Considering the virtual external force interference model, self-driving parameter perturbation and sensor perturbation, we adopt the [Formula: see text] control theory-design brake controller. Under different perturbation conditions the [Formula: see text] controller, PID controller, and [Formula: see text] controller are simulated and compared. The results show that the [Formula: see text] controller can effectively suppress sudden emergency conditions under parameter uncertainty and external sensor noise interference compared with the PID controller and the [Formula: see text] controller, realizing emergency braking and collision avoidance, and having better closed-loop robustness.

Research on Safe Following Distance on an Expressway Based on Braking Process Analysis

As an important part of the vehicle active collision avoidance system, improvement of the minimum safe following distance model has aroused the interest of researchers at home and abroad. According to the characteristics of the safe driving of vehicles on expressways, the braking process of vehicles is analyzed using the principle of kinematics. According to the requirements of the safe following distance between vehicles, the safe following distance of different braking system structures, different following states, different speeds and different slope sections on expressways is quantitatively analyzed. Three different safe following distance calculation methods based on braking deceleration under different slope conditions are established. Matlab software was used for simulation analysis. The simulation results show that the calculation method of the safe following distance meets the requirements of keeping safe distance in the Implementation Regulations of Road Traffic Safety Law of the People’s Republic of China and provides a more specific reference basis for speed limit used on expressways. This study provides a theoretical basis for the application and interpretation of the parking sight distance value stipulated in the Design Specification for Highway Alignment, and has certain practical guiding significance for improving the density and transportation efficiency of expressway vehicles and reducing the incidence of rear-end traffic accidents.

Decision-making of active collision avoidance system based on comprehensive evaluation method of dangerous scenarios

Dangerous scenario modeling is of great significance for the development of automatic driving functions, and the active collision avoidance system directly affects the safety of vehicles and the intelligence level of vehicles. However, the current existing collision risk evaluation methods are difficult to comprehensively evaluate different dangerous scenarios, the evaluation methods are complicated and there is no normalized description form. In addition, the traditional decision-making method of active collision avoidance system based on collision time distance will lead to the problems of inconsistent risk evaluation scale and single way of collision avoidance. To solve the above problems, the mechanism analysis of the longitudinal, lateral, and parallel collision risks is carried out respectively, and then the model based on kinematics and dynamics is established. After that, the corresponding expression form of collision risks is derived. Finally, the comprehensive evaluation method of dangerous collision scenarios is proposed. Secondly, based on the comprehensive evaluation method of collision risk, considering longitudinal constraints, lateral constraints, parallel constraints, and road regulations, an active collision avoidance decision-making method that used the cooperative collision avoidance mode of breaking and steering is designed. Thirdly, different simulation experiments are designed based on PanoSim/Simulink. The results show the comprehensive evaluation method can effectively model the collision risk of vehicles in the motion process. At the same time, the decision-making method of the active collision avoidance system achieves the expected working effect, thus improving driving stability and safety.

A data-driven approach for ship-bridge collision candidate detection in bridge waterway

The consequences caused by bridge failures owing to the ship-bridge collision are always severe in terms of loss of life, economy, and environmental consequences to individuals and societies. The previous studies focused on the ship-bridge collision mainly concentrated on passive anti-collision, such as strengthening the bridge structure or setting anti-collision facilities. Compared with the previous research, the contribution of this work is to facilitate the reduction of collision risk of ship-bridge collision from the perspective of active anti-collision. A data-driven approach for ship-bridge collision candidate detection method in inland bridge waterways is proposed in this research. The approach is mainly divided into two steps: 1) The features (channel boundary, pier domain, and ship domain) of bridge waterways are identified using Kernel Density Estimation (KDE) method based on the historical AIS data; 2) Collision candidate detection with Velocity Obstacle (VO) method considering the identified features. This work can provide beneficial support for the ship-bridge active collision avoidance system.

Intelligent Control of a Driverless Energy Vehicle Based on an Environment Sensing Sensor

In order to solve the complex environment in the process of vehicle driving and the complexity of self-vehicle structure, intelligent vehicles are prone to rear end collision, lateral collision, and other safety accidents in the presence of tall trees, mountains, and other road environments, endangering the safety of people on board. According to parameters such as the speed of the vehicle, the movement of the blind spot, and the relationship between the vehicle and the blind spot, the model is based on the safety mode of the preceding vehicle. Based on the static obstacles that may exist in the sensing blind area, a sensor sensing blind area safety distance model is established. Based on the possible dynamic obstacles, the active collision avoidance algorithm based on the sensor perceived blind area is studied and simulated. The experimental results show that the selected sensor sensing blind area active collision avoidance controller can well adapt to a variety of special and emergency working conditions, can accurately complete the accurate control of sensor sensing blind area active collision avoidance, and avoid collision accidents to the greatest extent. Compared with the control group, the system designed in this paper can avoid more than 80% of the collision scenes compared with the previous anticollision system. It provides a reference for the future research of sensor sensing blind area-related topics and sensor sensing blind area active collision avoidance system. To a certain extent, it can improve the ability of intelligent vehicle environmental perception and reduce the incidence of rear end collision accidents.

Segmented trajectory planning strategy for active collision avoidance system

This paper presents a segmented trajectory planning strategy for active collision avoidance system. Considering the longitudinal and lateral movement of the obstacle vehicle, as well as the ego vehicle and obstacle outer contour limitations, the collision avoidance trajectory is divided into three segments: lane changing, overtaking and back to original lane. The starting point and end point of lane-change are decided based on longitudinal and lateral safety distance model according to the relative speed and distance as well as the outer contour of the two vehicles. Based on system objective function and lane-change trajectory cluster, vehicle states, dynamic constraints and vehicle body kinematics constraints, the optimal trajectory can be selected, which can monitor the relative location of the obstacle vehicle constantly and then ensure the vehicle can accomplish the collision avoidance safely and smoothly. Simulation and experiment results demonstrate the effectiveness and feasibility of proposed trajectory planning strategy for the active collision avoidance.

Simulation and Verification of the Control Strategies for Pedestrian Active Collision Avoidance System Based on Internet of Vehicles

Simulation and Verification of the Control Strategies for Pedestrian Active Collision Avoidance System Based on Internet of Vehicles

Research Review on Parking Space Detection Method

The parking assist system is an essential application of the car’s active collision avoidance system in low-speed and complex urban environments, which has been a hot research topic in recent years. Parking space detection is an important step of the parking assistance system, and its research object is parking spaces with symmetrical structures in parking lots. By analyzing and investigating parking space information measured by the sensors, reliable detection of sufficient parking spaces can be realized. First, this article discusses the main problems in the process of detecting parking spaces, illustrating the research significance and current research status of parking space detection methods. In addition, it further introduces some parking space detection methods, including free-space-based methods, parking-space-marking-based methods, user-interface-based methods, and infrastructure-based methods, which are all under methods of parking space selection. Lastly, this article summarizes the parking space detection methods, which gives a clear direction for future research.

Super-twisting algorithm second-order sliding mode control for collision avoidance system based on active front steering and direct yaw moment control

Active collision avoidance system has received more and more attraction, which has the capability to avoid potential accidents and reduce driver burden. This paper proposes an active collision avoidance system which consists of a path planner and a coordinated lateral controller. In the path planner, cubic B-spline is developed to obtain collision-free trajectories to bypass the obstacle by steering. Based on this, a coordinated lateral dynamic control of autonomous ground vehicles is presented to improve the accuracy and robustness of path following and simultaneously ensure vehicle stability via active front steering and direct yaw moment control. Then, second-order sliding mode control, based on super-twisting algorithm, is applied to reduce lateral offset and heading angle deviation as much as possible and avoid chattering phenomenon of tradition sliding mode control. Meanwhile, a new form of sliding mode control based on improved reaching law is devoted to forcing the vehicle state sideslip angle and yaw rate to stability envelope with less chattering in the case of low road friction coefficient. Eventually, the effectiveness and robustness of active collision avoidance system against external disturbance and parametric uncertainties are confirmed through different test cases in the MATLAB/Simulink simulation platform.

LARUS: an unmanned aircraft for the support of maritime rescue missions under heavy weather conditions

In maritime emergencies, the time until arrival at the scene of an accident is a decisive factor for a successful rescue operation. In this context, the research project LARUS aims to support the rescue forces at sea with unmanned aerial systems and thus to optimize the rescue process. This refers on the one hand to the localization of potential accident sites and on the other hand to informing the rescuers about the situation on site as well as the provision of an efficient communication infrastructure. For this purpose, the UAS is equipped with various sensors and communication media. To ensure a seamless rescue procedure, the aircraft must be capable of operating even under severe weather conditions. In this regard, the Institute of Flight System Dynamics is currently investigating measures to reduce the gust loads to make the UAS robust against challenging weather conditions. The integration of the LARUS aerial system into airspace using an active collision avoidance system is also an important research aspect. In addition, the adaptation of flight control to the expanded requirements and influencing factors as well as the implementation of international SAR search strategies for flight guidance are also the subject of development work.

Active Collision Avoidance System Design Based on Model Predictive Control with Varying Sampling Time

In active collision avoidance, the trajectory tracking controller determines the deviation from the reference path and the vehicle stability. The main objective of this study was to reduce the tracking error and improve the tracking performance in collision avoidance. Unlike the previously proposed model predictive control (MPC) strategies with constant sampling time, an improved MPC controller with varying sampling time based on the hierarchical control framework was proposed in this paper. Compared with the original MPC tracking controller, the improved MPC controller demonstrated better adaptive capability for the varying road adhesion coefficients and vehicle speed on a curved road. The simulation results revealed that the hierarchical control framework generated an optimal trajectory for collision avoidance in real-time by minimizing the potential field energy.

Active Collision Avoidance for Human-Robot Interaction With UKF, Expert System, and Artificial Potential Field Method.

With the development of Industry 4.0, the cooperation between robots and people is increasing. Therefore, man—machine security is the first problem that must be solved. In this paper, we proposed a novel methodology of active collision avoidance to safeguard the human who enters the robot's workspace. In the conventional approaches of obstacle avoidance, it is not easy for robots and humans to work safely in the common unstructured environment due to the lack of the intelligence. In this system, one Kinect is employed to monitor the workspace of the robot and detect anyone who enters the workspace of the robot. Once someone enters the working space, the human will be detected, and the skeleton of the human can be calculated in real time by the Kinect. The measurement errors increase over time, owing to the tracking error and the noise of the device. Therefore we use an Unscented Kalman Filter (UKF) to estimate the positions of the skeleton points. We employ an expert system to estimate the behavior of the human. Then let the robot avoid the human by taking different measures, such as stopping, bypassing the human or getting away. Finally, when the robot needs to execute bypassing the human in real time, to achieve this, we adopt a method called artificial potential field method to generate a new path for the robot. By using this active collision avoidance, the system can achieve the purpose that the robot is unable to touch on the human. This proposed system highlights the advantage that during the process, it can first detect the human, then analyze the motion of the human and finally safeguard the human. We experimentally tested the active collision avoidance system in real-world applications. The results of the test indicate that it can effectively ensure human security.

Design of an Active Collision Avoidance System for a 4WIS-4WID Electric Vehicle

A novel four-wheel independent steering and four-wheel independent drive (4WIS-4WID) electric vehicle (EV) is proposed in this paper, which is regarded as an autonomous ground vehicle (AGV). Then, the active collision avoidance system of the 4WIS-4WID EV is designed, which mainly consists of the path planner design and the path-tracking controller design. Clothoid is used to planning the collision avoidance path and robust H∞ controller is applied to path tracking. To evaluate the performance of the active collision avoidance system for the 4WIS-4WID EV, simulations under two conditions are carried out. The simulation results indicate that the active collision avoidance system has good collision avoidance performance and robust performance, and the 4WIS-4WID EV has better path-tracking performance and handling stability than active front-wheel steering (AFS) vehicles.

Safety-related risk and benefit-cost analysis of crash avoidance systems applied to transit buses: Comparing New York City vs. Bogota, Colombia

Recent and continuing advances in active safety vehicle technology have created new possibilities for improving road safety. Crash-avoidance systems with the capability to warn and assist drivers are now available in most automotive market in developed countries. Despite this availability, investment in high-technology transit buses to prevent fatalities and injuries has been very slow. In this paper, we examine the safety benefits of using forward- and side-collision warning systems and active collision-avoidance systems in transit buses in New York City and Bogota, Colombia. Using historical data, we develop a transportation risk profile for each city by type of user (driver, passenger, pedestrian, and bicyclist) and crash severity. Because there is no historical data on the effectiveness of crash avoidance systems on buses in the U.S., we surveyed 12 leading experts on autonomous and connected vehicles to assess the potential reduction in injuries and fatalities in road crashes that involve buses. We report on the agreements and disagreements of expert’s judgments and contrast their judgment with the breakeven combination of risk reduction needed to overcome the cost of providing crash avoidance technology in the bus fleet. Additionally, we perform a benefit-cost analysis under uncertainty using Monte Carlo simulation to compute distributions of benefit-cost-ratio. The benefit-cost analysis reveals that implementing any of the technologies in NYC is economically justifiable. In Bogota, even though fatality and injury risks are higher, statistical valuation of lives and injuries are much lower. As a consequence, policy makers are likely to reject the investment in the technologies.

Simulation research on emergency path planning of an active collision avoidance system combined with longitudinal control for an autonomous vehicle

Autonomous vehicle technology is greatly valued nowadays, and an active collision avoidance system is one of the key parts for autonomous driving. This study presents a comprehensive architecture of an active collision avoidance system for an autonomous vehicle, which is integrated with a decision-making module, a path-planning module, a lateral-path-following module and a fuzzy adaptive following module (longitudinal motion) to deal with potential hazards on a straight road or a curved road. In order to make the planned path for overtaking manoeuvres safer, an improved harmonic velocity potential approach for path planning is presented, which innovatively enhances the effect of an obstacle potential on a road by adding a scale term, so that it can generate a smooth path for a vehicle-overtaking manoeuvre. All the potentials which are used for vehicle lane keeping or lane changing are well designed. The lateral-path-following module is based on the constrained linear model predictive control approach, which ensures that the host vehicle can follow the planned path precisely. Furthermore, when the overtaking manoeuvre is not suitable, the fuzzy adaptive following module is utilized to ensure that the host vehicle can adaptively keep a safe distance from the preceding vehicle. Tactical decisions, such as overtaking, accelerating or decelerating, are determined by the decision-making module. Finally, several typical scenarios with low traffic on a straight road or a curved road are simulated to verify the effectiveness and the feasibility of the active collision avoidance system. The simulation results show that the host vehicle can make a successful collision avoidance manoeuvre without the intervention of a human driver in different situations.

Research on Vehicle Safety Driving Distance Based on Decision Making

Security alarm algorithm is the key technology in the application of automotive active collision avoidance system, both at home and abroad are in-depth study. The main basis for security alarm is the distance between vehicles, when the distance between the two vehicles arrive at certain critical range, the alarm system will alarm, to remind the driver brake or deceleration. This paper mainly introduces the safety distance between vehicles of the problem, based on the research at home and abroad, is improved to make it more in line with the real traffic environment on the existing model.

Motion field estimation for a dynamic scene using a 3D LiDAR.

This paper proposes a novel motion field estimation method based on a 3D light detection and ranging (LiDAR) sensor for motion sensing for intelligent driverless vehicles and active collision avoidance systems. Unlike multiple target tracking methods, which estimate the motion state of detected targets, such as cars and pedestrians, motion field estimation regards the whole scene as a motion field in which each little element has its own motion state. Compared to multiple target tracking, segmentation errors and data association errors have much less significance in motion field estimation, making it more accurate and robust. This paper presents an intact 3D LiDAR-based motion field estimation method, including pre-processing, a theoretical framework for the motion field estimation problem and practical solutions. The 3D LiDAR measurements are first projected to small-scale polar grids, and then, after data association and Kalman filtering, the motion state of every moving grid is estimated. To reduce computing time, a fast data association algorithm is proposed. Furthermore, considering the spatial correlation of motion among neighboring grids, a novel spatial-smoothing algorithm is also presented to optimize the motion field. The experimental results using several data sets captured in different cities indicate that the proposed motion field estimation is able to run in real-time and performs robustly and effectively.

Active collision avoidance system for steering control of autonomous vehicles

The study proposes an active collision avoidance system to allow safe lane-changing manoeuvres by self-steering vehicles in the presence of the uncertainties associated with nearby vehicles and the surrounding environment. This system integrates estimation of conflict probability, model predictive control and dedicated short-range communications (DSRC) techniques to ensure a collision-free operation. To accomplish this, the proposed system uses model predictive control to predict the future positions of vehicles and estimates the conflict probability so as to reduce the risk of collision. The system also exploits DSRC techniques to facilitate the gathering of information from nearby vehicles so that potential conflicts can be detected at an earlier stage. Autonomous vehicles can thus make adjustments based on the acquired data to avoid collisions in a real communication environment. The effectiveness of the method has been verified under experimental conditions. The influences of key parameters in the control method are examined.

NCTUns tool for wireless vehicular communication network researches

Several goals such as improving road safety and increasing transport efficiency are being pursued in intelligent transportation systems (ITS). Wireless vehicular communication is one technology to achieve these goals. Conducting vehicular experiments on the roads is an approach to studying the effectiveness of wireless vehicular communication. However, such an approach is costly, hard-to-control (repeat), dangerous, and infeasible when many vehicles and people are involved in the field trial. In contrast, the simulation approach does not have these problems. It is a very useful approach and complements the field trial approach. This paper presents NCTUns, an open source integrated simulation platform, for wireless vehicular communication network researches. This tool tightly integrates network and traffic simulations and provides a fast feedback loop between them. Therefore, a simulated vehicle can quickly change its driving behavior such as moving speed and direction when it receives a message from the wireless vehicular communication network. This capability is required by several novel ITS applications such as active collision avoidance systems. In this paper, we present the design, implementation, validation, and performance of this tool.