Showing papers on "Collision avoidance system published in 2017"

A Practical Animal Detection and Collision Avoidance System Using Computer Vision Technique

Abstract: One serious problem that all the developed nations are facing today is death and injuries due to road accidents. The collision of an animal with the vehicle on the highway is one such big issue, which leads to such road accidents. In this paper, a simple and a low-cost approach for automatic animal detection on highways for preventing animal-vehicle collision using computer vision techniques are proposed. A method for finding the distance of the animal in real-world units from the camera mounted vehicle is also proposed. The proposed system is trained on more than 2200 images consisting of positive and negatives images and tested on various video clips of animals on highways with varying vehicle speed. As per the two-second rule, our proposed method can alert the driver when the vehicle speed is up to 35 km/h. Beyond this speed, though the animal gets detected correctly, the driver does not get enough time to prevent a collision. An overall accuracy of almost 82.5% is achieved regarding detection using our proposed method.

Crash prediction with behavioral and physiological features for advanced vehicle collision avoidance system

Abstract: Real-time crash prediction is the key component of the Vehicle Collision Avoidance System (VCAS) and other driver assistance systems. The further improvements of predictability requires the systemic estimation of crash risks in the driver-vehicle-environment loop. Therefore, this study designed and validated a prediction method based on the supervised learning model with added behavioral and physiological features. The data samples were extracted from 130 drivers’ simulator driving, and included various features generated from synchronized recording of vehicle dynamics, distance metrics, driving behaviors, fixations and physiological measures. In order to identify the optimal configuration of proposed method, the Discriminant Analysis (DA) with different features and models (i.e. linear or quadratic) was tested to classify the crash samples and non-crash samples. The results demonstrated the significant improvements of accuracy and specificity with added visual and physiological features. The different models also showed significant effects on the characteristics of sensitivity and specificity. These results supported the effectiveness of crash prediction by quantifying drivers’ risky states as inputs. More importantly, such an approach also provides opportunities to integrate the driver state monitoring into other vehicle-mounted systems at the software level.

Path planning and stability control of collision avoidance system based on active front steering

Abstract: Vehicle collision avoidance system is a kind of auxiliary driving system based on vehicle active safety, which can assist the driver to take the initiative to avoid obstacles under certain conditions, so as to effectively improve the driving safety of vehicle. This paper presents a collision avoidance system for an autonomous vehicle based on an active front steering, which mainly consists of a path planner and a robust tracking controller. A path planner is designed based on polynomial parameterization optimized by simulated annealing algorithm, which plans an evasive trajectory to bypass the obstacle and avoid crashes. The dynamic models of the AFS system, vehicle as well as the driver model are established, and based on these, a robust tracking controller is proposed, which controls the system to resist external disturbances and work in accordance with the planning trajectory. The proposed collision avoidance system is testified through CarSim and Simulink combined simulation platform. The simulation results show that it can effectively track the planning trajectory, and improve the steering stability and anti-interference performance of the vehicle.

WiSafe: Wi-Fi Pedestrian Collision Avoidance System

Abstract: In this paper, we present a novel Wi-Fi-based pedestrian collision avoidance (PCA) system: WiSafe. Compared to vision-based and radar-based PCA systems, WiSafe has a key advantage of Non-Line-of-Sight (NLOS). WiSafe can assist drivers in discovering pedestrians in NLOS and blind spots, where the views of drivers are blocked by buildings, vehicles, or other obstacles. In particular, it is very useful when driving in poor visibility conditions such as at night, in heavy rain, or thick fog. WiSafe can save split seconds, which can potentially save lives. Instead of using wireless access in vehicular environments/dedicated short-range communications to protect pedestrians, WiSafe provides a simple, effective, and low-cost solution. Without changing Wi-Fi standards, WiSafe is compatible with 802.11a/b/g/n and can be implemented by apps on smartphones or wearable devices. The complete analysis, implementation, and experiments are presented in this paper. The results show that WiSafe can achieve and even exceed the PCA requirements.

A Simplified Simulation Model of Ship Navigation for Safety and Collision Avoidance in Heavy Traffic Areas

Abstract: Based on our previously developed ship collision avoidance steering system, this paper develops a more extensive collision avoidance decision-making system for non-uniformly moving ships. A real-time simulator based on the Six-Dimensional (6D) Manoeuvring Modelling Group (MMG) model is used to simulate the ship's motion. To validate the manoeuvring mathematical model, sea trial measurements of a container ship (C-3) have been selected. This study incorporates Nomoto's second-order model into a numerical model to calculate the turning characteristics of the ship. The manoeuvring indices of Nomoto's model are the knowledge base of the simplified ship simulation model. To verify the ship collision avoidance system with respect to different traffic factors, simple and complex collision avoidance cases have been designed in fast-time simulations with multi-ship encounter conditions. The simplified simulation model developed here can quickly determine the helm angle when the ship makes a collision avoidance manoeuvre, which is helpful for the safety of ship navigation in heavy traffic areas.

Improving smartphone based collision avoidance by using pedestrian context information

Abstract: Pedestrians globally comprise 22 % of all road traffic deaths in 2013. Various approaches for reducing accident numbers have already been introduced and are still being researched. Most of these approaches have specific limitations, like requiring line of sight. To overcome these limitations, we propose the Wireless Seat Belt (WSB), a smartphone-based collision avoidance system for pedestrians. Unlike other systems, the WSB uses context information, obtained from a pedestrian's smartphone, not only as additional information but also for using the information to improve the collision detection accuracy. The WSB introduces independent, individual modules for recognizing the pedestrian's direction, position, and speed. We first evaluate the influence of the measurement errors of each module on the missed alarm probability in a typical urban collision scenario using a simulator. Then, the impact of using the pedestrian's context to decrease the missed alarm probability is evaluated. The evaluation is done using the example of a curb detection module. The curb detection is used to infer that the pedestrian has stepped onto the street to correct the pedestrian's position. The results show a decrease of the missed alarm probability by 46.5 % in the scenario considered.

An ultrasonic sensor distance induced automatic braking automobile collision avoidance system

Abstract: Collisions in automobiles have become a major safety concern; cases of damage and death due to automobile collisions are frequently reported The number of pedestrians knocked to death by automobiles is also on the rise in cities and highways Further into the game reserves, wild animals are also frequently knocked to death by automobiles The cost of a life cannot be estimated, the cost of damages to the automobiles also impacts negatively on investment In most cases drivers fail to notice the presence of obstacles ahead and brakes need a driver's response to operate thus increasing the response time, hence reducing their reliability Many approaches to automobile crash avoidance systems have been proposed in recent time, however, such approaches mainly concentrate on steering maneuvering control In addition, these approaches do not take into consideration the safety distance to stoppage of the automobile, more so, many approaches only provide a warning signal to the driver for activating the automatic braking This always provides a room for human error This paper presents the development of an automatic microcontroller based crash avoidance system that employs obstacle detection and distance measurement using ultrasonic sensors to detect obstacles and their distances Once the obstacle has been detected and safe separation distance is reached, the automobile performs safety distance induced braking at that distance to bring the automobile to a stoppage From the results obtained after tests, the system has an average response time of 086s to the activation of the brakes and a 128 percentage error with respect to the obstacle real distance

Driver Distraction: A Naturalistic Observation of Secondary Behaviors with the Use of Driver Assistance Systems

Abstract: This report describes the naturalistic observation of secondary behaviors performed by 66 drivers who took part in the Automotive Collision Avoidance System Field Operational Test (ACAS FOT). The ACAS FOT included two driver assistance systems, adaptive cruise control (ACC) and forward collision warning (FCW). Each driver participated in both baseline (no driver assistance systems for one week) and treatment conditions (both ACC and FCW available for 3 weeks). The method employed was to sub-sample video data, and code drivers’ secondary behaviors using 4 s video clips of the driver, collected every 5 minutes. Eight-hundred and ninety video clips were reviewed and coded while participants drove manually, with conventional cruise control, ACC, and FCW. The results show that drivers who took part in the field test were no more likely to engage in secondary behaviors when driving with ACC and FCW in comparison to manual control. When the driver assistance systems became available to the participants, there was an increase in the number of conversations drivers had with passengers, probably related to the driver explaining the novel ACAS system to passengers. The results have important implications in that, at least for the duration of exposure examined, they counter the concern often raised that driver assistance systems will promote driver distraction, lapses in attention or modification in perceived risk.

5G enabled cooperative collision avoidance: System design and field test

Abstract: We explore the feasibility of 5G for enhancing cooperative automated driving. A V2X solution for enhancing road safety through connected cars based on 5G radio technology is shown. Based on a flexible, re-configurable software defined radio test-bed, we examine the benefit of ultra low latency and high reliability (URLLC) profile for enhanced emergency brake maneuver. This use case reveals the advantages and additional requirements of using 5G for automated emergency braking based on vehicle-to-vehicle communication. We analyze the impact of communication latency and reliability on the maneuver performance and associated safety aspect. The results provide insights into the joint-design of a V2X communication system for enhancing road safety through cooperative automated driving.

Cooperative Intersection Collision Avoidance Persistent System Based on V2V Communication and Real-Time Databases

Abstract: Driving through intersections is potentially dangerous causing accidents and injury or death of the vehicle's conductor and/or his accompanists. Thanks to technological advances, many systems based on Vehicular Ad hoc Networks (VANET) are proposed to avoid collisions and improve road users' safety at intersections. In this paper, we investigate the use of Vehicle-To-Vehicle (V2V) communications and Real-Time Databases to mitigate collision risks, reduce the calculation time, and thus enhance safety at intersections. Specifically, we provide a new system, that we call Cooperative Intersection Collision Avoidance Persistent (CICAP) system to avoid potential accidents at intersections and minimize accident risk. Each vehicle stores its information as well as the nearby vehicles' information in a local Real-Time Database (RTDB). As it approaches to the intersection area, the vehicle queries its database and selects the target vehicles to execute the system. We used the VEINS framework to simulate different driving scenarios at urban intersections. Our simulation results confirm the proposed system's performance as a new cooperative intersection collision avoidance system based on V2V communication and RTDB.

Collision avoidance system, collision avoidance method and motor vehicle

Abstract: The invention discloses a collision avoidance system, a collision avoidance method and a motor vehicle. The early warning module of the collision avoidance system is used for conducting normalization processing on the emergency own vehicle braking times, current driving time, own vehicle state parameters, environment state parameters and preprocessed vehicle following state parameters, then inputting the information to a BP neural network pre-trained by a training sample and accordingly predicting the acceleration of an own vehicle to be braked, the early warning module judges whether early warning about vehicle following is needed to be started or not according to the predicted own vehicle braking acceleration, accordingly the purpose of integrating different types of driving habits of drivers into early warning about vehicle following is achieved, further the individualized early warning requirements of the drivers having different driving habits are met, and the phenomenon that the false alarm probability is higher for drivers having skilled driving experiences and radical characters but early warning is possibly not timely for novice drivers is avoided.

Intelligent algorithm based on support vector data description for automotive collision avoidance system

Abstract: This paper presents a theoretical expansion of a new intelligent algorithm called extended support vector data description (E-SVDD) for the analysis and control of dynamic groups to realize macroscopic and microscopic behavior prediction in an automotive collision avoidance system. The time to collision concept was extracted as a key parameter via system modeling and used with the E-SVDD algorithm to set up the relevant generalized theoretical system. A new method, along with its practical application, to predict the behavior of micro- and macro-systems in real time and improve the control logic for collision avoidance was realized. A numerical simulation based on actual driving data was performed to compare the proposed collision avoidance logic and the conventional one. The results confirmed the improved performance and effectiveness of the proposed control logic.

Automobile collision avoidance system early warning system based on car networking

Abstract: The utility model relates to an automobile collision avoidance system early warning system based on car networking comprises automobile -mounted terminal 1, 4G data module 2 and server / cloud platform 3. Automobile -mounted terminal 1 is to information such as 3 timed sending positions on server / the cloud platform, speed and direction of motions, the real time kinematic analysis is carried out to server / 3 pairs of all vehicle information on the cloud platform, when the actual car distance of closing on two cars is close or is less than minimum approach distance, sends early warning or warning message by server / cloud platform 3 to automobile -mounted terminal 1, server / cloud platform 3 also in time sends information such as the place ahead road, traffic (blocking up) situation to automobile -mounted terminal 1. The utility model has the advantages of data transmission is reliable, automobile -mounted terminal is with low costs, system easy operation.

Sense and avoid based on visual pose estimation for small UAS

Abstract: Small unmanned aircraft systems (UAS) must be able to detect and avoid conflicting traffic, an especially challenging task when the threat is another small UAS. Collision avoidance requires trajectory prediction and the performance of a collision avoidance system can be improved by extending the prediction horizon. We describe an algorithm that predicts the trajectory of a small, fixed-wing UAS using an estimate of its orientation. First, a computer vision algorithm locates specific feature points of the threat aircraft in an image. Next, the POSIT algorithm uses these feature points to estimate the pose (position and attitude) of the threat. A sequence of pose estimates is then used to predict the trajectory of the threat aircraft in order to avoid a collision. To assess the algorithm's performance, the predictions are compared with predictions based solely on position estimates for a variety of encounter scenarios. Simulation and experimental results indicate that trajectory prediction using orientation estimates provides quicker response to a change in the threat aircraft trajectory and better prediction and avoidance performance.

Unmanned aerial vehicle three-dimensional collision avoidance method based on binocular and ultrasonic fusion and unmanned aerial vehicle three-dimensional collision avoidance system thereof

Abstract: The invention provides an unmanned aerial vehicle three-dimensional collision avoidance method based on binocular and ultrasonic fusion and an unmanned aerial vehicle three-dimensional collision avoidance system thereof. The method comprises the steps that obstacles in the environment are detected through a binocular camera and an ultrasonic sensor; grid division is performed on a three-dimensional space, each frame is analyzed to obtain the probability of falling in the grid of local binocular point cloud, and coordinate system transformation is performed on the local binocular point cloud through an obstacle map fusion module and then an obstacle map is generated; and all the possible path points of an unmanned aerial vehicle from the start point to the end point are traversed by using an A* algorithm, and the optimal path is selected. Multiple obstacles of different materials can be detected by combining the binocular camera and the ultrasonic sensor so that the robustness of the system and the safety of the unmanned aerial vehicle can be enhanced; and the optimal path is computed based on a vertical sampling 2.5-dimensional A* collision avoidance technology, and the rotor unmanned aerial vehicle is controlled to fly according to the obtained optimal path so that the computing time of the conventional method can be greatly reduced and the flying efficiency of the unmanned aerial vehicle can be enhanced.

Collision avoidance system for vehicle

Abstract: A vehicular collision avoidance system includes a first image processor that processes image data captured by a forward-viewing camera to detect vehicles and determine vehicles present in the occupied lane and adjacent lane, and a second image processor that processes image data captured by a rearward-viewing camera to detect the presence of vehicles and determine vehicles present in the occupied lane and adjacent lane. Information relating to the vehicles is wirelessly transmitted between the vehicles. Responsive at least in part to at least one of (i) image processing of image data captured by the forward-viewing camera and/or rearward-viewing camera, (ii) sensor data sensed by at least one other sensor, and (iii) information transmitted to or from the equipped vehicle via the car2car (v2v) communication system, the collision avoidance system is operable to determine imminence of collision with the equipped vehicle by another vehicle present exterior the equipped vehicle.

Formally Verified Safe Vertical Maneuvers for Non-deterministic, Accelerating Aircraft Dynamics

Abstract: We present the formally verified predicate and strategy used to independently evaluate the safety of the final version (Run 15) of the FAAs next-generation air-traffic collision avoidance system, ACAS X. This approach is a general one that can analyze simultaneous vertical and horizontal maneuvers issued by aircraft collision avoidance systems. The predicate is specialized to analyze sequences of vertical maneuvers, and in the horizontal dimension is modular, allowing it to be safely composed with separately analyzed horizontal dynamics. Unlike previous efforts, this approach enables analysis of aircraft that are turning, and accelerating non-deterministically. It can also analyze the safety of coordinated advisories, and encounters with more than two aircraft. We provide results on the safety evaluation of ACAS X coordinated collision avoidance on a subset of the system state space. This approach can also be used to establish the safety of vertical collision avoidance maneuvers for other systems with complex dynamics.

Mobile platform automatic collision avoidance method and system and mobile platform

Abstract: The invention discloses a mobile platform automatic collision avoidance method. The mobile platform automatic collision avoidance method comprises the steps of acquiring environmental data of the surrounding environment of a mobile platform; recognizing whether there is an obstacle or not in the environmental data, and acquiring information of the obstacle and the current moving state of the mobile platform; calculating the maximum safe speed of the mobile platform; calculating target moving speed of the mobile platform and controlling the mobile platform to move according to the target moving speed; setting a distance threshold, judging a relation between the distance between the obstacle and the mobile platform and the distance threshold, and controlling the mobile platform to bypass the obstacle according to a judgment feedback result. The mobile platform automatic collision avoidance method provided by the invention can effectively respond to an obstacle in the environment and avoid collision with the obstacle. The invention further provides an automatic collision avoidance system and a mobile platform comprising the automatic collision avoidance system.

Collision Avoidance System for Collaborative Robotics

Abstract: In this paper a real-time collision avoidance algorithm, based on the method of artificial potentials an intended for collaborative robotics applications was studied. Within this work, the movements of a person are detected and acquired by a vision system and a dummy, developed to interact with a robot in a simulated workspace, replicates these actions. Ellipsoids are then defined to entirely include several parts of the dummy and the end-effector of the robot. The minimum distance between the ellipsoids of the dummy and the one of the end-effector is the input of the collision avoidance algorithm. The results of tests are presented to show the effectiveness of the algorithm. Finally, the influence of the velocity of the obstacle on the capability of the algorithm of ensuring safe collision avoidance is analyzed.

Collision avoidance system with cooperative adaptive cruise control in highway entrance ramp environment

Abstract: Although efforts have been done to solve collision avoidance using either environment recognition sensors or vehicle-to-vehicle (V2V) communication information, it is still a challenging problem in some specific scene, e.g. highway entrance ramp. In this paper, we propose a new cooperative adaptive cruise control (CACC) method which combines information of environment recognition sensors and V2V communication. A collision detection system of CACC will work based on the information of V2V communication before environment recognition sensors detecting obstacles accurately. Co-simulation experiment using PreScan and Simulink is conducted. The experimental results show that the intelligent vehicle with our method can pass the freeway entrance ramp more safely.

Performance Evaluation of Vehicle-to-Vehicle Communication for Cooperative Collision Avoidance at Urban Intersections

Abstract: Vehicle-to-Vehicle (V2V) communication can significantly enhance the performance of collision avoidance systems through periodically exchanging information between vehicles. At urban intersections, the effect of shadowing caused by buildings has a severe influence on the communication performance. In addition, an increased traffic density near an intersection creates a high level of interference, which can lead to a communication performance degradation. In this paper, we evaluate the performance of IEEE 802.11p based V2V communication for cooperative collision avoidance at urban intersections. We focus on the impact of shadowing from buildings and of traffic density on the communication performance. For this purpose, we investigate the effect of both the data rate and transmission power in different scenarios. The simulation results show that transmission power and data rate can be tailored to increase the reliability of the communication for the collision avoidance system. Simulation results also show that buildings at intersections reduce the interference from vehicles in other road sections. In addition, our simulation results reveal more insight on the main cause of packet loss near intersections. They show that loss due to packet collisions is the dominant reason, which can be reduced by increasing the data rate.

Dynamic Collision Avoidance System for a Manipulator Based on RGB-D Data

Abstract: The new paradigms of Industry 4.0 demand the collaboration between robot and humans. They could help and collaborate each other without any additional safety unlike other manipulators. The robot should have the ability of acquire the environment and plan (or re-plan) on-the-fly the movement avoiding the obstacles and people. This paper proposes a system that acquires the environment space, based on a kinect sensor, performs the path planning of a UR5 manipulator for pick and place tasks while avoiding the objects, based on the point cloud from kinect. Results allow to validate the proposed system.

A collision avoidance system with fuzzy danger level detection

Abstract: Collision avoidance is an essential component in advanced driving assistance systems, as it ensures the safety of the vehicle in near crash or crash scenarios. In this study, a collision avoidance system for lane change events is proposed which plans the trajectory based on the level of danger. The danger level is computed by a fuzzy inference system developed with naturalistic driving data to better capture the real-world factors, which may cause an accident. In addition, a fault determination classifier is introduced in order to determine the responsible driver in a near crash event. This system is evaluated on simulated naturalistic near crash events and the results demonstrate good performance of the proposed system.

Autonomous lane keeping based on approximate Q-learning

Abstract: Obstacle avoidance is one of the most important problems in autonomous robots. This paper suggests a collision avoidance system using reinforcement learning. Hand-crafted features are used to approximate Q value. With off-line learning, we develop a general collision avoidance system and use this system to unknown environment. Simulation results show that our mobile robot agent using reinforcement learning can safely explore a corridor even if the agent does not know the shape of corridor at all.

Driver Comprehension of Integrated Collision Avoidance System Alerts Presented through a Haptic Driver Seat

Abstract: The purpose of this study was to quantify the effects of increasing the number of collision avoidance system alerts presented through a haptic driver seat on drivers’ response performance. Twenty-four participants performed specific driving maneuvers in response to one, three, or seven haptic seat alerts while they drove an instrumented vehicle. Participants verbally identified the alerts after executing a maneuver. Results show that drivers made the correct driving maneuver in response to the alerts. This was likely because of the strong stimulus- response compatibility designed into the haptic seat. As predicted by Information Theory, drivers’ mean manual response time to the alerts significantly increased, and their verbal response accuracy significantly degraded, as the number of alerts increased. A three-alert haptic seat approach is recommended providing specific design requirements are met.

Intelligent vehicle collision avoidance system and method based on laser radar

Abstract: The present invention provides an intelligent vehicle collision avoidance system based on a laser radar and is applicable to the technical field of vehicles. The system comprises at least one laser radar which scans the position data of a surrounding environmental object, at least one intelligent vehicle which sends an area selection signal to the laser radar and receives the switching value signal transmitted by the laser radar as a control signal, and at least one collision avoidance module which analyzes the position data and transmits the switching value signal to the intelligent vehicle, wherein the intelligent vehicle, the laser radar and the collision avoidance module are in a communication connection. The invention provides an intelligent vehicle collision avoidance method based on a laser radar. Therefore, through using the laser radar to comprehensively detect whether a driving path has an obstacle, the assembly is simple, the system is convenient to use, the practicability of a product is improved, and the intelligent vehicle collision avoidance is achieved.