Journal articles: 'Intersection Collision Avoidance (ICA)'

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Wu, Zhizhou, Xin Zeng, and Haochun Yang. "System-Level Reliability Analysis of Cooperative Driving with V2X Communication for Intersection Collision Avoidance." Transportation Research Record: Journal of the Transportation Research Board 2674, no. 8 (2020): 696–709. http://dx.doi.org/10.1177/0361198120919756.

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Cooperative driving with vehicle-to-everything (V2X) communication is a promising technique to improve traffic safety and efficiency. Intersection collision avoidance (ICA) is a typical safety application of it. This paper analyzes reliability of ICA with cooperative manual driving at the system level. First, the reliability of an ICA system is defined as the probability of the ICA system avoiding collisions or near-misses at intersections without failure under conditions that collisions or near-misses are about to happen. Post-encroachment time is used in the expression of this definition. Then, components of the ICA system are classified into four types: hardware, software, maneuver, and V2X communication, and a reliability block diagram (RBD) is applied to reveal how these components contribute to system reliability. Five ICA system patterns with different V2X communication modes and strategy types are compared based on RBD analysis. This shows that centralized strategies are more reliable than decentralized ones for V2I communication if software reliability of these two strategies is the same. Furthermore, reliabilities of ICA components are analyzed in detail, and they are classified into two categories based on their different impact modes on the system. Finally, a numerical example shows how to test reliability of an ICA system using reliabilities of its components by Monte Carlo simulation. Results show that closer distances from vehicles to their conflict point when alerted, longer driver reaction time, and smaller vehicle deceleration rates are more likely to lead to system failure, whereas communication latency has little effect on it.

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Than, Than Yu. "Rules Based Intersection Collision Avoidance System for V2X Safety." International Journal of Advances in Scientific Research and Engineering (ijasre) 5, no. 10 (2019): 211–20. https://doi.org/10.31695/IJASRE.2019.33562.

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<em>The biggest problem associated with the increased use of private and public transport is the increasing number of accidents on the roads. Most of the intersection collision avoidance systems use vehicle-to-infrastructure communication to avoid accidents at urban intersections. However, they are costly because additional roadside infrastructure must be installed, and they suffer from problem-related to real-time information delivery. The proposed system namely, Rules-based Intersection Collision Avoidance System (RICA) is a novel application using GPS technology for vehicle-to-everything (V2X) safety. The distance to the intersection is calculated and a time-to-intersection index is computed to establish the risk of a collision. The proposed system was achieved through simulations. It is potential as a new intersection collision avoidance system for V2X safety based on vehicular ad hoc network (VANET) communication. The result reveals that the proposed system can effectively prevent the occurrence of traffic crashes at an intersection.</em>

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Kuo, C. C., J. K. Wu, and H. J. Shaw. "Collision Avoidance Schemes for Orthogonal Pipe Routing." Journal of Ship Production 15, no. 04 (1999): 198–206. http://dx.doi.org/10.5957/jsp.1999.15.4.198.

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This paper describes collision detecting and avoidance schemes to automatically lay out piping routes. The overlapping between the boundary boxes of equipment and pipelines is the basis for determining two types of collision: vertex-interference and edge-interference. Three collision-avoidance routing schemes have been developed using the modified adjacency and distance matrices and the line-surface intersection method. This collision avoidance scheme is for orthogonal pipe routing and forms the basis for extension to other routing principles.

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Fu, Yuchuan, Changle Li, Tom H. Luan, Yao Zhang, and Guoqiang Mao. "Infrastructure-cooperative algorithm for effective intersection collision avoidance." Transportation Research Part C: Emerging Technologies 89 (April 2018): 188–204. http://dx.doi.org/10.1016/j.trc.2018.02.003.

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Hankey, Jonathan M., Daniel V. McGehee, Thomas A. Dingus, Elizabeth N. Mazzae, and W. Riley Garrott. "Initial Driver Avoidance Behavior and Reaction Time to an Unalerted Intersection Incursion." Proceedings of the Human Factors and Ergonomics Society Annual Meeting 40, no. 18 (1996): 896–99. http://dx.doi.org/10.1177/154193129604001806.

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Initial driver avoidance behavior and reaction time to an unexpected intersection incursion was determined using a state-of-the-art motion-based driving simulator (Iowa Driving Simulator). The intersection used for the experiment was on a two-lane rural highway (55 mph speed limit) that controlled perpendicular (crossing) traffic by stop signs. The subject vehicle did not have to stop and had the right-of-way on the highway. At one of three possible start times, an intersecting vehicle began moving into the intersection in front of the subject vehicle. This incurring vehicle intersected from either the driver's left or right side. Ninety-six subjects participated in the study. Subjects in the shortest, most severe collision avoidance situation were significantly slower to react and equally likely to steer or release the accelerator pedal as the initial avoidance maneuver. Subjects in the longest, least severe collision avoidance situation often released the accelerator pedal and braked prior to steering. Gender differences are also discussed.

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Hou, Yew Cheong, Khairul Salleh Mohamed Sahari, Leong Yeng Weng, et al. "Development of collision avoidance system for multiple autonomous mobile robots." International Journal of Advanced Robotic Systems 17, no. 4 (2020): 172988142092396. http://dx.doi.org/10.1177/1729881420923967.

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This article presents a collision avoidance system for multiple robots based on the current autonomous car collision avoidance system. The purpose of the system is to improve the current autonomous car collision avoidance system by including data input of other vehicles’ velocity and positioning via vehicle-to-vehicle communication into the current autonomous car collision avoidance system. There are two TurtleBots used in experimental testing. TurtleBot is used as the robot agent while Google Lightweight Communication and Marshalling is used for inter-robot communication. Additionally, Gazebo software is used to run the simulation. There are two types of collision avoidance system algorithm (collision avoidance system without inter-robot communication and collision avoidance system with inter-robot communication) that are developed and tested in two main road crash scenarios, rear end collision scenario and junction crossing intersection collision scenario. Both algorithms are tested and run both in simulation and experiment setup, each with 10 repetitions for Lead TurtleBot sudden stop, Lead TurtleBot decelerate, Lead TurtleBot slower speed, and straight crossing path conditions. Simulation and experimental results data for each algorithm are recorded and tabulated. A comprehensive comparison of performance between the proposed algorithms is analyzed. The results showed that the proposed system is able to prevent collision between vehicles with an acceptable success rate.

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Németh, Balázs, and Péter Gáspár. "The Design of Performance Guaranteed Autonomous Vehicle Control for Optimal Motion in Unsignalized Intersections." Applied Sciences 11, no. 8 (2021): 3464. http://dx.doi.org/10.3390/app11083464.

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The design of the motion of autonomous vehicles in non-signalized intersections with the consideration of multiple criteria and safety constraints is a challenging problem with several tasks. In this paper, a learning-based control solution with guarantees for collision avoidance is proposed. The design problem is formed in a novel way through the division of the control problem, which leads to reduced complexity for achieving real-time computation. First, an environment model for the intersection was created based on a constrained quadratic optimization, with which guarantees on collision avoidance can be provided. A robust cruise controller for the autonomous vehicle was also designed. Second, the environment model was used in the training process, which was based on a reinforcement learning method. The goal of the training was to improve the economy of autonomous vehicles, while guaranteeing collision avoidance. The effectiveness of the method is presented through simulation examples in non-signalized intersection scenarios with varying numbers of vehicles.

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Yu, Than Than, Tin Maung Wynn, and May Zin Oo. "Rules Based Intersection Collision Avoidance System for V2X Safety." International Journal of Advances in Scientific Research and Engineering 05, no. 10 (2019): 211–20. http://dx.doi.org/10.31695/ijasre.2019.33562.

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ISMAIL B, MOHAMMED, MOHD ABDUL MUQEET, MOHAMMED FAWAD MALIK, and ABDUL KARIM KHAN. "Intersection Cross Traffic Warning System for Vehicle Collision Avoidance." International Journal of Advanced Research in Electrical, Electronics and Instrumentation Engineering 3, no. 11 (2014): 13155–60. http://dx.doi.org/10.15662/ijareeie.2014.0311031.

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Chen, Gang, Dan Liu, Yifan Wang, Qingxuan Jia, and Xiaodong Zhang. "Path planning method with obstacle avoidance for manipulators in dynamic environment." International Journal of Advanced Robotic Systems 15, no. 6 (2018): 172988141882022. http://dx.doi.org/10.1177/1729881418820223.

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Obstacle avoidance is of great importance for path planning of manipulators in dynamic environment. To help manipulators successfully perform tasks, a method of path planning with obstacle avoidance is proposed in this article. It consists of two consecutive phases, namely, collision detection and obstacle-avoidance path planning. The collision detection is realized by establishing point-cloud model and testing intersection of axis-aligned bounding boxes trees, while obstacle-avoidance path planning is achieved through preplanning a global path and adjusting it in real time. This article has the following contributions. The point-cloud model is of high resolution while the speed of collision detection is improved, and collision points can be found exactly. The preplanned global path is optimized based on the improved D-star algorithm, which reduces inflection points and decreases collision probability. The real-time path adjusting strategy satisfies the requirement of reachability and obstacle avoidance for manipulators in dynamic environment. Simulations and experiments are carried out to evaluate the validity of the proposed method, and the method is available to manipulators of any degree of freedom in dynamic environment.

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Han, Inhwan. "Car-mounted (black box) camera–based prediction and avoidance of intersection collisions for advanced driver assistance systems." Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering 235, no. 1 (2020): 231–44. http://dx.doi.org/10.1177/0954407020941370.

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This study analyzed video and quantitative data of 471 four-way intersection vehicle collisions obtained from Virginia Tech Transportation Institute near-accidents data and used the analysis results to determine the threshold value for each of the nine types of intersection collisions. The collision cases obtained for this study were categorized into nine groups based on the direction of the car that recorded the video and location of the other car estimated through video analysis. In obscure cases, the aspect rate was additionally used to assign a group. After the group it belongs to is identified, the change rate of aspect ratio and area change rate were used to determine the possibility and specific type of intersection collision. When a collision was imminent, avoidance possibility was calculated to avoid the collision completely, and if the collision was inevitable, partial collision maneuver method that causes the least damage was deduced. The suggested algorithms were verified using the black box video from 16 actual accident cases. With the exception of special cases such as when most of the vehicle was out of view, most of them showed high correspondence.

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Matsumi, Ryosuke, Pongsathorn Raksincharoensak, and Masao Nagai. "Development of Autonomous Intelligent Driving System to Enhance Safe and Secured Traffic Society for Elderly Drivers – Autonomous Collision Avoidance System with Hazard Anticipation Driver Characteristics –." Journal of Robotics and Mechatronics 25, no. 6 (2013): 966–72. http://dx.doi.org/10.20965/jrm.2013.p0966.

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In the aged society of Japan, accidents involving elderly drivers are increasing every year owing to their declined physical ability in terms of recognition and decision-making. An autonomous intelligent driving system is one of the promising technologies that can enhance safety and security for elderly drivers. This paper focuses on a situation in which drivers need to make a right turn at an intersection while negotiating pedestrians near a crosswalk region. An autonomous collision avoidance system associated with the electric braking torque of an electric vehicle is designed with the application of potential field theory while considering potential hazards because of occlusions at an intersection. Finally, the effectiveness of the autonomous collision avoidance systemis verified by computer simulations and driving experiments using a micro-scale electric vehicle.

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Gambhir, Mohit, and Sapna Gambhir. "Road Accident Prevention and Collision Avoidance at Intersection In VANET." International Journal of Computer Sciences and Engineering 7, no. 3 (2019): 1151–55. http://dx.doi.org/10.26438/ijcse/v7i3.11511155.

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Park, Soo-Yong, and Seok-Cheol Kee. "Optimized Right-Turn Pedestrian Collision Avoidance System Using Intersection LiDAR." World Electric Vehicle Journal 15, no. 10 (2024): 452. http://dx.doi.org/10.3390/wevj15100452.

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The incidence of right-turning pedestrian accidents is increasing in South Korea. Most of the accidents occur when a large vehicle is turning right, and the main cause of the accidents was found to be the driver’s limited field of vision. After these accidents, the government implemented a series of institutional measures with the objective of preventing such accidents. However, despite the institutional arrangements in place, pedestrian accidents continue to occur. We focused on the many limitations that autonomous vehicles, like humans, can face in such situations. To address this issue, we propose a right-turn pedestrian collision avoidance system by installing a LiDAR sensor in the center of the intersection to facilitate pedestrian detection. Furthermore, the urban road environment is considered, as this provides the optimal conditions for the model to perform at its best. During this research, we collected data on right-turn accidents using the CARLA simulator and ROS interface and demonstrated the effectiveness of our approach in preventing such incidents. Our results suggest that the implementation of this method can effectively reduce the incidence of right-turn accidents in autonomous vehicles.

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Colombo, Alessandro, and Domitilla Del Vecchio. "Least Restrictive Supervisors for Intersection Collision Avoidance: A Scheduling Approach." IEEE Transactions on Automatic Control 60, no. 6 (2015): 1515–27. http://dx.doi.org/10.1109/tac.2014.2381453.

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Baek, Min, Hwan Lee, Hyojin Choi, and Kyunbyoung Ko. "Development of Intersection Collision Avoidance Algorithm for B2V Safety Service." International Journal of Control and Automation 8, no. 12 (2015): 229–40. http://dx.doi.org/10.14257/ijca.2015.8.12.21.

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Brännström, Mattias, Jonas Sjöberg, Linus Helgesson, and Mikael Christiansson. "A Real-time Implementation of an Intersection Collision Avoidance System." IFAC Proceedings Volumes 44, no. 1 (2011): 9794–98. http://dx.doi.org/10.3182/20110828-6-it-1002.03172.

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Raksincharoensak, Pongsathorn, and Yuta Akamatsu. "Development of Collision Avoidance System in Right Turn Maneuver Using Vehicle-in-the-Loop Simulation." Journal of Robotics and Mechatronics 27, no. 6 (2015): 627–35. http://dx.doi.org/10.20965/jrm.2015.p0627.

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<div class=""abs_img""><img src=""[disp_template_path]/JRM/abst-image/00270006/04.jpg"" width=""300"" /> Right turn collision avoidance</div>Collisions in Japan between vehicles during right turns account for a high number of other intersection accidents. We present collision avoidance that introduces speed control assistance combined with autonomous emergency braking when vehicles approach and a collision becomes imminent. Our proposal uses on-board sensors such as radar and cameras to handle situations without depending on X2X communication and infrastructure. We also propose a speed control algorithm. A “vehicle-in-the-loop test” involving a virtual test drive for rapid system development verifies the effectiveness of our proposals.

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Brow, Gerald R. "Traffic conflicts for road user safety studies." Canadian Journal of Civil Engineering 21, no. 1 (1994): 1–15. http://dx.doi.org/10.1139/l94-001.

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In this paper we advocate an approach to road safety studies in which traffic conflicts are used as indicators of roadway hazard. The critical traffic process event used to define conflict severity is the time to collision, modified by an observer's evaluation of the risk of collision. Field studies were done to assess the validity, reliability, and practicality of traffic conflicts. Experiments were conducted to test the threshold value of time to collision, and to examine a visual perception theory of crash avoidance behaviour. The experiments demonstrate that a time to collision threshold value of 1.5 s is a reasonable time-based index of hazard and that a visual perception model of breaking is a promising concept. The wider potential for traffic conflicts as a measure of driver risk, and as a basis for safety models, is discussed in the paper. The technique has been used for some 45 intersection safety studies. From the application to date it appears that the systematic observation of crash avoidance behaviour of drivers in unsafe conditions provides a useful tool for traffic engineering analysis of intersection traffic control and design problems. Key words: road safety, traffic conflicts, time to collision, driver risk, safety models.

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Kaneko, Fujio. "A method for estimating the number of collision candidates in two waterways – for all intersection angles." Journal of Navigation 75, no. 2 (2022): 400–420. http://dx.doi.org/10.1017/s0373463321000898.

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AbstractEstimating the collision frequency of ships (F) is important for assessing collision risk on waterways. To date, F has been estimated as the product of the number of collision candidates $({N_{a }})$ and the causation probability $({P_c})$: $F = {N_{a}} \cdot {P_c}$, where ${N_{a }}$ represents the number of collisions that occur when related ships continue on course with no intervention, and ${P_c}$ is the probability that collision avoidance fails. Fujii developed a general method and Pedersen formulated it to estimate ${N_{a }}$ in an intersectional area. Their method is generally called ‘the geometric method’ because collision candidates are estimated only from the geometric relationship between two ships. The method has been used in many projects to estimate F in waterways; however, its use should be limited to intersection angles ranging from 10° to 170°. This paper presents a method, statistically verified by computer simulation, that can be used at all intersection angles to overcome this limitation. Moreover, it demonstrates strong agreement with Pedersen's method at intersection angles of 10° to 170°.

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Song, Jie, Mikhail Svinin, and Naoki Wakamiya. "Control for Autonomous Intersection Management Based on Adaptive Control Barrier Function." Applied Sciences 15, no. 5 (2025): 2315. https://doi.org/10.3390/app15052315.

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Autonomous intersection management (AIM) is gaining increasing attention due to its crucial role in ensuring safety and efficiency. Various methods have been proposed in the literature to address the AIM problem, including traffic light optimization, connected vehicle optimization based on vehicle-to-anything (V2X) communication technology, and multi-agent autonomous systems. However, each of these approaches has its own limitations, such as parking delays, communication latency, or the lack of guaranteed collision avoidance. This paper presents a novel approach to AIM using adaptive control barrier functions (aCBFs). The proposed aCBF first estimates the power transmission efficiency and incorporates it into the CBF design to ensure collision-free operation. Compared to existing methods, the aCBF approach offers several advantages. Firstly, it eliminates parking delays caused by traffic light systems. Secondly, it can be deployed in intersections with limited network coverage, unlike IoT-based solutions that rely heavily on connectivity. Thirdly, it ensures guaranteed collision-free agent movement at intersections. Specifically, our method guarantees that the minimum distance between agents remains no less than the safe distance at all times, significantly enhancing safety. Furthermore, compared to the TriPField algorithm, our approach achieves a 95% success rate in collision avoidance, demonstrating reliability in autonomous intersection management. The effectiveness of the proposed aCBF-based AIM algorithm has been validated through simulations and experiments with multiple autonomous agent-like robots.

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Chang, Che-Cheng, Wei-Ming Lin, and Chuan-An Lai. "Using Real-Time Dynamic Prediction to Implement IoV-Based Collision Avoidance." Applied Sciences 9, no. 24 (2019): 5370. http://dx.doi.org/10.3390/app9245370.

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For some IoV-based collision-avoidance architectures, it is not necessary that all vehicles have communication abilities. Hence, they need some particular designs and extra components. In the literature, one of them uses a camera mounted onto the infrastructure at an intersection to realize collision detection. Consequently, technologies for real-time object detection and dynamic prediction are required for the purposes of collision avoidance. In this paper, we propose an interesting method to predict the future position of a vehicle based on a well-known, real-time object detection project, YOLOv3. Our algorithm utilizes the concept of vehicle dynamics and the confidence region to predict the future position on vehicles. This will help us to realize real-time dynamic prediction and Internet of Vehicles (IoV)-based collision detection. Lastly, in accordance with the experimental results, our design shows the performance for predicting the future position of a vehicle.

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Lee, Suzanne E., Sarah B. Brown, Miguel A. Perez, Zachary R. Doerzaph, and Vicki L. Neale. "Normal and Hard Braking Behavior at Stop Signs and Traffic Signals." Proceedings of the Human Factors and Ergonomics Society Annual Meeting 49, no. 22 (2005): 1897–901. http://dx.doi.org/10.1177/154193120504902203.

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A testbed intersection violation warning system was developed to address the problem of intersection crashes. The effectiveness of such systems is fundamentally dependent on the driver-braking model used to decide if a warning should be issued to the driver. If the model is unrealistic, drivers can either be annoyed due to assumed braking levels that are too low, or can be warned too late if braking expectations are too high. Initial algorithm development relied on data from the Collision Avoidance Metrics Partnership (CAMP) Forward Collision Warning (FCW) project. However, it was unknown whether the CAMP data (collected in the presence of stopped lead vehicles) would be applicable to the intersection problem (e.g., will drivers respond similarly to red traffic signals and stopped lead vehicles). Braking profile and performance tests were thus conducted to determine the applicability of the CAMP FCW results to the intersection violation warning.

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Choi, Young-In, Jae-Hoon Cho, and Yong-Tae Kim. "Collision Avoidance Algorithm of Mobile Robots at Grid Map Intersection Point." INTERNATIONAL JOURNAL of FUZZY LOGIC and INTELLIGENT SYSTEMS 20, no. 2 (2020): 96–104. http://dx.doi.org/10.5391/ijfis.2020.20.2.96.

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Lloyd, Mary M., Glenn D. Wilson, Chris J. Nowak, and Alvah C. Bittner. "Brake Pulsing as Haptic Warning for an Intersection Collision Avoidance Countermeasure." Transportation Research Record: Journal of the Transportation Research Board 1694, no. 1 (1999): 34–41. http://dx.doi.org/10.3141/1694-05.

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Chen, Ting, Youjing Chen, Hao Li, Tao Gao, Huizhao Tu, and Siyu Li. "Driver Intent-Based Intersection Autonomous Driving Collision Avoidance Reinforcement Learning Algorithm." Sensors 22, no. 24 (2022): 9943. http://dx.doi.org/10.3390/s22249943.

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With the rapid development of artificial intelligent technology, the deep learning method is widely applied to predict human driving intentions due to its relative accuracy of prediction, which is one of critical links for security guarantee in the distributed, mixed driving scenario. In order to sense the intention of human-driven vehicles and reduce the self-driving collision avoidance rate, an improved intention prediction method for human-driving vehicles based on unsupervised, deep inverse reinforcement learning is proposed. Firstly, a contrast discriminator module was proposed to extract richer features. Then, the residual module was created to overcome the drawbacks of gradient disappearance and network degradation with the increase in network layers. Furthermore, the dropout layer was generated to prevent the over-fitting phenomenon in the whole training process of the GRU network, so as to improve the generalization ability of the network model. Finally, abundant experiments were conducted on datasets to evaluate our proposed method. The pass rate of self-driving vehicles with conservative driver probabilities of p = 0.25, p = 0.4, and p = 0.6 improved by a maximum of 8%, 10%, and 3%, compared with the classical method LSTM and VAE + RNN. It indicates that the prediction results of our proposed method fit more with the basic structure of the given traffic scenario in a long-term prediction range, which verifies the effectiveness of our proposed method.

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Zhang, Yunfan, Xuedong Yan, Jiawei Wu, and Ke Duan. "Effect of Warning System on Interactive Driving Behavior at Unsignalized Intersection under Fog Conditions: A Study Based on Multiuser Driving Simulation." Journal of Advanced Transportation 2020 (December 29, 2020): 1–16. http://dx.doi.org/10.1155/2020/8871875.

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The intersection collision warning system (ICWS) is an emerging technology designed to assist drivers in avoiding collisions at intersections. ICWS has an excellent performance in reducing the number of collisions and improving driving safety. Previous studies demonstrated that when visibility was low under fog conditions, ICWS could help drivers timely detect hazardous conflicting vehicles. However, the influences of ICWS on interactive driving behavior at unsignalized intersection between different vehicles have barely been discussed. This study aimed to investigate the patterns of drivers’ interactive behaviors with the assistance of a new kind of ICWS under fog conditions based on Multiuser Driving Simulation. The Multiuser Driving Simulation allowed multiple drivers to operate in the same simulation scenario at the same time, and it could capture drivers’ interactions preferably. Forty-eight licensed drivers completed the driving simulation experiment in three fog conditions (no fog, light fog, and heavy fog) and two warning conditions (warning and no warning), in which the drivers drove in a straight-moving situation at unsignalized intersection with potential collision risks caused by the encounter of two vehicles. The results verified that warning and fog conditions were significant factors that affected the interactive driving behavior in the unsignalized intersection collision avoidance process, including the driver’s decision, TTC of action point, average acceleration (deceleration) rate, and postencroachment time. Compared to conditions without ICWS, the ICWS could help drivers make collision avoidance actions earlier and change the speed more smoothly. In addition, with the help of Multiuser Driving Simulation, associations between decision driving behaviors of vehicles were discussed with caution. The results revealed the decision-making mechanism of drivers in the process of interaction with other drivers. Under the influence of fog, interactive driving processes were fraught with increased risk at unsignalized intersection. However, the ICWS helped drivers interact more harmoniously, safely, and efficiently. The findings shed some light on the further development of ICWS and the study on interactive driving behavior.

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Yang, Shujie, and Wei Sun. "Effective Ship Domains Considering Ship Encounter Situations and Speeds." Journal of Physics: Conference Series 2219, no. 1 (2022): 012031. http://dx.doi.org/10.1088/1742-6596/2219/1/012031.

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Abstract Ship domain is an important concept in assessing navigation situation and planning collision avoidance manoeuvres of a ship. For purpose of improving the precision and adaptability of the ship domains, effective ship domains are proposed for ships with different speeds in a variety of encounter situations in this work. Firstly, the COLREGs-based division of encounter types and corresponding collision avoidance actions are further optimized. Therefore, the problem of unclear division of responsibilities caused by the intersection of relative position and relative heading is resolved. On this basis, ship domains are determined by the encounter situations and the target ship’s speed. More specifically, the ship domain is approximated to a circle, and the dependence of the domain size on the encounter situation and the target ship’s speed has been analysed and described, that enable us to determine effective ships domains for ships varying in speeds and encounter situations. The simulation results show that ships can make effective collision-avoidance actions in different encounter scenarios based on the optimized COLREGs-based division of encounter types and effective ship domains.

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Wang, Jian, Xinyu Guo, and Xinyu Yang. "Efficient and Safe Strategies for Intersection Management: A Review." Sensors 21, no. 9 (2021): 3096. http://dx.doi.org/10.3390/s21093096.

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Intersection management is a sophisticated event in the intelligent transportation system due to a variety of behavior for traffic participants. This paper primarily overviews recent studies on the scenes of intersection, aiming at improving the efficiency or guaranteeing the safety when vehicles pass the crossing. These studies are respectively surveyed from the perspectives of efficiency and safety. Firstly, recent contributions to efficiency-oriented, intersection management overviews from four scenes, including congestion avoidance, green light optimized speed advisory (GLOSA), trajectory planning, and emergency vehicle priority preemption control. Furthermore, the studies on intersection collision detection and abnormal information warning are surveyed in the safety category. The corresponding algorithms for velocity and route management presented in the surveyed works are discussed.

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Christian, Vitale, Kolios Panayiotis, and Ellinas Georgios. "Autonomous Intersection Crossing With Vehicle Location Uncertainty." IEEE Transactions on Intelligent Transportation Systems 23, no. 10 (2022): 17546–61. https://doi.org/10.1109/TITS.2022.3152006.

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To date, a large body of the literature has looked into the problem of autonomous intersection crossings facilitated by Connected Autonomous Vehicles (CAVs). Nevertheless, existing approaches assume that CAVs know their exact location and system state. This work presents a novel framework that allows for an optimized intersection management, which considers vehicle location uncertainties for linear-Gaussian systems. Building upon the proposed framework, a family of 0−1 integer linear programming optimizations are presented that can set, sequentially or simultaneously, the acceleration profiles of all vehicles in the intersection. Extensive simulation results are presented, proving that the proposed framework represents a real-time near-optimal approach that maximizes intersection throughput with probabilistic collision avoidance guarantees

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Fujinami, Yohei, Pongsathorn Raksincharoensak, Dirk Ulbricht, and Rolf Adomat. "Risk Predictive Driver Assistance System for Collision Avoidance in Intersection Right Turns." Journal of Robotics and Mechatronics 30, no. 1 (2018): 15–23. http://dx.doi.org/10.20965/jrm.2018.p0015.

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Most traffic accidents that result in injuries or fatalities occur in intersections. In Japan, where cars drive on the left, most of such accidents involve cars that are turning right. This situation serves as the basis of the development of our Advanced Driver Assistance System (ADAS) for intersection right turns. This research focuses on the scenario in which an object darts out from the blind spot created by heavy oncoming traffic as a vehicle is making an intersection right turn. When this happens, even if the driver brakes as hard as possible or an active safety function such as the Autonomous Emergency Braking System (AEBS) applies the brakes, the natural limits of physical friction may make it impossible to avoid a collision. To improve traffic safety given the limited potential of physical friction, this research seeks to develop a risk-predictive right-turn assistance system. The system predicts potential oncoming objects and reduces the vehicle velocity in advance. Blind corners can be detected by on-board sensors without requiring information from surrounding infrastructure. This paper presents a right-turn assistance system that avoids conflict with the AEBS in emergencies by decelerating the ego vehicle to a safe velocity.

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Ahn, Heejin, Andrea Rizzi, and Alessandro Colombo. "Robust Supervisors for Intersection Collision Avoidance in the Presence of Legacy Vehicles." International Journal of Control, Automation and Systems 18, no. 2 (2019): 384–93. http://dx.doi.org/10.1007/s12555-018-0768-4.

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Wang, Fu Ji, Zhen Yuan Jia, Ming Xing Li, Jian Wei Ma, and Lei Ding. "Generation of Geometric Measurement Collision-Free Path for Curved Part." Applied Mechanics and Materials 421 (September 2013): 427–32. http://dx.doi.org/10.4028/www.scientific.net/amm.421.427.

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Collision between the contact probe and the measuring part will occur easily when conducting geometric measurement of the curved parts with complex surface shape. To solve the security problem of geometric measurement, a generation method of collision-free measurement path was proposed. First, collision check was simplified into the calculation of line-surface intersection. Meanwhile, we used bounding box method and triangulation method as auxiliary tools. Then, when dealing with collision avoidance, we utilized bounding box in parametric directions to avoid collisions caused by neighboring surfaces. In addition, we used parameter extreme points to avoid collisions caused by the measuring surface itself. At last, path simulation of a complex curved part verifies the security of the path generated by means of the method proposed in this paper.

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Zhang, Jie, and Yingjun Zhang. "A Novel Ship-Ship Distance Model in Restricted Channel via Gaussian-TRR Identification." Mathematical Problems in Engineering 2021 (March 1, 2021): 1–19. http://dx.doi.org/10.1155/2021/6626850.

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Very large ships are crucial cargo ships that are relatively difficult to manoeuvre, and ship-ship distance is a vital manoeuvring parameter in restricted channel. To ensure ship safety and improve scheduling efficiency, this study established a ship-ship distance model in restricted channel by ship manoeuvring motion simulation, collision detection, and identification modelling. Firstly, the ship manoeuvring model calculated the forces and moments of ship-ship interaction and ship-bank interaction. Then, the collision detection was applied to calculate the intersection area of ship collision. Secondly, the discrete numerical simulation approach was employed with varying speed and distance, and the intersection area was counted. Finally, the 3D Gaussian models of encountering and overtaking were identified by the trust-region-reflective (TRR) algorithm, and ship-ship distance and prohibited zone were proposed. The results show that the minimum ship-ship distance for encountering and overtaking is 1.50 and 2.4 ship beam, respectively, which is consistent with Japan’s standard. The numerical results revealed that the prohibited zone is an elliptical shape. The ship-ship distance and prohibited zone serve as ship safety domain for collision avoidance during harbor approaching.

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Wang, Michael I. C., Charles H. P. Wen, and H. Jonathan Chao. "Roadrunner+: An Autonomous Intersection Management Cooperating with Connected Autonomous Vehicles and Pedestrians with Spillback Considered." ACM Transactions on Cyber-Physical Systems 6, no. 1 (2022): 1–29. http://dx.doi.org/10.1145/3488246.

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The recent emergence of Connected Autonomous Vehicles (CAVs) enables the Autonomous Intersection Management (AIM) system, replacing traffic signals and human driving operations for improved safety and road efficiency. When CAVs approach an intersection, AIM schedules their intersection usage in a collision-free manner while minimizing their waiting times. In practice, however, there are pedestrian road-crossing requests and spillback problems, a blockage caused by the congestion of the downstream intersection when the traffic load exceeds the road capacity. As a result, collisions occur when CAVs ignore pedestrians or are forced to the congested road. In this article, we present a cooperative AIM system, named Roadrunner+ , which simultaneously considers CAVs, pedestrians, and upstream/downstream intersections for spillback handling, collision avoidance, and efficient CAV controls. The performance of Roadrunner+ is evaluated with the SUMO microscopic simulator. Our experimental results show that Roadrunner+ has 15.16% higher throughput than other AIM systems and 102.53% higher throughput than traditional traffic signals. Roadrunner+ also reduces 75.62% traveling delay compared to other AIM systems. Moreover, the results show that CAVs in Roadrunner+ save up to 7.64% in fuel consumption, and all the collisions caused by spillback are prevented in Roadrunner+.

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Zhang, Hui, Rongqing Zhang, Chen Chen, Dongliang Duan, Xiang Cheng, and Liuqing Yang. "A Priority-Based Autonomous Intersection Management (AIM) Scheme for Connected Automated Vehicles (CAVs)." Vehicles 3, no. 3 (2021): 533–44. http://dx.doi.org/10.3390/vehicles3030032.

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In this paper, we investigate the intersection traffic management for connected automated vehicles (CAVs). In particular, a decentralized autonomous intersection management scheme that takes into account both the traffic efficiency and scheduling flexibility is proposed, which adopts a novel intersection–vehicle model to check conflicts among CAVs in the entire intersection area. In addition, a priority-based collision-avoidance rule is set to improve the performance of traffic efficiency and shorten the delays of emergency CAVs. Moreover, a multi-objective function is designed to obtain the optimal trajectories of CAVs, which considers ride comfort, velocities of CAVs, fuel consumption, and the constraints of safety, velocity, and acceleration. Simulation results demonstrate that our proposed scheme can achieve good performance in terms of traffic efficiency and shortening the delays of emergency CAVs.

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Sassen, Josua, Henrik Schumacher, Martin Rumpf, and Keenan Crane. "Repulsive Shells." ACM Transactions on Graphics 43, no. 4 (2024): 1–22. http://dx.doi.org/10.1145/3658174.

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This paper develops a shape space framework for collision-aware geometric modeling, where basic geometric operations automatically avoid inter-penetration. Shape spaces are a powerful tool for surface modeling, shape analysis, nonrigid motion planning, and animation, but past formulations permit nonphysical intersections. Our framework augments an existing shape space using a repulsive energy such that collision avoidance becomes a first-class property, encoded in the Riemannian metric itself. In turn, tasks like intersection-free shape interpolation or motion extrapolation amount to simply computing geodesic paths via standard numerical algorithms. To make optimization practical, we develop an adaptive collision penalty that prevents mesh self-intersection, and converges to a meaningful limit energy under refinement. The final algorithms apply to any category of shape, and do not require a dataset of examples, training, rigging, nor any other prior information. For instance, to interpolate between two shapes we need only a single pair of meshes with the same connectivity. We evaluate our method on a variety of challenging examples from modeling and animation.

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Jia, Jin Wei, Jian Feng Yu, and Jie Zhang. "An Obstacle Avoidance Method Based on Distance Fields in C-Space for Virtual Arm." Advanced Materials Research 591-593 (November 2012): 827–31. http://dx.doi.org/10.4028/www.scientific.net/amr.591-593.827.

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Collision detection is widely used in human motion simulation, however, it is difficult to work in large equipment model. To overcome the problem, this paper studies a collision detection method especially for virtual arm simulation. First, the method simplifies arm and obstacles in its reaching space with the C-space theory, and divides the space into small unit cells to form a distance fields, then extends the surfaces of obstacles to calculate the distances between each cell and its nearest obstacles, so the result of collision detection is depending on the distance fields’ value. Use CAA to redevelop DELMIA and apply it to the virtual assembly simulation of a certain type of aircraft center wing, compared with triangle intersection algorithm and mixed bounding box method, the result shows that the proposed method improves the efficiency of anthropology ergonomics simulation by more than 20% in the same condition.

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Aoki, Sota, Yohei Fujinami, Pongsathorn Raksincharoensak, and Roman Henze. "Proactive Braking Control System for Collision Avoidance during Right Turns with Occluded Vision at an Intersection." Applied Sciences 14, no. 6 (2024): 2661. http://dx.doi.org/10.3390/app14062661.

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This paper describes the development of an Advanced Driver Assistance System (ADAS) which will allow drivers to avoid collisions with an oncoming vehicle from an occluded area when turning right at intersections in left-hand traffic. Connected vehicles, in coordination with infrastructure, represent one of the commercialized ADAS technologies for collision avoidance. However, the coverage of the ADAS will be limited to designated intersections only, as communication equipment needs to be installed in both the vehicle and infrastructure to enable the assistance. This paper proposes an ADAS using on-board sensors, independent of infrastructure facilities, to control the vehicle velocity to avoid collisions. Most current intersection assistance, by using an Autonomous Emergency Braking System (AEBS), allows the driver to avoid a collision with oncoming vehicles when there is clear vision without occlusion. However, many accidents occur when the vehicle detects the oncoming vehicle too late because of occlusion in the intersection, such as a vehicle in the opposite lane. This system calculates the hazardous speed criteria of the ego vehicle, which might result in a high risk of collision when darting out occurs, and provides speed control assistance to allow the driver to escape from the hazardous speed region. The simulation results reveal that the proposed system effectively reduces the possibility of collisions compared to conventional AEBS.

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Wu, Zhizhou, Jie Yang, and Luoyi Huang. "Study on the Collision Avoidance Strategy at Unsignalized Intersection based on PreScan Simulation." Procedia - Social and Behavioral Sciences 96 (November 2013): 1315–21. http://dx.doi.org/10.1016/j.sbspro.2013.08.149.

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Komol, Md Mostafizur Rahman, A. N. M. Mizanur Rahman, Amit Kumer Podder, Md Sabid Hasan, and Sayemul Islam. "Design of Automated Bascule Bridge and Collision Avoidance with Water Traffic." Transport and Telecommunication Journal 25, no. 1 (2024): 54–65. http://dx.doi.org/10.2478/ttj-2024-0006.

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Abstract The development of movable bridges is a modern technological advancement that requires the integration of multi-disciplinary concepts such as control, automation, and design. In order to demonstrate how a collision avoidance system works, this research offers the design of an automated double-leaf bascule bridge with a pulley-rope moving mechanism and Pratt truss. The bridge is created where a settled railway or roadway intersection of a navigable stream cannot attain a steep profile. The design took into account the length, height, and width of the bridge as well as automatic ship identification and scaffold leaf movement activity for ship crossing. For the safe passage of cars on the bridge and for stopping vehicles during bridge movement, the system includes a collision avoidance control system and an automated road barrier system. After sensor adjustment, the model bridge’s performance under test produced results that were adequate, with a success rate of 100%.

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Zhang, Qiqian, Weiwei Xu, Honghai Zhang, and Han Li. "The Obstacle-Avoidance Path Planning for UAV Based on IOCAD." Xibei Gongye Daxue Xuebao/Journal of Northwestern Polytechnical University 38, no. 2 (2020): 238–45. http://dx.doi.org/10.1051/jnwpu/20203820238.

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To plan the path for UAV flying in the complex, dense and irregular obstacles environment, this paper proposed an obstacle collision-avoidance detection model and designed an UAV path planning algorithm based on irregular obstacles collision-avoidance detection (IOCAD), which includes irregular obstacles pretreatment method. The proposed method uses the grid method to model the environment. Rough set theory and convexity filling are used to pretreat the obstacles, and the ray method is used to select the available points. The intersection detection and the distance detection are held for the obstacle to the flight path. The objective function minimizes the distance from the obstacle to the flight path to get planned paths. The simulation results show that the proposed method can effectively plan the paths with the constraints of the assumed environment and UAV performances. It is shown that the performance of the proposed method is sensitive to the grid length and safety distance. The optimized values for the grid length and safety distance are 0.5 km and 0.4 km respectively.

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Wenhui, Liu, Zhao Jiandong, Zheng Jun, and Shen Tong. "Study on Cooperative Vehicles Infrastructure Collision Avoidance in Unsignalized Intersection using Simplified Conflict Table." Information Technology Journal 13, no. 2 (2014): 231–41. http://dx.doi.org/10.3923/itj.2014.231.241.

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Thangeswaran Natarajan. "Enhancing road safety through integrated vehicle communication systems and autonomous features." Global Journal of Engineering and Technology Advances 23, no. 3 (2025): 021–28. https://doi.org/10.30574/gjeta.2025.23.3.0174.

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Vehicle-to-Vehicle (V2V) and Vehicle-to-Infrastructure (V2I) communication technologies represent transformative advancements in automotive safety, offering unprecedented capabilities to prevent accidents and enhance traffic efficiency. These systems enable real-time information exchange between vehicles and infrastructure, creating a connected ecosystem that extends driver awareness beyond line-of-sight limitations. V2V technology demonstrates remarkable effectiveness in preventing crashes through applications like Forward Collision Warning and Intersection Movement Assist, addressing scenarios responsible for a substantial percentage of light-vehicle crashes and associated economic costs. Complementary V2I systems further enhance safety through hazard detection and dynamic traffic management capabilities. When integrated with autonomous features like automatic lane-changing, these technologies create a synergistic safety ecosystem that fundamentally transforms collision avoidance capabilities on modern roadways. Field operational testing confirms that vehicles equipped with integrated systems maintain significantly higher safety margins in emergency scenarios, while simultaneously improving traffic flow in congested environments. The economic justification for widespread implementation is compelling, with benefit-to-cost ratios indicating substantial returns on investment through crash prevention and efficiency improvements. These technologies collectively represent a paradigm shift in transportation safety, moving from reactive collision mitigation to proactive hazard avoidance through expanded situational awareness and coordinated vehicle responses.

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Wang, Ta-Chung, and Tz-Jian Lin. "UNMANNED VEHICLE OBSTACLE DETECTION AND AVOIDANCE USING DANGER ZONE APPROACH." Transactions of the Canadian Society for Mechanical Engineering 37, no. 3 (2013): 529–38. http://dx.doi.org/10.1139/tcsme-2013-0041.

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This paper proposes an obstacle avoidance algorithm for unmanned vehicles in unknown environment. The vehicle uses an ultrasonic sensor and a servo motor which rotates from 0 to 180 degrees to obtain the distance data, and the profile of the obstacle. In this avoidance algorithm we will use the danger zone concept to judge whether the obstacle will cause a possible collision. The danger zone concept surrounds the vehicle through the intersection of semi-algebraic sets. These semi-algebraic sets use the relative velocity of the obstacle to calculate the area in which obstacles will collide with the vehicle within a pre-specified time period. Combining the profile of the boundary of the obstacle with the danger zone concept, a method for determining the safe maneuvers to avoid collisions is also provided.

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FUJINAMI, Yohei, Pongsathorn RAKSINCHAROENSAK, Yuta AKAMATSU, Dirk ULBRICHT, and Rolf ADOMAT. "Development of Intersection Right Turn Collision Avoidance System by Using Risk Predictive Safe Speed Control." Proceedings of the Transportation and Logistics Conference 2016.25 (2016): 3302. http://dx.doi.org/10.1299/jsmetld.2016.25.3302.

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Muftygendhis, Rizky, Wei-Jung Shiang, and Chia-Hung Hsu. "A Study of AGV Collaboration with Internet of Things Concept for Collision Avoidance at Warehouse Intersection." RSF Conference Series: Engineering and Technology 2, no. 1 (2022): 01–06. http://dx.doi.org/10.31098/cset.v2i1.537.

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With advance of technology, automated guided vehicle (AGV) will become common daily vehicles, which means collaboration between AGVs are more and more important. This paper suggests that how to make AGV avoid collisions with other AGVs is a practical problem, and it is a common need and should be solved if there are two or more AGVs interacting with others. Therefore, a better system design should be developed and implemented. This paper used a three-layer structure of internet of things (IoT) to design an AGV collaboration system, to avoid collisions with other AGVs in this system, and to decrease path deviation. The concept of IoT was applied for AGV communicating with other AGVs through sending AGV position messages. In such a case, AGV would know other AGV positions and decide which actions to take. This paper used Robot Operating System (ROS) to design an AGV collaboration system, and conducted an experiment to verify the feasibility of this system. The experiment simulated the intersection of warehouse in the real world. According to the results, two AGVs can avoid collisions by knowing positions of each other in every path scenario. When two AGV both followed straight paths, the deviation was the smallest. When one AGV turned left and another turned right, it might have largest deviation.

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White, Bryon, and Kimberly A. Eccles. "Inexpensive, Infrastructure-Based, Intersection Collision-Avoidance System to Prevent Left-Turn Crashes with Opposite-Direction Traffic." Transportation Research Record: Journal of the Transportation Research Board 1800, no. 1 (2002): 92–99. http://dx.doi.org/10.3141/1800-12.

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Zhang, Yuting, Xuedong Yan, Xiaomeng Li, and Jiawei Wu. "Changes of drivers’ visual performances when approaching a signalized intersection under different collision avoidance warning conditions." Transportation Research Part F: Traffic Psychology and Behaviour 65 (August 2019): 584–97. http://dx.doi.org/10.1016/j.trf.2017.12.018.

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Vats, Hitender, and Ranjeet Singh Tomar. "RMAC." International Journal of E-Health and Medical Communications 12, no. 2 (2021): 77–92. http://dx.doi.org/10.4018/ijehmc.2021030105.

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One knows that smart transport is also an integrated part of healthcare technologies. To minimize the pollution for benefiting the healthcare, the traffic throughput on roundabout intersection has to be increased which will reduce wasted time and will also enhance passenger comfort. This paper presents a new approach by use of cooperative vehicular control utilizing VANET without compromising the safety of vehicles. This intersection side unit (ISU)-based system use lane change mechanism. The modular use of lane with lane change in newly designed protocol CARA (collision avoidance at roundabout algorithm) will greatly enhance the capacity utilization of roundabout. A new simulator ‘RoundSim' was also developed exclusively for simulation in roundabout. A new MAC protocol RMAC (roundabout MAC) is also designed which will suit the roundabout management utilizing lane change to minimize sudden jerk to passengers, thus enhancing healthcare of people. This RMAC utilizes message set with different prioritization scheme which results in better utilization of allotted frequency spectrum.

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Journal articles on the topic 'Intersection Collision Avoidance (ICA)'

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