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The aircraft collision avoidance system (ACAS) is a surveillance system required in all airplanes to ensure a safe flight. To locate the presence of any surrounding aircraft that may pose a threat, the ACAS sequentially scans the fixed sectors (0° to 90°, 90° to 180°, 180° to 270°, and 270° to 360°) for a specified duration. As a result, ACAS necessitates a highly directional multi-element antenna capable of spanning the whole 360° azimuth plane. Over the past decade, studies on the performance enhancement of ACAS antennas have become increasingly prevalent due to the numerous limitations of the typical ACAS antenna, which include poor gain ( $3.6dB$ ), larger size ( $>\lambda$ ), high side-lobe level ( $-7dB$ ), challenges with beam tuning, etc. The main focus of this study is to improve the gain and bandwidth (BW) of an ACAS antenna using the notion of MTM, hence a novel U and L-shaped compact negative index MTM structure is developed. Because the ACAS antenna broadcasts the signal in the entire azimuth region, the proposed MTM should be competent to endure its double negative behavior for all incident angles; thus, the MTM cell is evaluated for different incident angles ranging from 0° to 360° in the azimuth plane with a 60° offset, and for all incident angles, the proposed design exhibits DNG behavior in the required frequency spectrum. The effective medium ratio (EMR) of 12.86 at 1.06GHz demonstrates the efficacy and compactness of the proposed design. The proposed MTM cell is expanded as a $5\times 4$ array, and placed as a superstrate at a fixed distance from the proposed ACAS antenna, and the MTM-loaded antenna outperforms the conventional antenna in terms of overall gain by 2.09dB and BW by 27.2MHz. Further, for the experimental verification, the MTM cell and its array structures are fabricated, and in both designs, the fabricated results correspond well with the simulated results.

A maritime collision avoidance system built on a database is being developed. Different information important for navigation, like electronic charts, bathymetric data, sea current and forecast weather conditions, etc., as well as knowledge about weather and loaddependent maneuvering capabilities of the involved vessels, are entered into the database tables. When using the system in real-time, the targeted data must be found very quickly in the database. In parallel, for the prediction of ship courses and for the calculation of evasive courses, the system must be capable of solving very many calculations in the shortest possible time, and these calculations often use database tables. Fast communication for updating database tables with the latest data is equally important in such a system. This article briefly presents the hardware developed for the project. We designed such data models for the efficient application of the Postgres database, capable of real-time calculation. [ABSTRACT FROM AUTHOR]

Unsignalized intersections are identified as the critical locations due to higher number of road crashes at these locations. The primary causes of crashes at unsignalized intersections are limited sight distance, incorrect assessment of gaps by drivers on the minor road, and higher speeds of vehicles on the major road. In an effort to improve safety and reduce the severity of crashes at unsignalized intersections, an intelligent transportation system (ITS) called the intersection conflict warning system (ICWS) has been developed. The ICWS consists of an activated warning sign and sensors that detect vehicles approaching the intersection. This paper aims to summarize the performance evaluation of ICWS that has been published in the literature. The review commences with an overview of the purpose of designing and installing ICWS at unsignalized intersections. It then discusses driving performance measures considered to evaluate the effectiveness of ICWS in three different environments, i.e., real world, driving simulator, and simulations, and their results are presented. The paper also discusses the type of sensors used to detect vehicles approaching the intersection and their accuracy in vehicle detection. The results reveal that ICWS had substantially improved driver behaviour. In the presence of ICWS, drivers resulted in shorter reaction time, lower approach speed, increased critical gap acceptance, and reduction in conflicts. An improvement in the performance of ICWS can be achieved by educating drivers about the sign, maintaining system reliability, and further examining the effect of various traffic factors, driver factors, and environmental factors on ICWS. The findings of this study can help researchers and engineers to design a better ICWS that can greatly enhance driving performance and safety at unsignalized intersections.

Unsignalized intersections are identified as the critical locations due to higher number of road crashes at these locations. The primary causes of crashes at unsignalized intersections are limited sight distance, incorrect assessment of gaps by drivers on the minor road, and higher speeds of vehicles on the major road. In an effort to improve safety and reduce the severity of crashes at unsignalized intersections, an intelligent transportation system (ITS) called the intersection conflict warning system (ICWS) has been developed. The ICWS consists of an activated warning sign and sensors that detect vehicles approaching the intersection. This paper aims to summarize the performance evaluation of ICWS that has been published in the literature. The review commences with an overview of the purpose of designing and installing ICWS at unsignalized intersections. It then discusses driving performance measures considered to evaluate the effectiveness of ICWS in three different environments, i.e., real world, driving simulator, and simulations, and their results are presented. The paper also discusses the type of sensors used to detect vehicles approaching the intersection and their accuracy in vehicle detection. The results reveal that ICWS had substantially improved driver behaviour. In the presence of ICWS, drivers resulted in shorter reaction time, lower approach speed, increased critical gap acceptance, and reduction in conflicts. An improvement in the performance of ICWS can be achieved by educating drivers about the sign, maintaining system reliability, and further examining the effect of various traffic factors, driver factors, and environmental factors on ICWS. The findings of this study can help researchers and engineers to design a better ICWS that can greatly enhance driving performance and safety at unsignalized intersections. [ABSTRACT FROM AUTHOR]

As the number of vehicles increases day by day, accidents are also rapidly increasing. This surge in accidents poses a significant challenge for road safety authorities, necessitating innovative solutions and stricter enforcement of traffic regulations. Addressing the root causes, such as driver education and infrastructure improvements, is crucial to mitigating the escalating risks on our roads. These accidents can occur due to false estimation of nearby vehicles, disturbances in the mind of the driver, or any other reasons that prevent the driver from maintaining focus on driving. Therefore, not only is the accurate estimation of the distance to other surrounding vehicles necessary, but quick actions are also required to avoid any kind of accidents. In addition, advancements in technology, such as the integration of automated driving assistance systems, aim to enhance the precision of distance estimation and mitigate the risk of accidents caused by human errors. As the automotive industry continues to innovate, the intersection of human vigilance and technological support becomes crucial for ensuring road safety. This paper is specifically focused on preventing accidents. The system is designed to measure the distance between the driving car and the front object. If the driver fails to maintain the minimum safety distance from the front object, the system will warn the driver to slow down the speed of the car and avoid a collision. The driver will receive both visual and audio warnings to ensure that a collision does not occur. Additionally, the paper incorporates advanced sensor technologies and real-time data analysis to enhance the accuracy of distance measurements, providing a robust and reliable solution for accident prevention. [ABSTRACT FROM AUTHOR]

Intelligent Transportation System (ITS) is continuously evolving alongside communication technologies and autonomous driving, giving way to new applications and services. Considering the significant rise in traffic casualties, protecting vulnerable road users (VRU), such as pedestrians, cyclists, motorcycles, animals, etc., has become ever more critical. That said, technological advances alone can not meet the requirements of such crucial applications. Therefore, combining them with architectural revolutions, particularly cloud, fog, and edge computing, is essential. In this review, we scrutinize the VRU safety application with regard to technological evolution. This review establishes the foundations for designing resilient, more reliable, end-to-end VRU protection services. It illustrates the possibility of combining the performance of different technologies through exploiting 5G architectural advantages (function placement, direct/indirect communication, etc.) for the intended application. In the context of 5G architecture, collision avoidance systems consider network and application-related challenges and solutions. This survey provides standardization, studies, and project efforts related to the use case and considers the different types of messages in the V2VRU communication-based safety application. We investigate how adapting the application parameters to the network state and devices' available resources can use network resources efficiently and provide reliable services. [ABSTRACT FROM AUTHOR]

Decision making is an essential component of autonomous vehicle technology and received significant attention from academic and industry organizations. One of the promising approaches in designing a decision-making method is Reinforcement Learning (RL). To apply an RL algorithm to an autonomous driving problem, a feature representation of the state must first be chosen. The most commonly used representation is the spatial-temporal state feature. However, if the number or order of the surrounding vehicle changes, the feature representation will be affected. In this paper, we utilize time-to-collision (TTC) as the feature representation and propose a TTC-based safety check system. The action output by the RL controller would be replaced with a safer action chosen by the safety check system when an agent detects a potential collision, i.e., the TTC is below the time threshold. A ramp merging task is used to illustrate the effect. Simulation results show that the proposed method can effectively improve the arrival rate and reduce the collision rate, even in the case of dense traffic situations. Furthermore, we also conducted experiments to examine the performance of the safety check system with different time thresholds. [ABSTRACT FROM AUTHOR]

A proposed mathematical model has been constructed to avoid both fixed and moving obstacles encountered on the ship's route. The mathematical model includes the manoeuvring model, MMG (Manoeuvring Modeling Group), and controller parts, MPC (Model Predictive Control), and PD controllers, separately. First, the turning and zigzag tests have been performed to validate the mathematical model. Especially, the turning test results are crucial since they are used as data in the control algorithm. The distance between the controlled ship and the obstacles is calculated in a time interval and the rudder is commanded according to these results. Second, a course including moving and fixed obstacles is determined for the case study. Finally, the path-following simulations for the determined course have been obtained thanks to the controllers. As a result, the ship reached the target coordinates without any collision and the fuel consumption differed depending on the controller selection. [ABSTRACT FROM AUTHOR]

The reliability of collision avoidance systems for Maritime Autonomous Surface Ships is one of the most critical factors for their safety. In particular, since many ship collisions occur in coastal areas, it is crucial to ensure the reliability of collision avoidance algorithms in geographically limited coastal waters. However, studies on maritime autonomous surface ships collision avoidance algorithms mainly focus on the traffic factor despite the importance of the geographic factor. Therefore, this study presents a methodology for establishing a practical collision avoidance system test bed, considering the geographic environment. The proposed methodology is a data-driven approach that objectively categorizes collision risk situations by extracting these risks using Automatic Identification System (AIS) and Electronic Navigational Chart (ENC) data, followed by clustering algorithms. Consequently, the research results present a direction for establishing test beds from the perspective of geographic and traffic factors. [ABSTRACT FROM AUTHOR]

Purpose – Basic safety message (BSM) is a core subset of standard protocols for connected vehicle system to transmit related safety information via vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I). Although some safety prototypes of connected vehicle have been proposed with effective strategies, few of them are fully evaluated in terms of the significance of BSM messages on performance of safety applications when in emergency. Design/methodology/approach – To address this problem, a data fusion method is proposed to capture the vehicle crash risk by extracting critical information from raw BSMs data, such as driver volition, vehicle speed, hard accelerations and braking. Thereafter, a classification model based on information-entropy and variable precision rough set (VPRS) is used for assessing the instantaneous driving safety by fusing the BSMs data from field test, and predicting the vehicle crash risk level with the driver emergency maneuvers in the next short term. Findings – The findings and implications are discussed for developing an improved warning and driving assistant system by using BSMs messages. Originality/value – The findings of this study are relevant to incorporation of alerts, warnings and control assists in V2V applications of connected vehicles. Such applications can help drivers identify situations where surrounding drivers are volatile, and they may avoid dangers by taking defensive actions.

In this article, a unified lane-keeping and forward collision avoidance system is proposed for semi-trailer trucks. Kinematic and dynamic models are described for lateral motion of the semi-trailer truck. The variation of the cornering stiffness is considered because its value depends on driving conditions such as vehicle speed and vertical load. The proposed system consists of the hitch angle estimation algorithm of the semi-trailer truck and the Model Predictive Controller (MPC) for the lateral motion of the semi-trailer truck. In the hitch angle estimation, the disturbance observer is utilized to compensate the lateral uncertainties and the estimation performance is validated in simulations and experiments. In the controller design, an MPC controller is designed both for lane keeping and collision avoidance, but their constraints in lateral motion are considered separately. In constructing the objective functions, constraint smoothing is applied to improve the feasibility of the semi-trailer truck motion. A simplification method is also introduced to reduce the computational complexity of the MPC and to improve the real-time performance. The proposed system is evaluated in simulations for lane keeping and collision avoidance, respectively.

The reliability of collision avoidance systems for Maritime Autonomous Surface Ships is one of the most critical factors for their safety. In particular, since many ship collisions occur in coastal areas, it is crucial to ensure the reliability of collision avoidance algorithms in geographically limited coastal waters. However, studies on maritime autonomous surface ships collision avoidance algorithms mainly focus on the traffic factor despite the importance of the geographic factor. Therefore, this study presents a methodology for establishing a practical collision avoidance system test bed, considering the geographic environment. The proposed methodology is a data-driven approach that objectively categorizes collision risk situations by extracting these risks using Automatic Identification System (AIS) and Electronic Navigational Chart (ENC) data, followed by clustering algorithms. Consequently, the research results present a direction for establishing test beds from the perspective of geographic and traffic factors.

The main objective of this paper was to propose a collision avoidance system that could be implemented in vehicles to prevent accidents. Collision Avoidance System is a system invented to prevent a collision. Whenever a collision is detected, they provide warning to the driver. There are different forms in which these collision avoidance systems are implemented in cars. The various causes for a collision include carelessness of the driver, blind spots on the road to the driver and sudden break down of other vehicles. The proposed approach helped to prevent the collision between the vehicles based on the detection of the obstacles. The system provides information about the possibility of a collision by detecting them. These obstacles are the vehicles that come within the safe limit (the minimum distance that is to be maintained between two vehicles) of the vehicle. This helps the vehicle to take control action on its own. It also provides alert messages. This system is simple and economical. Simulation studies demonstratedthat the proposed system can prevent a collision. It is capable of achieving a realistic collision avoidance system. Experimental results of the proposed system under various conditions are discussed. [ABSTRACT FROM AUTHOR]

Abstract Purpose Advanced Driver Assistance Systems (ADAS) have been among the key innovations in the automotive market for over a decade, since they promote traffic safety. This tendency is strengthened even more lately, with the introduction of the autonomous vehicles. A plethora of ADAS exist in the market today, using common warning thresholds for all drivers. However, since we are not all driving the same way, by offering common systems for all the drivers, neither the acceptance nor the effectiveness levels of ADAS are optimal. This manuscript attempts to optimize the Collision Avoidance System (CAS) warning, through intelligent personalized algorithms. Methods Starting with the identification of the dynamic parameters for driving behaviour modeling on the longitudinal road axis, the personalization parameters for ADAS are derived that form the basis for the algorithms developed. Also, based on literature studies, the safety boundaries for warning provision by the CAS are set and implemented in the algorithms. Results Specific personalized algorithms for the longitudinal road axis behaviour are developed, based on Time to Collision and Time Headway. The proposed algorithms based on Time Headway were assessed on-road with 10 drivers and were positively evaluated by the majority of the participants, with a varying degree of reliability and usability. Conclusions Based on the results obtained, it can be concluded that with the proposed algorithms, the initial hypothesis of the paper is verified, i.e. personalised warnings would get a greater acceptance by the drivers, of course without braking the safety limits. Further improvements of the algorithm could be achieved, possibly through a better determination of the car following event, since its definition includes a few assumptions.

Dynamic All-Red Extension (DARE) has recently attracted research interest as a non-traditional intersection collision avoidance method. We propose a probabilistic model to predict red light running (RLR) hazard for dynamic all-red extension system. The RLR hazard, quantified by a predicted encroachment time, has contributory factors including the speed, distance and car-following status of the violator and the empirical distribution of the entry time of conflict traffic. An offline data analysis procedure is developed to set the parameters for RLR hazard prediction. Online-wise, a two-dimensional normal model is developed to predict the vehicle’s stop-go maneuver based on speeds at advanced detectors. Additionally, unlike most prediction models which are designed to minimize mean errors, our model identifies two types of errors, namely the false alarm and missed report. The capability of distinguishing these two types of errors is crucial to the effectiveness of dynamic systems. To quantify the trade-off between these two types of errors in the system design, a system operating characteristics (SOC) function is then defined. Performance of the proposed model and its prediction algorithm is evaluated using data collected from a field intersection. At a false alarm rate of 5%, the algorithm reach a correct detection rate of over 65% to over 90% for various legs of the test intersection. Performance evaluation results showed that the proposed models and algorithms within the DARE framework can effectively detect the RLR hazards.

With the development of marine technology, the research of unmanned surface vehicles (USVs) has received wide attention from the world. Designing effective collision avoidance algorithm in dynamic sea environment is necessary for the navigation of USVs. This paper describes a collision avoidance system (CAS) with COLREGs compliance to improve autonomous navigational ability of USV. For small podded propulsion USV, a three-DOFs maneuvering model is established and the parameters of model are determined by the parameter identification method based on field experiments. About the COLREGs rules, the different maneuvering behaviors are summed up according to encounter situation and collision risk assessment. In the CAS, finite control set model predictive control is adopted, and COLREGs rules are taken as an evaluation standard in the quality function. Finally, the system is verified to avoid multiple dynamic obstacles and compliance vessel in the simulation and real environment, and the results of collision avoidance under four encounter situations are described in detail.

This paper describes automobile collision avoidance system by using of an ultrasonic sensor for a vehicle. We utilize the electronic systems application embedded in car that is anticipated to minimize the disaster of car accident. This paper is concentrating on developing a model of rear end car collision avoidance system that detects the gap among motors moving in the identical lane, inside the identical direction and alert the driver each time she or he is in danger range by using a microcontroller. The gap is measured via an ultrasonic sensor used to experience the obstacle beforehand. [ABSTRACT FROM AUTHOR]

This paper presents vehicle collision avoidance system using an ultrasonic sensor for a car. We use the application of electronic systems embedded in automobile which is expected to minimize the vehicle accident disaster. This paper concentrates on developing a model of rear end vehicle collision avoidance system that detects the distance between two vehicles moving in the same lane, in the same direction and alert the driver whenever he or she is in danger range using a microcontroller. The distance is measured by an ultrasonic sensor used to sense the obstacle ahead. [ABSTRACT FROM AUTHOR]

• Eye movements are recorded during simulated red-light-running driving. • Collision avoidance process was divided into detection stage and reaction stage. • Effects of warning timings and warning content on visual performances were conducted. Intersections have been recognized as hazard locations with lots of visual information that drivers need to process. Although the collision avoidance systems (CASs) have been proved to effectively reduce the crash rate and much research on the effectiveness of CASs has been conducted with regard to the driving behaviors, drivers' visual performances under the effects of different collision avoidance warning conditions that were closely related to the effectiveness of CAS have been neglected. In this study, a driving simulator experiment was conducted to evaluate the relationships among drivers' visual performances, drivers' different warning conditions (warning timings × warning content) and driver's gender when they crossed the intersections involved with red-light running (RLR) vehicles. The experimental results showed that warning timings had significant effects on the detection stage and reaction stage. Specifically, drivers could detect the conflicting RLR vehicle most quickly in the warning timings of 4.5 s ahead of a collision. When the warning was released earlier than 5.0 s ahead of a collision, driver tended to take brake action earlier than paying a fixation on a conflicting RLR vehicle. Warning content only had significant effects on drivers' detection stage. Compared to the non-directional warning, the specific directional information could shorten the time spent in detecting the conflicting RLR vehicle. Besides, directional information could increase drivers' average blink duration during the process of collision avoidance. Additionally, the results showed that female drivers were more likely to be involved with RLR collisions, and male drivers could detect the conflicting RLR vehicle more quickly than female drivers. Also, it had been found that later warning timings tended to increase female drivers' blink rate, and non-directional warning tended to increase female drivers' blink rate. These findings could direct warning condition design to improve the effectiveness of collision avoidance systems. [ABSTRACT FROM AUTHOR]

Urban environments are among the most challenging scenarios for car-following systems, since pedestrians may interfere with the platoon unexpectedly. To address this problem, this paper proposes a cooperative system using vehicle-to-vehicle and vehicle-to-pedestrian communication links. A fractional-order control-based cooperative adaptive cruise control benefits of communication for tighter inter-vehicle distances, while pedestrian communication is fused with LiDAR sensing to allow the detection of occluded pedestrians. The prediction of the pedestrians’ trajectories is used to perform a speed reduction or an emergency braking that interrupts the car-following yif necessary. Whenever a platoon decoupling occurs, a gap-closing maneuver is executed so that the ego-vehicle rejoins the platoon in a string stable way. The complete system was tested on experimental platforms at inria facilities, providing encouraging results and demonstrating the correct performance of the integrated systems. [ABSTRACT FROM AUTHOR]

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In this paper the key concepts of ITS - Intelligent Transport Systems, CPS - Cyber-Physical Systems and SM - Smart Mobility are defined and correlated with the need for ACAS – Airborne Collision Avoidance System, as the last resort safety net and indispensable ingredient in civil aviation. Smart Mobility is addressed from a Cyber Physical-Systems perspective, detailing some of the elements that this entails. Here we consider the Air Transportations System of the future as a Cyber-Physical System and analyze the implications of doing so from different perspectives. The objective is to introduce a 4D collision avoidance shield technology which forms a last resort safety net technology for the next generation air transport (2050 and beyond). The new system will represent a step change over the performance of current technology. As conclusions, the benefits of implementing Transport Cyber-Physical Systems are discussed, as well as what this would require for future deployment.

The Traffic Alert and Collision Avoidance System (TCAS) is recognized worldwide as the last resort for avoiding midair collisions. The existing TCAS can solve pairwise conflict effectively, but cannot manage multi-aircraft conflict satisfactorily, and more seriously, can even trigger domino conflicts in some situation. In response to the increasingly frequent multi-aircraft conflicts, especially three-aircraft conflicts, it is necessary to improve the ability of TCAS. This paper studies the collision avoidance of multi-aircraft scenarios and innovatively proposes a collaborative optimization of a collision avoidance system (CAS) based on the state prediction of the aircraft. In the process, not only invading aircraft but also potential invading aircraft are considered in the plan for an optimal conflict resolution program. From the perspective of mathematics, the collaborative multi-aircraft conflict detection and resolution algorithm is described in detail in this paper. In the end, this paper conducts a comparative experiment to prove the feasibility of the algorithm in three-aircraft scenarios using InCAS software and Gmas simulation software based on graphical modeling of complex systems. The experimental results show that the CAS proposed in this paper can efficiently prevent the occurrence of domino conflicts and guide each aircraft to avoid conflict areas and return to their origin trajectories. In contrast, the existing TCAS will cause the target aircraft to intensify the conflict with the potential invading aircraft when avoiding intruder aircraft. The research greatly remedies the gaps in the area of multi-aircraft collision avoidance and greatly improves the ability and efficiency of TCAS.

The operation of Unmanned Aerial Vehicles (UAVs) in civil airspace is restricted by the aviation authorities, which require full compliance with regulations that apply for manned aircraft. This paper proposes control algorithms for a collision avoidance system that can be used as an advisory system or a guidance system for UAVs that are flying in civil airspace under visual flight rules. A decision-making system for collision avoidance is developed based on the rules of the air. The proposed architecture of the decision-making system is engineered to be implementable in both manned aircraft and UAVs to perform different tasks ranging from collision detection to a safe avoidance manoeuvre initiation. Avoidance manoeuvres that are compliant with the rules of the air are proposed based on pilot suggestions for a subset of possible collision scenarios. The proposed avoidance manoeuvres are parameterized using a geometric approach. An optimal collision avoidance algorithm is developed for real-time local trajectory planning. Essentially, a finite-horizon optimal control problem is periodically solved in real-time hence updating the aircraft trajectory to avoid obstacles and track a predefined trajectory. The optimal control problem is formulated in output space, and parameterized by using B-splines. Then the optimal designed outputs are mapped into control inputs of the system by using the inverse dynamics of a fixed wing aircraft.