Collision Avoidance System Research Articles

Highly-sensitive expandable microsphere-based flexible pressure sensor for human–machine interaction

Flexible microstructural pressure sensors (FMPSs) have been widely used in different areas including health monitoring, human–machine interaction and electronic skin for their good reliability, easy fabrication, and highly sensitive sensing performance. Although the use of a sensing layer with microstructure improves the sensor sensitivity, it also results in limited sensitive pressure range, slow response and poor cyclic stability, which prevents the sensors from being utilized in applications requiring wide detect range, real-time response and high durability. Here, we propose an advanced micro-structured sensing layer through doping thermally expandable microspheres into the screen-printing carbon black slurry to enhance its mechanical properties. An FMPS is then developed based on this enhanced micro-structured sensing layer. Benefiting from the expanded microsphere-like microstructure, the as-prepared sensor features high sensitivity (37.16 kPa−1), fast response/recovery time (126/52 ms), and good mechanical stability (over 3000 cycles). In addition, a home-made and effective collision avoidance system consisting of a robotic arm, the pressure sensor, a MEGA2560 microcontroller unit and a computer is constructed to indicate the sensor’s outstanding tactile perception characteristic, making it a promising candidate for intelligent robotic applications such as human–robot collaboration. Furthermore, we develop a pressure sensor array and demonstrate its ability to spatial pressure distribution perception. The developed microsphere-based pressure sensor and its array show great potential to be adopted in various monitoring and interactive applications such as humanoid robots, smart home, human–machine interaction, etc.

Driving Difficulties and Preferences of Advanced Driver Assistance Systems by Older Drivers With Central Vision Loss.

The purpose of this study was to investigate driving difficulties and Advanced Driver Assistance Systems (ADAS) use and preferences of drivers with and without central vision loss (CVL). Fifty-eight drivers with CVL (71 ± 13 years) and 68 without (72 ± 8 years) completed a telephone questionnaire. They rated their perceived driving difficulty and usefulness of technology support in 15 driving situations under good (daytime) and reduced visibility conditions, and reported their use experience and preferences for 12 available ADAS technologies. Drivers with CVL reported more difficulty (P = 0.002) and greater usefulness of technology support (P = 0.003) than non-CVL drivers, especially in reduced visibility conditions. Increased driving difficulty was associated with higher perceived technology usefulness (r = 0.34, P < 0.001). Dealing with blind spot road users, glare, unexpected pedestrians, and unfamiliar areas were perceived as the most difficult tasks that would benefit from technology support. Drivers with CVL used more advanced ADAS features than non-CVL drivers (P = 0.02), preferred to own the blind spot warning, pedestrian warning, and forward collision avoidance systems, and favored ADAS support that provided both information and active intervention. The perceived benefits of and willingness to own ADAS technologies were high for both groups. Drivers with CVL used more advanced ADAS and perceived greater usefulness of driver assistance technology in supporting difficult driving situations, with a strong preference for collision prevention support. This study highlights the specific technology needs and preferences of older drivers with CVL, which can inform future ADAS development, evaluation, and training tailored to this group.

Collision Avoidance of Autonomous Driving at Low Speed in the Near Field of Vehicle

This paper aims to propose a new idea for realizing low-power-consumption, real-time, microcontroller-based, redundant embedded collision avoidance systems in autonomous driving applications. When operating a fully automated vehicle, the vehicle generates a driving trajectory based on the global route to the destination. The car must follow the generated driving path. It is essential to ensure the safety of this path by checking that it is collision-free. The goal of our low-level embedded collision avoidance system is to guarantee the safety of the path. After defining the driving path area associated with the generating path and the safe monitoring distance, the system can monitor the vehicle's defined Keep-Out-Area (KOA) by using 3D Light Detection and Ranging (LiDAR) sensor. Considering the relatively limited computing power of the microcontroller, the KOA is calculated offline and stored in a look-up table (LUT). This paper also introduces an experimental hardware platform based on the proposed system concept. This platform can facilitate the testing of various collision avoidance algorithms. Moreover, we also identify the challenges, such as false positives and deviation from the actual driving path.

Generating Structured Set of Encounters for Verifying Automated Collision and Grounding Avoidance Systems

It is a clear consensus in the maritime industry that ships, both conventional and with automated Collision and Grounding Avoidance (CAGA) systems, shall be navigated following the Convention on the International Regulations for Preventing Collisions at Sea (COLREG), ensuring a level playing field and a common understanding of the responsibilities between conventional and autonomous ships, allowing safe co-existence in the waterways. Simulation-based testing is expected to play an important role to explore and document safety and the ability to adhere to the COLREG, as it allows for rigorous testing of performance and failure handling before the software is installed on the ship. Many terms in COLREG used to specify acceptable behavior are qualitative, such as “ample time” and “apparent maneuver” and need to be viewed in light of a specific situation to be applied in practice. As the COLREG includes a large set of obligations specific to different types of situations, a significant number of ship encounters spread out across the different aspects of the regulations will be necessary to enable any judgments about the overall ability to adhere to these rules. The work presented in this paper provides a method and software toolbox for generating ship encounters to allow a systematic assessment of the vessel’s ability to act according to COLREG using simulation-based testing, and it is made freely available to vendors, students, or any other actors involved in the development or assurance of algorithms for automated collision and grounding avoidance systems.

Interaction between COLREG-compliant collision avoidance systems in a multiple MASS scenario

The transportation systems are heading towards increasing autonomy in all domains, and the maritime field makes no exception. The International Maritime Organization has been working on releasing a regulatory framework for Maritime Autonomous Surface Ships (MASS) to keep pace with the technological developments in the field. Autonomous shipping forces the researcher and the designers to face a wide range of scientific challenges, such as navigation decision support systems, collision avoidance algorithms, path planning, navigation and control, sensor data processing and fusion, remote control, and communication, with the final intent of achieving a fully integrated and autonomous worldwide maritime transportation system, where a human-less collaborative conflict resolution could potentially retire the COLREGs. However, the maritime sector will first face a transition period where traditional ships will share the seas and interact with heterogeneous MASS with various autonomous capabilities featuring different and probably incompatible communication protocols. In such a scenario, the COLREGs will still play a primary role in helping the collision avoidance systems resolve conflicts and limiting the degrees of freedom. This paper aims to study the interaction among multiple vessels with autonomous collision avoidance capabilities operating in a close navigation scenario. The ships operate according to a COLREG-compliant collision avoidance algorithm. The paper relies on numerical simulation to systematically investigate different scenarios in which autonomous vessels operate and interact in the presence of fixed obstacles. Results are presented and critically discussed.

Design of a microcontroller-based quadcopter prototype module Fly Sky XL163RX take off and landing

This research paper presents the design and development of a microcontroller-based quadcopter prototype module, named Fly Sky XL163RX, with the capability of take off and landing. The objective of this study is to design a reliable and efficient quadcopter module that can be utilized for various applications, such as aerial photography, surveillance, and delivery services. The proposed quadcopter module is equipped with the Fly Sky XL163RX microcontroller, which serves as the control unit for managing the flight operations. The design process involves several key steps, including the selection of appropriate components, integration of sensors and actuators, and the development of control algorithms. The quadcopter module utilizes a combination of sensors, including gyroscopes, accelerometers, and altimeters, to gather real-time data and stabilize the flight. The control algorithm employs a proportional-integral-derivative (PID) controller to adjust the motor speeds and maintain stability during take off and landing. The Fly Sky XL163RX microcontroller offers a user-friendly interface and supports various communication protocols, allowing for easy customization and control of the quadcopter module. Additionally, the module incorporates safety features, such as emergency landing capabilities and collision avoidance systems, to enhance flight security and prevent potential accidents. The performance of the Fly Sky XL163RX quadcopter module was evaluated through extensive flight testing. The results demonstrate the module's capability to achieve stable take off and landing operations, as well as its responsiveness to user commands. The module's compact size and lightweight design make it suitable for indoor and outdoor applications. In conclusion, this research presents the design and development of the Fly Sky XL163RX microcontroller-based quadcopter module, which exhibits reliable and efficient take off and landing operations. The module's integration of sensors, control algorithms, and safety features contribute to its overall performance and usability. Future work may focus on enhancing the module's capabilities, such as implementing autonomous flight modes and improving battery efficiency.Quadcopter, Microcontroller, FlySky XL163RX, Take Off, Landing, Control Algorithm, Sensors, Actuators, PID Controller, Flight Testing, Aerial Applications.

Crashworthiness design of functional gradient bionic structures under axial impact loading

Gradient structures have become a hot research topic because of their excellent crashworthiness. Inspired by the gradient distribution of human bone and the excellent energy absorption properties of thin-walled constructions, a novel biologically inspired functionally graded lattice-filled tube (FGLT) is proposed in this paper by combining a radial gradient lattice with a thin-walled structure. Lattice arrays with different gradient patterns were prepared by laser melting (SLM) technique and embedded in square thin-walled tubes for experimental crashworthiness study. It was found that there was a 25.47% increase in specific absorption energy of uniform lattice-filled tubes with respect to empty tubes, and a 36.65% increase in specific absorption energy of graded grating filled tubes with respect to empty tubes. It is noteworthy that the peak load of the structure is only improved by 3.95% compared to the empty tube for the gradient lattice as a filler embedded in the thin-walled tube. Finally, based on the response surface methodology (RSM) and the second-generation non-dominated ranking genetic algorithm (NSGA-II), the multi-objective optimization of the new bionic gradient structure with the maximum specific energy absorption and the minimum peak load is performed. The expression of the maximum standardized impact force is obtained by dimensionless processing, which can fully explore the influence of the structural parameters on the impact load. The functional gradient bionic structure provides new ideas for the design of more effective energy absorption structures and collision avoidance systems.

Towards an approach to define transparency requirements for maritime collision avoidance

This study discusses an approach to support human supervision of autonomous maritime collision avoidance systems by disclosing the system’s perceived information, internal reasoning, decisions, and planned actions as layers of transparency. Information requirements, identified through a cognitive task analysis, were structured using the information processing model by Parasuraman, Sheridan, and Wickens (2000). This model was contextualized to the maritime collision avoidance setting such that the information from the analysis could be structured into unique and distinct layers. A set of minimum information requirements was identified depicting the system’s decisions and planned action, supported by additional layers to reveal its internal reasoning. This approach aims at supporting humans in effectively supervising autonomous collision avoidance systems in their operational context by providing understandability and predictability about what the system is doing, why it is doing it, and what it will do next, i.e., transparency.

Robust visual detection of brake-lights in front for commercialized dashboard camera.

The collision avoidance system (CAS) is an essential system for safe driving that alerts the driver or automatically applies the brakes in an expected situation of a vehicle collision. To realize this, an autonomous system that can quickly and precisely detect brake-lights of preceding vehicle is essential and this should works well in various environments for safety reason. Our proposed vision algorithm solves these objectives focusing on simple color features rather than a learning algorithm with a high computational cost, since our target system is a real-time embedded device, i.e., forward-facing dashboard camera. However, the existing feature-based algorithms are vulnerable to the ambient noise (noise problem), and cannot be flexibly applied to various environments (applicability problem). Therefore, our method is divided into two stages: rear-lights region detection using gamma correction for noise problem, and brake-lights detection using HSV color space for applicability problem, respectively. (i) Rear-lights region detection: we confirm the presence of the vehicle in front and derive the rear-lights region, and used non-linear mapping of gamma correction to make the detected region robust to noise. (ii) Brake-lights detection: from the detected rear-lights region, we extract color features using the HSV color range so that we can classify brake on and off in various conditions. Experimental results show that our algorithm overcomes the noise problem and applicability problem in various environments.

The Terprom® Digital Terrain System (DTS)

Developed specifically for tactical military aircraft operations, TERPROM® is the world leading Digital Terrain System, offering a range of capabilities that can provide both safety and tactical benefits to the aircraft. The system is an established and well-proven product that has been in production since 1991. To date it has been selected by fourteen Nations worldwide for use on numerous platforms. The number of military aircraft equipped with TERPROM® is now over 5000 and growing. TERPROM® provides the following functions: Terrain Referenced Navigation (TRN), Predictive Ground Collision Avoidance System (PGCAS), Advanced Terrain Avoidance Cueing (ATAC), Obstruction and Wires Warning and Cueing (OWWC), Database Terrain Following (DBTF), Air to Ground Ranging Functions, Terrain Awareness Display (TAD). At the core of the system is the Terrain Referenced Navigation (TRN) capability which navigates by combining aircraft navigation data (e.g. inertial and, or GPS) and radar altimeter measurements of height above ground level (AGI), with terrain heights alms from the stored map data, to produce a navigation solution referenced to the terrain map data. This navigation solution then allows the other TERPROM® functions to use the map data to provide their safety and tactical capabilities. Three variants of TERPROM® have been developed to satisfy the airborne platform market: - Fast Jet, Military Transport, Helicopter. TERPROM® is a living product that has and continues to receive significant internal investment to increase its capability, functionality and performance to support future opportunities. Current areas of development include: Use of higher resolution map data which will increase the performance of TERPROM® and offer enhanced capability to platforms flying nap of the earth, enhanced capability in urban areas and could also reduce any platform reliance on GPS. Integration with active forward looking sensors to provide additional information to the Navigation, Situational Awareness and Ranging functions and also to provide new capabilities such as real time mapping of unmapped terrain features and obstructions.

Adaptive IMM-UKF for Airborne Tracking

In this paper, we propose a nonlinear tracking solution for maneuvering aerial targets based on an adaptive interacting multiple model (IMM) framework and unscented Kalman filters (UKFs), termed as AIMM-UKF. The purpose is to obtain more accurate estimates, better consistency of the tracker, and more robust prediction during sensor outages. The AIMM-UKF framework provides quick switching between two UKFs by adapting the transition probabilities between modes based on a distance function. Two modes are implemented: a uniform motion model and a maneuvering model. The experimental validation is performed with Monte Carlo simulations of three scenarios with ACAS Xa tracking logic as a benchmark, which is the next generation of airborne collision avoidance systems. The two algorithms are compared using hypothesis testing of the root mean square errors. In addition, we determine the normalized estimation error squared (NEES), a new proposed noise reduction factor to compare the estimation errors against the measurement errors, and an estimated maximum error of the tracker during sensor dropouts. The experimental results illustrate the superior performance of the proposed solution with respect to the tracking accuracy, consistency, and expected maximum error.

Conflict Free Flight Path: A Design Study for Automation

A number of future air traffic management concepts are being studied to enhance efficiency and flight safety. Conflict Detection and Resolution (CDR) is one such initiative for operation much beyond the capability of the conventional Traffic Collision Avoidance System where the resolutions are generally in terms of changing speed or heading depending upon the situation. The design studies presented in this paper investigate possibility of generating heading change commands and integrating with Autopilot for closed loop operation for conflict resolution as well as for recovering the flight path to the original flight leg. Simulation results for open loop and closed loop operation are presented to validate the approach. Topics requiring further studies are highlighted.

Identifying risky driving behavior: a field study using instrumented vehicles

ABSTRACT Road crashes continue to be a leading cause of death globally, with most of these crashes reportedly occurring due to human factors. Traditional road safety assessment utilises geometric and traffic parameters that consider road design inadequacies and identify traffic conflicts. However, previous studies do not represent risky driving behavior and its influence on crash occurrence. Incorporating human factors into safety evaluation is crucial to enhance the prediction and subsequent prevention of unsafe events. This research establishes a methodology to identify risky driving behavior using driving performance measures. These measures are computed based on continuous driving profiles collected using instrumented vehicles from a sample set of drivers on an expressway and are compared with historical crash data. The results indicate the significance of driving performance measures in evaluating road safety. The performance measures find application in collision avoidance systems, assessing the road design quality, testing safety countermeasures and guide for policymakers..

Implementation of Collision Avoidance System Algorithm in NPC Game 3D

Nowadays, with the rapid development of technology, we are given the convenience of finding entertainment such as games. Now this game can be quickly run on various media, one of them is a smartphone. Most smartphones' operating systems (OS) are Android and IOS. Among the both of OS which is currently popular is Android. This research aims to create an Artificial Intelligent of Non-Player Character (NPC) that can avoid every obstacle using the Collision Avoidance System algorithm. The result of the research is an android game app that applies the Collision Avoidance System that can make AI NPC avoid obstacles. The application of the algorithm to the NPC is made in 3 stages, namely, design by making a flowchart of the algorithm, then writing a program from the Collision Avoidance System, and finally, testing the AI ​​NPC. The test is carried out by comparing the reactions of NPC 1 and NPC 2 in passing through obstacles when on different paths by being carried out jointly between NPC. Based on the tests on AI NPC, NPC managed to avoid obstacles in front of them and the players, and it is almost 93% successful.

Vision-Based In-Flight Collision Avoidance Control Based on Background Subtraction Using Embedded System.

The development of high-performance, low-cost unmanned aerial vehicles paired with rapid progress in vision-based perception systems herald a new era of autonomous flight systems with mission-ready capabilities. One of the key features of an autonomous UAV is a robust mid-air collision avoidance strategy. This paper proposes a vision-based in-flight collision avoidance system based on background subtraction using an embedded computing system for unmanned aerial vehicles (UAVs). The pipeline of proposed in-flight collision avoidance system is as follows: (i) subtract dynamic background subtraction to remove it and to detect moving objects, (ii) denoise using morphology and binarization methods, (iii) cluster the moving objects and remove noise blobs, using Euclidean clustering, (iv) distinguish independent objects and track the movement using the Kalman filter, and (v) avoid collision, using the proposed decision-making techniques. This work focuses on the design and the demonstration of a vision-based fast-moving object detection and tracking system with decision-making capabilities to perform evasive maneuvers to replace a high-vision system such as event camera. The novelty of our method lies in the motion-compensating moving object detection framework, which accomplishes the task with background subtraction via a two-dimensional transformation approximation. Clustering and tracking algorithms process detection data to track independent objects, and stereo-camera-based distance estimation is conducted to estimate the three-dimensional trajectory, which is then used during decision-making procedures. The examination of the system is conducted with a test quadrotor UAV, and appropriate algorithm parameters for various requirements are deduced.

Design and analyses of shipborne multifunctional Automatic Identification System (AIS) antenna

ABSTRACT This paper is introducing analyses of new design of the automatic identification system (AIS) ships antenna that will serve for both VHF-band radio and satellite tracking and identification system for maritime applications. The current AIS network is an automatic tracking system used by ships of vessel traffic service for identification and location of vessels by electronically exchanging data between nearby ships and on-shore base station. In the AIS system for the electronic data exchange, the very high frequency (VHF) range is used. Utilizing of the VHF range makes the AIS as short-range communication, identification and collision avoidance system between AIS equipped ships and base station is possible in the antennas line-of-sight . In order to widen the range of the AIS from short range up to long or global range, AIS communication should be used via a satellite. In order to provide communication via satellite as well should be designed multifunctional antenna for both radio AIS (R-AIS) and satellite AIS (S-AIS) communication antenna. The analyses and design of a new multifunctional antenna, calculation and development, including implementation and testing of helical VHF antenna for R-AIS and S-AIS equipment are discussed.

A study on the development and trend of COLREGs – A broader perspective

AbstractWith the rapid development of the maritime industry and the emergence of unmanned ships, it is necessary to continuously review the International Regulations for Preventing Collisions at Sea (1972, COLREGs). This paper provides an overview of the developing history of the COLREGs and summarises the interpretations made by the International Maritime Organization official and academic scholars. Additionally, the paper discusses the application of the COLREGs in collision avoidance geometry and autonomous collision avoidance systems. Furthermore, the necessity and key points of revisions to adapt to industry advancements are discussed, along with an analysis of the main challenges faced. Finally, in light of the continuous progress and implementation of the outcome of the Regulatory Scoping Exercise for the Use of Maritime Autonomous Surface Ships (MASS), the paper points out that achieving consistency between manned and unmanned vessels, as well as developing COLREGs-based autonomous collision avoidance systems for more complex scenarios, is expected to be a significant trend in the future.

Lane Change–Intention Inference and Trajectory Prediction of Surrounding Vehicles on Highways

The behavior prediction of the surrounding vehicles is crucial when planning a minimal-risk path when realizing a collision-avoidance system. Herein, we propose a multiple model–based adaptive estimator (MMAE) that infers the lane-change intention of the surrounding vehicles and then predicts their trajectories. Specifically, first, a path is generated in the form of a cubic spline curve using the Frenet coordinate system, which is robust to changes in road curvatures. Linearized recursive least-squares estimation (LRLSE) method is used to adaptively predict a future trajectory based on the past trajectory of the target vehicle. Preview time is defined as a time-varying parameter that determines the final point of the path, and LRLSE updates it in real time. The MMAE applies LRLSEs to multiple paths and obtains the mode probability for each path, then the lane-change intention is inferred using the mode probability and preview time. The predicted future trajectory is the cubic spline curve determined based on the preview time. Further, we verify the performance of our approach using highD, a naturalistic dataset of vehicle trajectories, and compare it with those of existing methods. The proposed method does not require a large amount of data for training and has a low computational burden and high real-time performance.

Implementation of International Regulations for Preventing Collisions at Sea Using Coloured Petri Nets

The purpose of this study is to show how coloured Petri nets can be used to select the crossing rules guaranteeing that two ships avoid collisions at sea in accordance with the international regulations on this matter. This paper is exclusively focused on the solution to this small sub-problem within the overall “Collision Avoidance System” that the authors of the present study are currently developing. For easier understanding, the overall system is also briefly presented. How the Petri net in the CPN Tools software is fed with “Real Time Real World” data is presented. These data are generated outside the Petri net from the function block to predict a possible collision and from the current meteorological data. We also demonstrate how the rule selections made by the Petri net are transferred from the CPN Tools software into the “Real Time Real World”. This transferred information is used outside the Petri net in the function block to calculate avoidance routes. The definition of the colour sets that are used and the individual operations applied to these colour sets in the coloured Petri net are presented.

Business Case for Transit Bus Automated Collision Avoidance Systems

Although the National Transportation Safety Board has strongly recommended the application of collision avoidance warning systems and automated emergency braking (CAWS/AEB), the transit industry has lagged behind autos and trucks. CAWS/AEB for buses is more complex than for cars and trucks and represents a niche market. If bus manufacturers and suppliers are to invest in developing this technology, they will need to be convinced there is a market for it. Transit agencies also will need to be convinced that the technology works and is affordable. For both vendors and purchasers, a business case could be made that some or all of the expense of procuring and deploying the technology can be recovered through savings from reduced insurance premiums and claims payouts by preventing or mitigating collisions. This paper describes two methods for estimating the business case for equipping transit buses with CAWS/AEB. First, industrywide data on the numbers of collisions and casualty and liability expenses incurred by transit agencies were examined, and statistical relationships were modeled to determine whether reducing the numbers of collisions would reduce casualty and liability expenses. Second, individual collision claims records for specific transit agencies were examined to determine whether the collisions could have been prevented by CAWS/AEB, and the potential savings.