Cooperative Collision Avoidance Research Articles

Cooperative Collision Avoidance for Overtaking Maneuvers in Cellular V2X-Based Autonomous Driving

In this paper, we consider a cooperative autonomous driving system where a vehicle overtakes the one in front based on collective perception. To avoid collisions with vehicles on the other lane, we propose a V2X-based cooperative collision avoidance scheme. The overtaking vehicle estimates the distance between itself and the neighbors via V2V communications and decides whether to overtake or not. Two cases where the distance information is obtained independently and cooperatively are taken into account. We derive the probability of collision avoidance and analyze the influence of different factors such as speed and density of vehicles on the system performance. Simulation results verify our analysis and show that our V2X-based cooperative collision avoidance scheme performs better than traditional GNSS-based collision avoidance scheme. The performance gain brought by the cooperative case compared to the independent case in our scheme can also be observed.

Bio-Inspired Routing Protocol in VANET Networks- A Case Study

Vehicular Ad-Hoc NETworks (VANETs) have received considerable attention in recent years, due to its unique characteristics, which are different from Mobile Ad-Hoc NETworks (MANETs) such as rapid topology change, frequent link failure, and high vehicle mobility. VANET will provide several applications and services such as cooperative collision avoidance, emergency warning messages, cooperative intersection collision avoidance, and traffic management. VANET’s routing objective is to conduct packets through a path in the network to their final destinations. Currently, most of the proposed VANET routing protocols focus on urban or highway environments. The contribution of the paper falls within the study of VANET routing protocol in extreme and complex environments such as underground mines. This paper addresses the need for a bio-inspired adaptive routing protocol in VANETs which can tolerate low-density network traffic with little throughput and delay variation.

Cooperative collision avoidance algorithm for multi-vehicle based on vehicle networking technology

This paper addresses the problem of low success rate of traditional algorithm collision avoidance and poor control of parking distance. The vehicle network system and the vehicle kinematics model are established. The paper describes accurate estimation of the vehicle driving state in tunnel intranet based on vehicle sensor and vehicle GPS data. Constraints are established for fast response disturbances, rapid stabilisation, reduced braking acceleration and deceleration, and safe distances. From the energy point of view, we consider the relative kinetic energy of any two vehicles under the vehicle network, measure the collision risk, establish the objective function, and analyse the relative kinetic energy of all vehicles approaching the preceding vehicle. In this way, a multi-vehicle cooperative collision avoidance method based on vehicle network technology is realised. The experimental results show that the algorithm has strong collision avoidance performance, and the parking distance control is better, which can ensure safety.

Cooperative collision avoidance algorithm for multi-vehicle based on vehicle networking technology

Cooperative collision avoidance algorithm for multi-vehicle based on vehicle networking technology

Distributed model predictive control for vessel train formations of cooperative multi-vessel systems

Recently, the cooperative control of multiple vessels has been gaining increasing attention because of the potential robustness, reliability and efficiency of multi-agent systems. In this paper, we propose the concept of Cooperative Multi-Vessel Systems (CMVSs) consisting of multiple coordinated autonomous vessels. We in particular focus on the so-called Vessel Train Formation (VTF) problem. The VTF problem considers not only cooperative collision avoidance, but also grouping of vessels. An MPC-based approach is proposed for addressing the VTF problem. A centralized and a distributed formulation based on the Alternating Direction of Multipliers Method (ADMM) are investigated. The distributed formulation adopts a single-layer serial iterative architecture, which gains the benefits of reduced communication requirements and robustness against failures. The impacts of information updating sequences and responsibility parameters are discussed. We furthermore analyze the scalability of the proposed method. Simulation experiments of a CMVS navigating from different terminals in the Port of Rotterdam to inland waterways are carried out to illustrate the effectiveness of our method. The proposed method successfully steers the vessels from different origins to form a vessel train. Due to the effective communication, vessels can timely respond to the velocity changes that others make. After the formation is formed, the distances between vessels become constant. The results show the potential to use CMVSs for inland shipping with enhanced safety.

Cooperative Collision Avoidance for Nonholonomic Robots

In this paper, we present a method, namely $\epsilon$ CCA, for collision avoidance in dynamic environments among interacting agents, such as other robots or humans. Given a preferred motion by a global planner or driver, the method computes a collision-free local motion for a short time horizon, which respects the actuator constraints and allows for smooth and safe control. The method builds on the concept of reciprocal velocity obstacles and extends it to respect the kinodynamic constraints of the robot and account for a grid-based map representation of the environment. The method is best suited for large multirobot settings, including heterogeneous teams of robots, in which computational complexity is of paramount importance and the robots interact with one another. In particular, we consider a set of motion primitives for the robot and solve an optimization in the space of control velocities with additional constraints. Additionally, we propose a cooperative approach to compute safe velocity partitions in the distributed case. We describe several instances of the method for distributed and centralized operation and formulated both as convex and nonconvex optimizations. We compare the different variants and describe the benefits and tradeoffs both theoretically and in extensive experiments with various robotic platforms: robotic wheelchairs, robotic boats, humanoid robots, small unicycle robots, and simulated cars.

Method to Improve the Positioning Accuracy of Vehicular Nodes Using IEEE 802.11p Protocol

Currently, vehicle incidence remains high, but the related research is mainly focused on single-vehicle collision warning, which is unable to notice the following multiple endangered vehicles in emergency. The main technical challenge of chain collision warning is accurate and seamless ranging or positioning of the neighboring multiple vehicles. Because of the non-line of sight (NLOS) environments, the traditional ultrasonic or laser method does not work. At the same time, the accuracy of global navigation satellite system (GNSS) is over 10 m, such as global positioning system (GPS) or BeiDou satellite positioning system (BDS), which is not efficient for the cooperative collision avoidance (CCA) system. Moreover, GNSS fails to operate in NLOS tunnels or downtown areas where blockage of satellite signals is frequent. Thus, in this paper, a seamless and high accuracy positioning method based-on three kind of multi-source information fusion is proposed, i.e., the high accuracy local positioning information is provided by IEEE 802.11p protocol, the dual-mode wide area differential positioning information provided by the fusion of BDS and GPS, the positioning information of dead reckoning provided by the fusion of on-board diagnostic (OBD) and micro-electro-mechanical system-inertial navigation system. In vehicle positioning system, the accurate time of arrival (TOA) estimation is very important, so in this paper, a two steps method for TOA estimation using the IEEE 802.11p short preamble is proposed. Simulations show that in both the international telecommunication union vehicular multipath channel and the additive white Gaussian noise channel, the proposed method provides better accuracy and is less time complex than some well-known methods. The estimated TOA fused with the GNSS and OBD information can be used for seamless and high accuracy positioning in the CCA system to avoid traffic accident.

Virtual-Grid Based Traffic Control Strategy With Multiple Intersections Collaboration

This paper proposes a dynamic cooperative traffic control framework for multiple intersections based on virtual grids to optimize the throughput and ensure fairness among all traffic flows. The traffic flows are divided by virtual grids; we call it virtual grid-based cooperative control of multiple-intersections (VGCC). The road segment between two intersections has been divided into two parts, which are defined as the reference region and the decision region. When the vehicle arrives at or goes away from any one part, it registers or deregisters itself to the road side unit. The traffic controller at intersection, called intersection control unit, collects the traffic information from all road segments and receives traffic messages from adjacent intersections. The proposed signal-scheduling algorithm considers not only the flows at the local intersection with higher passing rates but also the flows at downstream signalized intersections with higher passing rates. To ensure fairness, the algorithm gives chances to those phases who has a lower passing rate by using the ageing-counter matrix. According to the real-time traffic information, this paper makes signal timing for each phase of a signal cycle one by one. Moreover, a cooperative collision avoidance predictive control algorithm is proposed, which can assist vehicles to pass the next intersection without stopping, by predicting the time conflict. The results indicate that the VGCC algorithm significantly decreases the average number of vehicles on a road segment by 30.77%, reduces the average queuing length by 28.89%, decreases the average time spent on passing intersection by 26.93%, and reduces the average waiting time by 35.21% than the intersection of common road networks algorithm.

Estimating meteorological visibility range under foggy weather conditions: A deep learning approach

Systems capable of estimating visibility distances under foggy weather conditions are extremely useful for next-generation cooperative situational awareness and collision avoidance systems. In this paper, we present a brief review of noticeable approaches for determining visibility distance under foggy weather conditions. We then propose a novel approach based on the combination of a deep learning method for feature extraction and an SVM classifier. We present a quantitative evaluation of the proposed solution and show that our approach provides better performance results compared to an earlier approach that was based on the combination of an ANN model and a set of global feature descriptors. Our experimental results show that the proposed solution presents very promising results in support for next-generation situational awareness and cooperative collision avoidance systems. Hence it can potentially contribute towards safer driving conditions in the presence of fog.

Using improved particle swarm optimization to tune PID controllers in cooperative collision avoidance systems

The introduction of proportional-integral-derivative (PID) controllers into cooperative collision avoidance systems (CCASs) has been hindered by difficulties in their optimization and by a lack of study of their effects on vehicle driving stability, comfort, and fuel economy. In this paper, we propose a method to optimize PID controllers using an improved particle swarm optimization (PSO) algorithm, and to better manipulate cooperative collision avoidance with other vehicles. First, we use PRESCAN and MATLAB/Simulink to conduct a united simulation, which constructs a CCAS composed of a PID controller, maneuver strategy judging modules, and a path planning module. Then we apply the improved PSO algorithm to optimize the PID controller based on the dynamic vehicle data obtained. Finally, we perform a simulation test of performance before and after the optimization of the PID controller, in which vehicles equipped with a CCAS undertake deceleration driving and steering under the two states of low speed (≤50 km/h) and high speed (≥100 km/h) cruising. The results show that the PID controller optimized using the proposed method can achieve not only the basic functions of a CCAS, but also improvements in vehicle dynamic stability, riding comfort, and fuel economy.

Cooperative Collision Avoidance and Formation Control for Objects with Heterogeneous Shapes

This paper addresses the problem of formation control with collision avoidance, in scenarios comprising robots of heterogeneous shapes and with double integrator dynamics, moving on a plane. The exact shapes of the robots are taken into account in developing two cooperative collision avoidance strategies, and these are based on the collision cone approach. The two collision avoidance strategies treat the acceleration magnitude and direction, respectively, as inputs to facilitate cooperative collision avoidance. Analytical expressions for these cooperative collision avoidance laws are presented. These are then integrated with formation control laws, and simulations demonstrate the satisfactory performance of the overall system.

Emergency Messages Broadcasting with Multi-Forwarder in Vehicular Ad hoc Networks

ABSTRACT One important application in Vehicular ad hoc networks, VANET, is applied for the cooperative collision avoidance (CCA) in the intelligent transportation system, ITS. In CCA, a driver could broadcast emergency messages to advice the vehicle behind accident through VANET. Thus how to design an efficient broadcasting method for forwarding the emergency messages is important in ITS. However, most of researches focused on avoiding broadcast storm by selecting only one forwarder for broadcasting. In this way, it caused that emergency messages could not be spread in other direction roads. Thus the cars in these directions of the crossroad cannot receive the emergency messages to prevent the traffic accident. To address this issue, we proposed an emergency messages broadcasting by multi-forwarder (EMBM) to select the appropriate forwarders for each brand at the intersection. Thus the emergency message could be forwarded through each brand when the messages were broadcasted across the intersection. The simulation results showed that the reachability in EMBM was 44.9 % and higher than that in binary partition assisted broadcast (BPAB), and 46.6 % higher than that in cell broadcast for streets, CBS. The average delay time of EMDM was 32.3 % lower than that in BPAB, and 69.1 % lower than that in CBS.

Collision avoidance on winding roads using dedicated short-range communication

The emergence of wireless communication technologies such as Dedicated Short-Range Communication (DSRC) has promoted the evolution of collision warning from simple ranging-sensor-based systems to cooperative systems. In cooperative systems, path prediction is a promising method for reflecting a driver’s intention and estimating the future position of vehicles. In this study, a short-term trajectory-modelling method is proposed to predict vehicle motion behaviour in the cooperative vehicular environment. In addition, a collision detection algorithm for winding roads is presented based on a model for determining the minimum distance of vehicles’ future trajectories. The cooperative collision avoidance system’s performance is analysed through simulation, providing useful theoretical insights into the effects of DSRC technology on vehicle collision avoidance in a curved road environment.

Novel Cooperative Collision Avoidance Model for Connected Vehicles

Connected vehicle technology exchanges real-time vehicle and traffic information through vehicle-to-vehicle and vehicle-to-infrastructure communication. The technology has the potential to improve traffic safety applications such as collision avoidance. In this paper, a novel cooperative collision avoidance (CCA) model that could improve the effectiveness of the collision avoidance system of connected vehicles was developed. Unlike traditional collision avoidance models, which relied mainly on emergency braking, the proposed CCA approach avoided collision through a combination of following vehicle deceleration and leading vehicle acceleration. Through spacing policy theory and nonlinear optimization, the model calculated the desired deceleration rate for the following vehicle and the acceleration rate for the leading vehicle, respectively, at each time interval. The CCA approach was then tested on a scaled platform with hardware-in-the-loop simulation embedded with MATLAB/Simulink and a car simulator package, CarSim. Results show that the proposed model can effectively avoid rear-end collisions in a three-vehicle platoon.

Building, Verifying and Validating a Collision Avoidance Model for Unmanned Aerial Vehicles

This paper documents verification and validation of a multi-rotor aircraft emulator in a collision avoidance simulation scenario by comparing its behaviour during a specific flight plan against a “live” hexacopter following the same flight plan. Positional data is collected using telemetry downlink with the precision of onboard global positioning sensors.Scenario described above is part of an ongoing research project to create a cooperative collision avoidance system for small unmanned aerial vehicles with a specified reliability level.

BIG-CCA: Beacon-Less, Infrastructure-Less, and GPS-Less Cooperative Collision Avoidance Based on Vehicular Sensor Networks

This paper proposes a lane-level beacon-less, infrastructure-less, and GPS-less cooperative collision avoidance (BIG-CCA) framework for preventing rear-end collisions. The BIG-CCA framework applies vehicular sensor networks to prevent chain vehicle collisions, which are common road accidents that occur when vehicles make sudden stops. BIG-CCA enables vehicles equipped with only onboard sensors to prevent such accidents. Based on extensive research, BIG-CCA is the first lane-level CCA solution that provides the following features: 1) BIG-CCA does not maintain a list of neighboring vehicles through beacons and, thus, the overall signaling overhead can be reduced to conserve bandwidth; 2) BIG-CCA does not use the GPS positions of vehicles to facilitate collision avoidance and, thus, the inaccuracy and unavailability of a GPS can be avoided; and 3) BIG-CCA does not rely on costly roadside infrastructures but employs only vehicle-to-vehicle communications to form warning groups for vehicles driving along in the same lane. BIG-CCA consists of a distributed grouping mechanism and a receiver-based forwarding scheme. Vehicles join or leave a warning group through only single-hop transmissions with the low overhead of group maintenance. When sudden braking occurs in a warning group, the proposed receiver-based forwarding scheme can specify a single forwarder without message contention. The performance of BIG-CCA is evaluated by conducting mathematical analysis and computer simulations, which outperform existing methods. An Android-based prototype is also implemented to verify the feasibility of BIG-CCA.

Design and Analysis of an Infrastructure-Less Framework for Lane Positioning, Tracking, and Requesting through Vehicular Sensor Networks

In this letter, we design and analyze an infrastructure-less framework for lane positioning, tracking, and requesting through vehicle-to-vehicle communications. The proposed framework involves applying vehicular sensor networks to localize the lane position of vehicles on road segments. It enables vehicles equipped with image sensors to detect the current lane location without using a global positioning system, which may give an inaccurate location, and without the need for roadside infrastructures, which can be costly. Through image sensors, the proposed framework can maintain the recognition of the lane position of a vehicle. By using vehicle-to-vehicle communications, the proposed framework enables lane position information to be requested from other vehicles in the same lane when required. The proposed framework facilitates the development of innovative applications for the next-generation intelligent transportation systems that rely on high positioning accuracy, such as lane-level cooperative collision avoidance, dynamic traffic control, and intelligent personal navigation systems. An analytical model is derived for estimating the positioning success ratio of the proposed framework. The analytical and simulation results show that the proposed framework can significantly improve the positioning success ratios by cooperative lane requesting.

Context and Network Aware Communication Strategies for Connected Vehicle Safety Applications

Connected vehicle systems, such as cooperative collision warning (CCW) or avoidance (CCA) systems, rely on vehicle-to-vehicle communication for obtaining real-time situational awareness and detecting possible hazards. The majority of systems that use vehicular networks may benefit from separation of functionalities in communication and application layers. This separation streamlines design of many applications and provides Internet-style flexibility. However, for critical applications, the inherent loss of performance due to independent operation of communication and application layers may result in unacceptable degradation of reliability. We show that by considering the context and network performance in the communication subsystem design (thus weakening layer independence), significant gain in system reliability is possible. Context awareness is achieved by coupling communication behavior to safety system performance; for example using vehicle tracking accuracy to determine the required communication timing. Network awareness is achieved by using feedback from the network to influence the estimated system performance (tracking error), and consequently the communication controller. Safety performance metrics that can be used include hazard detection accuracy, or warning accuracy for CCW, or vehicle tracking accuracy. Simulation results, using data from field tests, show the effectiveness of context and network aware communication.

Finding Lane Positions of Vehicles: Infrastructure-Less Cooperative Lane Positioning Based on Vehicular Sensor Networks

In this article, we proposed an infrastructureless cooperative lane positioning (ICLP) framework using vehicle-to-vehicle (V2V) communications. The ICLP framework applies vehicular sensor networks (VSNs) to localize lane positions of vehicles on roads. ICLP allows the vehicles equipped with image sensors to detect the current located lane without utilizing global positioning system (GPS) locations and roadside infrastructures. Through image sensors, ICLP can keep recognizing the lane position for a vehicle. In addition, ICLP can request lane position information from other vehicles in the same lane as necessary, based on V2V communications. ICLP makes innovative applications of intelligent transportation systems relying on accurate positioning possible, such as lane-level cooperative collision avoidance, dynamic traffic control, and intelligent personal navigation. An Android-based prototype is implemented to verify the feasibility and superiority of our framework. The experimental results show that ICLP can achieve high positioning success ratios and provide accurate lane positions for vehicles.

Improved cooperative collision Avoidance (CCA) model considering driver comfort

In this paper, we propose an improved cooperative collision Avoidance (CCA) system based on V2V communication for connected vehicles. To avoid the emergency braking and ensure the driver comfort, the collision can be prevented by not only decelerating the following vehicle, but also allowing the preceding vehicle to accelerate. Two collision avoidance models are thus developed: braking model and acceleration model, which calculate the desired deceleration rate of the following vehicle and the acceleration rate of preceding vehicle at each control time interval. It mainly addresses two issues, firstly, the traditional collision avoidance models mainly rely on emergency braking of the following vehicle, and the spacing will decrease suddenly, so the safety risk to drivers and passengers still exist; secondly, emergency braking always raise the driver discomfort. To address these issues, The improved CCA system is then tested on the platform of Matlab/Simulink embedded with a car simulator package, CarSim. The simulation results show that the improved CCA model can effectively avoid collision and ensure the driver comfort at the same time.