scholarly journals A Novel V2V Cooperative Collision Warning System Using UWB/DR for Intelligent Vehicles

Sensors ◽  
2021 ◽  
Vol 21 (10) ◽  
pp. 3485
Author(s):  
Mingyang Wang ◽  
Xinbo Chen ◽  
Baobao Jin ◽  
Pengyuan Lv ◽  
Wei Wang ◽  
...  
Keyword(s):  
Kinematic Model ◽  
Dead Reckoning ◽  
Warning System ◽  
Wheel Speed ◽  
Intelligent Vehicles ◽  
The Body ◽  
Ultra Wideband ◽  
Collision Warning ◽  
Vehicle Collision ◽  
Vehicle Active Safety

The collision warning system (CWS) plays an essential role in vehicle active safety. However, traditional distance-measuring solutions, e.g., millimeter-wave radars, ultrasonic radars, and lidars, fail to reflect vehicles’ relative attitude and motion trends. In this paper, we proposed a vehicle-to-vehicle (V2V) cooperative collision warning system (CCWS) consisting of an ultra-wideband (UWB) relative positioning/directing module and a dead reckoning (DR) module with wheel-speed sensors. Each vehicle has four UWB modules on the body corners and two wheel-speed sensors on the rear wheels in the presented configuration. An over-constrained localization method is proposed to calculate the relative position and orientation with the UWB data more accurately. Vehicle velocities and yaw rates are measured by wheel-speed sensors. An extended Kalman filter (EKF) is applied based on the relative kinematic model to combine the UWB and DR data. Finally, the time to collision (TTC) is estimated based on the predicted vehicle collision position. Furthermore, through UWB signals, vehicles can simultaneously communicate with each other and share information, e.g., velocity, yaw rate, which brings the potential for enhanced real-time performance. Simulation and experimental results show that the proposed method significantly improves the positioning, directing, and velocity estimating accuracy, and the proposed system can efficiently provide collision warning.

Implementation 2D Lidar and Camera for detection object and distance based on RoS

2020 ◽  
Vol 4 (4) ◽  
pp. 231
Author(s):  
Agus Mulyanto ◽  
Rohmat Indra Borman ◽  
Purwono Prasetyawan ◽  
A Sumarudin
Keyword(s):  
Warning System ◽  
Driver Assistance ◽  
Driver Assistance Systems ◽  
Human Errors ◽  
Collision Warning ◽  
Robot Operating System ◽  
Vehicle Collision ◽  
Environment Perception ◽  
Assistance Systems ◽  
Camera Sensors

The advanced driver assistance systems (ADAS) are one of the issues to protecting people from vehicle collision. Collision warning system is a very important part of ADAS to protect people from the dangers of accidents caused by fatigue, drowsiness and other human errors. Multi-sensors has been widely used in ADAS for environment perception such as cameras, radar, and light detection and ranging (LiDAR). We propose the relative orientation and translation between the two sensors are things that must be considered in performing fusion. we discuss the real-time collision warning system using 2D LiDAR and Camera sensors for environment perception and estimate the distance (depth) and angle of obstacles. In this paper, we propose a fusion of two sensors that is camera and 2D LiDAR to get the distance and angle of an obstacle in front of the vehicle that implemented on Nvidia Jetson Nano using Robot Operating System (ROS). Hence, a calibration process between the camera and 2D LiDAR is required which will be presented in session III. After that, the integration and testing will be carried out using static and dynamic scenarios in the relevant environment. For fusion, we use the implementation of the conversion from degree to coordinate. Based on the experiment, we result obtained an average of 0.197 meters

Vehicle Collision Warning System and Algorithm at Intersection under Internet-Connected Vehicles Environment

CICTP 2012 ◽  
2012 ◽  
Author(s):  
Tianping Liu ◽  
Yunpeng Wang ◽  
E. Wenjuan ◽  
Daxin Tian ◽  
Guizhen Yu ◽  
...  
Keyword(s):  
Warning System ◽  
Connected Vehicles ◽  
Collision Warning ◽  
Vehicle Collision

Improved Position and Attitude Determination Method for Monocular Vision in Vehicle Collision Warning System

2016 ◽  
Vol 30 (07) ◽  
pp. 1655019 ◽  
Author(s):  
Lijuan Qin ◽  
Ting Wang ◽  
Yulan Hu ◽  
Chen Yao
Keyword(s):  
Real Time ◽  
Solution Method ◽  
Warning System ◽  
Time Characteristic ◽  
Monocular Vision ◽  
Theoretical Research ◽  
Driving Safety ◽  
License Plate ◽  
Collision Warning ◽  
Vehicle Collision

Vehicle collision warning system can determine the relative distance and speed between target vehicle and the front vehicle by monocular vision positioning technique from automobile license plate image captured by camera so as to judge danger level and remind the driver to make appropriate action and avoid vehicle collision timely. Study on the positioning technology of this system aims to help the driver to judge and improve driving safety. Thus, the system has a broad application prospect. The research content of this paper could enrich and supply PNL visual locating method, endowing with significance of theoretical research. The paper proposes an improved vehicle measuring method based on monocular vision for vehicle license plate. This method combines the characteristics of fast speed for analytical solution method and high positioning accuracy for iterative solution method, therefore has a high robustness and overcomes the multi-solution problem of P3P iterative method. The simulation experiments show that localization precision of the improved positioning method has been improved greatly as compared with P4L method. At the same time, the real-time characteristic of collision avoidance warning system with improved visual locating method has been improved a lot, and the new location algorithm has good performance in real-time characteristic, which greatly improve the processing ability of the system for images.

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