Cooperative vehicle collision warning system using the vector-based approach with dedicated short range communication data transmission

2014 ◽  
Vol 8 (2) ◽  
pp. 124-134 ◽  
Author(s):  
Chung-Ming Huang ◽  
Shih-Yang Lin
Transport ◽  
2017 ◽  
Vol 33 (2) ◽  
pp. 461-469 ◽  
Author(s):  
Daxin Tian ◽  
Yong Yuan ◽  
Jian Wang ◽  
Haiying Xia ◽  
Jian Wang

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.


2020 ◽  
Vol 4 (4) ◽  
pp. 231
Author(s):  
Agus Mulyanto ◽  
Rohmat Indra Borman ◽  
Purwono Prasetyawan ◽  
A Sumarudin

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


Author(s):  
Tianping Liu ◽  
Yunpeng Wang ◽  
E. Wenjuan ◽  
Daxin Tian ◽  
Guizhen Yu ◽  
...  

Sign in / Sign up

Export Citation Format

Share Document