In view of the images collection and processing problems of the smart car camera, the paper introduces a method which deals with field and line synchronization signal separation and binarization processing of the vide...In view of the images collection and processing problems of the smart car camera, the paper introduces a method which deals with field and line synchronization signal separation and binarization processing of the video signal collected from track fields, and which is capable to extract and position black border trajectory images effectively. According to the experiment results of the method, the camera images can be collected and processed effectively, and the accurate image information can be provided for the smart cars to travel along the track. The method has the advantages of being easy to use, strong adaptability, ideal performance and high practical value. On the basis of advantages the method is of high practical value in smart car races.展开更多
Smart cars are promising application domain for ubiquitous computing. Context-awareness is the key feature of a smart car for safer and easier driving. Despite many industrial innovations and academic progresses have ...Smart cars are promising application domain for ubiquitous computing. Context-awareness is the key feature of a smart car for safer and easier driving. Despite many industrial innovations and academic progresses have been made, we find a lack of fully context-aware smart cars. This study presents a general architecture of smart cars from the viewpoint of context- awareness. A hierarchical context model is proposed for description of the complex driving environment. A smart car prototype including software platform and hardware infrastructures is built to provide the running environment for the context model and applications. Two performance metrics were evaluated: accuracy of the context situation recognition and efficiency of the smart car. The whole response time of context situation recognition is nearly 1.4 s for one person, which is acceptable for non-time critical applications in a smart car.展开更多
感知,规划、决策、控制是自动驾驶车辆的核心控制问题,而智能小车自动避障系统设计是自动驾驶控制的基础。文章基于超声波雷达传感器感知、Arduino UNO R3开发板以及避障程序等设计智能小车避障系统来控制小车的避障运动,并在无障碍物...感知,规划、决策、控制是自动驾驶车辆的核心控制问题,而智能小车自动避障系统设计是自动驾驶控制的基础。文章基于超声波雷达传感器感知、Arduino UNO R3开发板以及避障程序等设计智能小车避障系统来控制小车的避障运动,并在无障碍物、前方纸盒障碍物、3面纸盒障碍物3种工况下验证了该避障系统的有效性。展开更多
文摘In view of the images collection and processing problems of the smart car camera, the paper introduces a method which deals with field and line synchronization signal separation and binarization processing of the video signal collected from track fields, and which is capable to extract and position black border trajectory images effectively. According to the experiment results of the method, the camera images can be collected and processed effectively, and the accurate image information can be provided for the smart cars to travel along the track. The method has the advantages of being easy to use, strong adaptability, ideal performance and high practical value. On the basis of advantages the method is of high practical value in smart car races.
基金Project supported by the National Hi-Tech Research and Develop-ment Program (863) of China (Nos. 2006AA01Z198, and2008AA01Z132)the National Natural Science Foundation of China(No. 60533040)the National Science Fund for Distinguished Young Scholars of China (No. 60525202)
文摘Smart cars are promising application domain for ubiquitous computing. Context-awareness is the key feature of a smart car for safer and easier driving. Despite many industrial innovations and academic progresses have been made, we find a lack of fully context-aware smart cars. This study presents a general architecture of smart cars from the viewpoint of context- awareness. A hierarchical context model is proposed for description of the complex driving environment. A smart car prototype including software platform and hardware infrastructures is built to provide the running environment for the context model and applications. Two performance metrics were evaluated: accuracy of the context situation recognition and efficiency of the smart car. The whole response time of context situation recognition is nearly 1.4 s for one person, which is acceptable for non-time critical applications in a smart car.
文摘感知,规划、决策、控制是自动驾驶车辆的核心控制问题,而智能小车自动避障系统设计是自动驾驶控制的基础。文章基于超声波雷达传感器感知、Arduino UNO R3开发板以及避障程序等设计智能小车避障系统来控制小车的避障运动,并在无障碍物、前方纸盒障碍物、3面纸盒障碍物3种工况下验证了该避障系统的有效性。
