UDP-YOLO: High Efficiency and Real-Time Performance of Autonomous Driving Technology

In recent years, autonomous driving technology has gradually appeared in our field of vision. It senses the surrounding environment by using radar, laser, ultrasound, GPS, computer vision and other technologies, and then identifies obstacles and various signboards, and plans a suitable path to control the driving of vehicles. However, some problems occur when this technology is applied in foggy environment, such as the low probability of recognizing objects, or the fact that some objects cannot be recognized because the fog's fuzzy degree makes the planned path wrong. In view of this defect, and considering that automatic driving technology needs to respond quickly to objects when driving, this paper extends the prior defogging algorithm of dark channel, and proposes UDP-YOLO network to apply it to automatic driving technology. This paper is mainly divided into two parts: 1. Image processing: firstly, the data set is discriminated whether there is fog or not, then the fogged data set is defogged by defogging algorithm, and finally, the defogged data set is subjected to adaptive brightness enhancement; 2. Target detection: UDP-YOLO network proposed in this paper is used to detect the defogged data set. Through the observation results, it is found that the performance of the model proposed in this paper has been greatly improved while balancing the speed

Research on Vehicle Automatic Driving Target Perception Technology Based on Improved MSRPN Algorithm

Vehicle automatic driving technology can effectively improve the safety performance of vehicle driving. This research is aimed at the needs of vehicle automatic driving. Combined with vehicle perception technology, a better target recognition algorithm is proposed. By comparing the recognition and recall rate of ION algorithm, HYPERNET algorithm, R-CNN (Regions with CNN features) algorithm, and multi-strategy region proposal network (MSRPN) algorithm, it can be seen that MSPRN algorithm has better algorithm performance and is suitable for target detection and recognition in vehicle automatic driving

Research on road object detection algorithm based on improved YOLOX

Road object detection is an important branch of automatic driving technology, The model with higher detection accuracy is more conducive to the safe driving of vehicles. In road object detection, the omission of small objects and occluded objects is an important problem. therefore, reducing the missed rate of the object is of great significance for safe driving. In the work of this paper, based on the YOLOX object detection algorithm to improve, proposes DecIoU boundary box regression loss function to improve the shape consistency of the predicted and real box, and Push Loss is introduced to further optimize the boundary box regression loss function, in order to detect more occluded objects. In addition, the dynamic anchor box mechanism is also used to improve the accuracy of the confidence label, improve the label inaccuracy of object detection model without anchor box. A large number of experiments on KITTI dataset demonstrate the effectiveness of the proposed method, the improved YOLOX-s achieved 88.9% mAP and 91.0% mAR on the KITTI dataset, compared to the baseline version improvements of 2.77% and 4.24%; the improved YOLOX-m achieved 89.1% mAP and 91.4% mAR, compared to the baseline version improvements of 2.30% and 4.10%.Comment: 9 pages; in Chines

Analysis on the Development of Business Invitation and Investment Attraction in Nansha Free Trade Zone—Taking the Pony.ai’s “Unicorn” Project as an Example

Nansha Free Trade Zone is one of the most representative and potential free trade zones in China. Since its establishment in 2015, with the unique geographical advantages of the geometric geographical center of the Greater Bay Area (GBA) and relying on the strategic development plan of “Three Areas Integration”, it had made continuous innovation and development in political, economic, cultural and other fields. The plan is constantly innovating and developing in various fields such as politics, economy, and culture. In the past two years, the development of the Nansha free trade zone had attracted cooperation and investment from many well-known enterprises. The municipal government had also invested in many key projects in Nansha. The Pony.ai’s “Unicorn” Project, as a project just started in recent years, had undoubtedly become a key project for business invitation and investment attraction in the Nansha Free Trade Zone in the near future. Taking the “unicorn” pony Zhixing project as an example, this paper analyzes the current situation and existing problems of business invitation and investment attraction in the Nansha Free Trade Zone and puts forward some suggestions

マクロ-フェムトセルシステムの最適化モデルに関する研究

早大学位記番号:新8266早稲田大

Efficiency Through Automation: A Single System for Multiple Railway Guard Posts

One of the important factors in train travel is the guarding of railroad crossings. Unfortunately, the number of unguarded railway crossings is still quite large. This condition makes it prone to accidents, especially at crossings that are heavily traveled by vehicles. Most of the railway crossing guards in Indonesia use a manual system, where in this system one guard post can only guard one railway crossing, due to limited human resources from PT KAI, many railway crossing doors are not guarded. To reduce accidents and cover the lack of human resources from PT.KAI, an Efficiency tool through Automation was made: One System for Multiple Railway Crossing Guard Posts. This tool is equipped with several main components, namely PLC, HMI, Infrared Sensor, and servo motor. The crossing gate is fully controlled by PLC and HMI as a monitoring system for all components in real-time. By detecting the arrival of the train, the infrared sensor can work by utilizing the movement of the train passing the sensor, not only detecting the arrival of the train, the infrared sensor also works to give orders so that the Servo Motor as a crossing door can be immediately closed and opened on the miniature, the railroad crossing itself is also equipped with an infrared sensor that functions to detect the presence of vehicles in the middle of the railroad crossing controlled by PLC and HMI as a monitoring system. This tool has been tested and the device functions properly and can help reduce the accident rate at railroad crossings