A5067032919- Remote Sensing and LiDAR Applications
- Autonomous Vehicle Technology and Safety
- Video Surveillance and Tracking Methods
- Simulation and Modeling Applications
- Advanced Optical Sensing Technologies
- Traffic Prediction and Management Techniques
- Transportation Planning and Optimization
- Data Management and Algorithms
- Traffic control and management
- Advanced Decision-Making Techniques
- Image Processing and 3D Reconstruction
- Optical Systems and Laser Technology
- Advanced Measurement and Detection Methods
Shandong University
2021-2024
Shandong Transportation Research Institute
2021-2024
Suzhou Research Institute
2022-2024
Light detection and ranging (LiDAR) is a crucial roadside intelligent perception device in cooperative vehicle infrastructure systems, which can generate large amount of disordered 3-D point cloud data. Point clustering serves as prerequisite for road target identification, trajectory tracking, traffic conflict prediction. However, due to limitations data collection methods algorithms, pronounced delay exists. In this work, real-time algorithm LiDAR (RTPCC-RL) proposed, primarily comprises...
To obtain object micro traffic information, LiDAR plays an important role in intelligent perception. Many background filtering methods based on can detect the target, but data process is not simple enough and information will be lost easily. In this work, from principle of original point cloud capture, advanced algorithm PCAP (Packet Capture) file proposed. Firstly, a extraction for files designed. Then, one non-target frame chosen as frame. The distance difference method used to filter...
Roadside intelligent sensors can monitor road traffic status, and the installation method of sensing equipment greatly affects richness accuracy data information collection. The radar-video integrated machine integrates radar camera, is a new type perception device. This paper conducted experimental analysis on position, rotation angle, other aspects machine. Based Technique for Order Preference by Similarity to Ideal Solution (TOPSIS), an optimal solution was proposed. Firstly, before...
Abstract Grasping the status of vehicles timely and accurately is key to avoid traffic accidents collecting data from multi-sensors significant for development road-side intelligent sensor technology. In this paper, LiDAR (Light Detection Ranging) camera sensors are tested, can be processed analyzed, display integrated. a multi-sensor acquisition integration device based on Raspberry Pi proposed, which realize optimal processing simultaneous function. This method avoids tedium using an IPC...
With the increasing number of vehicles and continuous increase highway mileage. Traffic safety issues are gradually coming into view. Placing lidar on side road can driving at high speeds. In order to achieve uninterrupted detection highway. It is necessary rationally deploy lidar. this paper, installation inclination, height, distance from layout adjacent studied. And optimal scheme given according in different scenarios.
Accurate road information is important for modern intelligent transportation systems. Light Detection and Ranging (LiDAR) an ideal equipment to collect microscope traffic data which helpful analyze behavior operation mechanism. Background filtering the key obtaining target information. To reduce calculation, Region of Interest (ROI) area defined only ground lines targets are kept in ROI area. The traditional random sample consensus (RANSAC) algorithm filters out by establishing a plane...
Data sparseness is a common problem in many taxi trajectories. After analyzing the characteristics of operation, this paper proposes sparse trajectory recovery and calibrate algorithm which based on reference systems (RS) used heterogeneous data sources. The increases number points original through searching selecting RS points. Then interpolated calibrated to improve accuracy solve sparsity. We test our by real display visual results experiment. all-day restored showed with its high...