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A Real-Time Traffic Light Detection Algorithm Based on Adaptive Edge Information

  • Beihang University - Guizhen Yu, Ao Lei, Honggang Li, Yunpeng Wang, Zhangyu Wang, Chaowei Hu
  • Technical Paper
  • 2018-01-1620
Published 2018-08-07 by SAE International in United States
Traffic light detection has great significant for unmanned vehicle and driver assistance system. Meanwhile many detection algorithms have been proposed in recent years. However, traffic light detection still cannot achieve a desirable result under complicated illumination, bad weather condition and complex road environment. Besides, it is difficult to detect multi-scales traffic lights by embedded devices simultaneously, especially the tiny ones. To solve these problems, this paper presents a robust vision-based method to detect traffic light, the method contains main two stages: the region proposal stage and the traffic light recognition stage. On region proposal stage, we utilize lane detection to remove partial background from the original images. Then, we apply adaptive canny edge detection to highlight region proposal in Cr color channel, where red or green color proposals can be separated easily. Finally, extract the enlarged traffic light RoI (Region of Interest) to classify. On traffic light recognition stage, a tinny but effective convolution neural network (CNN), named TLRNet, classifies each traffic light RoI into its own class. In fact, deep learning (DL) is bad…

Target Detection and Tracking Algorithm Simulation for Automotive Millimeter-Wave Radar Based On SystemVue and MATLAB

  • Tongji Univ. - Zhexiang Yu, Jie Bai, Sihan CHEN, Libo Huang, Xin Bi
  • Technical Paper
  • 2018-01-1604
Published 2018-08-07 by SAE International in United States
Advance driver assistant system and autonomous driving system can greatly reduce traffic accidents. The advance driver assistant system and autonomous driving system use sensors to detect and tracking the vehicles, pedestrians and obstacles around the ego vehicle. Automotive millimeter-wave radar is the only sensor, which works in bad weather and night. Target detection and tracking is an important component of the radar system, whose performance is influenced by every components of the radar system. Automotive millimeter-wave radar is composed of millimeter-wave antennas and circuits, analog circuits, analog-digital converter, signal processing algorithm, target detection and tracking algorithm. Each component should be simulated and designed by a different tool, which is time-consuming. Simulate and design the whole radar system by using few tools can greatly reduce the development time of radar target detection and tracking algorithm. In this paper, one method which can simulate radar target detection and track algorithm by using SystemVue and MATLAB is presented. The hardware part of radar included signal source, noise source, transmitting antennas, simulated target, receiving antennas, intermediate frequency module and…

Camera-Radar Data Fusion for target detection via Kalman filter and Bayesian estimation

  • Tongji Univ. - Zhexiang Yu, Jie Bai, Sihan CHEN, Libo Huang, Xin Bi
  • Technical Paper
  • 2018-01-1608
Published 2018-08-07 by SAE International in United States
Target detection is essential to the advanced driving assistance system (ADAS) and automatic driving. And the data fusion of millimeter wave radar and camera could provide more accurate and complete information of targets and enhance the environmental perception performance. In this paper, a method of vehicle and pedestrian detection based on the data fusion of millimeter wave radar and camera was proposed. The first step is the targets data acquisition. A deep learning model called Single Shot MultiBox Detector (SSD) was utilized for targets detection in consecutive video frames captured by camera and further optimized for high real-time performance and accuracy. Secondly, the parallel Kalman filter was used to track the targets detected by radar and camera respectively. Since targets information provided by the camera and radar are different, different Kalman filters were designed to achieve the tracking process. Then, the targets of radar and camera were matched by using coordinate transformation. After that, fusion weight was calculated according to the tracking results. Finally, the targets data were fused based on Bayesian Estimation. At first,…

Embedding CNN-Based Real-Time Obstacles Detection for Autonomous Vehicles

  • Beihang University - Guizhen Yu, Chaowei Hu, Zhangyu Wang, Yunpeng Wang, Ao Lei, Zhehua Hu
  • Technical Paper
  • 2018-01-1622
Published 2018-08-07 by SAE International in United States
Forward obstacles detection is one of the key tasks in the perception system of autonomous vehicles. The perception solution differs from the sensors and the detection algorithm, and the vision-based approaches are always popular. In this paper, an embedding real-time obstacles detection algorithm is proposed to efficiently detect forward diverse obstacles from the image stream captured by the monocular camera. Specifically, our algorithm contains three components. The first component is an object detection method using convolution neural networks (CNN) for single image. We design a detection network based on shallow residual network, and an adaptive object aspect ratio setting method for training dataset is proposed to improve the accuracy of detection. The second component is a multiple object tracking method based on correlation filter for the adjacent images. Based on precise detection result, we use multiple correlation filters to track multiple objects in every adjacent frame, and a multi-scale tracking region method is applied to improve the tracking accuracy at the same time. The third component is fusing the detection method and tracking method based…

Driver Risk Perception model under Critical Cut-in scenario

  • Tongji University - Xuehan Ma, Zhiwei Feng, Xichan Zhu, Zhixiong Ma
  • Technical Paper
  • 2018-01-1626
Published 2018-08-07 by SAE International in United States
In China Cut-in scenario is quite common on both highway and urban road with heavy traffic and usually has a certain risk. While, research on the driver’s risk perception of Cut-in scenario is few. When facing a cutting-in vehicle, driver tends to brake in most case. The timing and dynamic characteristic of driver’s brake maneuver is the direct indicator of driver’s subjective risk perception. The objective risk evaluation factors include TTC (Time to collision), THW (Time Headway), longitudinal relative distance and lateral relative distance et al.. This paper aim at building a model quantitatively revealing the relationship between drivers’ subjective risk perception and the objective risk evaluation factors. Data is from China-FOT database, which has a travel distance about 130 thousand miles. It is found that in Cut-in scenario, driver tends to brake when the cutting-in vehicle right crossing line, and this time point is defined as initial brake time t_IB. Average brake pressure (ABP) and acceleration at t_IB indicate brake strength. Brake pressure change rate (BPCR) and longitudinal jerk (derivative of acceleration) at t_IB…

A Localization System for Autonomous Driving: Global and Local Location Matching based on Mono-SLAM

  • Tongji Univ. - Zhijun Xu, Sihan CHEN, Jie Bai, Libo Huang, Xin Bi
  • Technical Paper
  • 2018-01-1610
Published 2018-08-07 by SAE International in United States
The utilization of the SLAM (Simultaneous Localization and Mapping) technique was extended from the robotics to the autonomous vehicles for achieving the positioning. However, SLAM cannot obtain the global position of the vehicle but a relative one to the start. For sake of this, a fast and accurate system was proposed to obtain both the local position and the global position of vehicles based on mono-SLAM which realized the SLAM by using monocular camera with a lower cost and power consumption. Firstly, the rough latitude and longitude of current position was obtained by using common GPS without differential signal. Then, the Mono-SLAM operated on the consecutive video frames to generate the localization and local trajectory map and its accuracy was further improved by utilizing the IMU information. After that, a piece of Map centered in the rough position obtained by common GPS was downloaded from the Open Street Map. Finally, a searching process in the downloaded Map was executed by using chamfer matching algorithm to find a piece of path matched with the constructed trajectory…

Study on frequency domain noise jamming mechanism of vehicle millimeter wave radar based on traffic scene

  • Jilin Univ. && Aviation Univ. of AF - Xin Li
  • Jilin University - Weiwen Deng
  • Show More
  • Technical Paper
  • 2018-01-1624
Published 2018-08-07 by SAE International in United States
"Automobile Millimeter Wave Radar" has become one of the important sensors of "advanced driving aid system (ADAS)". However, although millimeter wave radars can operate all day long and all-weather, their detection capability and measurement accuracy are still largely affected by traffic scenarios. Main performance: Because the relative position and relative motion state between radar and scene elements (such as road, road facilities, moving vehicles and pedestrians, etc.) are different, based on the principle of Doppler effect, The scene elements may lead into different levels of noise pollution in the radar frequency domain, and then lead to radar "missing target, measurement is not allowed" and other common problems. Therefore, it is necessary for us to study the mechanism of frequency domain noise interference in order to develop a good ADAS system. The research content of this paper is the application background of Millimeter Wave Radar Virtual Test Simulation Platform. It was supported by two topics of the National Natural Science Foundation of China (U1564211) and the national key research and development program (2016YFB0100904). This paper unfold…

Critical Driving Scenarios Extraction Optimization Method Based on China-FOT Naturalistic Driving Study Database

  • Tongji Univ. - Yufan Zeng
  • Tongji University - Xichan Zhu
  • Show More
  • Technical Paper
  • 2018-01-1628
Published 2018-08-07 by SAE International in United States
Due to the differences in traffic situations and traffic safety laws, standards for extraction of critical driving scenarios (CDSs) vary from different countries and areas around the world. To maintain the characteristic variables under the Chinese typical CDSs, this paper uses the three-layer detection method to extract and detect CDSs in the Natural Driving Data from China-FOT project which executing under the real traffic situation in China. The first layer of detection is mainly based on the feature distributions which deviate from normal driving situations. These distributions associated with speed and longitudinal acceleration/lateral acceleration/yaw rate also quantify the critical levels classification. The second layer of detection based on the rate of brake pressure (Pressure peak/Time difference) and the relevant variables to TTC’s trigger, Pressure peak means the maximum value on brake pressure curve, Time difference means the difference between Pressure peak time and Hard breaking time (Time when driver starts to make emergency brake). The second layer could make corrections to the critical levels. The third layer of detection uses fuzzy comprehensive evaluation method to…

An ellipse fitting approach based on region division

  • Dongfeng Motor Corporation - Daike Kang, Yue Wang, Xiaolu Wu, Jin Hu
  • Technical Paper
  • 2018-01-1612
Published 2018-08-07 by SAE International in United States
An ellipse fitting approach based on region division is presented for faster fitting speed: Firstly, the valid region would be located which contains all of the points based on their coordinate value. Secondly, two horizontal lines and two upright lines would be calculated, so that the valid region could be divided into nine sections equally, and eight of them contain an elliptic arc. Thirdly, one point would be selected randomly from each elliptic arc, total eight points, and five of them would be used to solve the parameter of elliptic. Finally, the optimal parameter of elliptic would be found based on the arithmetic of minimum algebraic distance. The advantage of this approach is that the spots used to fit ellipse are dispersed, so that lots of ill-suited try would be avoided, such as getting an inaccurate ellipse or even failing to get an ellipse. For this reason, fitting speed would be increased. Setting the arithmetic presented in this paper as experimental group and the traditional algorithm as control group. In the MATLAB platform, both of…

Research on electromagnetic compatibility of vehicle wireless charging technology

  • CATARC - jiang li
  • Technical Paper
  • 2018-01-1630
Published 2018-08-07 by SAE International in United States
Wireless charging technology is an effective way to solve the problem of electric vehicle (EV) mileage, as well as an important part of auto-driving vehicle charging. Currently, wireless charging products have been introduced successively, foreign standards related to the performance have also been released, but on the electromagnetic compatibility national standard has just been established. This paper first summarizes the current automotive standards and regulations; and then through the study of WPT system with the external environment and internal environment of the electromagnetic interference, electromagnetic interference with the grid quality, a reasonable WPT system EMC test and evaluation is provided to give technical support for the development of National standards.