Driving Performance Assessment Based on Accurate Position Tracking

A driving performance assessment (DPA) system has been proposed in this paper to evaluate drivers’ skills in training. The system is based on centimeter-level localization of the vehicles, thanks to differential BeiDou Navigation Satellite System (BDS). Given a vehicle’s dimensions, its envelopment has been discretized both temporally and spatially as binary images, while the training area is modeled as a grayscale image where the intensity denotes the penalty of the certain area in unit time. The performance index can be obtained from the summation of images along with time. Experiments have been conducted to demonstrate the accuracy of vehicle tracking and the effectiveness of the proposed assessment system.

[1]  Larry H. Matthies,et al.  Two years of Visual Odometry on the Mars Exploration Rovers , 2007, J. Field Robotics.

[2]  Rui Zhang,et al.  The design of high accuracy differential positioning vehicle terminal based on BeiDou Navigation System , 2016, 2016 IEEE Advanced Information Management, Communicates, Electronic and Automation Control Conference (IMCEC).

[3]  Xingxing Li,et al.  Accuracy and reliability of multi-GNSS real-time precise positioning: GPS, GLONASS, BeiDou, and Galileo , 2015, Journal of Geodesy.

[4]  Shahram Azadi,et al.  Performance Evaluation of a Novel Vehicle Collision Avoidance Lane Change Algorithm , 2016 .

[5]  Alexey Dosovitskiy,et al.  End-to-End Driving Via Conditional Imitation Learning , 2017, 2018 IEEE International Conference on Robotics and Automation (ICRA).

[6]  Ching-Chih Tsai,et al.  Parallel Elite Genetic Algorithm and Its Application to Global Path Planning for Autonomous Robot Navigation , 2011, IEEE Transactions on Industrial Electronics.

[7]  Christoph Schuetz,et al.  An Autonomous and Flexible Robotic Framework for Logistics Applications , 2019, J. Intell. Robotic Syst..

[8]  Myoungho Sunwoo,et al.  Development of Autonomous Car—Part II: A Case Study on the Implementation of an Autonomous Driving System Based on Distributed Architecture , 2015, IEEE Transactions on Industrial Electronics.

[9]  Jie Hu,et al.  An Extended Kalman Filter and Back Propagation Neural Network Algorithm Positioning Method Based on Anti-lock Brake Sensor and Global Navigation Satellite System Information , 2018, Sensors.

[10]  Francesco Borrelli,et al.  Autonomous car following: A learning-based approach , 2015, 2015 IEEE Intelligent Vehicles Symposium (IV).

[11]  Long Tang,et al.  Instantaneous Real-Time Kinematic Decimeter-Level Positioning with BeiDou Triple-Frequency Signals over Medium Baselines , 2015, Sensors.

[12]  Fei-Yue Wang,et al.  Master general parking skill via deep learning , 2017, 2017 IEEE Intelligent Vehicles Symposium (IV).

[13]  Zhen Li,et al.  Real-time kinematic positioning over long baselines using triple-frequency BeiDou signals , 2015, IEEE Transactions on Aerospace and Electronic Systems.

[14]  Donald D. Duncan,et al.  The driver monitor system : A means of assessing driver performance , 2004 .

[15]  Shigeki Sugano,et al.  Analysis of individual driving experience in autonomous and human-driven vehicles using a driving simulator , 2015, 2015 IEEE International Conference on Advanced Intelligent Mechatronics (AIM).

[16]  Alexander Kleiner,et al.  A solution to room-by-room coverage for autonomous cleaning robots , 2017, 2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).

[17]  Xuefeng Lv,et al.  Natural Disaster Emergency Rescue System Based on the Mobile Phone's High-Precision Positioning , 2018, 2018 IEEE 3rd International Conference on Image, Vision and Computing (ICIVC).

[18]  Keiichi Uchimura,et al.  Driver inattention monitoring system for intelligent vehicles: A review , 2009 .

[19]  Joachim Deutscher,et al.  Continuous Curvature Trajectory Design and Feedforward Control for Parking a Car , 2007, IEEE Transactions on Control Systems Technology.

[20]  David Watson,et al.  Multi-GNSS precise point positioning for precision agriculture , 2018, Precision Agriculture.