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Automotive Innovation 2020年第1期3卷 88-100页

作者： Weichao Zhuang Liwei Xu guodong yin School of Mechanical Engineering Southeast UniversityNanjing 211189China

This paper proposes a robust cooperative control strategy for multiple autonomous vehicles to achieve safe and efficient platoon formation,and it analyzes the effects of vehicle stability boundaries and parameter *** cooperative vehicle control framework is composed of the upper planning level and lower tracking control *** the planning level,the trajectory of each vehicle is generated by using the multi-objective flocking algorithm to form the *** parameters of the flocking algorithm are optimized to prevent the vehicle speed and yaw rate from going beyond their *** the lower level,to realize the stable platoon formation,a lumped disturbance observer is designed to gain the stable-state reference,and a distributed robust model predictive controller is proposed to achieve the offset-free trajectory tracking while downsizing the effects of parameter *** simulation results show the proposed cooperative control strategy can achieve safe and efficient platoon formation.

关键词： Platoon formation Robust model predictive controller Multiple autonomous vehicles Parameter uncertainty

Vehicular Electronic Image Stabilization System Based on a Gasoline Model Car Platform

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Chinese Journal of Mechanical Engineering 2022年第6期35卷 351-362页

作者： Ning Zhang Yuan Yang Jianhua Wu Ziqian Zhao guodong yin School of Mechanical Engineering Southeast UniversityNanjing 211189China School of Instrument Science and Engineering Southeast UniversityNanjing 210096China

Noise,vibration and harshness(NVH)problems in vehicle engineering are always challenging in both traditional vehicles and intelligent *** high accuracy manufacturing,modern structural roads and advanced suspension technology have already significantly reduced NVH problems and their impacts;off-road condition,obstacles and extreme operating condition could still trigger NVH problems *** paper proposes a vehicular electronic image stabilization(EIS)system to solve the vibration problem of the camera and ensure the environment perceptive function of ***,feature point detection and matching based on an oriented FAST and rotated BRIEF(ORB)algorithm are implemented to match images in the process of ***,a novel improved random sampling consensus algorithm(i-RANSAC)is proposed to eliminate mismatched feature points and increase the matching accuracy *** an adaptive Kalman filter(AKF)is applied to improve the adaptability of the vehicular ***,an experimental platform based on a gasoline model car was established to validate its *** experimental results show that the proposed EIS system can satisfy vehicular performance requirements even under off-road condition with obvious obstacles.

关键词： Electronic image stabilization Environment perceptive function Feature point Adaptive Kalman filter Gasoline model car

Motion Control of a Four-Wheel-Independent-Drive Electric Vehicle by Motor Imagery EEG Based BCI System 36

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Motion Control of a Four-Wheel-Independent-Drive Electric Ve...

Integrated energy-oriented cruising control of electric vehicle on highway with varying slopes considering battery aging

第36届中国控制会议

作者： Jiayu Zhuang guodong yin School of Mechanical Engineering Southeast University State Key Laboratory of Automotive Simulation and Control Jilin University

ISBN: (纸本)9781538629185

This paper proposed a control structure of Four-Wheel-Independent-Drive electric vehicles by motor imagery Electroencephalography（EEG） based BCI *** work is the BCI system,Emotiv EPOC+ is used to acquire the raw EEG data,Independent Component Analysis（ICA） is used to preprocess the motor imagery EEG,then Common Spatial Pattern（CSP）is used to extract the features which is most related to the ERD/*** but not least,Back Propagation Neural Network（BPNN） is used to classify the left and right,at the meantime,subject’s threshold value of average band power is calculated to classify the accelerate and *** the test,there is about 84%accuracy rate of accelerate and brake and 89.92%for left and right *** second work is that we design and construct a real model FWID electric vehicle with environmental perception subsystem,including ultrasonic wave radars and cameras,which can avoid the risk when BCI command is *** also construct driving motor imagery sample data collector to get subjects’ motor imagery data for classifier to improve the accuracy of BCI system.

关键词： BCI Four-Wheel-Independent-Drive Electric Vehicles ICA CSP BPNN

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Science China(Technological Sciences) 2020年第1期63卷 155-165页

作者： ZHUANG WeiChao QU LingHu XU ShaoBing LI BingBing CHEN Nan yin guodong School of Mechanical Engineering Southeast UniversityNanjing 211189China Department of Mechanical Engineering University of MichiganAnn Arbor 48105USA

Eco-driving strategies for vehicles with conventional powertrains have been studied for years and attempt to reduce fuel consumption by optimizing the driving velocity *** electric vehicles(EVs)with regenerative braking,the speed profile with the best energy efficiency should be different from conventional *** paper proposes an energy-oriented cruising control strategy for EVs with a hierarchical structure to realize eco-cruising on highways with varying *** upper layer plans the energy-optimized vehicle velocity,and the lower layer calculates the torque allocation between the front and rear ***,the resulting speed profile with varying velocity may cause a high charge and discharge rate of the battery,resulting in rapid battery *** extend the battery life,we make a tradeoff between the energy consumption and wear of the battery by formulating an optimal control problem,where driving comfort and travel time are also *** indirect optimal control method is implemented to derive the optimal control *** an extension,the control rule for avoiding rear-end collisions is presented and simulated for driving in the real world.

关键词： eco-driving electric vehicle battery fading model dynamic programming energy management

Direction Control and Speed Control Combined Model of Motor-Imagery Based Brain-Actuated Vehicle 36

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Direction Control and Speed Control Combined Model of Motor-...

Combined Estimation of Vehicle Dynamic State and Inertial Parameter for Electric Vehicles Based on Dual Central Difference Kalman Filter Method

第36届中国控制会议

作者： guodong yin Lei Gong School of Mechanical Engineering Southeast University State Key Laboratory of Automotive Simulation and Control Jilin University

ISBN: (纸本)9781538629185

The brain-actuated vehicle model is of great value to develop a brain-actuated assistive driving. Furthermore, this study helps to develop other BCI systems such as mobile robots, wheelchairs and unmanned aerial vehicle. In this paper, we propose a control model of motor-imagery based brain-actuated vehicle. This model includes a direction control and speed control combined driver model, a motor imagery model, a brain-computer interface（BCI） performance model, a control model, a motor model and a vehicle model. The innovations of this paper are as follows: firstly, this model of the brain-actuated vehicle considers direction and speed control simultaneously and their coupling relationship;secondly, this model is based on motor imagery which is more applicable compared with other EEG signals. Simulation results show that the performance of the proposed model is close to expectant results.

关键词： motor-imagery brain-actuated vehicle BCI modeling steering and speed control

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Chinese Journal of Mechanical Engineering 2023年第4期36卷 339-354页

作者： Xianjian Jin Junpeng Yang Liwei Xu Chongfeng Wei Zhaoran Wang guodong yin School of Mechatronic Engineering and Automation Shanghai UniversityShanghai 200072China State Key Laboratory of Automotive Simulation and Control Jilin UniversityChangchun 130025China School of Mechanical Engineering Southeast UniversityNanjing 211189China Mechanical and Construction Engineering Northumbria UniversityNewcastle NE18STUK

Distributed drive electric vehicles(DDEVs)possess great advantages in the viewpoint of fuel consumption,environment protection and traffic *** the effects of inertial parameter variation in DDEV control system become much more pronounced due to the drastic reduction of vehicle weights and body size,and inertial parameter has seldom been tackled and systematically *** paper presents a dual central difference Kalman filter(DCDKF)where two Kalman filters run in parallel to simultaneously estimate vehicle different dynamic states and inertial parameters,such as vehicle sideslip angle,vehicle mass,vehicle yaw moment of inertia,the distance from the front axle to centre of *** proposed estimation method only integrates and utilizes real-time measurements of hub torque information and other in-vehicle sensors from standard *** four-wheel nonlinear vehicle dynamics estimation model considering payload variations,Pacejka tire model,wheel and motor dynamics model is developed,the observability of the DCDKF observer is analysed and derived via Lie derivative and differential geometry *** address system nonlinearities in vehicle dynamics estimation,the DCDKF and dual extended Kalman filter(DEKF)are also investigated and *** with various maneuvers are carried out to verify the effectiveness of the proposed method using Matlab/*** results show that the proposed DCDKF method can effectively estimate vehicle dynamic states and inertial parameters despite the existence of payload variations and variable driving *** research provides a boot-strapping procedure which can performs optimal estimation to estimate simultaneously vehicle system state and inertial parameter with high accuracy and real-time ability.

关键词： Distributed drive Electric vehicle State observation Inertial parameter Dual central difference Kalman filter

Energy-Saving and Punctuality Combined Velocity Planning for the Autonomous-Rail Rapid Tram with Enhanced Pseudospectral Method

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Chinese Journal of Mechanical Engineering 2023年第3期36卷 302-314页

作者： Jinxiang Wang Dongming Han Yongjun Yan Neng Liu Ning Sun guodong yin School of Mechanical Engineering Southeast UniversityNanjing 211189China School of Automotive and Traffic Engineering Nanjing Forestry UniversityNanjing 210037China

Autonomous-rail rapid transit(ART)is a new medium-capacity rapid transportation system with punctuality,comfort and convenience,but low-cost *** velocity planning is a critical approach to meet the requirements of energy-saving and *** ART velocity pre-planning and re-planning strategy based on the combination of punctuality dynamic programming(PDP)and pseudospectral(PS)method is proposed in this ***,the longitudinal dynamics model of ART is established by a multi-particle ***,the PDP algorithm with global optimal characteristics is adopted as the pre-planning strategy.A model for determining the number of collocation points of the real-time PS method is proposed to improve the energy-saving effect while ensuring computation *** the enhanced PS method is utilized to design the velocity re-planning ***,simulations are conducted in the typical scenario with sloping roads,traffic lights,and intrusion of the *** simulation results indicate that the ART with the proposed velocity trajectory optimization strategy can meet the punctuality requirement,and obtain better economy efficiency compared with the punctuality green light optimal speed advisory(PGLOSA).

关键词： Autonomous-rail rapid tram(ART) Velocity trajectory planning Dynamic programming Pseudospectral method

Adaptive Multi-modal Fusion Instance Segmentation for CAEVs in Complex Conditions:Dataset,Framework and Verifications

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Chinese Journal of Mechanical Engineering 2021年第5期34卷 96-106页

作者： Pai Peng Keke Geng guodong yin Yanbo Lu Weichao Zhuang Shuaipeng Liu School of Mechanical Engineering Southeast UniversityNanjingChina

Current works of environmental perception for connected autonomous electrified vehicles(CAEVs)mainly focus on the object detection task in good weather and illumination conditions,they often perform poorly in adverse scenarios and have a vague scene parsing *** paper aims to develop an end-to-end sharpening mixture of experts(SMoE)fusion framework to improve the robustness and accuracy of the perception systems for CAEVs in complex illumination and weather *** original contributions make our work distinctive from the existing relevant *** Complex KITTI dataset is introduced which consists of 7481 pairs of modified KITTI RGB images and the generated LiDAR dense depth maps,and this dataset is fine annotated in instance-level with the proposed semi-automatic annotation *** SMoE fusion approach is devised to adaptively learn the robust kernels from complementary *** comparative experiments are implemented,and the results show that the proposed SMoE framework yield significant improvements over the other fusion techniques in adverse environmental *** research proposes a SMoE fusion framework to improve the scene parsing ability of the perception systems for CAEVs in adverse conditions.

关键词： Connected autonomous electrified vehicles Multi-modal fusion Semi-automatic annotation Sharpening mixture of experts Comparative experiments

Automatic Miscalibration Detection and Correction of LiDAR and Camera Using Motion Cues

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Chinese Journal of Mechanical Engineering 2024年第2期37卷 318-329页

作者： Pai Peng Dawei Pi guodong yin Yan Wang Liwei Xu Jiwei Feng School of Mechanical Engineering Southeast UniversityNanjing 211102China School of Mechanical Engineering Nanjing University of Science and TechnologyNanjing 210014China School of Mechanical and Aerospace Engineering Nanyang Technological UniversitySingaporeSingapore

This paper aims to develop an automatic miscalibration detection and correction framework to maintain accurate calibration of LiDAR and camera for autonomous vehicle after the sensor ***,a monitoring algorithm that can continuously detect the miscalibration in each frame is designed,leveraging the rotational motion each individual sensor ***,as sensor drift occurs,the projection constraints between visual feature points and LiDAR 3-D points are used to compute the scaled camera motion,which is further utilized to align the drifted LiDAR scan with the camera ***,the proposed method is sufficiently compared with two representative approaches in the online experiments with varying levels of random drift,then the method is further extended to the offline calibration experiment and is demonstrated by a comparison with two existing benchmark methods.

关键词： Autonomous vehicle LiDAR and camera Miscalibration detection and correction Sensor drift

Trajectory Tracking of Autonomous Vehicle with the Fusion of DYC and Longitudinal–Lateral Control

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Chinese Journal of Mechanical Engineering 2019年第1期32卷 212-227页

作者： Fen Lin Yaowen Zhang Youqun Zhao guodong yin Huiqi Zhang Kaizheng Wang College of Energy and Power Engineering Nanjing University of Aeronautics and Astronautics School of Mechanical Engineering Southeast University

The current research of autonomous vehicle motion control mainly focuses on trajectory tracking and velocity tracking. However, numerous studies deal with trajectory tracking and velocity tracking separately, and the yaw stability is seldom considered during trajectory tracking. In this research, a combination of the longitudinal–lateral control method with the yaw stability in the trajectory tracking for autonomous vehicles is studied. Based on the vehicle dynamics, considering the longitudinal and lateral motion of the vehicle, the velocity tracking and trajectory tracking problems can be attributed to the longitudinal and lateral control. A sliding mode variable structure control method is used in the longitudinal control. The total driving force is obtained from the velocity error in order to carry out velocity tracking. A linear time-varying model predictive control method is used in the lateral control to predict the required front wheel angle for trajectory tracking. Furthermore, a combined control framework is established to control the longitudinal and lateral motions and improve the reliability of the longitudinal and lateral direction control. On this basis, the driving force of a tire is allocated reasonably by using the direct yaw moment control, which ensures good yaw stability of the vehicle when tracking the trajectory. Simulation results indicate that the proposed control strategy is good in tracking the reference velocity and trajectory and improves the performance of the stability of the vehicle.

关键词： Autonomous vehicle Trajectory tracking Direct yaw moment control(DYC) Model predictive control (MPC) Longitudinal–lateral control