To reduce the damages of pavement,vehicle components and agricultural product during transportation,an electric control air suspension height adjustment system of agricultural transport vehicle was studied by means of...To reduce the damages of pavement,vehicle components and agricultural product during transportation,an electric control air suspension height adjustment system of agricultural transport vehicle was studied by means of simulation and bench test.For the oscillation phenomenon of vehicle height in driving process,the mathematical model of the vehicle height adjustment system was developed,and the controller of vehicle height based on single neuron adaptive PID control algorithm was designed.The control model was simulated via Matlab/Simulink,and bench test was conducted.Results show that the method is feasible and effective to solve the agricultural vehicle body height unstable phenomenon in the process of switching.Compared with other PID algorithms,the single neuron adaptive PID control in agricultural transport vehicle has shorter response time,faster response speed and more stable switching state.The stability of the designed vehicle height adjustment system and the ride comfort of agricultural transport vehicle were improved.展开更多
Purpose–Precise vehicle localization is a basic and critical technique for various intelligent transportation system(ITS)applications.It also needs to adapt to the complex road environments in real-time.The global po...Purpose–Precise vehicle localization is a basic and critical technique for various intelligent transportation system(ITS)applications.It also needs to adapt to the complex road environments in real-time.The global positioning system and the strap-down inertial navigation system are two common techniques in thefield of vehicle localization.However,the localization accuracy,reliability and real-time performance of these two techniques can not satisfy the requirement of some critical ITS applications such as collision avoiding,vision enhancement and automatic parking.Aiming at the problems above,this paper aims to propose a precise vehicle ego-localization method based on image matching.Design/methodology/approach–This study included three steps,Step 1,extraction of feature points.After getting the image,the local features in the pavement images were extracted using an improved speeded up robust features algorithm.Step 2,eliminate mismatch points.Using a random sample consensus algorithm to eliminate mismatched points of road image and make match point pairs more robust.Step 3,matching of feature points and trajectory generation.Findings–Through the matching and validation of the extracted local feature points,the relative translation and rotation offsets between two consecutive pavement images were calculated,eventually,the trajectory of the vehicle was generated.Originality/value–The experimental results show that the studied algorithm has an accuracy at decimeter-level and it fully meets the demand of the lane-level positioning in some critical ITS applications.展开更多
基金the National Natural Science Foundation of China(Grant No.51375212,71373105)Research Fund for the Doctoral Program of Higher Education of China(Grant No.20133227130001)+1 种基金Research and Innovation Project for College Graduates of Jiangsu Province of China(Grant No.CXZZ12_0663)Jiangsu Provincial Natural Science Foundation of China(Grant No.BK20131255)。
文摘To reduce the damages of pavement,vehicle components and agricultural product during transportation,an electric control air suspension height adjustment system of agricultural transport vehicle was studied by means of simulation and bench test.For the oscillation phenomenon of vehicle height in driving process,the mathematical model of the vehicle height adjustment system was developed,and the controller of vehicle height based on single neuron adaptive PID control algorithm was designed.The control model was simulated via Matlab/Simulink,and bench test was conducted.Results show that the method is feasible and effective to solve the agricultural vehicle body height unstable phenomenon in the process of switching.Compared with other PID algorithms,the single neuron adaptive PID control in agricultural transport vehicle has shorter response time,faster response speed and more stable switching state.The stability of the designed vehicle height adjustment system and the ride comfort of agricultural transport vehicle were improved.
文摘Purpose–Precise vehicle localization is a basic and critical technique for various intelligent transportation system(ITS)applications.It also needs to adapt to the complex road environments in real-time.The global positioning system and the strap-down inertial navigation system are two common techniques in thefield of vehicle localization.However,the localization accuracy,reliability and real-time performance of these two techniques can not satisfy the requirement of some critical ITS applications such as collision avoiding,vision enhancement and automatic parking.Aiming at the problems above,this paper aims to propose a precise vehicle ego-localization method based on image matching.Design/methodology/approach–This study included three steps,Step 1,extraction of feature points.After getting the image,the local features in the pavement images were extracted using an improved speeded up robust features algorithm.Step 2,eliminate mismatch points.Using a random sample consensus algorithm to eliminate mismatched points of road image and make match point pairs more robust.Step 3,matching of feature points and trajectory generation.Findings–Through the matching and validation of the extracted local feature points,the relative translation and rotation offsets between two consecutive pavement images were calculated,eventually,the trajectory of the vehicle was generated.Originality/value–The experimental results show that the studied algorithm has an accuracy at decimeter-level and it fully meets the demand of the lane-level positioning in some critical ITS applications.
