Pub Date : 2018-06-01DOI: 10.1109/CCDC.2018.8407164
Peng Wang, Ge Li, Rusheng Ju, Xiang Zhang, Kedi Huang, Zhonghua Yang
Computer simulation has long been used for studying and predicting behaviors of complex systems. With the recent advances in sensor and network technologies, the availability and fidelity of real time measurements have been greatly increased. This makes the new simulation paradigm of dynamic data driven simulation more and more popular. It can assimilate the real time measurements for much better analysis and prediction of complex systems. Data assimilation techniques are the foundation of the dynamic data driven simulation, but the traditional particle filter based data assimilation algorithms can't meet the actual application requirements. In this paper, we study how to utilize the real time measurements for the dynamic data driven simulation. A new random finite set based data assimilation algorithm is proposed to overcome the limitations of the standard data assimilation algorithms. The random finite set based measurement model and simulation model that are used in the data assimilation process are introduced. The detailed implementation of the random finite set based data assimilation algorithm is presented. The study case with anti-piracy is used to practically illustrate the proposed data assimilation algorithm. The effectiveness and accuracy of the algorithm are checked by experiments.
{"title":"Random finite set based data assimilation algorithm for dynamic data driven simulation","authors":"Peng Wang, Ge Li, Rusheng Ju, Xiang Zhang, Kedi Huang, Zhonghua Yang","doi":"10.1109/CCDC.2018.8407164","DOIUrl":"https://doi.org/10.1109/CCDC.2018.8407164","url":null,"abstract":"Computer simulation has long been used for studying and predicting behaviors of complex systems. With the recent advances in sensor and network technologies, the availability and fidelity of real time measurements have been greatly increased. This makes the new simulation paradigm of dynamic data driven simulation more and more popular. It can assimilate the real time measurements for much better analysis and prediction of complex systems. Data assimilation techniques are the foundation of the dynamic data driven simulation, but the traditional particle filter based data assimilation algorithms can't meet the actual application requirements. In this paper, we study how to utilize the real time measurements for the dynamic data driven simulation. A new random finite set based data assimilation algorithm is proposed to overcome the limitations of the standard data assimilation algorithms. The random finite set based measurement model and simulation model that are used in the data assimilation process are introduced. The detailed implementation of the random finite set based data assimilation algorithm is presented. The study case with anti-piracy is used to practically illustrate the proposed data assimilation algorithm. The effectiveness and accuracy of the algorithm are checked by experiments.","PeriodicalId":409960,"journal":{"name":"2018 Chinese Control And Decision Conference (CCDC)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122994679","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-06-01DOI: 10.1109/CCDC.2018.8407299
Z. Fan, Ma Yan, Duan Peng, Mingchao Chen, Chen Hong
As power source of electric vehicles (EVs), the inconsistency of lithium-ion battery directly affects the performance and safety of EVs. A non-dissipative equalization scheme is proposed to improve the inconsistency in this paper. The bidirectional equalization circuit based on inductance as energy transferring media is designed to reduce the loss of equalization energy and improve the utilization of capacity for lithium-ion battery. To facilitate the implementation of battery equalization, the equalization strategy with voltage-difference control method is selected. Then the equalization system is built to demonstrate the feasibility of equalization scheme in MATLAB/Simulink. Finally, on the basis of field programmable gate array (FPGA), the actual hardware circuit is designed, and the equalization experiment of 4 LiFePO4 battery cells is carried out. The final range of charging voltage is 0.011V and the final standard deviation of charging voltage is 0.41%. The experimental results show that the cells actual voltage differences can converge to an acceptable range and verify the validity of the proposed non-dissipative equalization scheme.
{"title":"Non-dissipative equalization with voltage-difference based on FPGA for lithium-ion battery","authors":"Z. Fan, Ma Yan, Duan Peng, Mingchao Chen, Chen Hong","doi":"10.1109/CCDC.2018.8407299","DOIUrl":"https://doi.org/10.1109/CCDC.2018.8407299","url":null,"abstract":"As power source of electric vehicles (EVs), the inconsistency of lithium-ion battery directly affects the performance and safety of EVs. A non-dissipative equalization scheme is proposed to improve the inconsistency in this paper. The bidirectional equalization circuit based on inductance as energy transferring media is designed to reduce the loss of equalization energy and improve the utilization of capacity for lithium-ion battery. To facilitate the implementation of battery equalization, the equalization strategy with voltage-difference control method is selected. Then the equalization system is built to demonstrate the feasibility of equalization scheme in MATLAB/Simulink. Finally, on the basis of field programmable gate array (FPGA), the actual hardware circuit is designed, and the equalization experiment of 4 LiFePO4 battery cells is carried out. The final range of charging voltage is 0.011V and the final standard deviation of charging voltage is 0.41%. The experimental results show that the cells actual voltage differences can converge to an acceptable range and verify the validity of the proposed non-dissipative equalization scheme.","PeriodicalId":409960,"journal":{"name":"2018 Chinese Control And Decision Conference (CCDC)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114255166","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-06-01DOI: 10.1109/CCDC.2018.8407519
Xingyu Xia, Xi Wang, Haidong Hu, Dongmei Wu, Hao Gao
Depending on the power global search ability, artificial bee colony algorithm attracts more attentions in recent years. But its slow convergence rate constraints its development. To better balance its exploration and exploitation abilities, we define a new point named as mean history best points (MHB) to lead the direction of bee population. The numerical experiments on the basic benchmark functions validate the efficiency of our algorithm.
{"title":"An improved artificial bee colony algorithm with history best points","authors":"Xingyu Xia, Xi Wang, Haidong Hu, Dongmei Wu, Hao Gao","doi":"10.1109/CCDC.2018.8407519","DOIUrl":"https://doi.org/10.1109/CCDC.2018.8407519","url":null,"abstract":"Depending on the power global search ability, artificial bee colony algorithm attracts more attentions in recent years. But its slow convergence rate constraints its development. To better balance its exploration and exploitation abilities, we define a new point named as mean history best points (MHB) to lead the direction of bee population. The numerical experiments on the basic benchmark functions validate the efficiency of our algorithm.","PeriodicalId":409960,"journal":{"name":"2018 Chinese Control And Decision Conference (CCDC)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114295681","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-06-01DOI: 10.1109/CCDC.2018.8407690
Yong-zhong Lu, Jin Zhao
Predictive torque control for induction motor is a control strategy uses the model of the motor drive and an appropriate cost function to directly control torque and flux. This strategy is easy to implement but depends upon parameters of motor drive. This paper presents the design and analysis of a sliding mode flux observer to improve the parameter robustness. The observer estimates the stationary reference frame flux of the induction motor by using sliding mode terms based on the current mismatches and flux mismatches. The novelty is the method use the current mismatches to estimate the flux mismatches in the situation when the real fluxes is not available. Simulations presented in this paper prove the sliding mode observer improve the parameter robustness of predictive torque controlled induction motor drive.
{"title":"A sliding mode flux observer for predictive torque controlled induction motor drive","authors":"Yong-zhong Lu, Jin Zhao","doi":"10.1109/CCDC.2018.8407690","DOIUrl":"https://doi.org/10.1109/CCDC.2018.8407690","url":null,"abstract":"Predictive torque control for induction motor is a control strategy uses the model of the motor drive and an appropriate cost function to directly control torque and flux. This strategy is easy to implement but depends upon parameters of motor drive. This paper presents the design and analysis of a sliding mode flux observer to improve the parameter robustness. The observer estimates the stationary reference frame flux of the induction motor by using sliding mode terms based on the current mismatches and flux mismatches. The novelty is the method use the current mismatches to estimate the flux mismatches in the situation when the real fluxes is not available. Simulations presented in this paper prove the sliding mode observer improve the parameter robustness of predictive torque controlled induction motor drive.","PeriodicalId":409960,"journal":{"name":"2018 Chinese Control And Decision Conference (CCDC)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116838611","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-06-01DOI: 10.1109/CCDC.2018.8407708
Zhenhao Tang, Mingxuan Yang, Bo Zhao
Superheated steam temperature is a vital factor that affects the power generation efficiency. A data-driven based approach is proposed to modeling the superheated steam temperature. The ReliefF algorithm is employed to select the input features. In addition, a back propagation neural network(BP) model with parameters optimized by genetic algorithm (GA) is proposed to constructed the prediction model. Experiment results demonstrate that the proposed method can get better forecasting results in comparison with the PSO-BP(particle swarm optimized back propagation neural network), linear regression approach and the MLP(multi-layer perceptron) approach.
{"title":"Modeling the superheated steam temperature with a data-driven based approach","authors":"Zhenhao Tang, Mingxuan Yang, Bo Zhao","doi":"10.1109/CCDC.2018.8407708","DOIUrl":"https://doi.org/10.1109/CCDC.2018.8407708","url":null,"abstract":"Superheated steam temperature is a vital factor that affects the power generation efficiency. A data-driven based approach is proposed to modeling the superheated steam temperature. The ReliefF algorithm is employed to select the input features. In addition, a back propagation neural network(BP) model with parameters optimized by genetic algorithm (GA) is proposed to constructed the prediction model. Experiment results demonstrate that the proposed method can get better forecasting results in comparison with the PSO-BP(particle swarm optimized back propagation neural network), linear regression approach and the MLP(multi-layer perceptron) approach.","PeriodicalId":409960,"journal":{"name":"2018 Chinese Control And Decision Conference (CCDC)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117018004","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In this paper, the operation strategy of thermal power units after the configuration of phase change heat storage station is put forward, and the mathematical model for calculating the peak-shaving capacity of thermal power units after the allocation of phase change heat storage stations is established. Based on the analysis of frequency requirements of electric power system, puts forward the analysis of high frequency and low frequency demand method by using the discrete Fourier transform, and the actual system all day long the proportion of high frequency components are quantitatively analyzed. Analyzes the effect of two typical 300MW and 200MW heating units in Northeast China on improving peak shaving capacity after installing heat storage stations. The results show that the peak shaving capacity of the two units can be increased by 21% and 14% at a given heat load level in the middle heating period. And based on the actual system data, the paper simulates and analyzes the FM strategy of energy storage participating in automatic generation control (AGC). The results show that the flexible allocation of energy storage resources based on area regulation requirement (ARR) has a better FM effect.
{"title":"Research on the control strategy of phase-change heat storage station with automatic generation system in power network peak regulation and frequency modulation","authors":"Qingqi Zhao, Yong-Xing Li, Hongyu Zhang, Tingxu Gao, Yi Yang, Wen Zheng","doi":"10.1109/CCDC.2018.8407875","DOIUrl":"https://doi.org/10.1109/CCDC.2018.8407875","url":null,"abstract":"In this paper, the operation strategy of thermal power units after the configuration of phase change heat storage station is put forward, and the mathematical model for calculating the peak-shaving capacity of thermal power units after the allocation of phase change heat storage stations is established. Based on the analysis of frequency requirements of electric power system, puts forward the analysis of high frequency and low frequency demand method by using the discrete Fourier transform, and the actual system all day long the proportion of high frequency components are quantitatively analyzed. Analyzes the effect of two typical 300MW and 200MW heating units in Northeast China on improving peak shaving capacity after installing heat storage stations. The results show that the peak shaving capacity of the two units can be increased by 21% and 14% at a given heat load level in the middle heating period. And based on the actual system data, the paper simulates and analyzes the FM strategy of energy storage participating in automatic generation control (AGC). The results show that the flexible allocation of energy storage resources based on area regulation requirement (ARR) has a better FM effect.","PeriodicalId":409960,"journal":{"name":"2018 Chinese Control And Decision Conference (CCDC)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128387098","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-06-01DOI: 10.1109/CCDC.2018.8408090
Zhao Wang, Yuhuan Shi, Shurong Li
Aiming at the swing problem of container cranes in the process of loading and unloading cargo, an adaptive neural fuzzy (ANFIS) control method based on Takagi-Sugeno (T-S) model is proposed in this paper. Firstly, the mathematical model of crane trolley-hoist system was established based on Lagrange's equation. Secondly, an improved T-S fuzzy neural network is proposed. Since the SNPRP conjugate gradient method has sufficient descent and global convergence under strong search conditions. In this paper, SNPRP conjugate gradient method is used to train the premise parameters and the consequent parameters of T-S model. In order to obtain the best controller, the optimal control matrix of the system is obtained by linear quadratic optimal control using the minimum energy as an indicator, so that the neural network is used to train the ANFIS controller. Finally, the trained ANFIS controller is applied in the crane trolley-hoist system for simulation. The results show that this control method in this paper has better control effect and robustness under different rope lengths and different working conditions.
{"title":"Research on anti-swaying of crane based on T-S type adaptive neural fuzzy control","authors":"Zhao Wang, Yuhuan Shi, Shurong Li","doi":"10.1109/CCDC.2018.8408090","DOIUrl":"https://doi.org/10.1109/CCDC.2018.8408090","url":null,"abstract":"Aiming at the swing problem of container cranes in the process of loading and unloading cargo, an adaptive neural fuzzy (ANFIS) control method based on Takagi-Sugeno (T-S) model is proposed in this paper. Firstly, the mathematical model of crane trolley-hoist system was established based on Lagrange's equation. Secondly, an improved T-S fuzzy neural network is proposed. Since the SNPRP conjugate gradient method has sufficient descent and global convergence under strong search conditions. In this paper, SNPRP conjugate gradient method is used to train the premise parameters and the consequent parameters of T-S model. In order to obtain the best controller, the optimal control matrix of the system is obtained by linear quadratic optimal control using the minimum energy as an indicator, so that the neural network is used to train the ANFIS controller. Finally, the trained ANFIS controller is applied in the crane trolley-hoist system for simulation. The results show that this control method in this paper has better control effect and robustness under different rope lengths and different working conditions.","PeriodicalId":409960,"journal":{"name":"2018 Chinese Control And Decision Conference (CCDC)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128335884","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-06-01DOI: 10.1109/ccdc.2018.8407883
Zhou Yuan, Wang Ting
A platform inertial platform system (IPS) is a kind of independent navigation system. A fiber optic gyro (FOG) based IPS can stabilize its inertial measurement unit (IMU) in inertial space using its FOG readouts, and calculate its carrier's real-time displacement and velocity using its accelerometer readouts. Alignment is the initialization process of the IPS. During the coarse alignment of the FOG based IPS, the instrument errors, random noise and base vibration can cause decline of the alignment accuracy. To improve the precision of coarse alignment, the IMU rotation modulation is used to suppress the errors of inertial instruments by utilizing the equivalent integration process contained in the averaging computation. On the stationary base, calculate the attitude matrix of the rotating IMU in each sampling period, and averaging computation can compensate the errors caused by biases of inertial instruments. When the carrier is in vibration condition, the alignment coordinate frame (CF) is introduced to assist the rotation modulation. Carry out the attitude updating within the alignment CF in each sampling period to correct the estimated attitude matrix, and the rotation modulation based method can still improve the precision of coarse alignment in vibration condition.
{"title":"A method of coarse alignment for FOG based inertial platform system using rotation modulation","authors":"Zhou Yuan, Wang Ting","doi":"10.1109/ccdc.2018.8407883","DOIUrl":"https://doi.org/10.1109/ccdc.2018.8407883","url":null,"abstract":"A platform inertial platform system (IPS) is a kind of independent navigation system. A fiber optic gyro (FOG) based IPS can stabilize its inertial measurement unit (IMU) in inertial space using its FOG readouts, and calculate its carrier's real-time displacement and velocity using its accelerometer readouts. Alignment is the initialization process of the IPS. During the coarse alignment of the FOG based IPS, the instrument errors, random noise and base vibration can cause decline of the alignment accuracy. To improve the precision of coarse alignment, the IMU rotation modulation is used to suppress the errors of inertial instruments by utilizing the equivalent integration process contained in the averaging computation. On the stationary base, calculate the attitude matrix of the rotating IMU in each sampling period, and averaging computation can compensate the errors caused by biases of inertial instruments. When the carrier is in vibration condition, the alignment coordinate frame (CF) is introduced to assist the rotation modulation. Carry out the attitude updating within the alignment CF in each sampling period to correct the estimated attitude matrix, and the rotation modulation based method can still improve the precision of coarse alignment in vibration condition.","PeriodicalId":409960,"journal":{"name":"2018 Chinese Control And Decision Conference (CCDC)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128564195","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-06-01DOI: 10.1109/CCDC.2018.8407448
Chunbo Xiu, Yalong Zhao, Ruosi Wang
The accuracy of tracking based on Camshift would decrease due to the similarity between target color and background color or the target is obscured. For the above problems, improved target tracking algorithm based on Camshift is proposed in this paper. The Camshift algorithm is improved by using the contour features of the target, and Camshift search window is updated according to the contour feature of the target. Thus, interference of background and strong light is weakened. Kalman filtering algorithm is used to predict the motion state of the tracking target, enhancing the efficiency of tracking when the tracking target is obscured. Experiments show that Camshift is combined with the contour feature of target and make the tracking more effectively under the conditions of background. And the Kalman filtering algorithm is used to predict position of the target to make the tracking effectively when the target is obscured.
{"title":"Design of quad-rotor target tracking system","authors":"Chunbo Xiu, Yalong Zhao, Ruosi Wang","doi":"10.1109/CCDC.2018.8407448","DOIUrl":"https://doi.org/10.1109/CCDC.2018.8407448","url":null,"abstract":"The accuracy of tracking based on Camshift would decrease due to the similarity between target color and background color or the target is obscured. For the above problems, improved target tracking algorithm based on Camshift is proposed in this paper. The Camshift algorithm is improved by using the contour features of the target, and Camshift search window is updated according to the contour feature of the target. Thus, interference of background and strong light is weakened. Kalman filtering algorithm is used to predict the motion state of the tracking target, enhancing the efficiency of tracking when the tracking target is obscured. Experiments show that Camshift is combined with the contour feature of target and make the tracking more effectively under the conditions of background. And the Kalman filtering algorithm is used to predict position of the target to make the tracking effectively when the target is obscured.","PeriodicalId":409960,"journal":{"name":"2018 Chinese Control And Decision Conference (CCDC)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128577032","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-06-01DOI: 10.1109/CCDC.2018.8407710
Junxiang Li, Xiaohui Li, Bohan Jiang, Q. Zhu
The accurate maneuver prediction for dynamic vehicles can enhance driving safety in complex environments. This paper presents a maneuver prediction method for dynamic vehicles in highway scenarios. The method effectively combines multi-frame vehicle states, road structures and interactions among vehicles. With a novel extraction algorithm of environment feature, the method infers the probability of each driving maneuver by using a Dynamic Bayesian Network. The experimental results demonstrate that our method can predict lane-change maneuvers at least 2 seconds before they occur in real environments with an accuracy of 84.9%.
{"title":"A maneuver-prediction method based on dynamic bayesian network in highway scenarios","authors":"Junxiang Li, Xiaohui Li, Bohan Jiang, Q. Zhu","doi":"10.1109/CCDC.2018.8407710","DOIUrl":"https://doi.org/10.1109/CCDC.2018.8407710","url":null,"abstract":"The accurate maneuver prediction for dynamic vehicles can enhance driving safety in complex environments. This paper presents a maneuver prediction method for dynamic vehicles in highway scenarios. The method effectively combines multi-frame vehicle states, road structures and interactions among vehicles. With a novel extraction algorithm of environment feature, the method infers the probability of each driving maneuver by using a Dynamic Bayesian Network. The experimental results demonstrate that our method can predict lane-change maneuvers at least 2 seconds before they occur in real environments with an accuracy of 84.9%.","PeriodicalId":409960,"journal":{"name":"2018 Chinese Control And Decision Conference (CCDC)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129022896","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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