Research on Local Dynamic Path Planning Method for Intelligent Vehicle Lane-Changing

Liu, Zhiqiang; Zhang, Teng; Wang, Yifan

doi:10.1155/2019/4762658

Cited by 14 publications

(8 citation statements)

References 9 publications

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“…System Model. Aiming at the dense heterogeneous wireless network scenario with multilevel network structure composed of high-power Hong Jizhan and low-power micro base stations [11,12], as shown in Figure 1, this paper proposes a network fault diagnosis model based on GAN to locate faults, so as to avoid losses caused by fault propagation.…”

Section: Fault Diagnosis Algorithm Based Onmentioning

confidence: 99%

Research on Fault Diagnosis Model of Generative Adss Based on Improved Semisupervised Diagnosis Algorithm

Yi¹

2021

Mobile Information Systems

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With the advent of the era of big data and the rapid development of deep learning and other technologies, people can use complex neural network models to mine and extract key information in massive data with the support of powerful computing power. However, it also increases the complexity of heterogeneous network and greatly increases the difficulty of network maintenance and management. In order to solve the problem of network fault diagnosis, this paper first proposes an improved semisupervised inverse network fault diagnosis algorithm; the proposed algorithm effectively guarantees the convergence of generated against network model, makes full use of a large amount of trouble-free tag data, and obtains a good accuracy of fault diagnosis. Then, the diagnosis model is further optimized and the fault classification task is completed by the convolutional neural network, the discriminant function of the network is simplified, and the generation pair network is only responsible for generating fault samples. The simulation results also show that the fault diagnosis algorithm based on network generation and convolutional neural network achieves good fault diagnosis accuracy and saves the overhead of manually labeling a large number of data samples.

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Section: Fault Diagnosis Algorithm Based Onmentioning

confidence: 99%

Research on Fault Diagnosis Model of Generative Adss Based on Improved Semisupervised Diagnosis Algorithm

Yi¹

2021

Mobile Information Systems

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“…Therefore, we need to carry on local path planning in real time according to the complex and changeable situation. Local path planning is guided by global path and uses realtime local environment information to quickly confirm suspicious targets (Liu et al 2019).…”

Section: Local Path Planning Based On Real-time Informationmentioning

confidence: 99%

Efficient Path Planning Method of USV for Intelligent Target Search

Zhang

Liu

et al. 2019

J geovis spat anal

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In order to accomplish a target search task safely and efficiently and make full use of prior information and real-time information, a path planning method of unmanned surface vehicle (USV) for intelligent target search is proposed. The overall strategy is divided into three parts: global path planning based on prior information, local path planning based on real-time information, and improved A* obstacle avoidance algorithm. Before the start of the task, the global path planning is carried out based on prior information such as the initial position of USV, the predicted position of the target and range of search area. After the start of the task, if USV finds suspicious targets, in order to further approach these suspicious targets, it will enter different local path planning modes according to the characteristics of these targets. During task execution, if obstacles are encountered, an improved A* obstacle avoidance algorithm is adopted. The simulation results show that the proposed method can improve the efficiency of target recognition and reduce the turning cost of USV when encountering obstacles. So, for USV intelligent target search, the proposed path planning method can save resources and improve search efficiency.

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“…In the last decades, the lane changing/lane keeping system [1,2], antilock braking system [3], cruise control system (CCS) [4], advanced vehicle motion control systems [5][6][7], etc. have been widely implemented on the intelligent vehicles.…”

Section: Introductionmentioning

confidence: 99%

An Eco-Cruise Control for Electric Vehicles Moving on Slope Road with Constant Speed

Zhang

Liu

et al. 2021

Journal of Advanced Transportation

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The unreasonable actuation of electric vehicle’s motor drive system usually results in a lot of unwanted energy consumption on a slope road. This paper proposes an eco-cruise control (ECC) scheme based on the driving condition estimation to decrease electric vehicle’s energy consumption in the constant-speed cruise control mode. The eco-cruise control scheme is realized by reducing the unreasonable actuation of the motor drive system. The vehicle’s total mass and pitch angle are estimated in real time by using an improved base-vector-based cross iteration estimator (BVCIE). Based on the estimated results, the required torque is predicted. Combining the speed deviation between the desired speed and the real speed, and the torque deviation between the required torque and the real torque, a three-power nonlinear controller of the ECC scheme is designed. The ECC scheme is validated on a slope road with different cruise speeds on a cosimulation platform, and the results indicate that the proposed strategy enjoys a better speed maintenance ability and energy efficiency compared with the benchmarked cruise control.

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Research on Local Dynamic Path Planning Method for Intelligent Vehicle Lane-Changing

Cited by 14 publications

References 9 publications

Research on Fault Diagnosis Model of Generative Adss Based on Improved Semisupervised Diagnosis Algorithm

Research on Fault Diagnosis Model of Generative Adss Based on Improved Semisupervised Diagnosis Algorithm

Efficient Path Planning Method of USV for Intelligent Target Search

An Eco-Cruise Control for Electric Vehicles Moving on Slope Road with Constant Speed

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