Multi-objective adaptive cruise control optimization algorithm for electric vehicles based on model predictive control

Xu, Jiasen; Zhang, Niaona; Wang, Jieshu; Yang, Sheng

doi:10.1109/cvci56766.2022.9965121

Cited by 2 publications

(2 citation statements)

References 8 publications

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“…In view of this situation, Xiao [1] and others described the concept, composition, structure, design and development process of ACC system for ACC vehicles. Li Xu et al [2] verified that this method can improve the comfort of ACC system by improving the variable sampling time model predictive control strategy based on the fuzzy control framework. VOLLRATH M [3][4] has carried out a lot of research work on traffic flow characteristics such as traffic capacity and traffic safety of ACC car following model.…”

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confidence: 97%

Research on Vehicle Lane Keeping Capability in Low-Speed Scenarios Based on Autonomous Driving Technology

Duan,

Wu,

et al. 2024

Preprint

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Absrtact: In order to ensure the safety, stability and driving comfort of vehicle lane keeping in low-speed scenarios, this paper proposes an evaluation method of lane keeping behavior capability based on automatic driving technology. Taking low-speed scene as the research object, based on automatic driving technology, IDM intelligent driving model is applied to describe ACC car following model, and MATLAB/Simulink and Carsim are used to build a low-speed scene lane keeping simulation platform The three aspects of comfort are used to evaluate the vehicle lane keeping ability in low-speed scenarios. The structure shows that when the distance between the target vehicle behind and the vehicle in front reaches a stable safety distance, the average speed of the vehicle is 21.6 (km · h -1 ), and the floating size is not more than 1. The difference between floating up and floating down is 0.0002, which is conducive to the stability of the lane during driving. In addition, based on the IDM intelligent driving model, this paper obtains data through vehicle to vehicle communication in the urban low-speed scenario, that is, when the vehicle is driving in the lane, its acceleration changes slightly. When it approaches zero, it can reduce unnecessary deceleration, so as to improve the driver's riding comfort. Based on ACC simulation, the difference between the actual following distance between the target vehicle and the vehicle in front during lane keeping and the target following distance fluctuates between -0.06 and 0.05m, and most of the differences are greater than the average difference, which can well meet the actual requirements and make car following safer. It can be seen that it is effective to study the lane keeping ability of vehicles in low-speed scenarios based on automatic driving technology in this paper.

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confidence: 97%

Research on Vehicle Lane Keeping Capability in Low-Speed Scenarios Based on Autonomous Driving Technology

Duan,

Wu,

et al. 2024

Preprint

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“…For the multiobjective task of supply chain demand forecasting, in practical applications or various competitions, most solutions are to split it into a simple single-objective problem (Xu et al, 2022). Some of these solutions are to preprocess the historical data and build it, to build a single-target regression model of time series based on historical data, or to use a single-target time series weighted model (Wu et al, 2022).…”

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confidence: 99%

A Multi-Objective Method Based on Tag Eigenvalues Is Used to Predict the Supply Chain for Online Retailers

Jiang,

Hu,

Dong

et al. 2024

International Journal of Information Systems and Supply Chain Management

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E-commerce has grown quickly in recent years thanks to advancements in Internet and information technologies. For the majority of consumers, online shopping has emerged as a primary mode of shopping. However, it has become more challenging for businesses to satisfy consumer demand due to their increasingly individualized wants. To address the need for customized products with numerous kinds and small quantities, businesses must rebuild their supply chain systems to increase their efficiency and adaptability. The SI-LSF technique, which employs boosting learning in the target-relative feature space to lower the prediction error and enhance the algorithm's capacity to handle input-output interactions, is validated in this study using a genuine industrial dataset. The study successfully identifies the relationship between sales and sales as well as target-specific features by applying the multi-objective regression integration algorithm based on label-specific features to a real-world supply chain demand scenario.

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Multi-objective adaptive cruise control optimization algorithm for electric vehicles based on model predictive control

Cited by 2 publications

References 8 publications

Research on Vehicle Lane Keeping Capability in Low-Speed Scenarios Based on Autonomous Driving Technology

Research on Vehicle Lane Keeping Capability in Low-Speed Scenarios Based on Autonomous Driving Technology

A Multi-Objective Method Based on Tag Eigenvalues Is Used to Predict the Supply Chain for Online Retailers

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