Adaptive Cruise Control Strategy Design with Optimized Active Braking Control Algorithm

Wu, Wenguang; Zou, Debiao; Ou, Jian; Hu, Lin

doi:10.1155/2020/8382734

Cited by 13 publications

(12 citation statements)

References 34 publications

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“…In order to ensure the vehicle comfort when the vehicle speed changes significantly, Wu et al. [61] proposed an adaptive cruise control (ACC) system with an active braking algorithm, and an upper decision controller based on the MPC algorithm. The results show that the speed and distance of the vehicle are always within the specified comfort range.…”

Section: Comfort Of Ivsmentioning

confidence: 99%

“…González et al [60] use Bezier curve to smooth acceleration and bump curve, and improve riding comfort of automatic driving vehicle by limiting global acceleration in the whole driving process. In order to ensure the vehicle comfort when the vehicle speed changes significantly, Wu et al [61] proposed an adaptive cruise control (ACC) system with an active braking algorithm, and an upper decision controller based on the MPC algorithm. The results show that the speed and distance of the vehicle are always within the specified comfort range.…”

Section: Anthropomorphic Decision Makingmentioning

confidence: 99%

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A review on key challenges in intelligent vehicles: Safety and driver‐oriented features

Zhou

Zhang

et al. 2021

IET Intelligent Trans Sys

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The huge advantages of intelligent vehicles (IVs) in improving road safety and operating efficiency have become a research focus in the industry. IVs have made significant progress in recent years, but it is still face great challenges in order to be accepted by users on a large scale. In this regard, the authors propose that the research of IVs can be developed along the lines of safety, comfort and economy, gradually overcoming existing dilemmas. First of all, security is the most basic requirement of IVs. The authors sort out the key technologies and challenges of the basic architecture of IVs, and propose existing attack and defences strategies for IVs information security technology. Secondly, comfort is more about people's subjective feelings. From two aspects of physiological comfort and psychological comfort, the paper studies the anthropomorphic decision-making to overcome the mechanized speed control, human computer interaction design, personalized driving style and ethical decision-making methods. Then, aiming at the micro-and macro-levels of economy, it outlines technologies such as economic driving behavioural, collaborative control of people, vehicles and roads and IVs sharing. Finally, the authors summarized the challenges and future development directions in the three stages of IVs development.

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Section: Comfort Of Ivsmentioning

confidence: 99%

Section: Anthropomorphic Decision Makingmentioning

confidence: 99%

A review on key challenges in intelligent vehicles: Safety and driver‐oriented features

Zhou

Zhang

et al. 2021

IET Intelligent Trans Sys

Self Cite

View full text Add to dashboard Cite

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“…The inter-discipline consistency constraint is used as the response deviation to construct the dynamic relaxation factor, as shown in Equation (9).…”

Section: Math Problem Applicationmentioning

confidence: 99%

“…However, for automobiles, the research of lightweight should not only include passive safety; active safety is also an important factor that cannot be ignored [6,7]. The main problem of active safety is how to improve the handling stability, in addition to being improved by the electronic control safety system [8][9][10][11]. In [12], Yu pointed out that the vertical load of the tire on the ground is reduced by the aerodynamic lift on the automobile, and the change of the vertical load has a significant impact on the wheel cornering characteristics, thus affecting the handling stability, as well as the dynamic performance and braking performance of the automobile.…”

Section: Introductionmentioning

confidence: 99%

Multidisciplinary Lightweight Optimization for Front Impact Structure of Body Frame Based on Active and Passive Safety

Wang¹,

Wang²,

Li³

et al. 2021

Mathematics

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The Analytic Target Cascading (ATC) is an effective method for solving hierarchical Multidisciplinary Design Optimization (MDO) problems. At the same time, this method suffers from poor convergence and low accuracy, which is caused by the inconsistency of system constraints. In this paper, a novel ATC method based on dynamic relaxation factor is proposed. The dynamic relaxation factor of consistency constraint is added in the system level and is adjusted by the deviation of the linking variables between the levels to ensure the feasible region of the design space. The effectiveness and accuracy of this method are verified by a mathematical example. This method is used to solve the lightweight problem of the trussed front part of the vehicle body frame based on active and passive safety to achieve the collaborative optimization of lightweight trussed frame, crash safety, and aerodynamic characteristics. The important value of the novel ATC method based on dynamic relaxation factor in engineering applications is proven.

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“…Motivated by connected and automated vehicle (CAV) technologies, Zhao et al [13] proposed a data-driven optimization-based MPC modeling framework for the Cooperative Adaptive Cruise Control (CACC) of a string of CAVs under uncertain traffic conditions. Wu et al [14] designed an ACC system based on an active braking algorithm to improve vehicle safety and comfort. Jiang et al [15] considered the driver's risk sensitivity under system and measurement uncertainty, and proposed a personalized stochastic optimal adaptive cruise control algorithm.…”

Section: Introductionmentioning

confidence: 99%

Research on Vehicle Adaptive Cruise Control Method Based on Fuzzy Model Predictive Control

Mao

Yang

et al. 2021

Machines

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Under complex working conditions, vehicle adaptive cruise control (ACC) systems with fixed weight coefficients cannot guarantee good car following performance under all conditions. In order to improve the tracking and comfort of vehicles in different modes, a fuzzy model predictive control (Fuzzy-MPC) algorithm is proposed. Based on the comprehensive consideration of safety, comfort, fuel economy and vehicle limitations, the objective function and constraints are designed. A relaxation factor vector is introduced to soften the hard constraint boundary in order to solve this problem, for which there was previously no feasible solution. In order to maintain driving stability under complex conditions, a multi-objective optimization method, which can update the weight coefficient online, is proposed. In the numerical simulation, the values of velocity, relative distance, acceleration and acceleration change rate under different conditions are compared, and the results show that the proposed algorithm has better tracking and stability than the traditional algorithm. The effectiveness and reliability of the Fuzzy-MPC algorithm are verified by co-simulation with the designed PID lower layer control algorithm with front feedforward and feedback.

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Adaptive Cruise Control Strategy Design with Optimized Active Braking Control Algorithm

Cited by 13 publications

References 34 publications

A review on key challenges in intelligent vehicles: Safety and driver‐oriented features

A review on key challenges in intelligent vehicles: Safety and driver‐oriented features

Multidisciplinary Lightweight Optimization for Front Impact Structure of Body Frame Based on Active and Passive Safety

Research on Vehicle Adaptive Cruise Control Method Based on Fuzzy Model Predictive Control

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