Coordinated Throttle and Brake Control for Adaptive Cruise Control Strategy Design

Luu, Duc Lich; Lupu, Ciprian; Alshareefi, Hamid; Pham, Huu Truyen

doi:10.1109/cscs52396.2021.00009

Cited by 4 publications

(1 citation statement)

References 23 publications

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“…These two control factors can play a vital role in longitudinal dynamics vehicle to reduce and increase the required meters between two automobiles. The smooth control coordination between brake and accelerator or throttle has been realized in the studies [11,12]. In this literature, the braking system mathematically simplified to be first order plant.…”

Section: Introductionmentioning

confidence: 99%

Adaptive Cruise Control of A Simscape Driveline Vehicle Model Using Fuzzy Logic Controller

Mahmood,

Almaged,

Alnema

et al. 2023

JESA

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This paper shows the modelling and implementation of an adaptive cruise control (ACC) system for intelligent vehicles using fuzzy logic control approach. Initially, MATLAB Simulink is utilized to design an advanced vehicle model that takes into account most of the vehicle parameters using Simscape Driveline toolkit. Then, the fuzzy logic toolbox in MATLAB Simulink is introduced for designing and simulation of the fuzzy logic system. The proposed ACC algorithm functions in two different modes, the distance and velocity modes, based on the speed of the moving vehicle and the vehicle ahead. In distance control mode, the vehicle measures the actual distance to the vehicle ahead and compares it to the safe distance. If the measured distance is larger than the safe distance, the setpoint will be the safe distance and the system will work on maintaining the actual distance equal or greater than the safe distance. However, in speed control mode, the controller will operate according to the set speed adjusted by the driver given that the safe distance condition is met. This gives the vehicle the ability to make decisions relaying on both the set speed by the driver and the actual distance to the upfront objects. It is worth to mention that only a single controller is employed for both modes. According to MATLAB simulations, it is proven that the designed ACC algorithm using fuzzy logic controller is capable of retaining the vehicle in desired constraints as well as achieving satisfactory results owing to the simplicity of the proposed approach. The findings further demonstrate that the system have actually no overshoot with absolutely null steady state error while responding to the given speed with quite swift rising and settling times. However, there happen to be some rapid fluctuations in the throttle and brake values especially when the actual distance suddenly drops below the desired safe distance which may cause some driving inconvenience to the passengers.

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Section: Introductionmentioning

confidence: 99%

Adaptive Cruise Control of A Simscape Driveline Vehicle Model Using Fuzzy Logic Controller

Mahmood,

Almaged,

Alnema

et al. 2023

JESA

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Distributed MPC of vehicle platoons with guaranteed consensus and string stability

Feng

Chen

et al. 2023

Sci Rep

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Control of vehicle platoon can effectively reduce the traffic accidents caused by fatigue driving and misoperation, reduce air resistance by eliminating the inter-vehicle gap which will effectively reduce fuel consumption and exhaust emissions. A hierarchical control scheme for vehicle platoons is proposed in this paper. Considering safety, consistency, and passengers’ comfort, a synchronous distributed model predictive controller is designed as an upper-level controller, in which a constraint guaranteeing string stability is introduced into the involved local optimization problem so as to guarantee that the inter-vehicle gap error gradually attenuates as it propagates downstream. A terminal equality constraint is added to guarantee asymptotic consensus of vehicle platoons. By constructing the vehicle inverse longitudinal dynamics model, a lower-level control scheme with feedforward and feedback controllers is designed to adjust the throttle angle and brake pressure of vehicles. A PID is used as the feedback controller to eliminate the influence of unmodeled dynamics and uncertainties. Finally, the performance of longitudinal tracking with the proposed control scheme is validated by joint simulations with PreScan, CarSim, and Simulink.

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A Testing and Verification Approach to Tune Control Parameters of Cooperative Driving Automation Under False Data Injection Attacks

Holland,

Javidi-Niroumand,

Alnaser

et al. 2024

IEEE Access

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Control systems are used in safety-critical applications where tuning the system parameters is required to ensure safe and secure operation. The process of tuning these parameters can be arduous, timeconsuming, and unreliable as they are dependent on the operating environment. In this paper, we discuss a testing and verification approach for tuning the control parameters of a secure cooperative adaptive cruise controller (CACC) while simultaneously testing the safety of the algorithm under false data injection (FDI) attacks. In our approach, we use particle swarm optimization (PSO) to tune the parameters of the controller and observer. The performance of the controller will be evaluated before and after the optimization of control and detection parameters. After employing several swarms, it was noticed that the global optimal solution is reached within 74 iterations, on average. In summary, the configurations found by each swarm ensured that a safe following distance was achieved throughout testing. In terms of FDI estimation, however, the more conservative configuration with the minimum optimal parameter values performed the best.

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Coordinated Throttle and Brake Control for Adaptive Cruise Control Strategy Design

Cited by 4 publications

References 23 publications

Adaptive Cruise Control of A Simscape Driveline Vehicle Model Using Fuzzy Logic Controller

Adaptive Cruise Control of A Simscape Driveline Vehicle Model Using Fuzzy Logic Controller

Distributed MPC of vehicle platoons with guaranteed consensus and string stability

A Testing and Verification Approach to Tune Control Parameters of Cooperative Driving Automation Under False Data Injection Attacks

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