Adaptive Cruise Control for a SMART Car: A Comparison Benchmark for MPC-PWA Control Methods

Corona, Daniele; Schutter, Bart De

doi:10.1109/tcst.2007.908212

Cited by 136 publications

(48 citation statements)

References 24 publications

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“…, 6 in point to point secant approximation 1 . Additionally the function b(j, x 2 ) is approximated with its average values over all gears, thus the problem becomes linear as better detailed in [3].…”

Section: B Methods 2: Basic Gain Scheduling Approximation (Bgs)mentioning

confidence: 99%

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Comparison of a linear and a hybrid adaptive cruise controller for a SMART

Corona

Schutter

2007

2007 46th IEEE Conference on Decision and Control

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Abstract-An adaptive cruise controller (ACC) is a device used in modern automotive applications that aims to achieve the tracking of a leading vehicle, allowing safety, comfort driving and overall improvement of traffic streams. Through appropriate modeling and design it permits also to address other tasks such as energy saving, environmental protection and reduction of the mechanical stress. For a type of small car, a SMART, we propose the design of an ACC using control methods based on tuned proportional-integral (PI) action and on model predictive control (MPC), developed for linear and piecewise affine (PWA) systems. We implement these controllers and compare the main properties and strong/weak points of each method, collecting the comparison keys in a table. The trade-off between complexity and accuracy of the solutions is also discussed.

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Section: B Methods 2: Basic Gain Scheduling Approximation (Bgs)mentioning

confidence: 99%

“…The purpose of this paper is to present some of the results we have obtained within a wide comparison study [3] of possible control methods for an ACC of a 6 gears, 37 kW gasoline SMART. This study considers the ACC design as a benchmark problem for existing MPC-PWA methods.…”

Section: Introductionmentioning

confidence: 99%

Comparison of a linear and a hybrid adaptive cruise controller for a SMART

Corona

Schutter

2007

2007 46th IEEE Conference on Decision and Control

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“…A benchmark setup is proposed in (Corona and Schutter, 2008) to assess different model predictive control methods used for ACC. An overview on constraint MPC can be found in (Maciejowski, 2002); for a comprehensive survey on MPC with constraints, the reader is referred to (Mayne et al, 2000).…”

Section: Related Workmentioning

confidence: 99%

“…Finally, we compare our method with a state-of-the-art ACC approach applied in the automotive industry (Corona and Schutter, 2008;Yanakiev and Kanellakopoulos, 1998), which utilizes proportionalintegral control (PI). Here, we use an implementation based on (Yanakiev and Kanellakopoulos, 1998), where the desired inter-vehicle distance is a function of a constant spacing, a constant time headway, and the velocity of the leading vehicle.…”

Section: Numerical Experimentsmentioning

confidence: 99%

Adaptive Cruise Control with Safety Guarantees for Autonomous Vehicles

Magdici

Althoff

2017

IFAC-PapersOnLine

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This paper addresses the problem of following a vehicle with varying acceleration in a comfortable and safe manner. Our architecture consists of a nominal controller (here: model predictive control) and a safety controller. Although model predictive control attempts to keep a safe distance, it cannot formally guarantee it, due to the assumptions on the behavior of the leading vehicle. We address this problem by holding a formally verified safety controller available. Our novel mechanism gradually engages the safety maneuver since most critical situations resolve quickly. The overall approach is evaluated against real traffic data. The results show good position and velocity tracking performance, while safety and comfort are guaranteed.

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“…ACCS is used to provide safety, traffic fluency and also reduces fuel consumption [2,3]. Moreover, cruise control system helps in avoiding collisions between vehicles, better traffic management, reducing travel time and lower consumption of fuel by maintaining desired speed [4,5].…”

Section: Introductionmentioning

confidence: 99%

Performance Evaluation of PID Controller for an Automobile Cruise Control System using Ant Lion Optimizer

Pradhan¹,

Majhi²,

Pradhan³

et al. 2017

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Abstract. This paper considers the design and performance evaluation of PID controller for an automobile cruise control system (ACCS). A linearized model of the cruise control system has been studied as per the dominant characteristics in closed loop system. The design problem is recast into an optimization problem which is solved using Ant Lion Optimization (ALO). The transient performance of proposed ACCS i.e., settling time, rise time, maximum overshot, peak time and steady state error are investigated by step input response and root locus analysis. To show the efficacy of the proposed algorithm over a state space method, classical PID, fuzzy logic, genetic algorithm, a comparison study is presented by using MATLAB/SIMULINK. Furthermore, the robustness of the system is evaluated by using bode analysis, sensitivity, complimentary sensitivity and controller sensitivity. The results indicate that the designed ALO based PID controller for ACCS achieves better performance than other recent methods reported in the literature.

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Adaptive Cruise Control for a SMART Car: A Comparison Benchmark for MPC-PWA Control Methods

Cited by 136 publications

References 24 publications

Comparison of a linear and a hybrid adaptive cruise controller for a SMART

Comparison of a linear and a hybrid adaptive cruise controller for a SMART

Adaptive Cruise Control with Safety Guarantees for Autonomous Vehicles

Performance Evaluation of PID Controller for an Automobile Cruise Control System using Ant Lion Optimizer

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