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Analysis and Synthesis of Coordinated Control Systems for Automated Road Vehicles

A special issue of Energies (ISSN 1996-1073). This special issue belongs to the section "E: Electric Vehicles".

Deadline for manuscript submissions: closed (30 April 2022) | Viewed by 11469

Special Issue Editor


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Guest Editor
Institute for Computer Science and Control, 1111 Budapest, Hungary
Interests: automated and autonomous vehicle control systems; energy-optimal control of road vehicles; coordination of vehicle control systems
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Through the automation of road vehicles, several smart actuators have been developed with which various automated and autonomous functionalities can be performed. For example, the manoeuvring of a vehicle can be achieved through automated steering, torque vectoring, differential braking, and variable-geometry suspension. Despite the similarities in the functionalities, the operation capability and the cost aspects of each intervention can be different.

The goal of the Special Issue is to propose analysis and synthesis methods, with which safe and energy-optimal coordination strategies of automated vehicle control systems can be achieved. It poses various control-theoretical challenges, e.g., the handling of nonlinearities, the formulation of uncertainties, and the assessment of performance issues in automated systems. Nevertheless, the conventional reconfigurable, robust parameter-varying, and nonlinear methods provide a starting-point for finding solutions for the recent problems. Moreover, through the novel data-driven and learning-based approaches, promising results in the field of automated vehicle control have been achieved.

The coordination of vehicle control systems is incorporated in a high-level context, which goes beyond the problem of coordination at a vehicle level. The developed vehicle control solutions must guarantee its cooperation with human intervention, i.e., during the operation of partially automated systems, the intention and intervention capabilities of the driver must be considered. Furthermore, the integration of automated vehicles in an intelligent transportation system provides novel performance requirements at a vehicle level. Thus, the coordination of the vehicle control systems must be carried out so as to simultaneously improve the performances at a local and global level. The goal of the Special Issue is to provide new approaches in coordination considering the high-level context.

Dr. Balázs Németh
Guest Editor

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Keywords

  • analysis of vehicle control interventions
  • performance issues in the design of coordination strategies
  • coordination for achieving fault-tolerant vehicle operation
  • actuator reconfiguration strategies for automated vehicles
  • nonlinear and learning-based methods for coordinated control design
  • coordination of human interventions and automated control
  • integration of vehicle control and intelligent transportation systems

Published Papers (6 papers)

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Editorial

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2 pages, 153 KiB  
Editorial
Analysis and Synthesis of Coordinated Control Systems for Automated Road Vehicles
by Balázs Németh
Energies 2022, 15(20), 7674; https://0-doi-org.brum.beds.ac.uk/10.3390/en15207674 - 18 Oct 2022
Viewed by 684
Abstract
Through the automation of road vehicles, several smart actuators have been developed, with which various automated and autonomous functionalities can be performed [...] Full article

Research

Jump to: Editorial

17 pages, 1110 KiB  
Article
A Two-Stage Scheduling Model for the Tunnel Collapse under Construction: Rescue and Reconstruction
by Hongjun Cui, Lijun Liu, Ying Yang and Minqing Zhu
Energies 2022, 15(3), 743; https://0-doi-org.brum.beds.ac.uk/10.3390/en15030743 - 20 Jan 2022
Cited by 3 | Viewed by 1328
Abstract
In the process of transportation system construction, the tunnel is always an indispensable part of the traffic network due to terrain constraints. A collapse of the tunnel under construction may give rise to a potential for significant damage to the traffic network, complicating [...] Read more.
In the process of transportation system construction, the tunnel is always an indispensable part of the traffic network due to terrain constraints. A collapse of the tunnel under construction may give rise to a potential for significant damage to the traffic network, complicating the road conditions and straining relief services for construction workers. To cope with the variety of vehicle types during the rescue effort, this paper divides them into small, medium, and large sizes, herein correcting the corresponding speed considering six road condition factors on account of the previous research. Given the influence of different special road conditions on the speed of different sized vehicles, a multi-objective model which contains two stages is presented to make decisions for rescue vehicle scheduling. Under the priority of saving human life, the first-stage objective is minimizing the arrival time, while the objective of the second stage includes minimizing the arrival time, unmet demand level, and scheduling cost. To solve the currently proposed model, a non-dominated sorting genetic algorithm II (NSGA-II) with a real number coding method is developed. With a real tunnel example, the acceptability and improvement of the model are examined, and the algorithm’s optimization performance is verified. Moreover, the efficiency of applying real number coding to NSGA-II, the multi-objective gray wolf algorithm (MOGWO), and the traditional genetic algorithm (GA) is compared. The result shows that compared with the other two methods, the NSGA-II algorithm converges faster. Full article
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20 pages, 3354 KiB  
Article
Traffic and Energy Consumption Modelling of Electric Vehicles: Parameter Updating from Floating and Probe Vehicle Data
by Antonello Ignazio Croce, Giuseppe Musolino, Corrado Rindone and Antonino Vitetta
Energies 2022, 15(1), 82; https://0-doi-org.brum.beds.ac.uk/10.3390/en15010082 - 23 Dec 2021
Cited by 19 | Viewed by 2884
Abstract
This paper focuses on the estimation of energy consumption of Electric Vehicles (EVs) by means of models derived from traffic flow theory and vehicle locomotion laws. In particular, it proposes a bi-level procedure with the aim to calibrate (or update) the whole parameters [...] Read more.
This paper focuses on the estimation of energy consumption of Electric Vehicles (EVs) by means of models derived from traffic flow theory and vehicle locomotion laws. In particular, it proposes a bi-level procedure with the aim to calibrate (or update) the whole parameters of traffic flow models and energy consumption laws by means of Floating Car Data (FCD) and probe vehicle data. The reported models may be part of a procedure for designing and planning transport and energy systems. This aim is to verify if, and in what amount, the existing parameters of the resistances/energy consumptions model calibrated in the literature for Internal Combustion Engines Vehicles (ICEVs) change for EVs, considering the above circular dependency between supply, demand, and supply–demand interaction. The final results concern updated parameters to be used for eco-driving and eco-routing applications for design and a planning transport system adopting a multidisciplinary approach. The focus of this manuscript is on the transport area. Experimental data concern vehicular data extracted from traffic (floating car data and probe vehicle data) and energy consumption data measured for equipped EVs performing trips inside a sub-regional area, located in the Città Metropolitana of Reggio Calabria (Italy). The results of the calibration process are encouraging, as they allow for updating parameters related to energy consumption and energy recovered in terms of EVs obtained from data observed in real conditions. The latter term is relevant in EVs, particularly on urban routes where drivers experience unstable traffic conditions. Full article
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14 pages, 1276 KiB  
Article
Robust Control Design for Autonomous Vehicles Using Neural Network-Based Model-Matching Approach
by Dániel Fényes, Tamás Hegedus, Balázs Németh and Péter Gáspár
Energies 2021, 14(21), 7438; https://0-doi-org.brum.beds.ac.uk/10.3390/en14217438 - 08 Nov 2021
Cited by 5 | Viewed by 2038
Abstract
In this paper, a novel neural network-based robust control method is presented for a vehicle-oriented problem, in which the main goal is to ensure stable motion of the vehicle under critical circumstances. The proposed method can be divided into two main steps. In [...] Read more.
In this paper, a novel neural network-based robust control method is presented for a vehicle-oriented problem, in which the main goal is to ensure stable motion of the vehicle under critical circumstances. The proposed method can be divided into two main steps. In the first step, the model matching algorithm is proposed, which can adjust the nonlinear dynamics of the controlled system to a nominal, linear model. The aim of model matching is to eliminate the effects of the nonlinearities and uncertainties of the system to increase the performances of the closed-loop system. The model matching process results in an additional control input, which is computed by a neural network during the operation of the control system. Furthermore, in the second step, a robust H is designed, which has double purposes: to handle the fitting error of the neural network and ensure the accurate tracking of the reference signal. The operation and efficiency of the proposed control algorithm are investigated through a complex test scenario, which is performed in the high-fidelity vehicle dynamics simulation software, CarMaker. Full article
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15 pages, 6271 KiB  
Article
Vehicle Dynamic Control with 4WS, ESC and TVD under Constraint on Front Slip Angles
by Jaewon Nah and Seongjin Yim
Energies 2021, 14(19), 6306; https://0-doi-org.brum.beds.ac.uk/10.3390/en14196306 - 02 Oct 2021
Cited by 5 | Viewed by 2170
Abstract
To enhance vehicle maneuverability and stability, a controller with 4-wheel steering (4WS), electronic stability control (ESC) and a torque vectoring device (TVD) under constraint on the front slip angles is designed in this research. In the controller, the control allocation method is adopted [...] Read more.
To enhance vehicle maneuverability and stability, a controller with 4-wheel steering (4WS), electronic stability control (ESC) and a torque vectoring device (TVD) under constraint on the front slip angles is designed in this research. In the controller, the control allocation method is adopted to generate yaw moment via 4WS, ESC and TVD. If the front steering angle is added for generating yaw moment, the steering performance of the vehicle can be further deteriorated. This is because the magnitude of the lateral tire forces are limited and the required yaw moment is insufficient. Constraint is imposed on the magnitude of the front slip angles in order to prevent the lateral tire forces from saturating. The driving simulation is performed by considering the limit of the front slip angle proposed in this study. Compared to the case that uses the existing 4WS, the results of this study are derived from the actuator combination that enhances performance while maintaining stability. Full article
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17 pages, 1505 KiB  
Article
Coordination of Lateral Vehicle Control Systems Using Learning-Based Strategies
by Balázs Németh
Energies 2021, 14(5), 1291; https://0-doi-org.brum.beds.ac.uk/10.3390/en14051291 - 26 Feb 2021
Cited by 7 | Viewed by 1407
Abstract
The paper proposes a novel learning-based coordination strategy for lateral control systems of automated vehicles. The motivation of the research is to improve the performance level of the coordinated system compared to the conventional model-based reconfigurable solutions. During vehicle maneuvers, the coordinated control [...] Read more.
The paper proposes a novel learning-based coordination strategy for lateral control systems of automated vehicles. The motivation of the research is to improve the performance level of the coordinated system compared to the conventional model-based reconfigurable solutions. During vehicle maneuvers, the coordinated control system provides torque vectoring and front-wheel steering angle in order to guarantee the various lateral dynamical performances. The performance specifications are guaranteed on two levels, i.e., primary performances are guaranteed by Linear Parameter Varying (LPV) controllers, while secondary performances (e.g., economy and comfort) are maintained by a reinforcement-learning-based (RL) controller. The coordination of the control systems is carried out by a supervisor. The effectiveness of the proposed coordinated control system is illustrated through high velocity vehicle maneuvers. Full article
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