Feedback systems: Input-output properties

Modern society faces serious problems with transportation systems, including but not limited to traffic congestion, safety, and pollution. Information communication technologies have gained increasing attention and importance in modern transportation systems. Automotive manufacturers are developing in-vehicle sensors and their applications in different areas including safety, traffic management, and infotainment. Government institutions are implementing roadside infrastructures such as cameras and sensors to collect data about environmental and traffic conditions. By seamlessly integrating vehicles and sensing devices, their sensing and communication capabilities can be leveraged to achieve smart and intelligent transportation systems. We discuss how sensor technology can be integrated with the transportation infrastructure to achieve a sustainable Intelligent Transportation System (ITS) and how safety, traffic control and infotainment applications can benefit from multiple sensors deployed in different elements of an ITS. Finally, we discuss some of the challenges that need to be addressed to enable a fully operational and cooperative ITS environment.

Sensor Technologies for Intelligent Transportation Systems.

Control strategies for crane systems: A comprehensive review

With the emergence of in-vehicle applications, providing the required computational capabilities is becoming a crucial problem. This paper proposes a framework named autonomous vehicular edge (AVE) for edge computing on the road, with the aim of increasing the computational capabilities of vehicles in a decentralized manner. By managing the idle computational resources on vehicles and using them efficiently, the proposed AVE framework can provide computation services in dynamic vehicular environments without requiring particular infrastructures to be deployed. Specifically, this paper introduces a workflow to support the autonomous organization of vehicular edges. Efficient job caching is proposed to better schedule jobs based on the information collected on neighboring vehicles, including GPS information. A scheduling algorithm based on ant colony optimization is designed to solve this job assignment problem. Extensive simulations are conducted, and the simulation results demonstrate the superiority of this approach over competing schemes in typical urban and highway scenarios.

AVE: Autonomous Vehicular Edge Computing Framework with ACO-Based Scheduling

Structural dynamics: VonGyörgy Vértes. Amsterdam: Elsevier Science Publishers 1985. 320 S., US $72.25

In this paper, synchronization of fuzzy modeling chaotic time delay memristor-based Chua’s circuits is presented. Based on T–S fuzzy models, not only fuzzy model of the time delay memristor-based Chua’ circuit is constructed but the fuzzy control vector can also be derived to synchronize two different time delay memristor-based Chua’s circuits. Due to the dynamical behavior with complex transient transitions of the memristor-based chaotic system which is heavily dependent on the initial state of the memristor except for the circuit parameters, the memristor-based chaotic system can generate more complex and unpredictable time domain signals. An application to chaos secure communication is used to demonstrate the effectiveness of the proposed chaotic synchronization scheme.

Synchronization of Fuzzy Modeling Chaotic Time Delay Memristor-Based Chua’s Circuits with Application to Secure Communication

A surrounding bird view image generation method for use in an automobile-side device of an articulated vehicle is provided. The articulated vehicle includes a first body part, a second body part and a connection part. The proceeding directions of the first and the second body parts form an angle. The image processing method includes the steps of: storing an angle-to-surrounding-image model table; detecting an angle and providing an angle measurement; accessing the angle-to-surrounding-image model table to obtain a selected angle and a selected surrounding image model corresponding to the angle measurement; capturing 6 adjacent images corresponding to the surrounding of the vehicle body by the image capturers disposed on the 6 surrounding sides of the articulated vehicle; obtaining a practical operating surrounding image by processing the first to the sixth images with the selected surrounding image model.

Surrounding bird view monitoring image generation method and training method, automobile-side device, and training device thereof

A dynamic fusion method of images includes: receiving broadcast information from surrounding vehicles of a host vehicle; determining whether at least one of the surrounding vehicles travels in the same lane as the host vehicle to become a neighboring vehicle of the host vehicle according to the broadcast information; determining whether the neighboring vehicle is too close to the host vehicle and blocks the view of the host vehicle; and performing a transparentization or translucentization process on the neighboring vehicle in an image captured by the host vehicle when the neighboring vehicle blocks the view of the host vehicle.

Dymanic fusion method and device of images

This paper deals with vibration control for a light rail vehicle's pantographs. The concepts of force cancellation, skyhook damper, and contact wire-following spring are jointly applied to constitute an effective controller for vibration suppression. Performance of the control system is evaluated on the basis of variations of displacement and acceleration between the pantograph and contact wire. An active control law is developed by means of a linear quadratic regulator design to derive a stabilizing control law for the pantograph system with the time-varying contact force between the pantograph shoe and catenary. A systematic optimization process with Pareto set and variable weights for the design of active suspension parameters of the pantograph using a constrained multiobjective evolutionary algorithm is developed. Extensive simulations are well performed to verify our proposed design.

Robust Active Vibration Control for Rail Vehicle Pantograph

In this paper, an adaptive neuro-fuzzy predictor-based control (ANFPC) approach with integrated automotive radar and vehicle-to-vehicle (V2V) communication for the design of the cooperative adaptive cruise control (CACC) system is presented, which concerns not only the safety and riding comfort of a vehicle but also enhances its fuel efficiency. This paper consists of two main parts: preceding vehicle state estimation and following vehicle controller. First, the prospective information of the preceding vehicle, such as position, velocity, and acceleration, can be derived through radar sensor, and the control force of the preceding vehicle can be transmitted to the following vehicles through V2V communication. A Takagi–Sugeno fuzzy model is then utilized to estimate the preceding vehicle model, and the predicted state sequence of the preceding vehicle can be obtained. Second, based on these predicted data, the following vehicle is controlled by the proposed ANFPC scheme to maintain each vehicle within the desired distance headway and thus achieve string stability of vehicle platooning and fuel efficiency. The experimental results on the CarSim environment show that the proposed control strategy for the CACC system can significantly reduce the fuel consumption while ensuring driving comfort and safety.

Yu-Chen Lin

Papers

Synchronization of Fuzzy Modeling Chaotic Time Delay Memristor-Based Chua’s Circuits with Application to Secure Communication

Surrounding bird view monitoring image generation method and training method, automobile-side device, and training device thereof

Dymanic fusion method and device of images

Robust Active Vibration Control for Rail Vehicle Pantograph

Adaptive Neuro-Fuzzy Predictor-Based Control for Cooperative Adaptive Cruise Control System