Valente, Antonio Saverio (2015) Cooperative Driving in Inter-Vehicular Communication Network. [Tesi di dottorato]

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Item Type: Tesi di dottorato
Lingua: English
Title: Cooperative Driving in Inter-Vehicular Communication Network
Creators:
CreatorsEmail
Valente, Antonio Saverioantoniosaverio.valente@unina.it
Date: 30 March 2015
Number of Pages: 136
Institution: Università degli Studi di Napoli Federico II
Department: Ingegneria Elettrica e delle Tecnologie dell'Informazione
Scuola di dottorato: Ingegneria dell'informazione
Dottorato: Ingegneria informatica ed automatica
Ciclo di dottorato: 27
Coordinatore del Corso di dottorato:
nomeemail
Garofalo, Francescofrancesco.garofalo@unina.it
Tutor:
nomeemail
Santini, StefaniaUNSPECIFIED
Palladino, AngeloUNSPECIFIED
Date: 30 March 2015
Number of Pages: 136
Uncontrolled Keywords: Cooperative Driving, Synchronization, Consensus, HIL, VANET, Plexe Simulator, OBU, Inter Vehicular Communication, WAVE, IEEE 802.11p
Settori scientifico-disciplinari del MIUR: Area 09 - Ingegneria industriale e dell'informazione > ING-INF/04 - Automatica
Aree tematiche (7° programma Quadro): TECNOLOGIE DELL'INFORMAZIONE E DELLA COMUNICAZIONE > Macchine "più intelligenti", servizi migliori
TECNOLOGIE DELL'INFORMAZIONE E DELLA COMUNICAZIONE > Trasporti, telecomunicazioni, attrezzature mediche, etc. Tecnologie della fotonica, plastiche elettroniche, display flessibili e micro e nano sistemi
TECNOLOGIE DELL'INFORMAZIONE E DELLA COMUNICAZIONE > Ambiente, energia e trasporti
Date Deposited: 26 Apr 2015 16:44
Last Modified: 25 Sep 2015 09:42
URI: http://www.fedoa.unina.it/id/eprint/10316
DOI: 10.6092/UNINA/FEDOA/10316

Abstract

Design, synthesis and validation of cooperative driving algorithm are the main actor of our treatment. Owing to the ever-increasing traffic demand, modern societies, with well-planned road management systems, and sufficient infrastructures for transportation, still face problems like traffic congestion and pollution. Intelligent transportation system supporting the driver during driving task are called ADA systems or ADAS. ADAS promise to increase the driver's safety and comfort with positive impact on traffic flow performance, emissions and fuel consumption. Examples of ADAS system are various forms of cruise control, lane keeping systems and collision warning systems. Recently the development of new communication protocols for vehicular environment based on WAVE/IEEE 802.11p standard has pushed industry and researchers toward the development of the concept of Cooperative Driving and Cooperative Adaptive Cruise Control systems. Cooperative driving control systems exploit the wireless communication as an additional sensor both to perceive the presence of neighbouring vehicles and to communicate their own presence and in-vehicle data. One of the most envisioned applications in cooperative driving systems is certainly platooning. Platooning concept can be defined as a collection of vehicles that travel together, actively coordinated in formation. Some expected advantages of platooning include increased fuel and traffic efficiency, safety and driver comfort. All vehicles within the platoon communicate with each other and exchange information in order to reach a common target. Here we aim to represent the platooning as a complex network, in which nodes represent the vehicles belonging to platoon and links model the existence/absence of communication among vehicles. In particular, we model platooning not only as a complex network, but as a delayed complex network. First we present how a group of interconnected vehicles can be modelled as a complex networks and then we treat the platooning problem first as an high-order consensus problem and then as synchronization problem. The consensus goal is to regulate speed and relative position of each vehicle to that of the respective predecessor and of the leading vehicle. The idea is to analytically solve problem by designing a distributed control action depending on information received from the neighbouring vehicles (within the transmission range). The control approach is able to counteract the presence of different time-varying delays introduced by the wireless vehicular communications, take into account the drivetrain dynamics and the heterogeneity of the platoon. First of all we give sufficient and necessary condition on the control gain that guarantee both exponential and global asymptotic stability. The stability of the proposed control strategy, has been shown by exploiting the Lyapunov-Krasovkii theorem for retarded functional differential equations, according a delay dependent approach. The stability conditions gives as additional result, an upper bound estimation of the maximum allowable communication delay that guarantee stability. Then we solve the platooning problem as a synchronization problem. Our target is to synchronize the dynamics of all agent of the platoon to the leader dynamics. The problem essentially consists in leader tracking manoeuvres. The synchronization goal is achieved here by using an appropriate adaptive distributed strategy, depending from local state variables as well as from the information received by the neighbouring vehicles. The control approach counteract the presence of different time-varying delays introduced by the wireless vehicular communications, and is robust to parameter variations. Also in this case we prove the stability of the proposed control strategy exploiting the Lyapunov-Krasovkii theorem. Since in a real environment there is the unavoidable presence of time-delays, it is crucial, before the experimental validation of cooperative driving algorithms, of proper simulation tool taking into account of vehicular and control dynamics, not neglecting traffic patterns and the characteristics of the communication channel. These tools, known as VANET simulators, requires two types of simulation components: i) Network and ii) Mobility that in general are separate. Within a collaboration with the University of Trento, I have contributed to the development of Plexe, a VANET simulator, that is the evolution of the well known Veins framework. In particular we have contributed to the formulation of a vehicle model to embed into Plexe framework, that takes into account of transmission ratio and power of vehicles. All the proposed control strategy have been intensively validated and simulated with Plexe simulator, both with the vehicle model and with default mobility model already present in Plexe. The thesis is organized as follows. In Chap. 1 we give first an overview on the Cooperative Driving systems. After an introduction about them, we focus on the main application considered during the dissertation: i) Probe Vehicles, ii) Automated Fleets and Cooperative Driving. Then we will give an overview on communication paradigms and enabling technologies in support of cooperative driving systems. In Chap. 2 we focus on Plexe, an open source and free to download VANET simulator allowing the simulation, validation and analysis of cooperative driving control strategy in mixed traffic scenario. After a brief description of Plexe, we will illustrate the major enhancement and contributions given during this PhD work to develop a new vehicle dynamical model. We remark that these contributes have been embedded into Plexe as part of a collaboration with the DISI - University of Trento. In Chap. 3 first we present how a group of interconnected vehicles can be modelled as a complex networks and then we treat the platooning problem first as an high-order consensus problem and then as synchronization problem. The consensus goal is to regulate speed and relative position of each vehicle to that of the respective predecessor and of the leading vehicle. The idea is to analytically solve problem by designing a proper local action depending on the vehicle state variables and a cooperative action depending on information received from the neighbouring vehicles (e.g., within the transmission range). The control approach counteract the presence of different time-varying delays introduced by the wireless vehicular communications. We prove the stability of the proposed control strategy exploiting the Lyapunov-Krasovkii theorem and finally we will show the results obtained by exploiting Plexe simulator. Then we treat the platooning problem as a synchronization problem. Our target is to synchronize the dynamics of all agent of the platoon to the leader dynamics. The problem essentially consists in leader tracking manoeuvres. The synchronization goal is achieved here by using an appropriate adaptive distributed strategy, depending from local state variables as well as from the information received by the neighbouring vehicles. The control approach counteract the presence of different time-varying delays introduced by the wireless vehicular communications. We prove the stability of the proposed control strategy exploiting the Lyapunov-Krasovkii theorem and finally we will show the results obtained using Plexe simulator. In Chap. 4 are resumed the company duties. We will present in particular the design and implementation of an On Board Unit, for collection and transmission of in-vehicle data to neighbourhood vehicle in an ITS scenario. To this purpose, a proper DSRC communication system has been designed and implemented. To validate the effectiveness of the designed On Board Unit a proper Hardware In the Loop platform has been developed to test the effectiveness of the control and communication strategy. Finally, in Appendix A we present the maths instrument employed for our analysis: first we focus on the theorems used to show the stability of time delay systems; in second instance we present some theorems about the stability analysis of time-varying systems; finally we present some useful lemmas used in this thesis.

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