Flocking-based optimized control of cooperative automated vehicles
Financed by The Executive Agency for Higher Education, Research, Development and Innovation Funding (UEFISCDI), project number PNCDI PN-III-P1-1.1-TE, Human Resources Programme, Research projects for independent young research teams, Period: 01.2021-12.2022
[Română]
Cercetarea privind soluțiile de conducere conectate și extrem de automatizate pentru drumuri mai sigure are o relevanță strategică majoră pentru industria europeană, aceasta fiind una dintre prioritățile exprimate în mod clar în domeniul de focus „Digitalizarea și transformarea industriei și serviciilor europene” din Programul-cadru Orizont 2020. Pentru a optimiza fluxul de trafic, a crește siguranța și a reduce consumul de combustibil, vehiculele automate ar putea fi controlat ținând cont de vecinii lor prin decizii de cooperare utilizînd tehnologii de conectivitate. Scopul principal al acestui proiect a fost de a dezvolta un cadru general care să creeze capacitatea vehiculelor automate conectate de a-și coordona comportamentul de conducere prin utilizarea tehnicilor de optimizare bazate pe grupuri. Cadrul a inclus inteligența internă a vehiculului (legată de percepția mediului și capacitățile de conducere autonomă) și comunicarea fără fir (conectivitate) cu alte vehicule, precum și cu infrastructura inteligentă chiar din faza de proiectare a algoritmilor de control distribuit bazat pe grupuri pentru a optimiza fluxul de trafic, pentru a îmbunătăți siguranța, pentru a reduce consumul de combustibil, pentru a crește capacitatea drumurilor și pentru a reduce emisiile. Perspectiva interdisciplinară adoptată de acest studiu a urmărit să contribuie la dezvoltarea de noi cadre de modelare și strategii de control foarte avansate bazate pe optimizarea grupurilor în zone de aplicare care sunt caracterizate de medii de cooperare distribuite.
Îndeplinirea scopului principal enunțat pentru proiect s-a bazat pe un set de obiective specifice care vizează rezolvarea problemelor apărute în gruparea vehiculelor:
Riscul de accidente și poluarea sporită pe drumurile existente sunt probleme globale care depășesc granițele europene. Din punct de vedere științific, prin acest proiect, echipa de cercetare a dezvoltat algoritmi de control distribuit pentru grupurile cooperante de vehicule automatizate, care asigură performanțe mai bune pentru acestea. Impactul social este obținut prin obținerea unor drumuri mai sigure, cu un risc mai mic de accidente și stres și disconfort redus pentru șofer și pasageri. Din punct de vedere al mediului, algoritmii dezvoltați în cadrul acestui proiect pot contribui la reducerea CO2: vehiculele vor consuma mai puțin combustibil datorită rezistenței reduse la aer (impact economic). Mai mult, eficiența vehiculelor și capacitatea autostrăzilor și drumurilor urbane vor fi crescute.
Cel mai semnificativ rezultat obținut este dezvoltarea unor noi strategii de control cooperativ pentru vehiculele conectate cu scopul de a-și coordona comportamentul de conducere prin utilizarea tehnicilor de optimizare bazate pe grupuri, testarea făcându-se pe un pluton de vehicule la scară.
The research on connected and highly automated driving solutions for safer roads has major strategic relevance for the European industry, this being one of the priorities expressed clearly in the focus area on “Digitising and transforming European industry and services” in the Horizon 2020 Framework Programme. To optimize the traffic flow, increase safety and reduce fuel consumption the pace of automated vehicles could be controlled w.r.t. their neighbors through cooperative decisions by using connectivity technologies (vehicle flocking). The main goal of this project is to develop a general framework that creates the ability of connected automated vehicles to coordinate their driving behavior by using flocking-based optimization techniques. The framework will include internal vehicle intelligence (related to environment perception and self-driving capabilities) and wireless communication (connectivity) with other vehicles as well as with the smart infrastructure even from the design phase of the flocking-based distributed control algorithm to optimize/smoothen the traffic flow, to improve safety, to reduce fuel consumption, to increase road capacity and to decrease the emissions. The interdisciplinary perspective adopted by this study is aimed at contributing to the development of new modeling frameworks and highly advanced control strategies based on flocking optimization in application areas that are characterized by distributed cooperative environments.
The fulfillment of the main goal stated for the project relies on a set of specific objectives that aim at solving the problems arising in vehicle flocking:
Task 1.1. Select the most recent models for cooperative automated vehicles and develop a new distributed model that emphasizes the dynamical couplings between the vehicles
Task 1.2. Model the network-induced imperfections caused by the V2X communication technologies
Task 1.3. Develop a new realistic distributed model for cooperative automated vehicles which emphasizes the couplings between the vehicles and the wireless communication constraints
Task 1.4. Analyze the full model for control purposes
Deliverable 1: a report with the description of the imperfections model and dynamical couplings
Deliverable 2: a report with the description of the full model
Milestone 1: network-induced imperfections and dynamical couplings models
Milestone 2: full model for control purposes
Task 2.1. Develop flocking-based distributed control strategies relying on the realistic distributed model developed in WP1, Task 1.1
Task 2.2. Develop Matlab-SUMO emulator for automated vehicle groups
Task 2.3. Verify the string stability of the flocking-based automated vehicle group
Task 2.4. Analyze the flocking-based distributed control strategy
Deliverable 3: a report with the description of the flocking-based distributed control strategy
Deliverable 4: Matlab-SUMO emulator for automated vehicle groups
Deliverable 5: string stability analysis of the automated vehicle groups
Milestone 3: availability of the Matlab-SUMO emulator for automated vehicle groups
Task 3.1. Develop flocking-based distributed control strategies relying on the realistic distributed model developed in WP1, Task 1.3
Task 3.2. Develop Matlab-SUMO emulator for cooperative automated vehicle groups
Task 3.3. Verify the string stability of the flocking-based cooperative automated vehicle group
Task 3.4. Analyze the flocking-based cooperative distributed control strategy
Deliverable 6: a report with the description of the flocking-based cooperative distributed control strategy
Deliverable 7; Matlab-SUMO emulator for cooperative automated vehicle groups
Deliverable 8: string stability analysis of the cooperative automated vehicle groups
Milestone 4: availability of the Matlab-SUMO emulator for cooperative automated vehicle groups
Task 4.1. Development of real-time software for implementing the designed flocking-based distributed control algorithms on embedded systems
Task 4.2. Test the developed distributed control strategies on a lab-scale automated vehicle group
Task 4.3. Performance analysis of the real-time flocking-based distributed control algorithms
Task 4.4. Comparison of the developed control algorithms with state-of-art vehicle group controllers
Deliverable 9: a report with the description of the real-time software
Deliverable 10: a report with the description of the real-time lab-scale environment and the experimental results with performance analysis and comparisons
Milestone 5: availability of the real-time distributed controller for cooperative automated vehicle groups
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