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Control De Crucero Cooperativo Mediante Comunicaciones V2X Escuela Tecnica´ Superior de Ingenieros Informaticos´ Universidad Politecnica´ de Madrid Control de crucero cooperativo mediante comunicaciones V2X Trabajo Fin de Master´ Master´ Universitario en Inteligencia Artificial AUTOR: Aitor G´omez Torres DIRECTOR: Jos´e Eugenio Naranjo TUTOR: Javier de Lope Asia´ın 2018 i RESUMEN El objeto de este trabajo de fin de m´aster se enmarca en elambito ´ de los Siste- mas de Transporte Inteligente (ITS, Intelligent Transportation Systems), donde se intenta desarrollar e implantar una nueva tecnolog´ıa para la mejora de la seguridad y la eficacia en lo que respecta a la circulaci´on de veh´ıculos, especialmente aut´onomos. Actualmente empiezan a aparecer los primeros s´ıntomas de la ineficiencia de las v´ıas convencionales y de sus m´etodos de gesti´on. Una de las principales ra´ıces de este problema es que, aunque los veh´ıculos han avanzado mucho en cuanto a tecnolog´ıa y seguridad en losultimos ´ a˜nos, la infraestructura apenas ha cambiado en lasulti- ´ mas d´ecadas. Con la llegada de los veh´ıculos aut´onomos y de las tecnolog´ıas ITS se presenta la oportunidad de implantar tecnolog´ıas que permitan actualizar la infra- estructura provocando un m´ınimo impacto sobre ella y sobre los usuarios, abriendo la puerta a nuevos m´etodos de gesti´on que permitan solventar estos problemas. En concreto, dentro de los ITS, la gesti´on autom´atica de la velocidad es uno de los temas que ha experimentado un gran inter´es dadas sus m´ultiples aplicaciones en la actualidad en los sistemas de seguridad en la conducci´on. Por ello, este tra- bajo tiene como objetivo dise˜nar e implementar un modelo de sistema de Control de Crucero Cooperativo (CCC,Cooperative Cruise Control) queunicamente ´ utilice las comunicaciones, el GPS y el bus CAN del veh´ıculo como informaci´on. Para ello se han dise˜nado una serie de algoritmos y estrategias con el fin de poder afron- tar diversas situaciones de tr´afico de manera eficiente, bas´andose en la informaci´on transmitida desde un centro de control que gestiona la v´ıa. ii iii SUMMARY The purpose of this end-of-master project is within the scope of the Intelligent Transportation Systems (ITS), where an attempt is being made to develop and im- plement a new technology for the improvement of safety and efficiency with respect to the circulation of vehicles, especially autonomous. Currently, the first symptoms of the inefficiency of conventional roads and their management methods begin to appear. One of the main reasons for this problem is that, although vehicles have advanced a lot in terms of technology and safety in recent years, infrastructure has hardly changed in recent decades. With the arrival of autonomous vehicles and ITS technologies, the opportunity is presented to imple- ment technologies that allow the infrastructure to be updated, causing a minimum impact on it and on users, opening the door to new management methods to solve these problems. Specifically, within the ITS, the automatic control of speed is one of the issues that has experienced a great interest given its multiple applications today in the safety systems in driving. Therefore, this work aims to design and implement a Cooperative Cruise Control (CCC) model that uses only the communications, GPS and CAN bus of the vehicle as information. For this, a series of algorithms and strategies have been designed in order to be able to deal with various traffic situations efficiently, based on the information transmitted from a control centre that manages the route. iv ´Indice v ´Indice 1. Introducci´on................................ 1 1.1. AUTOCITS ................................ 2 1.2.INSIA................................... 3 1.3.Objetivos................................. 4 2. Estadodelarte.............................. 7 2.1. Veh´ıculo aut´onomo............................ 7 2.1.1. Circulaci´on............................ 16 2.1.2.DARPAchallanges........................ 16 2.1.3.DARPAGrandChallenge2004................. 17 2.1.4.DARPAGrandChallenge2005................. 17 2.1.5.DARPAUrbanChallenge2007................. 18 2.2.SistemasCooperativos.......................... 19 2.3.Sistemasdetransporteinteligentescooperativos............ 21 2.4. Sistemas avanzados de asistencia a la conducci´on........... 22 2.4.1.Controldecrucero........................ 23 3. Evaluaci´ondeRiesgos.......................... 25 4. Metodolog´ıa................................ 29 4.1.Esquemageneral............................. 29 4.2.Sensores.................................. 30 4.2.1.CAN................................ 30 4.2.2.GPS................................ 31 4.2.3. M´odulo V2X ........................... 32 4.3. Control longitudinal ........................... 33 4.4.Controldebajonivel........................... 35 4.5.Controldedecisiones........................... 35 4.6.RobotOperatingSystem......................... 36 5. Resultados................................. 39 5.1.Equipoyentorno............................. 39 5.2. Eventos de deceleraci´on.......................... 40 5.3.Eventosdeparada............................ 41 5.4. Eventos de deceleraci´onporcentual................... 41 6. Conclusiones................................ 45 7. L´ıneasfuturas............................... 47 vi ´Indice ´Indice de figuras vii ´Indice de figuras 1. Integrantes del proyecto. El proyecto, con n´umero de expediente 2015- EU-TM-0243-S, es cofinanciado por la Comisi´on Europea, bajo el programa CEF- TRANSPORT SECTOR, en la convocatoria 2015. 2 2. InstalacionesdelINSIA.......................... 4 3. Firebird de la compa˜niaGeneralMotors................ 8 4. Veh´ıculoALVdesarrolladoporDARPA................. 9 5. Veh´ıculoNavlab,delaUniversidadCarnegieMellon.......... 11 6. Veh´ıculoparkshuttle,enfuncionameientoenlosPisesBajos..... 12 7. Veh´ıculo Navia, de Induct Technology .................. 13 8. Veh´ıculo Navia, de Induct Technology .................. 15 9. Conjunto de sensores del sistema Autopilot de Tesla. ......... 16 10. Algunos de los veh´ıculos integrantes de la DARPA Challlege 2005 . 18 11. Algunos de los veh´ıculos integrantes de la DARPA Challlege 2007 . 19 12. Algunos ejemplos de m´odulos V2X. De izquierda a derecha: Cohda MK5 OBU, Cohda MK5 RSU y m´odulo propio desarrollado en el INSIA.................................... 21 13. Niveles de automatizaci´on definidos en la instrucci´on 15/V-113 por laDGT................................... 23 14. Diagrama DAFO para el escenario de reconstrucci´on de la infraes- tructura................................... 26 15. Diagrama DAFO para el escenario de no actuar frente al problema. 27 16. Diagrama DAFO para el escenario de incorporaci´on de sistemas V2X alainfraestructura............................. 28 17.Arquitecturageneraldelsistema..................... 29 18.Maletadecontroldesarrolladaenelcentro................ 30 19.ArquitecturadelaredCANjuntoconlastarjetasdecontrol...... 32 20. GPS y antena equipados en el veh´ıculo.................. 32 21. Modelo OSI del protocolo para las comunicaciones V2X. ....... 33 22. Esquema de funcionamiento del CACC. El centro de control(DGT) publica un evento de retenci´on en una determinada ´area geogr´afica (Zona amarilla), cuando un veh´ıculo se encuentra a la distancia de propagaci´on del mensaje recibe el mismo y ajusta la velocidad seg´un se indique en el evento. Una vez fuera del ´areadeleventoelveh´ıculo recuperasuvelocidadnormal....................... 34 23. Diagrama de funcionamiento de un controlador PID. Debemos ajustar los tres par´ametros hasta obtener el comportamiento deseado. .... 36 24. Diagrama de flujo del proceso de decisi´on al aplicar la consigna de velocidad.................................. 37 25. Zona de realizaci´on de los ensayos, situada en el carril BUS-VAO de la A6. Los m´odulos verdes representan los aportados por el INSIA. En rojo los m´odulos aportados por INDRA. .............. 39 26. Veh´ıculo i-MiEV utilizado durante los ensayos. ............. 40 viii ´Indice de figuras 27. Comportamiento de deceleraci´on. El veh´ıculo reduce correctamente la velocidad de unos 80 km/h a 30 km/h, recuperando la velocidad inicial al salir del evento. ........................ 41 28. Comportamiento de parada. El veh´ıculo reduce correctamente la ve- locidad de unos 60 km/h a 0 km/h, deteniendo totalmente el veh´ıculo. 42 29. Comportamiento de deceleraci´on. El veh´ıculo reduce correctamente la velocidad de unos 80 km/h a 30 km/h, recuperando la velocidad inicial al salir del evento. ........................ 42 ´Indice de cuadros ix ´Indice de cuadros 1. ResultadosdelaDARPAChallenguede2005............. 17 2. ResuladosdelaDARPAChallenguede2007.............. 19 1 1. Introducci´on Desde la aparici´on de la automoci´on, esta ha ido evolucionado tanto en la mejora de los veh´ıculos como en la circulaci´on con los mismos y la mejora de la infraestruc- tura. Gracias a estas mejoras y a la formaci´on y concienciaci´on de los conductores se ha conseguido reducir en gran medida el numero de accidentes y de fallecidos en las carreteras. Podemos observar esta tendencia mirando el reporte de accidentes del a˜no 2016 [de Tr´afico, 2017](Ultimo´ disponible) y compar´andolo con su homologo del a˜nos 2006 [de Tr´afico, 2007]. Tras una d´ecada observamos que el n´umero de v´ıctimas mortales en accidentes ha descendido desde las 3119 victimas de 2006 hasta las 1663 de 2016. Tambi´en podemos observar c´omo, aunque se reduzca el n´umero de victimas el n´umero de accidentes permanece pr´acticamente igual, esto debido principalmente al aumento de veh´ıculos en circulaci´on,
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