Development of a Predictive Cruise Control to enhance the Adaptive Cruise Control using environmental information

In the context of Advanced Driving Assist Systems (ADAS), Adaptive Cruise Control (ACC) is essential for adaptation to real traffic, but does not consider road driving conditions such as signaling. The development of a Predictive Cruise Control (PCC) in MATLAB/Simulink is proposed to improve the per...

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Detalles Bibliográficos
Autor: Ramos Porras, Marina
Tipo de recurso: tesis de maestría
Fecha de publicación:2025
País:España
Institución:Universitat Politècnica de Catalunya (UPC)
Repositorio:UPCommons. Portal del coneixement obert de la UPC
Idioma:inglés
OAI Identifier:oai:upcommons.upc.edu:2117/442280
Acceso en línea:https://hdl.handle.net/2117/442280
Access Level:acceso abierto
Palabra clave:Automobiles--Speed--Automatic control
ADAS, ACC, PCC, V2X, SPaT, MATLAB, Simulink, RoadRunner, scenario
Automòbils--Velocitat--Control automàtic
Àrees temàtiques de la UPC::Informàtica
Descripción
Sumario:In the context of Advanced Driving Assist Systems (ADAS), Adaptive Cruise Control (ACC) is essential for adaptation to real traffic, but does not consider road driving conditions such as signaling. The development of a Predictive Cruise Control (PCC) in MATLAB/Simulink is proposed to improve the performance of an existing ACC, designed to follow the speed of a vehicle in front, in road situations that include speed limit signs and traffic lights. The surrounding information has been defined to come from static maps and V2X (vehicle-to-everything) communication using SPaT (Signal Phase and Timing) message, and the way to simulate these data has been studied. The algorithm for determining the optimal speed trajectory to be performed according to the environmental information is based on the compliance with the road regulation, efficiency of motion profile and safety, and has been tested on 3D virtual simulations from RoadRunner. To validate the PCC functionality, five different scenarios have been created, the last one belonging to an ongoing project for development of technologies for smart cities. The results demonstrate that the speed of the vehicle that integrates the PCC behaves according to the road speed constraints, and that the speed trajectory when approaching the intersection with a traffic light is decided depending on the current and future light state, optimizing driving.