2026-04-13T04:08:40Zhttps://recercat.cat/oai/request

oai:recercat.cat:2117/4422802025-09-24T13:25:03Zcom_2072_1033col_2072_452951

00925njm 22002777a 4500 dc Ramos Porras, Marina author 2025-07-17 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. Outgoing http://hdl.handle.net/2117/442280 Àrees temàtiques de la UPC::Informàtica Automobiles--Speed--Automatic control ADAS, ACC, PCC, V2X, SPaT, MATLAB, Simulink, RoadRunner, scenario Automòbils--Velocitat--Control automàtic Development of a Predictive Cruise Control to enhance the Adaptive Cruise Control using environmental information