2026-04-17T01:19:40Zhttps://recercat.cat/oai/requestoai:recercat.cat:2117/4422802025-09-24T13:25:03Zcom_2072_1033col_2072_452951
Development of a Predictive Cruise Control to enhance the Adaptive Cruise Control using environmental information
Ramos Porras, Marina
Àrees temàtiques de la UPC::Informàtica
Automobiles--Speed--Automatic control
ADAS, ACC, PCC, V2X, SPaT, MATLAB, Simulink, RoadRunner, scenario
Automòbils--Velocitat--Control automàtic
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
2025-09-24T13:25:03Z
2025-09-24T13:25:03Z
2025-09-24T13:25:03Z
2025-07-17
Master thesis
http://hdl.handle.net/2117/442280
Open Access
Universitat Politècnica de Catalunya