Trainee Project
Autonomous and Connected Vehicle: Estimation of the Necessary Variables for Vehicle Tracking
2023/04/01 - 2023/09/30
Other supervisor(s):
Madjid HADDAD (
As part of the research activities of SEGULA Technologies and in collaboration with the COSsyNL team of the CRAN laboratory at the IUT of Longwy, state estimation algorithms for classes of nonlinear systems will be developed for vehicle models. autonomous and connected. One of the main challenges is to combine classical estimation algorithms with deep learning techniques to simultaneously identify some nonlinearities of the model and estimate the state variables.
The objective of this step is the development of new estimation schemes for autonomous vehicle tracking and the identification of the forces applied on the tires, generally dependent on several parameters which vary over time and which are difficult to identify. These estimation algorithms make it possible to deal with malicious attacks (cyber/computer, or physical), faults, and other internal or external disturbances. This stage will particularly focus on the problem of semi-autonomous Adaptive Cruise Control (ACC). Once the nonlinear model is established, we will work on more complex cases of ACC, namely the CACC for "Cooperative", etc.
The development of the stage is done according to the following process:
State of the art on autonomous and connected vehicles;
State of the art on estimation techniques;
Study of different adaptive cruise control (SA-ACC, CACC, etc) and formulation of new estimation issues;
Development of new estimation algorithms for these models/issues;
Validation of methods by simulation on Matlab/Simulink;
Validation of methods using CARSIM software dedicated to the vehicle;
In case of an autonomous vehicle purchase: Experimental implementation on a prototype of an autonomous vehicle.
Control Identification Diagnosis