Intelligent vehicle systems

ID: 0713
Course type: scientific and vocational
Course coordinator: Aleksendrić S. Dragan
Lecturers: Aleksendrić S. Dragan
Contact: Aleksendrić S. Dragan
Level of studies: M.Sc. (graduate) Academic Studies – Mechanical Engineering
ECTS: 6
Final exam type: written
Department: Department of Motor Vehicles

Lectures

Goal

The goal of intelligent vehicles and accordingly intelligent vehicle systems is to augment vehicle autonomous driving either entirely or partly for the purposes of providing self driving abilities on different levels as well as safety, comfortability, and energy saving. The main goal of the subject is developemt student's capabilities for solving complex problems related to intelligent vehicles due to dynamic change of complex environment perception and necessity for sensing, modeling and prediction of different influencing factors on the vehicle performance. Autonomous intelligent vehicles have to perceiving and modeling environment in order to control the vehicle. The vehicle motion control faces the challenges of strong nonlinear characteristics due to high mass, especially in the processes of high speed and sudden steering/braking. It needs processing, modelling and prediction non-linear changes in the vehicle system operation based on large amounts of data from multi-sensors and complex dynamic changes in an environment. Course objective is to provide an understanding the design and development process of intelligent vehicle systems and to develop students’ skills and knowledge in the area of intelligent vehicle systems development.

Outcome

Course outcomes are development of student’s abilities to: a) understand requirements being imposed to intelligent vehicle and its systems, assemblies, sub – assemblies, and parts, b) analyze the vehicle system operation and understand influences of the new intelligent solutions in the vehicle systems design on the vehicle overall performance and quality of use c) application of artificial intelligence techniques in development of intelligent solutions of the vehicle systems, d) analyze, understand and reconcile the new intelligent solutions in the vehicle system operation with legislation related to the specific vehicle systems and sub systems.

Theoretical teaching

Theoretical lectures are divided into 7 sections: 1) Introduction – Intelligent vehicles and intelligent transport. 2) Monitoring and modeling of tire –road interaction. 3) Intelligent vehicle longitudinal control. 4) Intelligent vehicle lateral control. 5) Intelligent vehicle vertical control. 6) Intelligent vehicle vision systems. 7) Integrated intelligent control.

Practical teaching

Students carry out a group-engineering project. Project is related to introduction of intelligent solutions in the given vehicle system operation. Students have to: 1) critical analyze the design solutions of the given vehicle system. 2) identify possibilities for introduction of the system intelligent abilities. 3) model and predict the system performance based on artificial intelligence techniques 4) test the system intelligent solutions. 5) compare conventional and introduced intelligent system performance.

Attendance requirement

There is no precondition.

Resources

Аleksendrić D. Intelligent vehicle systems, (hand-out), 2022. (In Serbian). Aleksendrić D. Miljkovic Z. Artificial neural networks-solved examples with theoretical background, Faculty of Mechanical Engineering University of Belgrade, 2009. ISBN: 978-86-7083-961-8.

Assigned hours

Total assigned hours: 75

Active teaching (theoretical)

New material: 20
Elaboration and examples (recapitulation): 10

Active teaching (practical)

Auditory exercises: 10
Laboratory exercises: 0
Calculation tasks: 0
Seminar paper: 0
Project: 20
Consultations: 0
Discussion/workshop: 0
Research study work: 0

Knowledge test

Review and grading of calculation tasks: 0
Review and grading of lab reports: 0
Review and grading of seminar papers: 0
Review and grading of the project: 5
Test: 5
Test: 0
Final exam: 5

Knowledge test (100 points total)

Activity during lectures: 10
Test/test: 30
Laboratory practice: 0
Calculation tasks: 0
Seminar paper: 0
Project: 30
Final exam: 30
Requirement for taking the exam (required number of points): 30

Literature

H. Chneg: Autonomous intelligent vehicles - Theory, Algorithms, and Implementation , Springer 2011. ISBN 978-1-4471-2279-1; L. Li, F.-Y. Wang: Advanced Motion control and Sensing for Intelligent vehicles , Springer 2007. ISBN 978-1-4471-2279-1; R. Bishop: Intelligent vehicle technology and trends, © 2005 ARTECH HOUSE, INC. ISBN: 9781580539111