Surrey University Stag

INTELLIGENT VEHICLE DESIGN - 2022/3

Module code: ENGM298

Module Overview

An introduction to the technology and concepts which support the design of intelligent vehicles. The module includes three phases: i) Introduction to intelligent vehicles technologies and their subsystems (e.g., sensors, perception, localisation, motion planning, etc); ii) concepts for the modelling of intelligent vehicles and prediction of their behaviour (kinematic, dynamic, etc.) and iii) design of intelligent vehicle's control systems (behavioural planning, motion planning and trajectory tracking).

Module provider

Mechanical Engineering Sciences

Module Leader

FALLAH Saber (Mech Eng Sci)

Number of Credits: 15

ECTS Credits: 7.5

Framework: FHEQ Level 7

JACs code:

Module cap (Maximum number of students): N/A

Overall student workload

Independent Learning Hours: 106

Lecture Hours: 11

Laboratory Hours: 11

Captured Content: 22

Module Availability

Semester 2

Prerequisites / Co-requisites

Incoming exchange students please note: ENG2123 Control

Module content

Indicative content includes: Introduction to intelligent vehicles and their benefits, Introduction to perception systems, Introduction to positioning systems, Introduction to motion planning and control systems, Introduction to intelligent vehicle sensors and sensor fusion,  principles of modelling vehicle system, the principle of prediction for intelligent vehicles, the principle of behavioral planning, the principle of trajectory planning, the principle of  motion planning

Assessment pattern

Assessment type Unit of assessment Weighting
Coursework Coursework 100

Alternative Assessment

N/A

Assessment Strategy

The assessment strategy is designed to provide students with the opportunity to demonstrate an understanding of principles, methodologies, mathematical modelling, and control design in the final assessment (coursework). The project coursework allows students to model intelligent vehicles, to design their control and prediction systems and to analyse behaviour of intelligent vehicles. Thus, the summative assessment for this module consists of one coursework [ Learning outcomes 1, 2, 3, 4, 5]. Formative assessment and feedback:  formative verbal feedback is given in tutorials and lectures, written feedback is given on the coursework assessments including detailed comments on the coursework report. 

Module aims

  • Provide a general understanding of the concept of intelligent vehicles and their functionalities
  • Introduce the fundamental design of intelligent vehicles and develop skills to explain and critically evaluate and appropriately interpret their behavior.
  • Acquire first-hand skills in modelling and control of intelligent vehicles through the problem-based learning approach

Learning outcomes

Attributes Developed
Ref
001 Demonstrate a comprehensive understanding of principles and concepts relating to intelligent vehicles K M3
002 Identify and analyse the performance requirements of intelligent vehicle subsystems C M13
003 Recognise the need for models of intelligent vehicles in order to analyse their behaviour C M2
004 Apply mathematical and scientific models to control problems of intelligent vehicles CP M1
005 Undertake a brief research topic and model an intelligent vehicle system to analyse and evaluate its performance P M3

Attributes Developed

C - Cognitive/analytical

K - Subject knowledge

T - Transferable skills

P - Professional/Practical skills

Methods of Teaching / Learning

The learning and teaching strategy are designed to: introduce fundamentals of intelligent vehicles design through theory with theoretical and practical examples. This is delivered principally through lectures and tutorial classes. It concludes with two independently conducted projects involving theoretical and practical procedures. The learning and teaching methods include pre-recorded lectures, captured contents, Q&A sessions, and tutorials (in groups).

Indicated Lecture Hours (which may also include seminars, tutorials, workshops and other contact time) are approximate and may include in-class tests where one or more of these are an assessment on the module. In-class tests are scheduled/organised separately to taught content and will be published on to student personal timetables, where they apply to taken modules, as soon as they are finalised by central administration. This will usually be after the initial publication of the teaching timetable for the relevant semester.

Reading list

https://readinglists.surrey.ac.uk
Upon accessing the reading list, please search for the module using the module code: ENGM298

Other information

n/a

Programmes this module appears in

Programme Semester Classification Qualifying conditions
Mechanical Engineering MEng 2 Optional A weighted aggregate mark of 50% is required to pass the module
Automotive Engineering MEng 2 Optional A weighted aggregate mark of 50% is required to pass the module

Please note that the information detailed within this record is accurate at the time of publishing and may be subject to change. This record contains information for the most up to date version of the programme / module for the 2022/3 academic year.