INTELLIGENT VEHICLE DESIGN - 2022/3
Module code: ENGM298
In light of the Covid-19 pandemic the University has revised its courses to incorporate the ‘Hybrid Learning Experience’ in a departure from previous academic years and previously published information. The University has changed the delivery (and in some cases the content) of its programmes. Further information on the general principles of hybrid learning can be found at: Hybrid learning experience | University of Surrey.
We have updated key module information regarding the pattern of assessment and overall student workload to inform student module choices. We are currently working on bringing remaining published information up to date to reflect current practice during the academic year 2021/22.
This means that some information within the programme and module catalogue will be subject to change. Current students are invited to contact their Programme Leader or Academic Hive with any questions relating to the information available.
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).
Mechanical Engineering Sciences
FALLAH Saber (Mech Eng Sci)
Number of Credits: 15
ECTS Credits: 7.5
Framework: FHEQ Level 7
Module cap (Maximum number of students): N/A
Overall student workload
Independent Learning Hours: 106
Lecture Hours: 11
Laboratory Hours: 11
Captured Content: 22
Prerequisites / Co-requisites
Incoming exchange students please note: ENG2123 Control
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 type||Unit of assessment||Weighting|
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.
- 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
|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|
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.
Upon accessing the reading list, please search for the module using the module code: ENGM298
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.