This course introduces the concepts behind autonomous vehicle guidance and enables students to design and implement guidance strategies for vehicles incorporating planning, optimising and trajectory generation elements.

Teaching Sessions: 1 hour, twice per week

None

None

80% Examination

20% Coursework Assignment

This course aims to:

■ introduce students to the concepts behind autonomous vehicle guidance;

■ enable students to design and implement guidance strategies for vehicles incorporating planning, optimising and trajectory generation elements;

■ develop the theory behind trajectory optimisation;

■ introduce the use of graph theory for optimal path planning.

By the end of this course students will be able to:

■ develop path planning systems for autonomous vehicle guidance;

■ design and implement obstacle avoidance methods within an autonomous guidance regime;

■ implement trajectory optimisation and smoothing for both discrete and continuous paths.

Students must attend the degree examination and submit at least 75% by weight of the other components of the course's summative assessment.

Students must attend the timetabled laboratory classes.

Students should attend at least 75% of the timetabled classes of the course.

Note that these are minimum requirements: good students will achieve far higher participation/submission rates.  Any student who misses an assessment or a significant number of classes because of illness or other good cause should report this by completing a MyCampus absence report.