Postgraduate DiplomaAutonomous, ADAS & Software-Defined Vehicle Applications open

Postgraduate Diploma in Trajectory Planning (Sampling/Graph/Optimization)

Online 800-hour Postgraduate Diploma in Trajectory Planning (Sampling/Graph/Optimization). 8 modules covering ISO 26262:2018, ISO 21448:2022 (SOTIF) and OMPL. Assigned tutor and open enrolment.

Duration800 h
ModeOnline
LanguageEnglish
Start datesSet by the faculty
AwardSEIUM Institute diploma

Postgraduate Diploma in Trajectory Planning (Sampling/Graph/Optimization) — studying from New Zealand

Autonomy and advanced driver assistance work in New Zealand is mostly applied rather than manufacturing-led, with significant interest in autonomous systems for agriculture, forestry, mining and port logistics. Research groups at the University of Auckland and the University of Canterbury contribute to robotics, perception and control, and firms in these regions develop software for driverless and remote-operated machinery. Engineers in this area often collaborate with government transport agencies on the regulatory frameworks that will govern automated vehicles on public roads.

Fees for New Zealand: NZ$2,550 (New Zealand dollar), with instalments and employer sponsorship available.

Relevant bodies in New Zealand

  • New Zealand Transport Agency Waka Kotahi
  • Ministry of Transport
  • Engineering New Zealand

Typical roles

  • ADAS Software Engineer
  • Autonomy Systems Engineer
  • Perception Engineer
  • Embedded Automotive Software Engineer

Questions from New Zealand

Which New Zealand bodies oversee autonomous and ADAS vehicle work, and how is engineering registration handled?

Engineering registration in New Zealand is handled by Engineering New Zealand, which offers Chartered Professional Engineer status. Land transport rules, including those affecting vehicle technology, are administered by NZ Transport Agency Waka Kotahi. SEIUM is a private institute and its qualifications are not state degrees or accredited by a national body, so recognition is ultimately a matter for employers or the relevant body.

Who employs autonomous vehicle and ADAS engineers in New Zealand?

Demand comes mainly from vehicle importers and fleet operators exploring driver assistance, software suppliers, research organisations and firms developing mobility or automation systems. Employers typically look for software, sensing and systems skills backed by project evidence. A private online qualification may help show your learning, but it does not guarantee a role or any particular salary.

Is this programme workable online from New Zealand with a full-time job?

Yes. The programmes are 100% online and taught in English, so you can study from New Zealand without needing a student visa. You will have an assigned technical tutor and complete a final project. Specialist courses run 300 hours, diplomas 800 hours and master's programmes 1,900 hours. Fees can be paid in instalments, and your employer may be willing to sponsor you.

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Learning outcomes

What you will be able to do

01

Formulate the trajectory planning problem in driving.

02

Apply graph-based planning algorithms.

03

Implement sampling-based planners.

04

Solve planning as an optimisation problem.

05

Plan in dynamic environments with interaction.

06

Compare hybrid and learning-based planners.

07

Validate planners through scenarios and simulation.

Profile

Who it's for

  • Motion planning engineer who wants to specialise in Trajectory Planning (Sampling/Graph/Optimization).
  • Robotics engineer who wants to specialise in Trajectory Planning (Sampling/Graph/Optimization).
  • Autonomous driving software engineer who wants to specialise in Trajectory Planning (Sampling/Graph/Optimization).
  • Optimisation researcher who wants to specialise in Trajectory Planning (Sampling/Graph/Optimization).
  • Simulation engineer who wants to specialise in Trajectory Planning (Sampling/Graph/Optimization).
  • Validation engineer who wants to specialise in Trajectory Planning (Sampling/Graph/Optimization).
  • Engineering or science graduates looking to enter the automotive sector.
Standards & tools

What you'll work with

  • ISO 26262:2018
  • ISO 21448:2022 (SOTIF)
  • ISO 34502:2022
  • ASAM OpenSCENARIO 1.2
  • IEEE 2846-2022
  • UN Regulation No. 157
  • ISO 22737:2021
Syllabus

8 modules · 800 h

  1. 1.1Route, behaviour and motion
  2. 1.2Configuration and state spaces
  3. 1.3Kinematic and dynamic constraints
  4. 1.4Frenet frame
  5. 1.5Safety, comfort and progress costs
  6. 1.6Obstacle representation
  7. 1.7Real-time requirements
  8. 1.8Planning benchmarks
  9. 1.9Completeness and optimality of algorithms
  10. 1.10Case study: overtaking manoeuvre
  1. 2.1State grids and lattices
  2. 2.2Dijkstra and A* algorithms
  3. 2.3Hybrid A* for parking
  4. 2.4Admissible heuristics
  5. 2.5D* Lite and replanning
  6. 2.6Motion primitives
  7. 2.7Lane graphs
  8. 2.8Complexity and scalability
  9. 2.9Reeds-Shepp and Dubins curves
  10. 2.10Laboratory: Hybrid A* in Python
  1. 3.1Probabilistic Roadmaps
  2. 3.2RRT and RRT*
  3. 3.3Kinodynamic variants
  4. 3.4Sampling in the Frenet frame
  5. 3.5Informed and biased sampling
  6. 3.6Asymptotic optimality
  7. 3.7Comparison with graph methods
  8. 3.8Unstructured environments
  9. 3.9Efficient collision checking
  10. 3.10Laboratory: RRT* with OMPL
  1. 4.1Optimal control as a formulation
  2. 4.2Sequential quadratic programming
  3. 4.3Spline smoothing
  4. 4.4Collision constraints
  5. 4.5CHOMP and TrajOpt
  6. 4.6Planning with iLQR
  7. 4.7OSQP, IPOPT and acados solvers
  8. 4.8Convexification of free space
  9. 4.9Initialisation with graph solutions
  10. 4.10Practice: trajectory optimisation with CasADi
  1. 5.1Moving obstacles and prediction
  2. 5.2Spatio-temporal planning
  3. 5.3Speed profile with ST-graph
  4. 5.4Robust planning under uncertainty
  5. 5.5Interaction-aware planning
  6. 5.6Safety margins
  7. 5.7Responsibility-Sensitive Safety
  8. 5.8Temporal consistency when replanning
  9. 5.9Contingency planning
  10. 5.10Laboratory: ST planner in CommonRoad
  1. 6.1Sampling combined with optimisation
  2. 6.2Apollo and Autoware architectures
  3. 6.3Imitation for planning
  4. 6.4Trajectory evaluation with networks
  5. 6.5End-to-end planners
  6. 6.6Guarantees for learned planners
  7. 6.7nuPlan as a benchmark
  8. 6.8GPU parallelism
  9. 6.9Rule-based planners as a reference
  10. 6.10Case study: comparison on nuPlan
  1. 7.1Safety and comfort metrics
  2. 7.2Scenarios with OpenSCENARIO
  3. 7.3Closed-loop simulation
  4. 7.4Regression testing
  5. 7.5Formal verification of trajectories
  6. 7.6Compliance with traffic rules
  7. 7.7Functional safety requirements
  8. 7.8Vehicle testing
  9. 7.9Generation of critical scenarios
  10. 7.10Workshop: scenario battery for a planner
  1. 8.1Scenario and ODD
  2. 8.2Chosen planning approach
  3. 8.3Planner implementation
  4. 8.4Cost function and tuning
  5. 8.5Integration with prediction
  6. 8.6Simulation evaluation
  7. 8.7Comparison with another approach
  8. 8.8Analysis of limitations
  9. 8.9Report and presentation
  10. 8.10Final review with the tutor
Methodology, software & labs

How you'll learn

100% online training on the SEIUM campus, with downloadable material, recorded classes and an assigned technical tutor. No fixed timetables: students progress at their own pace within the intake, which makes it possible to combine study with work.

Each module combines theory, guided reading of the original standard and applied exercises. The working software is OMPL, CasADi, CommonRoad, Autoware, nuPlan devkit, in free, academic or evaluation versions. Tests are studied using real implementation procedures for Hybrid A* parking, trajectory optimisation on motorways and closed-loop evaluation of planners. Assessment is continuous across each module, plus the final integrating project.

Hands-on practical workwith industry-standard software, simulation, real case studies and guided practical exercises.
Evidence-oriented final project:safety case, test plan, compliance dossier and operational limits.
Industry Mentored:faculty with professional experience in the field and in real industry projects.
Flexible modality(100% online), international cohorts and support from SEIUM Career Services.
Ethics and safety:a safety-by-design approach, cybersecurity and regulatory compliance as pillars.
Capstone project

Build it end to end

Your final project follows the real engineering workflow, step by step, reviewed by your tutor.

Scenario and ODD

Formulate the trajectory planning problem in driving.

Chosen planning approach

Apply graph-based planning algorithms.

Planner implementation

Implement sampling-based planners.

Cost function and tuning

Solve planning as an optimisation problem.

Integration with prediction

Plan in dynamic environments with interaction.

Career opportunities

Where this takes you

Motion planning engineerRobotics engineerAutonomous driving software engineerOptimisation researcherSimulation engineerValidation engineer
Admissions & scholarships

Requirements

  • Prior technical training or professional experience in the sector. A university degree is not required.
  • Internet connection and a computer capable of running the programme's software.
  • Sufficient English to follow technical regulatory reading.

Ready to start?

Send your application today. Our admissions team replies within 72 hours with your study plan and funding options.

FAQ

Frequently asked questions

The programme comprises 800 total hours spread over 6 to 8 months. That is between 10 and 15 hours per week on average, compatible with a full-time job.

You will work with OMPL, CasADi, CommonRoad, Autoware and nuPlan devkit. Free, academic or evaluation versions are used, and the tutor indicates the free alternative where one exists.

An own diploma from SEIUM Institute upon passing the continuous assessment and the integrating project. It is in-house training, not an official Ministry qualification.

Yes. Modules passed in a course or postgraduate diploma in the same area are credited towards the advanced programme. Check the credit transfer policy when you enrol.

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