Units / CIV4802
CIV4802 · Smart urban mobility and digital twins
2026 Handbook6 credit pointsLevel 4Department of Civil and Environmental Engineering
Last checked: 23 Aug 2026 UTCOverview
This unit is designed to provide a deep understanding of urban mobility, fundamental principles and challenges, including sustainable mobility, intelligent transportation systems (ITS), and data-driven approaches. You will gain a comprehensive understanding of the concept of digital twins, their architecture, and the various data sources contributing to their creation and operation. The course emphasises practical implementation to design, develop, validate and optimise practical mobility solutions using digital twins to address specific urban mobility challenges like traffic congestion, energy efficiency, and accessibility.
Areas of study: Minor: Future mobility systems
Offerings
| Campus | Teaching period | Mode |
|---|---|---|
| Malaysia | Second semester | Teaching activities are on-campus (ON-CAMPUS) |
Assessment
The Handbook does not list a final examination among the assessment items. That is not a guarantee there is none.
| # | Assessment | Type | Weight | Hurdle |
|---|---|---|---|---|
| 1 | Case studies and proposals | Written | 30% | — |
| 2 | Quiz / Test | Quiz / Test | 30% | — |
| 3 | Project | Project | 40% | — |
Continuous assessment: 60% Final assessment: 40%
Assessment details may change. Please refer to the assessment information in Moodle closer to the start of the teaching period.
Requisites
prerequisite
- ENG2005 — Advanced engineering mathematics
Learning outcomes
- Analyse mobility problems to determine how smart mobility technologies and digital twins can provide effective solutions.
- Apply and assess smart mobility solutions and digital twin models using relevant modelling software.
- Evaluate the effectiveness of mobility solutions generated from digital twin models and recommend improvements.
- Integrate and appraise findings from smart mobility and digital twin applications to provide evidence-based recommendations for decision-making.
Workload
The minimum total expected workload to achieve the learning outcomes for this unit is 144 hours per semester typically comprising a mixture of 3-6 hours of scheduled learning activities and 6-9 hours of independent study per week. Scheduled activities may include a combination of teacher-directed learning, peer-directed learning and online engagement. Independent study may include associated readings, assessment and preparation for scheduled activities.
| Activity | Duration |
|---|---|
| Laboratories | 24 hours |
| Workshops | 24 hours |
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