Data driven extraction of challenging situations for autonomous vehicles
Autonomous vehicles or Self-Driven Vehicles (SDVs) are becoming increasingly common in Singapore and for a wide variety of applications – from first-and-last-mile commutes to logistics. The areas of deployment are similarly diverse, ranging from docks to housing estates and highways. This variance i...
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| Format: | Final Year Project |
| Language: | English |
| Published: |
2019
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| Online Access: | http://hdl.handle.net/10356/77665 |
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| Institution: | Nanyang Technological University |
| Language: | English |
| Summary: | Autonomous vehicles or Self-Driven Vehicles (SDVs) are becoming increasingly common in Singapore and for a wide variety of applications – from first-and-last-mile commutes to logistics. The areas of deployment are similarly diverse, ranging from docks to housing estates and highways. This variance in operating environments necessitates careful validation and analysis of SDVs in contextual situations before deployment. To support the Land Transport Authority's (LTA) development of test requirements and standards to deploy AVs in Singapore, NTU led the Centre of Excellence for Testing & Research of AVs – NTU (CETRAN). While CETRAN does not directly develop new technologies for AVs, it generates fundamental research on how these systems should operate, develop testing requirements, and establish an international standard for AVs |
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