AI for Mass Model Automation
Lead Participant:
CITY SCIENCE CORPORATION LIMITED
Abstract
**BUSINESS CHALLENGE:**
Detailed transport models are critical for supporting infrastructure investment and increasingly to help local authorities understand their actions to decarbonise transport. However, transport models are expensive and time consuming to build. Production inefficiency places a sizeable constraint on progress, hindering organisations that wish to test new interventions/infrastructure or monitor their effects.
**PROJECT GOAL:**
Our vision is to use AI to address current manual approaches and develop an end-to-end pipeline for full model automation. We aim to develop a system that delivers a first-of-its-kind, and meets relevant industry benchmarks essential to achieving industry acceptance. We will work closely with users throughout the project to ensure AI is used to address clear user needs.
Detailed transport models are critical for supporting infrastructure investment and increasingly to help local authorities understand their actions to decarbonise transport. However, transport models are expensive and time consuming to build. Production inefficiency places a sizeable constraint on progress, hindering organisations that wish to test new interventions/infrastructure or monitor their effects.
**PROJECT GOAL:**
Our vision is to use AI to address current manual approaches and develop an end-to-end pipeline for full model automation. We aim to develop a system that delivers a first-of-its-kind, and meets relevant industry benchmarks essential to achieving industry acceptance. We will work closely with users throughout the project to ensure AI is used to address clear user needs.
Lead Participant | Project Cost | Grant Offer |
|---|---|---|
| CITY SCIENCE CORPORATION LIMITED | £41,639 | £ 41,639 |
Participant |
||
| SUSTAINICITY LTD | £3,806 | £ 3,806 |
| UNIVERSITY OF EXETER | £3,772 | £ 3,772 |
People |
ORCID iD |
| Bethany Taylor (Project Manager) |