Simulating the Resilience of Transport Infrastructures Using QUANT

Lead Research Organisation: UNIVERSITY COLLEGE LONDON
Department Name: Centre for Advanced Spatial Analysis

Abstract

We have developed a model that simulates the pattern of land use and transportation for Great Britain which is configured in terms of thousands of small zones and three modes of transport which bind together employment at place of work and population at place of residence. The model is called QUANT and it runs in a web-based environment. It is optimised to run very rapidly and deliver results to the user in a matter of minutes so that users can derive and test future scenarios for land use and transport, on-the-fly so-to-speak. Our preliminary explorations of the model using the DAFNI model platform suggest that we can adapt part of the model to this platform and this project presents a proof of concept that this is possible and useful. We will adapt the 'what-if' scenario capability of QUANT to the platform so that users can run thousands of scenarios whose data can be used to train various optimisation models that show how future plans for the location of land uses and transport can be massively improved. The model predicts the impacts of such scenarios and we will fashion various user environments around the use of DAFNI that enable stakeholders to test various plans and to demonstrate how AI techniques can be used to inform the generation of many scenarios. We will demonstrate how models such as these can be used effectively to generate the impacts of shocks to the land use transport system such as those posed by new infrastructure projects such as HS2 which are continually being evolved. The fact that our model deals with different transport networks for Great Britain enables us to trace the repercussions of land use and transport change across networks that are composed of thousands of nodes and links which is key to assessing the repercussions of major changes on the UK's urban system.

Publications

10 25 50
 
Title Exhaustive set of 5KM single link road, bus and rail scenarios for UK from QUANT model 
Description We run every possible scenario for road, bus and rail for the UK with a single link less than 5KM. This results in approximately 175,000 scenarios for each of the three modes. This data is useful in showing where most impact from building scenarios in the UK is located and is useful for building automated planning tools for urban planners. 
Type Of Material Database/Collection of data 
Year Produced 2024 
Provided To Others? Yes  
Impact It has been used to create visualisations of the urban planning landscape of the UK which have gone into a number of presentations and meetings. 
URL https://github.com/maptube/PyQUANT-Jupyter
 
Title Random set of 2 link 5+5KM scenarios for road, bus and rail for the UK from running the QUANT model 
Description This dataset contains 2 link random (non-exhaustive) scenarios where each of the two links is less than 5KM. This is done for the road, bus and rail modes by running the QUANT model on the computer generated random scenario. 
Type Of Material Database/Collection of data 
Year Produced 2024 
Provided To Others? Yes  
Impact The results from this are going into a forthcoming paper showing the additive nature of links for the bus and rail modes which is an important property for building up larger scenarios from smaller building blocks, breaking the computational dependency on having to run the whole scenario as an integrated whole. This enables greater computational efficiency and searching of pre-created scenario data to enable optimisation where it required a full model run before. 
URL https://github.com/maptube/PyQUANT-Jupyter
 
Title PyQUANT3 (DAFNI) 
Description This is a spatial interaction model (gravity model) of England, Scotland and Wales at MSOA (and Intermediate zone) level based on the QUANT model (http://quant.casa.ucl.ac.uk). It is designed to run from the command line locally, or as part of a workflow on the DAFNI system using Docker. 
Type Of Technology Webtool/Application 
Year Produced 2024 
Open Source License? Yes  
Impact The software was used to produce 1,000,000 road, bus and rail scenarios for the UK to aid urban modellers in producing higher impact scenarios. 
URL https://github.com/maptube/PyQUANT-Jupyter
 
Description Lancaster University Keynote on City Modelling at Workshop 
Form Of Engagement Activity Participation in an activity, workshop or similar
Part Of Official Scheme? No
Geographic Reach Regional
Primary Audience Other audiences
Results and Impact Keynote presentation and subsequent 2 day workshop on modelling opportunities using new and emerging forms of data.
Year(s) Of Engagement Activity 2024
 
Description Meeting with UK2070 Commission about East West Corridor 
Form Of Engagement Activity A talk or presentation
Part Of Official Scheme? No
Geographic Reach Local
Primary Audience Policymakers/politicians
Results and Impact It was a morning discussion with members from the UK2070 Commission and Royal School of Arts (RSA) about using the QUANT modelling to run some simulations of scenarios proposed by the UK2070 Commission. This was an opportunity for a discussion about the sort of modelling we can do and about whether houses create jobs, or jobs are needed before houses, relating to the Government's plan to build housing to generate growth.
Year(s) Of Engagement Activity 2024
 
Description QUANT Demo to Visitors from Beijing 
Form Of Engagement Activity A talk or presentation
Part Of Official Scheme? No
Geographic Reach International
Primary Audience Policymakers/politicians
Results and Impact We did a morning presentation to a delegation from Beijing about how we're using QUANT in the urban planning process
Year(s) Of Engagement Activity 2024
 
Description Visit by Korean Delegation 
Form Of Engagement Activity A talk or presentation
Part Of Official Scheme? No
Geographic Reach International
Primary Audience Professional Practitioners
Results and Impact Presentation of QUANT work to a delegation of urban planners and academics from Korea, followed by a half day discussion of practices.
Year(s) Of Engagement Activity 2024