DRF Lunchtime Clinic - Dr Tom Kelly, Dr Khashayar Kazemzadeh & Dr Lilia Potseluyko, University of Cambridge

We are delighted to have two talks this week from our colleagues on the Digital Roads and Future Roads programmes. 

Our first speaker will be Dr Tom Kelly, Senior Research Associate in Digital Twins from the Digital Roads Prosperity Partnership. 

Dr Kelly will be speaking on: Doing the DR:DT  

Abstract: The talk introduces the implementation of the Digital Roads: Digital Twin application. We will review the CAMHighways dataset and highlight the need for a database in addressing infrastructure challenges. Such databases, which support both reading and writing, are referred to as 'digital twins.' The presentation will provide an overview of the design and implementation of such a system, along with the technical solutions and tools used in its development. We will then do a deep dive into two example applications will be presented: visualizations of the entire A14 highway and a demonstration of an automated pruning pipeline.  

Our second talk will be delivered by Dr Khashayar Kazemzadeh, Marie Sklodowska Curie Fellow on the Future Roads programme and Dr Lilia Potseluyko, Costain Industry Research Fellow from the Digital Roads Prosperity Partnership. 

They will be speaking on: A Digital Twin Video Experiment to Assess Cyclist Experience 

Abstract: Cycling is an active mode of transport that alleviates issues associated with motorised vehicles, such as traffic congestion and environmental concerns while promoting a healthy lifestyle. However, cycling remains a small proportion of the overall mode share, particularly in the UK and the US. Enhancing cyclists' experience is key to promoting and prioritising cycling, yet research in this area is limited. In this study, we assess cyclists' experiences in both on-road facilities, where cyclists share infrastructure with motorised vehicles, and off-road facilities, which are dedicated to vulnerable road users. Specifically, we employ a digital twin model of a section of London to create various unique scenarios and evaluate how infrastructure modifications impact cyclist experience in both on- and off-road settings. Additionally, we model cyclist behaviour across different recorded infrastructure scenarios, identifying how distinct groups of cyclists prefer various infrastructure improvements. This research underscores the value of digital twin models in generating realistic scenarios to better understand cyclist behaviour and provides essential insights for planners and policymakers on prioritising cycling infrastructure enhancements.