Who is More Likely (Not) to Make Home-Based Work Trips during the COVID-19 Pandemic? The Case of Scotland
Journal Article
Semple, T., Fountas, G., & Fonzone, A. (in press)
Who is More Likely (Not) to Make Home-Based Work Trips during the COVID-19 Pandemic? The Case of Scotland. Transportation research record, https://doi.org/10.1177/03611981221119192
In this study, we use survey data (n=6,000) to investigate the work trip patterns of Scottish residents at various points of the COVID-19 pandemic. We focus specifically on th...
The Impact Of COVID-19 On Future Public Transport Use In Scotland
Journal Article
Downey, L., Fonzone, A., Fountas, G., & Semple, T. (2022)
The Impact Of COVID-19 On Future Public Transport Use In Scotland. Transportation Research Part A: Policy and Practice, 163, 338-352. https://doi.org/10.1016/j.tra.2022.06.005
This paper examines the determinants of changes in future public transport use in Scotland after the COVID-19 pandemic. An online questionnaire was distributed to 994 Scottish...
DATASET: The impact of Covid-19 on travel behaviour, transport, lifestyles and residential location choices in Scotland
Dataset
Downey, L., Fonzone, A., & Fountas, G. (2022)
DATASET: The impact of Covid-19 on travel behaviour, transport, lifestyles and residential location choices in Scotland. [Dataset]. https://doi.org/10.17869/enu.2022.2853752
In response to the COVID-19 pandemic, Edinburgh Napier University’s Transport Research Institute has been undertaking a study, funded by the Scottish Funding Council (SFC), in...
Analysis of Pedestrian Accident Injury-Severities at Road Junctions and Crossings using an Advanced Random Parameter Modelling Framework: The Case of Scotland
Journal Article
Olowosegun, A., Babajide, N., Akintola, A., Fountas, G., & Fonzone, A. (2022)
Analysis of Pedestrian Accident Injury-Severities at Road Junctions and Crossings using an Advanced Random Parameter Modelling Framework: The Case of Scotland. Accident analysis and prevention, 169, Article 106610. https://doi.org/10.1016/j.aap.2022.106610
This paper investigates the determinants of injury severities in pedestrian-motor vehicle accidents at signalised and unsignalised junctions, and at physically-controlled and ...
Trips for Outdoor Exercise at Different Stages of the COVID-19 Pandemic in Scotland
Journal Article
Semple, T., Fountas, G., & Fonzone, A. (2021)
Trips for Outdoor Exercise at Different Stages of the COVID-19 Pandemic in Scotland . Journal of transport & health, 23, Article 101280. https://doi.org/10.1016/j.jth.2021.101280
Introduction
The COVID-19 pandemic has had exceptional effects on travel behaviour in the UK. This paper focuses specifically on the outdoor exercise trips of Scottish residen...
Access to Ubiquitous Real-Time Information by Bus Passengers in Urban Contexts
Conference Proceeding
Islam, M. F., Fonzone, A., & Fountas, G. (2021)
Access to Ubiquitous Real-Time Information by Bus Passengers in Urban Contexts. In 2021 7th International Conference on Models and Technologies for Intelligent Transportation Systems (MT-ITS). https://doi.org/10.1109/mt-its49943.2021.9529270
Due to higher smartphone uptake and Internet penetration rate, Ubiquitous Real-time Passenger Information (URTPI) has become available to and required by larger segments of th...
Addressing Unobserved Heterogeneity in the Analysis of Bicycle Crash Injuries in Scotland: A Correlated Random Parameters Ordered Probit Approach with Heterogeneity in Means
Journal Article
Fountas, G., Fonzone, A., Olowosegun, A., & McTigue, C. (2021)
Addressing Unobserved Heterogeneity in the Analysis of Bicycle Crash Injuries in Scotland: A Correlated Random Parameters Ordered Probit Approach with Heterogeneity in Means. Analytic Methods in Accident Research, 32, https://doi.org/10.1016/j.amar.2021.100181
This paper investigates the determinants of injury severities in single-bicycle and bicycle-motor vehicle crashes by estimating correlated random parameter ordered probit mode...
Multi-stage deep learning approaches to predict boarding behaviour of bus passengers
Journal Article
Tang, T., Fonzone, A., Liu, R., & Choudhury, C. (2021)
Multi-stage deep learning approaches to predict boarding behaviour of bus passengers. Sustainable Cities and Society, 73, https://doi.org/10.1016/j.scs.2021.103111
Smart card data has emerged in recent years and provide a comprehensive, and cheap source of information for planning and managing public transport systems. This paper present...
Impact of COVID-19 on travel behaviour, transport, lifestyles and residential location choices in Scotland
Report
Downey, L., Fonzone, A., Fountas, G., & Semple, T. Impact of COVID-19 on travel behaviour, transport, lifestyles and residential location choices in Scotland. Scottish Funding Council)
Downey, L., Fonzone, A., Fountas, G., & Semple, T. Impact of COVID-19 on travel behaviour, transport, lifestyles and residential location choices in Scotland. Scottish Funding Council
COVID-19 was declared a pandemic by the World Health Organisation (WHO) on 21st March 2020 and on 24th March 2020, the UK and Scottish Governments imposed a ‘lockdown’, restri...
Bus passenger path choices after consulting ubiquitous real-time information
Journal Article
Islam, F., & Fonzone, A. (2021)
Bus passenger path choices after consulting ubiquitous real-time information. Travel Behaviour and Society, 23, 226-239. https://doi.org/10.1016/j.tbs.2021.01.001
Ubiquitous real-time passenger information (URTPI) enables public transport (PT) users to make better travel choices at both pre-trip and en-route stages. A significant amount...