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Daniel Watts

Daniel Watts has won the 2021 Voorhees-Large Prize for his University of Westminster Transport Planning and Management MSc dissertation ‘A Methodology To Create A Work-From-Home Trip Generation Indicator: An Application In England And Wales’.

Dan is a Senior Transport Planner with consultants WSP based in Guildford. He joined Mouchel, now part of WSP, on a work placement scheme and was then appointed to their modelling team.   Keen to become a Chartered Transport Planner, CTPP, Dan was sponsored by WSP to study part-time for the Westminster Masters, graduating with distinction.

Known amongst his colleagues for providing innovative solutions to complex matrix and data analytical problems, Dan is skilled in strategic and micro-simulation transport software packages such as SATURN, VISSIM, and Paramics Discovery as well as assessing economic impacts using TUBA, COBALT, MyRiad and QUADRO and in using technical programs such as Excel, Access and GIS.

 

In his spare time, Dan is an avid golfer as well as enjoying hiking, travelling and baking.

 

With his knowledge of forecasting travel demand, Dan was aware that little consideration had been given to the impact which increasing levels of working from home was having.  The Covid pandemic had caused a dramatic shift in trip generation during 2020; in particular, commute trips were significantly reduced due to working-from-home (WFH). This dissertation exploits the consequence of the pandemic to produce a methodology that creates a WFH trip generation indicator, which can be applied to current demand forecasting processes.

The analysis found that the change in GDP alone cannot account for the reduction in observed trips across different lockdown scenarios from the case study area (Gravesend, Kent). Moreover, when a bespoke WFH score for the study area was included in the formula, calculated by manipulating Office for National Statistics’ (ONS) published ‘ability to WFH scores’, car commuter trips were found to be more accurately forecasted. Through statistical testing using the GEH methodology, four indicators and their estimated flows were compared to observed flows to establish the best performing indicator. Separate to this, statistical and spatial analysis also found that ONS ‘ability to WFH scores’ were agreeable with current research in the impact occupation has on WFH. Furthermore, when applied to electoral wards across England and Wales, the spatial pattern of ability to WFH correlated well with relevant literature related to location and WFH rates.

 

These outcomes are important because home working is likely to remain more popular than pre-pandemic. The forecast demand dataset published by Department for Transport shapes forecast transport models throughout England and Wales and therefore impacts decision-makers when approving transport schemes. The findings suggest that current forecasting techniques engender inaccurate forecast demand estimates that exclude the impact of home working on car commuter trips.

 

Responding to the decision to award him the Voorhees-Large Prize, Dan said ‘I am thrilled, surprised (pleasantly!) and honoured to win such a prestigious prize in the transport industry. There has been a plethora of research (with more to be released) relating to the impact the pandemic had on transport in the UK and globally. I hope that my research highlights the need of greater consideration of WFH when calculating forecast demand in a post-pandemic world. It would be remiss of me to not mention that this research would have been of inferior quality without the support of my dissertation supervisor - Mengqiu Cao as well as Enrica Papa (course leader) and David Carrignon (Technical Director at ARCADIS)’.

 

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