Identify how different factors influence day-to-day transport mode choice and provide evidence based interventions to reduce car use.
Engage Smart Transport was a unique project between social scientists and statisticians to reduce car use through targeted information provision, i.e. weather and traffic.
Initial surveys of 2,500 participants in 2016 identified, based on travel choices, 5 main types of respondents. This included that although people have a main mode that they use for their commute, over a 20 day period a significant number of people don’t use just one type of transport mode and instead tended to use multiple modes (albeit to varying frequency). For example, a commuter may drive on 16 days, but catch the bus in on 4 days over a 20 day period.
The surveys also asked stated preference questions to identify how much receiving information would affect their choice of travel mode information would affect their choice of travel mode to their place of work/study.
These responses were then used as the basis of a statistical model to quantify how much different factors influence day-to-day transport mode choice within each group.
The goal of the project was to identify if providing targeted information could increase the number of days they travelled by a non-car mode. For example, if the user was provided travel information prior to their trip that identified delays on the road network, would they be more likely to get the bus (where they could utilise the time reading/on smart phone) and therefore increase the number of bus days to 6 days over a 20 day period.
Part of an innovate UK project with 9 Partner Authorities. Transport survey and statistical modelling part of the project undertaken by the University cost £290,000. This included the cost of staff resources, including mathematicians, and marketing to generate over 2000 responses.
Evidence of success
Stated preference surveys identified transport delay information can result in a 15-20% reduction in the probability of using a motor vehicle.
Due to limited responses in the live trial, it was not possible to validate the statistical models.
Nevertheless, the surveys suggest that provision of travel and weather information could represent a low cost way of increasing sustainable travel.
With identification of 5 different user groups, it was challenging to get suitable sample size for the intervention phase. Community level engagement could to help get a good representative sample
Project missed out on Public Transport engagement, could be improved by doing this up front.
Potential for learning or transfer
Stated preference surveys suggest that information provision can make a significant difference to modal choice.
As society and Transport Planning evolve, more integrated approaches such as this are likely to have a greater role. This project provided a first attempt at identifying the link between information and behaviour which could be explored further
The project identified how certain users were most influenced, and those outputs are likely to be transferable to other areas.
Group Message theme 1 Message theme 2
Motor vehicle Traffic information Traffic information
Public transport Environmental concern Weather information
Cycle Fitness Weather information
Walk Control (flexibility) Weather information
Combo Environmental concern Cost
Learnings from the project (not of all which realte to transport, are also being taken forward by the organisations involved in the project.
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