OptiWaSP - Optimised Walking Schoolbus Planning

Lead Research Organisation: Lancaster University
Department Name: Management Science

Abstract

In the past four decades there has been a considerable modal shift from walking to school to going by car for primary school children in England. This has led to increased congestion and air pollution and decreased traffic safety. Meanwhile, many studies have shown the health benefits to children of active travel to school. The UK Government set a target to increase the percentage of children aged 5 to 10 that usually walk to school in England from 49% in 2014 to 55% in 2025. However, despite recent initiatives, such as the national Walk to School Outreach programme, the National Travel Survey in 2019 recorded the lowest ever percentage of primary school children walking to school at 46%.
Time constraints are often cited as the main barrier to parents accompanying children in walking to school with concerns about safety deterring parents from allowing children to travel independently. This highlights that if a system of providing adult supervision for walking to school can be set up then there is good scope to increase the numbers of children walking to school. A walking school bus (WSB) involves a group of children walking to school with one or more adults and following a set route. WSBs have increased walking to school in Australia, New Zealand and the United States but the UK has not widely adopted them. Taking up WSBs in significant numbers requires a degree of organisation to establish meeting points, safe routes, adult supervisors and timetables. The proposed research will develop a planning tool to enable schools to maximise the number of children walking to school using safe routes accompanied by adults.
At the heart of the tool will be an Optimisation Model that identifies walking routes to school and meeting points, while addressing multiple objectives (travel time, safety and air pollution exposure). We will develop this based on our extensive experience in developing multi-objective problem solutions for public transport scheduling and other transport and healthcare applications. The Optimisation Model will work in conjunction with a Modal Choice Model, which estimates student modal choices as input to the Optimisation Model, and with a Road Network Model, which estimates the consequences of a particular walk-to-school scenario on road network conditions. The Modal Choice Model will include a novel development recognising that decisions by parents on how their children get to school are based not only on individual considerations, such as minimising travel time, but on the opinions and choices made by other parents. This will build on the team's previous work exploring the role of social influence in travel choices. The Road Network Model will allow assessments to be made of traffic management measures that can be combined with WSBs to increase confidence in walking to school.
We will design the tool so that it can be used repeatedly as circumstances change. It will be able to be used reactively for re-planning when there have been changes (e.g. children absent, new school years, etc.) or proactively to put in place 'ghost' routes/stops to attract new users where potential is identified (e.g. where there is a clustering of children or where WSBs can have maximum influence on reducing pollution near a school). Our aim is for the tool to support the work of organisations such as our Project Partner Living Streets delivering the Government's Walk to School Outreach programme. A Stakeholder Advisory Group will help steer the project. The academic team will partner with Living Streets to ensure the tool is well-grounded (for example, in terms of how parents perceive walking routes or how parents' willingness for their child to walk to school is affected by physical and social context) and is practically useful for real-world application. We will demonstrate the planning tool in Bradford where the local authority and schools have agreed to work with us in designing and applying our work.

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