Conference Papers 2019

Seminar
Day 3 (11 Oct 2019), Session 9, Transport Models, 11:30 - 13:00

Status
Accepted, documents submitted

Submitted by / Abstract owner
Joshua Jiao

Authors
Joshua (Xihe) Jiao

Short abstract
This paper reports on the development of a new travel demand model that is capable of representing and predicting travel to individual outdoor recreational sites, and importantly, the model has very strong transferability.

Abstract
This paper is based on the dissertation of my PhD research in the Martin Centre for urban and transport studies at the University of Cambridge. It reports on development of a new travel demand model, that is capable of representing and predicting travel to individual outdoor recreational sites. Travel to outdoor recreational spaces belongs to a general class of research questions for understanding destination and travel mode choices. The relevant literature suggests that the analysis and modelling of outdoor recreational trips appear to fall between two poles: on the one hand, the Discrete Choice Model (DCM) based travel modelling, has rarely touched outdoor recreational travel; on the other hand, the regression models that have been developed and applied within the environmental geography and economics for predicting outdoor recreational travel have not engaged in the field of travel demand modelling; instead, such models place a unique emphasis on the use of land cover/land use data which is absent from the four-step models. Therefore, outdoor recreational travel demand remains poorly understood in transportation modelling.
Why understood travel to outdoor recreational sites is important? Besides the age-old belief that outdoor activities are good for the body and spirit, in recent years, there has been a growing evidence base showing that outdoor recreation is closely associated with human health and wellbeing. This evidence appears to have started to influence how people perceive the benefits of outdoor recreation. In a systematic survey on Monitor the Engagement with the Natural Environment (MENE) that has been going for nine years, the proportion of outdoor recreation visits where health and exercise were cited as a motivation rose from 34 per cent in 2009 to 50 per cent in 2018. The overall number of outdoor recreational trips has risen from 2.8 billion (2009-2010) to 3.4 billion (2017-2018). Given the importance of outdoor recreational activities to urban land use planning and public health, this is a clear gap needs to be filled.
Since the MENE survey came online in 2010, it becomes possible to study outdoor recreational trips without extensive on-site data collecting exercise which is time-consuming and expensive. The UK National Ecosystem Assessment (NEA) has developed a Negative Binomial Regression (NBR) model to estimate the outdoor recreational trips generation and distribution. Although it has proven the value of this kind of model for city planners and designers by testing different planning scenarios, the model is not intended for assessing choices of individual sites. One reason for this, as identified by previous studies, is that compared with the DCMs, the NBR models have certain limits on estimating people’s choice behaviours.
In this study a new DCM based travel demand model has been developed for outdoor recreational trips. This is achieved by answering three main research questions: First, how to build a new model for outdoor recreational travel? Secondly, is the estimation accurate enough? And, finally, how can city planners and designers use this new method? The data used to build up the new model are collated from a wide range of sources, most of which are open-source data includes: OpenStreetMap, Ordnance Survey map, Google API, literature reviews and the most importantly, the MENE survey data. The new model has been calibrated for a case study area which spanned 14 selected districts in the North-West region. Validation of the new model is based on counting data of a recreational site - Wigg Island Nature Reserve. In the final stage of the research, the new model is applied to estimate the changes that would arise from planning and design interventions in existing and proposed sites.
The outcome of this study is a new model that can predict the number of trips to individual destinations, and that the model presented here is capable of predicting the changes in the volume and catchment of visits to an existing green space after land use planning or urban ecological interventions. This is a completely new theoretical model that is focused on understanding and quantifying the travel choices to outdoor recreation sites, which can be transferred to any other sites in England with little requests for data collection.

Programme committee
Young Researchers' and Practitioners' Forum