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Presentation 1:Urban Transport Modelling for Sustainable Well-Being in Hanoi: Implementing a new traffic model
By: Eric Wanjau
Abstract: Many cities are expanding rapidly, but formal infrastructure is failing to keep pace with the burgeoning population. This is further complicated by the emergence of informal transport infrastructures that develop in areas of unplanned urban sprawl.
This project aims at creating statistical and spatial models of transport behaviors and attitudes. It uses data collected as part of a British Academy project undertaking urban transport modeling in Hà Nội, Vietnam, where there are severe problems: congestion, transport infrastructures failing to keep pace with urban expansion, the emergence of informal transport infrastructures and traffic being dominated by motorbikes. To this effect, a transport survey has been undertaken to capture the dynamics and trends of people’s regular travel in and around the city, including the attitudes towards different transport modes and a proposed motorbike ban.
The aim of the modeling is to be able to predict the impact of different transport policy changes and to understand the process driving different travel behaviors. Some of the models being investigated are Spatial Interaction Models which aim at addressing the effect of different policy scenarios, and Classification Models which aim at predicting individuals’ attitudes towards the ban and investigating the underlying factors/reasons.
As such this project will address questions regarding how, where, and when planned policies should be implemented, what the impacts on local communities would be, whether public transport can cope, individuals’ attitudes, and whether there are alternatives.
The wider project also includes a data dashboard, being developed by fellow intern Kristina Bratkova using R Shiny, which will serve as a communication tool of the survey findings.
Presentation 2:Urban Transport Modelling for Sustainable Well-Being in Hanoi: Developing a New Data Dashboard
By: Kristina Bratkova
Hà Nội is a rapidly expanding city with sprawling infrastructure. Unlike many European cities, Hà Nội transport is dominated by private vehicles—predominantly motorbikes—that often follow an informal set of traffic rules. The data are being collected in Hà Nội as part of a British Academy project to support urban transport modelling in the context of a rapid urban expansion and the difficulties this places on formal infrastructures. Therefore, a household survey is currently conducted that collects information about demographics, trip data, vehicle ownership, attitudes towards a proposed motorbike ban and others. The geospatial data modelling of origin and destination of trips with different purpose and frequency is the topic of Eric Wanjau’s project and presentation.
This project develops a data dashboard using R Shiny to serve as a communication tool of the survey findings. The interim development of the dashboard will be discussed with the breakdown of both the functionality (what the user sees) and the code (the development process and structure of the app).
The dashboard will allow policy makers in Vietnam to interrogate these models and data in order to develop an understanding of the trends in the data, and answer research questions, and to thereby make informed decisions. As well as generating summaries of the data, the dashboard will allow policy makers to explore ‘what if’ scenarios around attitudes towards a proposed motorbike ban in Hà Nội and stated transport preferences.
Presentation 3:Open access data for transport research: tools, modelling and simulation
By: Greta Timaite
Abstract: Motor traffic-centric perspectives dominate road infrastructure planning (Parkin, 2018). Yet, other (active) travel modes, such as cycling and walking, have been found to bring an array of benefits: improved mental and physical health, decarbonisation, as well as being more efficient in terms of space (i.e., requires less space) (Parkin, 2018). Acknowledging the significance of active travel, new policies and investment programs (e.g., Department for Transport’s £250m Active Travel Fund) have led to the increasing demand for local evidence to inform interventions such as new cycleways and better-quality pavements. As a result, this project aims to investigate the applicability of open source, namely OpenStreetMap (OSM), data understand, prioritise, and design active travel infrastructure. The overall aim of the project is to understand the use of OSM data for transport planning, which, consequently, has the potential to lead to more inclusive and accessible evidence-based decision–making due to its crowdsourced nature.
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