This PhD research will develop and apply advanced econometric models in estimating injury severity models for active travellers. The study will also examine the impact of advanced vehicular technology on active travellers’ safety.
Moreover, it will address several methodological issues in developing injury severity models for active travellers including unobserved heterogeneity, endogeneity, and temporal instability.
Further, this research will develop an integrated travel demand and safety forecasting framework to identify proactive, reactive, and systematic managed approaches to improve active travellers’ safety. The data-driven and evidence-based forecasting framework will allow us to identify where to focus our attention to encourage more sustainable travel behaviour while also improving the safety for active travellers.
Walking and cycling, often referred to as active transport mode, are essential elements of road transport system and human activities. Active transport is an integrated part of sustainable transport systems due to the low carbon footprint of this transport mode.
Additionally, active transport adoption is likely to have added health benefit through increased level of physical activity while also reducing national health service concern overall. Therefore, governments around the world are encouraging their citizens to walk and bike more. The underlying desire of promoting active transport is to de-prioritise car-dependency, specifically for short trips.
In addition, with the COVID-19 outbreak, the active travel mode is surfacing with its ultimate values in our transport network system. People tend to walk or ride a bicycle more rather than using other travel modes since they can maintain the required social distancing measures. Therefore, this behaviour transformation is consistent with many governments’ attitude to provide more walking and biking facilities for their citizens.
Despite significant efforts in promoting active transport, road safety concern remained an impediment to significant uptake of walking and cycling. For example, in Australia, approximately 16 percent of road crashes are related to pedestrian and bicyclist. Between 2012 and 2019, the crash database of Queensland has a record of 5,262 pedestrian- and 6,190 bicyclist-involved crashes, resulting in 240 and 69 pedestrian and bicyclist fatalities respectively.
These numbers represent approximately 14% of all recorded fatalities in Queensland. In Victoria in 2017, 17% of all lives lost in road traffic crashes were reported to be pedestrians. These statistics clearly signify the need for continual effort in achieving the sustainability goal and improving the overall safety situation for active travellers in Australia.
It is imperative to improve the road safety situation for active transport modes which will encourage people to walk or bike more frequently. As such, the overarching aim of the current research is to contribute towards active travel safety by addressing the following empirical issues in examining the injury severity mechanism of active travellers who were recorded to be involved in a motor vehicle crashes:
- What are the critical factors contributing towards active transport crash risk and injury severity?
- What is the impact of motor vehicle traffic stress on active travel safety?
- What are the effects of shared space on active transport safety?
- How network accessibility affects activity level and safety of active transport modes?
- To what extent, the advanced vehicle technologies are contributing towards active travel safety?
This PhD research aims to address these pressing challenges in active transport safety by uncovering the underlying injury severity mechanism of crashes involving pedestrians and bicyclists by employing advanced econometric models.
It will also address several methodological issues including unobserved heterogeneity, endogeneity and temporal stability which are critical in developing efficient models. The research will build on the databases from traditional crash data, data collected through traffic data, transport infrastructure data, land use data and other multimodal interactions data.
The outcome of the study will allow us to understand the integration and implications of different databases in examining the active transport safety.
Furthermore, the research will investigate the influence of accessibility in a futuristic scenario of connected and automated vehicle on active travel mode behaviour, risk perception, and the associated safety.
Finally, the research will develop an innovative unified policy analysis tool of active transport safety by considering a full range of policy instruments (proactive, reactive, and systematic managed approaches).
- Develop a joint econometric model for examining pedestrian and bicyclist crash likelihood and injury severity.
- Examine the effect of vehicle type and advanced driving assistance systems on pedestrian and bicyclist injury severity mechanism.
- Examine the effects of temporal heterogeneity on active traveller’s injury severity mechanism.
- Develop a hierarchical model of active traveller safety for modelling crash severity and crash risk mechanisms in an integrated framework.
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