Presentation Lineup

Presenter Name: Chenhui Liu 
Title: Explore Driver Behavior at Rural High-Speed All-Way Stop Control Intersections by Visualizing Naturalistic Driving Data 
More Information:   View

Presenter Name: Kyle Titlow 
Title: Interactive Pedestrian Fatality Web Application 
More Information: I will discuss the development of the Department of Transportation's (USDOT) "Pedestrian Fatality Risk Map", an interactive, online ArcGIS web map tool that depicts the output of a predictive model that estimated and quantified pedestrian fatality risk for all neighborhoods (Census tracts) in the United States. I will concentrate on the features of the map included specifically to maximize the accessibility of the model output to policy-makers and members of the general public interested in improving pedestrian safety.  View

Presenter Name: Gareth Robins 
Title: Predicting Crashes by Applying Machine Learning on New Sources of Driver Behaviour Data 
More Information: A key component of Vision Zero is identifying and understanding the user attributes that contribute to the incidence of deaths and serious injury in road crashes. As traditional observational methods reach their limits, results should inevitably stagnate, and we have to look toward new techniques to address a large number of traffic-related crashes.

In this study, we used several geospatial and machine learning techniques to determine the similarities between crashes from the CAS dataset and vehicle's harsh-braking from EROAD, a regulatory telematics company. When applied to the New Zealand road network, results in a targeted list of locations that may be susceptible to experiencing crashes.

By utilising this approach, road-controlling-authorities can test the efficacy of their interventions through a faster feedback loop, experimenting with more cost-effective solutions.  View

Presenter Name: Sean Lynn 
Title: Utilizing GIS for Traffic Safety 
More Information:   View