Mapping Pedestrian Activities and Safety in Melbourne



Monash City Science

The above diagram shows the distribution of pedestrian counts and crashes over 24-hour. The map on the right shows the individual pedestrian crashes as white dots. The coverage area of each pedestrian count sensor is shown as a square changing from yellow (low activity) to red (high activity). [Preliminary Results]

Melbourne is a sleepless city with more than 800,000 people moving around it everyday. This number is estimated to increase to a million people by 2030. Walking accounts for 66% of the trips made in the city. Walking trips are a major contributor to the economy, being the dominant mode for shopping and tourism. City of Melbourne has recently released a draft walking plan proposing ways to improve walking condition in the city as population grows.

This project aims to analyse and visualise the relationship between number of pedestrian activities and pedestrian safety over time. Our goal is to contribute to the transport strategic plan of the City of Melbourne, specifically the Draft Walking Plan. The project provides further insights into the spatial and temporal distribution of pedestrian activities and crashes and help planners and decision-makers to make informed and data-driven decisions on pedestrian related policies in the city.

The above diagram shows hourly average pedestrian counts over 5 years for each sensor. The map on the right shows the location of individual pedestrian count sensors (total 42) across City of Melbourne. [Preliminary Results]

In the City of Melbourne, a pedestrian is involved in a fatal or serious injury crash every two days. In 2009-2013, near 1,000 pedestrian crashes were reported in the city, which is the highest number of pedestrian crashes in the state of Victoria. Improving the safety and security of the walking environment in the city increases the number of pedestrian activities and therefore contributes to the economy and well-being of the society.

We used a number of open datasets to deliver this project. We used 5-years worth of pedestrian count data (2009-2013) from City of Melbourne Open Data Portal containing more than 1.1 million rows combined with 5-years worth of pedestrian crash data (2009-2013) from Victorian Government Data Directory.

The chart on the right shows the correlation between the number of pedestrian crashes (sum value over 2009-2013) and hourly pedestrian counts (average value over 2009-2013) across City of Melbourne. Each dot represents one hour in a day. The observed linear relationship suggests that if the number of pedestrian activities increases, the number of crashes is likely to increase.

Developed by Monash City Science team: Meead Saberi, Bryan Hong, Julian Li, Emily Chen, and Sajjad Shafiei