Article content
This year, we launched the Urban Analytics module, which helps make decisions about the future of the urban environment using measurable data. The module has six tools in total, and today we highlight the one that will save lives, it is called “Road accidents”.
Reducing road traffic fatalities, as well as reducing accident-prone sections on the road network, are important national objectives. They are declared among the priority goals of the Safe and High-Quality Roads project in Russia, which is aimed at creating a comfortable and safe living environment.
We rose to the challenge and we made a cartographic analytical service that would allow us to visualize road accidents, their hotspot locations, the causes and dynamics of their changes over time. This information will help to prioritize when working on the development or reconstruction of the road network.
Another benefit is that it gives valuable insights on the measures taken to improve traffic safety. Imagine city management puts a new road sign, traffic light or a pedestrian island by the road, or maybe reconstructs the road itself. Find out if these measures took the expected effect and reduced the number of accidents
With the help of the “Road accidents” tool, you can easily find the most problematic sections of the city’s road network in terms of safety, focus on them and find effective solutions.
What features go with the tool?
User can choose object and display its record with attributes of each accident: the date of the accident, the category of the accident, the number of injured, the number of deaths, the severity of the accident, the weather conditions at the time of the accident, or whether pedestrians were involved. Filter can be applied by any of listed attributes to show only filtered accidents on the map:
With the help of the tool, it is possible to find the hotspots of accidents for a given period of time (orange symbols) and accidents involving pedestrians (dark gray symbols). The map shows the proportion of accidents involving pedestrians in each of the accident hotspot:
The tool also highlights the concentration of accidents in terms of severity and harm to health: bright pink symbols show severe accidents. Here you can also see the proportion of severe accidents in relation to minor ones:
Another feature is a comparison map showing change in the number of accidents relative to the same time of year in the past. The user provides input of two time periods, and the system shows if number of accidents has increased or decreased in each part of the city. The size of the arrows is proportional to the number of accidents:
Thus, the “Road accidents” tool makes it possible to find out details about specific accidents, their concentration in different parts of the city and compare data with the same time of the year in the past. In the next article, we will talk about the “Private cars density” tool, which helps our users get information about how cars are distrubuted around the city.
You can read about all the features of the Urban Analytics module in our article.