How digital hazard data helps to optimize winter road and cycle path maintenance

Every year, winter is just around the corner. In times of climate change, it is now often somewhat milder, but still regularly with icy temperatures, accompanied by frozen roads and/or snow. This means that the gritting vehicles from bonnorange, which carry out the winter service on behalf of the city of Bonn, are deployed.

Where to clear and grit first?

But where are bonnorange employees most urgently needed for winter maintenance? Until now, the prioritization for the deployment of personnel and vehicles was based on daily weather data from a weather service and empirical values from previous winters. A new, more modern approach should now be found for this, which also draws on various data bases in order to be able to make even better decisions for planning winter road maintenance.

Localize winter danger spots

A joint project by bonnorange and the Initiative for Safe Roads, which was presented to the public for the first time at the Bonn Digital Factory 2023, came up with exciting solutions to this issue. The Initiative for Safe Roads was able to filter out key danger hotspots from its rich data pool of accident data, user-generated danger spots and much more: Appropriate filters were set in the company’s SMART tool to locate the most dangerous areas for cyclists that were related to winter weather.

Supplementary live data

The resulting hazard map for winter operations is supplemented by current measurement data from bonnorange. The company itself has developed a prototype LoRaWAN sensor that can be attached to a wastepaper basket to measure temperature and humidity at ground level. Based on the areas identified as dangerous for cyclists in winter, such live sensors are now to be installed throughout the city in order to provide additional up-to-date information and thus optimize winter road and cycle path maintenance based on data.

Conclusion

This pragmatic approach to optimizing winter road maintenance in municipalities shows how a lot can be achieved with manageable resources – towards a data-based decision-making basis for greater road safety, in this case for cyclists in particular, especially in winter.