Transport for London (TfL) and Mercedes-Benz Urban Mobility Solutions (UMS) have developed the „Mercedes-Benz Road Safety Dashboard“ in a joint development approach. A cross-functional team of engineers, safety experts, data protection specialists and data analysts from London and Mercedes-Benz worked intensively together hand in hand to make London’s streets safer for everyone, in particular for people walking and cycling.
Transport for London (TfL) is the integrated transport authority responsible for delivering the Mayor of London’s strategy and commitments in this field. It runs the day-to-day operation of the Capital's public transport network as well as promoting walking and cycling and managing London's main roads. TfL does all it can to keep the city moving, working and growing and reinvests all income generated through fares and commercial revenue to run and improve services. Including the safety of all road users.
Transparency: easy-to-use overview of critical safety hotspots
Decision support for traffic and city planners
Increasing Safety: saving lives and physical integrity
Efficiency: Economic efficiency by optimized use of resources
Head of Commercial Innovation at Transport for London
The first talks between representatives from London and Mercedes-Benz took place in 2019. Rikesh Shah, Head of Commercial Innovation at Transport for London, and Daniel Deparis, Head of Urban Mobility Solutions at Mercedes-Benz AG, partnered to work together on the use of an innovative solution.
In the first step, the current challenges regarding London's road safety were discussed and possible solutions brainstormed. The two partners were able to bring in different perspectives and skills.
By matching data sources and existing road safety models, a data-based innovative model for the identification of danger spots was gradually developed. Step by step. Anonymized vehicle data from Mercedes-Benz driver assistance systems were enriched with additional infrastructure data from London.
On-site visits to algorythmically determined accident blackspots as well as the analysis of historical accident data were able to validate and enrich the algorithm. Thus, the two-year development phase was successfully completed in 2021.
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