Data evaluation of the circulation plan in the city of Aalst
21060
From 2021 to 2022
TML evaluated the renewed circulation plan of the city of Aalst by analysing critical performance indicators (KPIs) related to road safety, liveability, and car accessibility, using quantitative data collected before and after the implementation of the plan. After statistical analysis and data processing via Excel and Python, TML provided insight into the evolution of these KPIs in an overview presentation to the city.
With a view to possible adjustments, the city of Aalst wanted to thoroughly evaluate the circulation plan. To this end, they wrote an assignment for data evaluation. This should at least make a statement about the impact on the three spearheads of the circulation plan: accessibility, liveability, and safety.
TML made a statistical analysis of the evolution of the KPIs. We based this on various data sources such as bicycle counts, parking space counts, traffic intensities, and public transport users. In doing so, we needed to align and streamline data so that it was practically usable and we could process it into KPIs. We processed the data we collected via Telraam and floating car data providers via Excel and Python, to provide a graphical picture of the evolution of the KPIs with the help of a map. We poured all this into a clear presentation for the city of Aalst, focusing on graphs, tables, and map material.
With a view to possible adjustments, the city of Aalst wanted to thoroughly evaluate the circulation plan. To this end, they wrote an assignment for data evaluation. This should at least make a statement about the impact on the three spearheads of the circulation plan: accessibility, liveability, and safety.
TML made a statistical analysis of the evolution of the KPIs. We based this on various data sources such as bicycle counts, parking space counts, traffic intensities, and public transport users. In doing so, we needed to align and streamline data so that it was practically usable and we could process it into KPIs. We processed the data we collected via Telraam and floating car data providers via Excel and Python, to provide a graphical picture of the evolution of the KPIs with the help of a map. We poured all this into a clear presentation for the city of Aalst, focusing on graphs, tables, and map material.
