This thesis investigates the impact of Munich's aqt project, focusing on traffic effects in two areas with newly implemented car-free zones. Using historical open source data, a Random Forest regression model was developed to predict traffic impacts for future similar projects. The study researched travel behavior changes due to road closures, including traffic, alternative transport, weather, and sports activity data. Results show no significant change in relative speed, indicating stable traffic conditions with minor improvements. The models, utilizing averaged historical data by weekdays for future feature values, achieved modest accuracy (R² ~ 0.2), surpassing linear regression models. Key features influencing accuracy included speed, day of the week, and weather, while nontime-dependent factors like demographics and amenities had negligible impact. These outcomes support existing literature on road closures, indicating an elastic reaction to reduced car infrastructure and confirming minimal observed traffic changes. Overall, the aqt project demonstrated a non-significant effect on traffic conditions, mitigating concerns about increased congestion from restricting car access.     «

This thesis investigates the impact of Munich's aqt project, focusing on traffic effects in two areas with newly implemented car-free zones. Using historical open source data, a Random Forest regression model was developed to predict traffic impacts for future similar projects. The study researched travel behavior changes due to road closures, including traffic, alternative transport, weather, and sports activity data. Results show no significant change in relative speed, indicating stable traff...     »