Munich is the third largest city in Germany with 1.55 million inhabitants.
According to several forecasts, the population in 2022 will exceed the 1.7 million mark.
Greater Munich is the economic center of Bavaria. 22.3% of the Bavarian population lives in the Munich region and generates around 31% of the Bavarian GDP. Munich is Germany's second largest employment location with around 822,000 employees in the urban area and 1.37 million employees in the region. The year-on-year growth has been exceeding 2% in the last six years, and the consequent increase of commuters has caused a spike in traffic that can be summarized with few numbers: based on a TomTom study, in Munich travel time in rush hours increases by almost 50% compared to off peak hours. Even off-peak, a route that would take one hour, takes additional 17 minutes (+28%). The average time spent in traffic queues in Europe is 30 hours per year, while in Munich it is 49 hours (+63%)
The air quality in Munich is one of the worst in Germany. The Bavarian capital is, behind Stuttgart, the negative leader in terms of NO2 pollution.
Therefore, the Free State of Bavaria was legally convicted by the Bavarian Administrative Court for the preparation of diesel bans from 2018 in Munich.
Public transport in Munich is already overloaded at peak times and urgently needs new,
efficient and sustainable mobility solutions.
The proposed solution is the introduction of a demand-oriented transport service, which shall be deployed by cooperating companies in Munich which are already offering the "Anrufsammeltaxi" service. As of now, those companies, operate in a traditional way: the customer must call the operator in advance and the service is managed without any optimization. A smart service, provided by a dedicated app and the dispatching managed by Artifical Intelligence, while guaranteeing a smooth and worry-free service, would harness efficiency and increase significantly the seat occupancy ration of the circulating vehicles, therefore reducing pollution per capita, traffic congestion and costs.
The trip planning is managed by predictive algorithms and by requests that are generated via the dedicated app, with the possibility to reserve in advance. The reservations are consolidated by intelligent algorithms to achieve the optimal seat occupancy rate, and thus guarantee the highest efficiency and lowest environmental impact per capita.
Ideally, the vehicles should powered by electricity or natural gas.
The system also includes a targeted advertisement platform that can generate further revenue and reduce the cost of the service.
A full explainer of the solution can be viewed here