Autonomous driving is becoming increasingly important in the 21st century.
It offers the possibility to complement existing mobility concepts and to enable new groups of people to move independently, such as people with limited mobility.\cite{maurer2015autonomes}
In recent years, many new and innovative ideas have been established, bringing the boundaries between local public transport and individual transport ever closer.

The BVG (Berliner Verkehrsgesellschaft) in Berlin, for example, offers the BerlKönig service, which functions as a mix of on\textendash call bus and cab.
When ordering a ride, specify the start and destination points and the number of people to get transported.
The system then bundles similar trips together so that the called BerlKönig bus can run several tours simultaneously.
That reduces both the fare compared to a cab ride and is better for the environment.\cite{berlkoenig}
Uber modernizes the cab industry and manages to use a higher capacity utilization of existing resources.
Thus, Uber's drivers have a significantly increased workload and fewer empty runs.\cite{10.1257/aer.p20161002}
The quoted article points out that these improvements to detect outdated and inefficient regulations for the cab industry that do not apply to Uber, but also to better driver coordination with \q{more efficient driver\textendash passenger matching technology based on mobile Internet technology}.

The route planning for the drivers is usually already predefined by the system and is controlled by the system by suggesting possible connecting tours.
In the case of BerlKönig, the driver no longer has any room for maneuver.
Both concepts presented can be further optimized by autonomous vehicles.

Safety plays a unique role in the development of autonomous cars.
In theory, autonomous vehicles from Waymo, a subsidiary of the Alphabet Group, to which Google also belongs, have been driving since 2012, have covered more than 14 million kilometers in the period up to 2018, and in autonomous mode have caused only one accident themselves.\cite{Herger_2018}
In practice, many questions are still unanswered.
Sensors and vehicle communication can be disturbed, legal liability issues are still unresolved, and the technical aspects, including implementation, are still partially unresolved.\cite{glancy2015autonomous}
Because of these many problems, Waymo cars only drive on specific routes in simple neighborhoods with little traffic in California's sunny Mountain View.

Concerning safety, the detection of traffic light signals in road traffic, in the following called traffic lights, is an essential part of autonomous driving.
Previous technology used at the Free University of Berlin to detect traffic lights is based on markings in maps in which the car searches for traffic lights using image processing methods.
Furthermore, as part of a project carried out in the past two years in a test area in Berlin in cooperation with the Senate Department for Environment, Traffic and Climate Protection, and the Fraunhofer Institute FOKUS, who have extended traffic light systems at intersections with transmitter masts.
These indicate not only the general condition of the crossings (including the layout of the turning lanes and road works) but also the current status of the traffic lights.\cite{safari}

\begin{figure}[!htbp]
    \vspace{0cm}
    \minipage{0.0\textwidth}
    \endminipage\hfill
    \minipage{0.85\textwidth}
    \includegraphics[width=\linewidth]{../data/safari.png}
    \caption{Funktionsweise von SAFARI}    %Bildunterschrift
    \label{fig:safari}       %fig:ID
    \endminipage\hfill
    \minipage{0.0\textwidth}
    \endminipage
\end{figure}

This method of detecting traffic lights works very well on test routes or routes that have been upgraded for this purpose, but not in unknown terrain.
The systems fail at temporary traffic lights at road works and in other countries that are not equipped with such a system.
In many situations, such retrofitting of existing traffic lights is not economically viable, especially since all traffic lights would have to be retrofitted for the use of autonomous cars without a transitional period.

In this thesis, a different approach to traffic light detection shall be applied.
Here, the hardware of the cameras and graphic units already installed in the autonomous car shall be used to detect traffic lights in real\textendash time utilizing a neural network.
