  This paper presents the $\mathrm{\mu}$Car, a 1:18 model-scale vehicle with
Ackermann steering geometry developed for experiments in networked and
autonomous driving in research and education. The vehicle is open source,
moderately costed and highly flexible, which allows for many applications. It
is equipped with an inertial measurement unit and an odometer and obtains its
pose via WLAN from an indoor positioning system. The two supported operating
modes for controlling the vehicle are (1) computing control inputs on external
hardware, transmitting them via WLAN and applying received inputs to the
actuators and (2) transmitting a reference trajectory via WLAN, which is then
followed by a controller running on the onboard Raspberry Pi Zero W. The design
allows identical vehicles to be used at the same time in order to conduct
experiments with a large amount of networked agents.
