Huan Zhang, MPEPO

GPS-based path-following control used for local distributions

Examiner: Jonas Fredriksson, Dept of Electrical Engineering
Supervisor: Maliheh Sadeghi Kati, Dept of Electrical Engineering


Automation of local distribution using automated dolly technology is a viable and productive alternative for future state of art green terminals and local distribution of container trailers. This technology offers unmanned transports. It reduces driver operator cost and removes diesel fuel cost. The semi-trailer unit is towed by an intelligent and electrically propelled converter dolly (i-dolly) with automatic coupling and parking of semi-trailers. In this solution, autonomous dolly-semitrailer combination is considered to be used to transport the containers between the dry port and company terminals.

Within this thesis, a GPS-based path-following control of i-dolly for the local distribution is designed and implemented. The thesis starts with the study and derivation of a kinematic model of single unit vehicle. Then the control algorithm for a single unit vehicle (i-dolly) is designed and implemented based on the predefined path with Global Position System*(GPS). Then, an articulation angle between the dolly and semitrailer is considered in the kinematic model and control algorithm. The kinematic model and control algorithms are upgraded for the double units vehicle (i-dolly and semitrailer). At last, the kinematic model is replaced by the advanced vehicle model VTM (Volvo Trucks Model) and the control algorithms are tested on VTM.

The controller is designed as low-speed independent and works well to make the single unit vehicle track the given trajectory closely. It makes the autonomous vehicle drive up to 9m/s forward and -3m/s backward to follow the given path within a high precision. But the linear controller does not work well to control the
combination vehicle to follow the given path stably and precisely.
Category Student project presentation
Location: Web seminar
Starts: 18 September, 2020, 09:00
Ends: 18 September, 2020, 10:00

Published: Fri 11 Sep 2020.