The capacity of public roads has become a serious problem all over the world. The traffic is constantly increasing, while the capacity remains almost the same. This causes traffic jams and road accidents. An effective way to increase the road throughput employs vehicular platoons, which allow to decrease inter-vehicle distances without compromising road safety.

The urgent necessity to increase road capacity has lead to the substantial interest in Cooperative Adaptive Cruise Control (CACC), which uses measurements of on-board sensors and inter-vehicle communication to provide safe platooning. Numerous theoretical works and extensive experiments have proved that the possibility to exchange certain parameters via wireless communication allows for a significant decrease of the inter-vehicle distance.

Cooperative Adaptive Cruise Control systems should comply with several requirements. One of the requirements is so-called string stability, which prevents amplification of disturbances, propagating along the string of vehicles. To simplify the design of CACC, vehicles in a platoon are often assumed to have identical and fully known dynamics. These assumptions in practice are too restrictive. The heterogeneity of vehicles increases the complexity of CACC controller design problem.

In this master thesis a decentralized CACC algorithm is implemented based on continuous sliding-mode control and adaptation laws, which estimate uncertain vehicle’s parameters. Evaluation of Cooperative Adaptive Cruise Control algorithm has been conducted on a vehicle simulator DYNACAR.