There are two critical issues involved as a mobile node moving across two different network sub-domains. One of them is to minimize the possible packet loss and the other is to shorten the handover time. Fast handover is a remedy to these problems. It minimizes the packet loss by making use of buffers, and speed up the handover procedure by L2 triggering. There are two components contributing to the handover delay, namely L2 handover delay and L3 handover delay. The L3 handover delay consists of movement detection delay, duplicate address detection delay, as well as registration delay. With fast handover, the movement detection delay can be lowered by using L2 trigger, and the registration delay can be decreased by buffering and tunneling. However, the problem of out-of-order packets is still in its existence. A novel handover scheme incorporating the anycast technology is developed and presented in this thesis. With refined buffer control scheme and the switching between unicast and anycast addressing, the handover performance can be greatly improved by the proposed approach.

<p>This Master’s thesis is a pilot study that investigates different systems to drive autonomous and non-autonomous vehicles simultaneously on test tracks. The thesis includes studies of communication, positioning, collision avoidance, and techniques for surveillance of vehicles which are suitable for implementation. The investigation results in a suggested system outline.</p><p>Differential GPS combined with laser scanner vision is used for vehicle state estimation (position, heading, velocity, etc.). The state information is transmitted with IEEE 802.11 to all surrounding vehicles and surveillance center. With this information a Kalman prediction of the future position for all vehicles can be estimated and used for collision avoidance.</p>

This Master’s thesis is a pilot study that investigates different systems to drive autonomous and non-autonomous vehicles simultaneously on test tracks. The thesis includes studies of communication, positioning, collision avoidance, and techniques for surveillance of vehicles which are suitable for implementation. The investigation results in a suggested system outline. Differential GPS combined with laser scanner vision is used for vehicle state estimation (position, heading, velocity, etc.). The state information is transmitted with IEEE 802.11 to all surrounding vehicles and surveillance center. With this information a Kalman prediction of the future position for all vehicles can be estimated and used for collision avoidance.