We propose a novel distributed approach for the problem of scheduling a fleet
of autonomous vehicles. Our distributed system avoids a single point of
failure, is scalable, fault tolerant and robust. We describe an agent-based
distributed system to conduct a set of procurement auctions. The vehicles are
the "sellers" and the passengers are the "buyers" in the auction. Each
vehicle bids for the passengers with a bid value which is an inverse function
of the time it would take the vehicle to reach the passenger. In our agent
based architecture, the various software agents reside on different systems
and we describe distributed algorithms for their communication. We have
performed simulations of a vehicle fleet in two different locations
(Bangalore, India and Tyson's Corner, Virginia, USA) and compare the maximum
and average waiting times of the passenger of our algorithm with a FIFO
algorithm. We also compute the ratio of the time in which the vehicle is
servicing a passenger to the total time, to compute the fuel wastage. The
results show that our system improves the maximum and average waiting times of
the passengers, as well as the fuel costs for the vehicle fleet. Furthermore,
we show that such a distributed system reduces the time it would take on
average to respond to customer requests, as compared to a system which is not
distributed.