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Online scheduling of a fleet of autonomous vehicles using agent-based procurement auctions

机译:使用基于代理的采购拍卖在线调度自动驾驶车队

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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.
机译:我们针对调度无人驾驶车辆的问题提出了一种新颖的分布式方法。我们的分布式系统避免了单点故障,具有可扩展性,容错性和鲁棒性。我们描述了一种基于代理的分布式系统来进行一组采购拍卖。在拍卖中,车辆是“卖方”,乘客是“买方”。每辆车都以一个出价值出价给乘客,出价值是车辆到达乘客所用时间的反函数。在我们基于代理的体系结构中,各种软件代理驻留在不同的系统上,并且我们描述了用于其通信的分布式算法。我们对两个不同地点(印度班加罗尔和美国弗吉尼亚州泰森角)的车队进行了仿真,并将我们算法的乘客的最大和平均等待时间与FIFO算法进行了比较。我们还计算了车辆为乘客服务的时间与总时间之比,以计算出燃油浪费。结果表明,我们的系统改善了乘客的最大和平均等待时间,以及车队的燃油成本。此外,我们表明,与未分布式系统相比,这种分布式系统平均减少了响应客户请求所需的时间。

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