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Effect of Self-driving Buses on Vehicle Scheduling

机译:自动驾驶公共汽车对车辆调度的影响

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We are more and more close to the time when a higher number of autonomous vehicles are appearing in road traffic. The number of unanswered questions does not diminish but grow. One such issue is the role of autonomous vehicles in public transport. When talking about autonomous vehicles we often think of only cars and we think less about self-driving buses. But the economic potential inherent in autonomous buses is huge. In the Hungarian vehicle and crew scheduling practice (and also in other countries) the one driver-one vehicle control is typical. This method closely links the vehicles and the drivers. Vehicles should therefore adapt to the rest time of the crew and the employment rules. Unused reserves are generated in the system. Autonomous vehicles can release this overcapacity. Thanks to that, fewer vehicles can carry out public transport tasks and we can save extra rides. It also provides a solution to the lack of drivers, which is a basic problem in many countries. In our study we show the reserves that can be recovered from the system in the case of three Hungarian cities (Eger, Dunaújváros, Gy?r). We show how much savings can be achieved by running autonomous buses in European cities with a population of 45 000, 54 000 and 130 000 inhabitants. The results are promising. In smaller cities we could achieve about 20% of economical savings but in bigger cities 40% is also realistic. Our statements are based on only rough calculations and they try to help in preparation for the future.
机译:在道路交通中出现了较高数量的自治车辆时,我们越来越接近时间。未答复的问题的数量并没有减少但增长。一个这样的问题是自动车辆在公共交通工具中的作用。在谈论自治车辆时,我们经常只想到汽车,我们少考虑自行车公共汽车。但自主公交车中固有的经济潜力是巨大的。在匈牙利车辆和船员调度练习(以及其他国家)中,一个驱动器 - 一个车辆控制是典型的。该方法紧密联系起来的车辆和司机。因此,车辆应适应机组人员的休息时间和就业规则。在系统中生成未使用的储备。自治车辆可以释放这种超现代。由于这一点,较少的车辆可以开展公共交通任务,我们可以节省额外的游乐设施。它还提供了缺乏司机的解决方案,这是许多国家的基本问题。在我们的研究中,我们展示了在三个匈牙利城市(Eger,Dunaújváros,Gy'r)的情况下从系统中恢复的储备。我们展示了通过在欧洲城市的自主公共汽车,人口为45 000,54 000和130 000名居民来实现多少节省。结果是有前途的。在较小的城市中,我们可以实现大约20%的经济储蓄,但在更大的城市中,40%也是现实的。我们的陈述仅基于粗略的计算,并试图帮助准备未来。

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