Automatic passenger counting (APC) in public transport has been introduced in the 1970s and has been rapidly emerging in recent years. APC systems, like all other measurement devices, are susceptible to error, which is treated as random noise and is required to not exceed certain bounds. The demand for very low errors is especially fueld by applications like revenue sharing, which is in the billions, annually. As a result, both the requirements as well as the costs heavily increased. In this work, we address the latter problem and present a solution to increase the efficiency of initial or recurrent (e.g. yearly or more frequent) APC validation. Our new approach, the partitioned equivalence test, is an extension to this widely used statistic hypothesis test and guarantees the same bounded, low user risk while reducing effort. This can be used to either cut costs or to extend validation without cost increase. It involves a pre-classification step, which itsself can be arbitrary, so we evaluated several use cases: entirely manual and algorithmic, artificial intelligence assisted workflows. For former, by restructuring the evaluation of manual counts, our new statistical test can be used as a drop-in replacement for existing test procedures. The largest savings, however, result from latter algorithmic use cases: Due to the user risk being as bounded as in the original equivalence test, no additional requirements are introduced. Algorithms are allowed to be failable and thus, our test does not require the availability of general artificial intelligence. All in all, automatic passenger counting as well as the equivalence test itself can both benefit from our new extension.
翻译:在公共运输中自动计票(APC)是1970年代引入的,近年来也迅速出现。APC系统与所有其他测量装置一样,容易出错,被作为随机噪音处理,而且不能超过一定范围。对非常低错误的需求特别受到诸如收入分享等应用的推动,每年有数十亿个,因此,要求和费用都大大增加。在这项工作中,我们处理后一个问题,并提出提高APC初始或经常性(例如每年或更频繁)验证效率的解决方案。我们的新办法,即分解等值测试,是这一广泛使用的统计假设测试的延伸,并保障相同的受约束的低用户风险,同时减少努力。这可以用来降低成本或扩大验证范围,而无需增加成本。因此,分类前的步骤本身可能是任意的,因此我们评估了一些使用的案例:完全手工和算法、人工智能辅助工作流程。前,通过调整手动计数评估,我们的新统计测试可以用来作为现有测试程序的递减价替代标准,而不是现有自动定量,因此,最大的预算法要求从最初的预算到最后的预算法检验,因此,不能进行最大的预算。