The proven benefits of limited-stop services have captured the attention of researchers, especially during the last decade. However, to solve the limited-stop service design problem many existing works directly impose a capacity constraint to a total social cost objective function. This “naïve approach” implicitly assumes that passengers behave altruistically, basing their decisions on what is best for the whole system. Although this issue has been identified in earlier works, the magnitude of the error induced by this simplification has not been studied yet. The objective of this work is to measure this error and to understand how it misrepresents passenger flows and bus occupation rates. To measure this error gap, we optimize a set of test scenarios by applying a naïve approach, and then take the resulting design and obtain a benchmark passenger assignment using a simple behavioral model. We propose two main indicators to compare both passenger assignment: the total passenger deviation, and the total capacity deficit. This comparison reveals that the assignment of the naïve approach may indeed be unrealistic, and raises concerns that a network design based on the naïve approach might have severe problems when implemented. Thus, the work highlights the importance of taking the results of the naïve approach with caution and verify them with a passenger assignment model before their implementation.

限时服务的公认优势已引起研究人员的关注，尤其是在过去的十年中。然而，为了解决限时服务设计问题，许多现有工作直接对总的社会成本目标函数施加了能力约束。这种“幼稚的方法”隐含地假设乘客的行为是利他的，并基于对整个系统最有利的决策。尽管在较早的工作中已经发现了这个问题，但是由于这种简化而导致的误差的大小尚未得到研究。这项工作的目的是测量此错误并了解它如何错误地代表了客流和公交车的占用率。为了衡量这一误差差距，我们采用了一种幼稚的方法来优化一组测试方案，然后采用简单的行为模型进行最终设计并获得基准乘客分配。我们提出了两个主要指标来比较这两个乘客分配：总乘客偏差和总运力不足。这种比较表明，天真的方法的分配确实确实是不现实的，并引起了人们的担忧，即基于天真的方法的网络设计在实施时可能会遇到严重的问题。因此，这项工作突显了谨慎采用朴素方法的结果并在实施之前用乘客分配模型对其进行验证的重要性。这种比较表明，天真的方法的分配确实确实是不现实的，并引起了人们的担忧，即基于天真的方法的网络设计在实施时可能会遇到严重的问题。因此，这项工作突显了谨慎采用朴素方法的结果并在实施之前用乘客分配模型对其进行验证的重要性。这种比较表明，天真的方法的分配确实确实是不现实的，并引起了人们的担忧，即基于天真的方法的网络设计在实施时可能会遇到严重的问题。因此，这项工作突显了谨慎采用朴素方法的结果并在实施之前用乘客分配模型对其进行验证的重要性。