Reliability is a measure of network performance that reflects the ability of the network to provide predictable travel times. Deviations from planned travel times can increase travel costs for users. To improve the system's performance, it is crucial to identify sources of unreliability, particularly the location on the network of unreliable performance. The large amount of travel time data recorded by Transportation Network Providers (TNPs) in recent years has enabled researchers to study the performance of entire networks. In this study, a real-world dataset provided by TNPs in Chicago is used to determine time of day, and day of week distribution of travel time per unit distance for origin–destination (OD) pairs. Eight measures of reliability are calculated for OD pairs in the network. Standard deviation (SD), planning time index (PTI), and on-time measure (PR) are used for a network-wide comparison of reliability performance. K-means clustering is performed on more than 21.3 million trips to divide 3,450 eligible OD pairs in the Chicago network into three groups with low, medium, and high intensity of each reliability metric. Lastly, metrics in each cluster of SD, PTI, and PR are compared. The results show that ranking PTI and PR is not sufficient for identifying unreliable/congested OD pairs in the network. Approaches for comparing reliability performance over different periods of the day for the same segment and over different segments in the network are discussed, along with network-wide measures of reliability.

可靠性是网络性能的一种度量，反映了网络提供可预测的运行时间的能力。偏离计划的旅行时间会增加用户的旅行成本。为了提高系统性能，至关重要的是找出不可靠的根源，尤其是网络上不可靠性能的位置。近年来，运输网络提供商（TNP）记录的大量旅行时间数据使研究人员能够研究整个网络的性能。在这项研究中，由TNP在芝加哥提供的真实数据集可用于确定一天中的时间以及一周中每一天相对于起点-终点（OD）的旅行时间分布。为网络中的OD对计算了八种可靠性度量。标准差（SD），计划时间指数（PTI），K-均值聚类在超过2130万次旅行中执行，将Chicago网络中的3450个合格OD对分为三个组，每个组分别具有低，中和高强度。最后，比较SD，PTI和PR的每个群集中的指标。结果显示，对PTI和PR进行排名不足以识别网络中不可靠/拥塞的OD对。讨论了用于比较一天中不同时间段内同一段和网络中不同段上的可靠性性能的方法，以及整个网络范围内的可靠性度量。