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Urban transit networks typically consist of multiple modes and the journeys may involve a transfer within or across modes. Therefore, the passenger experience of travel time reliability is based on the whole journey experience including the transfers. Although the impact of transfers on reliability has been highlighted in the literature, the existing indicators either focus on unimodal transfers only or fail to include all components of travel time in reliability measurement. This study extends the existing “reliability buffer time” metric to transit journeys with multimodal transfers and develops a methodology to calculate it using a combination of smartcard and automatic vehicle location data. The developed methodology is applied to a real-life case study for the Amsterdam transit network consisting of bus, metro, and tram lines. By using a consistent method for all journeys in the network, reliability can be compared between different transit modes or between multiple routes for the same origin–destination pair. The developed metric can be used to study the reliability impacts of policies affecting multiple transit modes. It can also be used as an input to behavioral models such as mode, route, or departure time choice models.

Highlights Use logsum to assess impact of individual characteristics on transport equity & accessibility. Alternate formulations of logsum with and without individual characteristics are compared. Ignoring individual characteristics leads to an underestimation of variability in accessibility. Individual characteristics in logsum measures provide more insight into the causes of inequity.

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Perceived travel times of travelers are usually longer than actually realized travel times, implying that passengers’ experience of travel time savings is different from objectively calculated savings. This study provides additional empirical evidence on this topic, by comparing the passengers’ perceived travel times reported in an (online) survey with their corresponding actual in-vehicle travel times from Automatic Vehicle Location (AVL) data. The case study involves the metro, tram and bus network of Amsterdam, the Netherlands. On average, travelers perceive their travel time to be 1.9 min (11%) longer than their actual realized travel time. The perceived values match the scheduled values slightly better than the actually realized values. Furthermore, we found a larger travel time over-perception for metro compared to tram and bus. This is a counter-intuitive result, since the metro has been found to have a less negative travel time perception than busses in the public transport choice modelling literature. When the travel purpose is considered, the leisure time purposes recreation and shopping have a significantly smaller travel time over-perception than work-related journeys. Opening a new metro line did not have a significant influence on the travel time perception of travelers in Amsterdam.