Modelling of public transport route choice adaptations to unplanned metro disruptions using smart card data

It is vital that public transport disruption mitigation strategies are supported by a clear understanding of travel behaviour and preferences, including of disrupted route choices. This paper, for the first time, uses smart card data to analyse multimodal public transport route choices immediately after being disrupted by an unplanned metro service closure while en route. We develop methodologies for identifying commuters and their usual commute route, approximating home/work locations, and identifying disrupted trips and onward post-disruption routes. These methodologies are operationalised in a case study of Lyon, France, where 5031 post-metro-disruption routes are identified, including routes taking bridging buses (bus replacement services). These route observations are used to estimate a multimodal route choice model with a detailed utility function that provides good fit to the data. Route choice preferences and behaviours are analysed and compared with those from usual commute route choices. Some of the key findings are that, post-disruption: there is a stronger dispreference for transferring and a lower dispreference for in-vehicle time, metro is less innately attractive than bus/tram, contrasting with usual commuting preferences, bridging bus is the least innately attractive mode, users have a stronger dispreference for egress time than access time (from the disrupted metro), and there is a positive preference for route robustness. Results are also compared with those from existing studies, impacts of disruptions on travel times are evaluated, and policy implications of the work are discussed.