An Investigation of the Willingness to Pay to Reduce Rail Overcrowding

By G. Whelan, J. Crockett. 2009

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Crowding valuation in urban tram and bus transportation based on smart card data (2018, methodology): “To this end, we applied the transfer inference algorithm as described by Yap et al. (2017). This algorithm is an extension on the algorithm described by Gordon et al.”
Does crowding affect the path choice of metro passengers (2015, background): “Whelan and Crockett (2009), on the other hand, used the time spent sitting and standing, the occupancy rate, i.e., the ratio of load to capacity, and the number of passenger per square meter as the criteria.”
Multimodal pricing and optimal design of urban public transport: The interplay between traffic congestion and bus crowding (2014, background): “Previous research has shown the influence of crowding and standing on increasing the value of travel time savings (e.g., Maunsell and Macdonald, 2007; Whelan and Crockett, 2009; Hensher et al., 2011; Wardman and Whelan, 2011).”
Comparing operator and users costs of light rail, heavy rail and bus rapid transit over a radial public transport network (2010, background): “9 Using a Stated Preference study, Whelan and Crockett (2009) estimate piecewise linear, power, exponential and Gompertz functions for the crowding factor, finding that the more complex functions do not yield results significantly different from the piecewise linear. waiting time cost, in-vehicle…”