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This paper uses automatic vehicle location(AVL) records to investigate the effect of weather conditions on the travel time reliability of on-road rail transit,through a case study of the Melbourne streetcar(tram) network.The datasets available were an extensive historical AVL dataset as well as weather observations.The sample size used in the analysis included all trips made over a period of five years(2006-2010 inclusive),during the morning peak(7 am-9 am) for fifteen randomly selected radial tram routes,all traveling to the Melbourne CBD.Ordinary least square(OLS) regression analysis was conducted to create a linear model,with tram travel time being the dependent variable.An alternative formulation of the model is also compared.Travel time was regressed on various weather effects including precipitation,air temperature,sea level pressure and wind speed;as well as indicator variables for weekends,public holidays and route numbers to investigate a correlation between weather condition and the on-time performance of the trams.The results indicate that only precipitation and air temperature are significant in their effect on tram travel time.The model demonstrates that on average,an additional millimeter of precipitation during the peak period adversely affects the average travel time during that period by approximately 8 s,that is,rainfall tends to increase the travel time.The effect of air temperature is less intuitive,with the model indicating that trams adhere more closely to schedule when the temperature is different in absolute terms to the mean operating conditions(taken as 15 ℃).
This paper uses automatic vehicle location (AVL) records to investigate the effect of weather conditions on the travel time reliability of on-road rail transit, through a case study of the Melbourne streetcar (tram) network. The datasets were were extensive historical AVL dataset as well as weather observations. the sample size used in the analysis includes all trips made over a period of five years (2006-2010 inclusive), during the morning peak (7 am-9 am) for fifteen randomly selected radial tram routes, all traveling to the Melbourne CBD.Ordinary least square (OLS) regression analysis was conducted to create a linear model, with tram travel time being the dependent variable. An alternative formulation of the model is also compared. Travel time was regressed on various weather effects including precipitation, air temperature, sea level pressure and wind speed; as well as indicator variables for weekends, public holidays and route numbers to investigate a correlation between weather conditions and the on-time performance of the trams. The results indicate that only precipitation and air temperatures are significant in their effect on tram travel time. The model demonstrates that on average, an additional millimeter of precipitation during the peak period adversely affects the average travel time during that period by approximately 8 s, that is, rainfall tends to increase the travel time. the effect of air temperature is less intuitive, with the model indicate that trams adhere more closely to schedule when the temperature is different in absolute terms to the mean operating conditions (taken as 15 ° C).