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MODEL OF TRAM LINE OPERATION
(2006)

From passenger's perspective punctuality is one of the most important features of trams operations. Unfortunately in most cases this feature is only insufficiently fulfilled. In this paper we present a simulation model for trams operation with special focus on punctuality. The aim is to get a helpful tool for designing time-tables and for analyzing the effects by changing priorities for trams in traffic lights respectively the kind of track separation. A realization of trams operations is assumed to be a sequence of running times between successive stops and times spent by tram at the stops. In this paper the running time is modeled by the sum of its mean value and a zero-mean random variable. With the help of multiple regression we find out that the average running time is a function depending on the length of the sections and the number of intersections. The random component is modeled by a sum of two independent zero-mean random variables. One of these variables describes the disturbance caused by the process of waiting at an intersection and the other the disturbance caused by the process of driving. The time spent at a stop is assumed to be a random variable, too. Its distribution is estimated from given measurements of these stop times for different tram lines in Kraków. Finally a special case of the introduced model is considered and numerical results are presented. This paper is involved with CIVITAS-CARAVEL project: "Clean and better transport in cites". The project has received research funding from the Community's Sixth Framework Programme. The paper reflects only the author's views and the Community is not liable for any use that may be made of the information contained therein.

From passenger’s perspective, punctuality is one of the most important features of tram route operation. We present a stochastic simulation model with special focus on determining important factors of influence. The statistical analysis bases on large samples (sample size is nearly 2000) accumulated from comprehensive measurements on eight tram routes in Cracow. For the simulation, we are not only interested in average values but also in stochastic characteristics like the variance and other properties of the distribution. A realization of trams operations is assumed to be a sequence of running times between successive stops and times spent by tram at the stops divided in passengers alighting and boarding times and times waiting for possibility of departure . The running time depends on the kind of track separation including the priorities in traffic lights, the length of the section and the number of intersections. For every type of section, a linear mixed regression model describes the average running time and its variance as functions of the length of the section and the number of intersections. The regression coefficients are estimated by the iterative re-weighted least square method. Alighting and boarding time mainly depends on type of vehicle, number of passengers alighting and boarding and occupancy of vehicle. For the distribution of the time waiting for possibility of departure suitable distributions like Gamma distribution and Lognormal distribution are fitted.