Abstract: Disclosed is a method for guiding passengers of public transport, in particular of trams or trains respectively, at stations or in station areas and/or inside the transportation unit. The passengers embark and disembark in the embark-/disembark area via at least two doors, and the embark-/disembark area extends to the length of the vehicle. The method includes: generating a prediction of the occupancy level of the vehicle with regard to the resulting situation in the vehicle after disembarking at each stop; distributing of the passengers which are moving to the entry area and/or waiting in the entry area ready for embarking corresponding to the prediction to the area of the doors for an approximately uniform distribution of the passengers inside the vehicle; and if applicable, distribution of the passengers inside the vehicle under consideration of the predicted, preferably section-wise occupancy level and of the passengers actually ready for embarking.

Abstract: Disclosed is a method for guiding passengers of public transport, in particular of trams or trains respectively, at stations or in station areas and/or inside the transportation unit. The passengers embark and disembark in the embark-/disembark area via at least two doors, and the embark-/disembark area extends to the length of the vehicle. The method includes: generating a prediction of the occupancy level of the vehicle with regard to the resulting situation in the vehicle after disembarking at each stop; distributing of the passengers which are moving to the entry area and/or waiting in the entry area ready for embarking corresponding to the prediction to the area of the doors for an approximately uniform distribution of the passengers inside the vehicle; and if applicable, distribution of the passengers inside the vehicle under consideration of the predicted, preferably section-wise occupancy level and of the passengers actually ready for embarking.

Abstract: A method for planning trips to transport passengers on the basis of a preferably statistical predictive model, in particular to plan capacities, optimize the utilization of vehicle fleets, determine the routes to be taken, etc., preferably in short-distance passenger traffic, wherein the predictive model takes into account, using parameters, characteristic passenger patterns over the course of a day, week, and/or year, is characterized in that the predictive model additionally uses weather-specific parameters.

Abstract: A method for planning trips to transport passengers on the basis of a preferably statistical predictive model, in particular to plan capacities, optimize the utilization of vehicle fleets, determine the routes to be taken, etc., preferably in short-distance passenger traffic, wherein the predictive model takes into account, using parameters, characteristic passenger patterns over the course of a day, week, and/or year, is characterized in that the predictive model additionally uses weather-specific parameters.

Abstract: A machine is described for producing a knitted fabric with at least partial use of fibrous material (10), in particular a circular knitting machine (1). At least selected knitting stations (6) are assigned drawing frames (8) for producing threads (11) which are formed from the fibrous materials (10). According to the invention, the drawing frames (8) lie in the reaching area of an operator (5) working on the machine (1) and can be opened downwards (arrow v) or to the side.

Abstract: A machine is described for producing a knitted fabric with at least partial use of fibrous material (10), in particular a circular knitting machine (1). At least selected knitting stations (6) are assigned drawing frames (8) for producing threads (11) which are formed from the fibrous materials (10). According to the invention, the drawing frames (8) lie in the reaching area of an operator (5) working on the machine (1) and can be opened downwards (arrow v) or to the side.