An approach for ensuring data flow in freight delivery and management system

Abstract

This research is intended in developing the approach for more effective freight delivery and transportation process management. The road congestions and the identification of causes are important, as well as the context information recognition and management. The measure of many parameters during the transportation period and proper control of driver work became the problem. The number of vehicles per time unit passing at a given time and point for drivers can be evaluated in some situations. The collection of data is mainly used to establish new trips. The flow of the data is more complex in urban areas. Herein, the movement of freight is reported in detail, including the information on street level. In congestion case, when traffic density is extremely high, and the speed of traffic is incredibly low, the transmission of data reaches the peak. The different data sets are generated, the size of which depends on the type of freight delivery network. There are three types of networks: long-distance delivery networks, last-mile delivery networks and mode-based delivery networks, when the last one includes different modes, in particular, railways and other networks. When freight delivery is switched from one type of the above-stated network to another, more data could be included for reporting purposes and vice versa. However, the new tendencies show that the number of data flows generated by freight traffic will be increased by more than 50% and the transfer of data will become an even more serious issue in the coming years when now. In case, the significant amount of this data is used for control operations, and the problem requires an integrated methodological approach. The paper presents the approach for providing e-services for drivers by including the assessment of multi-component infrastructure needed for delivery of freights following the network type. The construction of such methodology is required seeking to evaluate data flow conditions and overloads and to minimize the time gaps in data reporting. The results obtained show that methodological approach still supports the management in decision-making when such incorporates network specifics and helps to minimize the overloads in data reporting.