Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 31903
An Approach for Ensuring Data Flow in Freight Delivery and Management Systems

Authors: Aurelija Burinskienė, Dalė Dzemydienė, Arūnas Miliauskas

Abstract:

This research aims at 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. When traffic density is extremely high in congestion cases, and the traffic speed is incredibly low, data transmission reaches the peak. Different data sets are generated, which depend 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; 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. In this case, a significant amount of these data is used for control operations, and the problem requires an integrated methodological approach. The paper presents an approach for providing e-services for drivers by including the assessment of the multi-component infrastructure needed for delivery of freights following the network type. The construction of such a methodology is required to evaluate data flow conditions and overloads, and to minimize the time gaps in data reporting. The results obtained show the possibilities of the proposing methodological approach to support the management and decision-making processes with functionality of incorporating networking specifics, by helping to minimize the overloads in data reporting.

Keywords: Transportation networks, freight delivery, data flow, monitoring, e-services.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 309

References:


[1] C. Woroniuk, M. Marinov, T. Zunder, and P. Mortimer, "Time series analysis of rail freight services by the private sector in Europe," Transp. Pol., 25, 2013, pp. 81-93.
[2] European Commission, "European Transport Policy for 2011: Roadmap to a single European Transport Area-Towards a Competitive and Resource Efficient Transport System," White Paper, European Commission, Brussels, 2011.
[3] D. Dzemydienė, S. Maskeliūnas, G. Dzemydaitė, A. Miliauskas, "Semi-Automatic Service Provision Based on Interaction of Data Warehouses for Evaluation of Water Resources," Informatica, 27(4), 2016, pp. 709-722.
[4] D. Dzemydienė, A. Burinskienė, A. Miliauskas, "An assessment of provision of heterogeneous services for sustainable cargo transportation process management by roads," Sustainability, 12(20), 2020, pp. 1-20.
[5] C-ITS Platform, "C ITS Platform," Final Report, 2016.
[6] S. Bock, "Real-time control of freight forwarder transportation networks by integrating multi-modal transport chains," Eur. J. of Oper. Res., 200(3), 2010, pp. 733-746.
[7] H. Sternberg, G. Prockl, and J. Holmström, "The efficiency potential of ICT in haulier operations," Comp. in Ind., 65(8), 2014, pp. 1161-1168.
[8] C-ROADS, "C-ROADS - The Platform of Harmonized C-ITS Deployment in Europe", Accessed on 15th of October 2020, https://www.c-roads.eu/platform.html
[9] C-MobILE. "C-MobILE (accelerating C-ITS Mobility Innovation and depLoyment in Europe) description of work," C-MobILE Consortium, Brussels, 2017.
[10] COOPERS, "COOPERS Co-operative Networks for Intelligent Road Safety," Final report on demonstration, 2010.
[11] SAFESPOT, Final Report, 2010.
[12] D. Dzemydienė, G. Dzemydaitė, D. Gopisetti, "Application of multi-criteria decision aid for evaluation of ICT usage in business," Cent. Eur. Jour. of Oper. Res., 2020, pp. 1-21.
[13] I. Harris, Y. Wang, and H. Wang, "ICT in multi-modal transport and technological trends: Unleashing potential for the future," Int. J. of Prod. Econ., 159, 2015, pp. 88-103.
[14] B. Royo, A. Fraile, E. Larrodé, and V. Muerza, "Route planning for a mixed delivery system in long distance transportation and comparison with pure delivery systems," J. of Computat. and App. Math., 291, 2016, pp. 488-496.
[15] T. G., Crainic, and B. Montreuil, “Physical internet enabled hyperconnected city logistics”, Trans. Res. Procedia, 12, 2016, pp. 383-398.
[16] Y. Fan, B. Behdani, J. Bloemhof-Ruwaard, and R. Zuidwijk, "Flow consolidation in hinterland container transport: An analysis for perishable and dry cargo," Transp. Res. Part E: Log. and Transp. Rev., 130, 2019, pp. 128-160.
[17] S. Cepolina, and H. Ghiara, "New trends in port strategies. Emerging role for ICT infrastructures," Res. in Transp. Bus. & Man., 8, 2013, pp. 195-205.
[18] K. Sörensen, C. Vanovermeire, and S. Busschaert, "Efficient metaheuristics to solve the intermodal terminal location problem," Comp. & Oper. Res., 39(9), 2012, pp. 2079-2090.
[19] S. Tadić, M. Krstić, and N. Brnjac, "Selection of efficient types of inland intermodal terminals," J. of Transp. Geog., 78, 2019, pp. 170-180.
[20] M. Janic, "An assessment of the performance of the European long intermodal freight trains (LIFTS)," Transp. Res. Part A: Polic. and Pract., 42(10), 2008, pp. 1326-1339.
[21] A. Kengpol, W. Meethom, and M. Tuominen, "The development of a decision support system in multi-modal transportation routing within Greater Mekong sub-region countries," Int. j. of Prod. Econ., 140(2), 2012, pp. 691-701.
[22] OECD, "Goods transport database", Accessed on 20th of August 2020, https://stats.oecd.org/Index.aspx?DataSetCode=ITF_GOODS_TRANSPORT.