Citation: Rusca, F.; Rusca, A.; Rosca,
E.; Coman, C.; Burciu, S.; Oprea, C.
Evaluating the Influence of Data
Entropy in the Use of a Smart
Equipment for Traffic Management at
Border Check Point. Machines 2022,
10, 937. https://doi.org/10.3390/
machines10100937
Academic Editors: Shuai Li,
Dechao Chen, Mohammed
Aquil Mirza, Vasilios N. Katsikis,
Dunhui Xiao and Predrag
S. Stanimirovic
Received: 23 August 2022
Accepted: 13 October 2022
Published: 16 October 2022
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Article
Evaluating the Influence of Data Entropy in the Use of a Smart
Equipment for Traffic Management at Border Check Point
Florin Rusca
1,2,
* , Aura Rusca
1,2
, Eugen Rosca
1,2
, Catalin Coman
1,2
, Stefan Burciu
1
and Cristina Oprea
1
1
Faculty of Transport, University Politehnica of Bucharest, Spl Independentei, No 313,
060042 Bucharest, Romania
2
Inteligent Convergent Solutions, Washington No 39, 011793 Bucharest, Romania
* Correspondence: florin.rusca@upb.ro
Abstract:
The transit through a Border Check Point of cargo vehicles supposes, in the case of the
Romanian highway network, the carrying out of a process of weighing and verifying of transport
licenses. The limited number of weighing equipment and the long duration of these processes cause
large queues and long waiting times. A solution for these problems is to use smart equipment
to identify the cargo vehicles and to separate the vehicles that require weighing from exempted
ones. The separation process is made using external input data. The quality of received data can
generate some dysfunctionality in the separation process. The discrete simulation model can be
used to evaluate the influence of the uncertainty over the system serving parameters. A study
case is developed for a real situation using real data collected from a Romanian Highway Traffic
Control Center (HTMC). The results are used in the implementation of the new smart equipment in a
Romanian Border Check Point.
Keywords: uncertainty; traffic data; smart equipment; discrete simulation model
1. Introduction
Border Check Points (BCPs) are important for national road networks because they
ensure the connection with other national road networks. In the case of the Romanian
Highway Network, some specific processes are made for monitoring the cargo entry and
exit flows in/from the country. A scaling process is made using dedicated equipment for
all cargo vehicles. According to national legislation, it is mandatory to weigh all vehicles
from outside the European Union or the ones that exceed the maximum allowed weight.
The lack of information regarding the country of origin and their condition obliges the
national authority to carry out the weighing process for all cargo vehicles. The reduced
number of weighing equipment and, respectively, the long duration of the process, leads
to long queues of cargo vehicles. Thus, the waiting time in BCPs can increase to high
values. For the case of BCP Nadlac, analyzed in this paper, the waiting queue stretches for
approximately 10 km. Cargo vehicles are obliged to wait up to 48 h.
To reduce this negative impact of the weighing process, the introduction of specially
designed smart equipment can be a solution. The authors of this paper were asked to
design a system based on smart equipment that would allow the separation of flows of
cargo vehicles according to a set of rules established by the national authority. The input
data in the logical separation process are obtained from the system’s external sensors that
can record vehicle numbers (License Plate Recognition camera-LPR). A second flow of
input data is obtained from the Highway Traffic Management Center (HTMC). The last
flow will contain information regarding the plate number, the number of axles, the weight
on the axle and the total weight for vehicles.
The analysis of the external data flow provided by HTMC showed the existence of
some uncertainty regarding the method by which to identify cargo vehicles. The system
Machines 2022, 10, 937. https://doi.org/10.3390/machines10100937 https://www.mdpi.com/journal/machines
