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11 July 2025

Research and Analysis of Traffic Intensity on a Street with High Traffic Load: Case Study of the City of Sofia †

,
and
Department of Combustion Engines, Automobile Engineering and Transport, Faculty of Transport, Technical University of Sofia, 8 St. Kliment Ohridski, 1000 Sofia, Bulgaria
*
Author to whom correspondence should be addressed.
†
Presented at the 14th International Scientific Conference TechSys 2025—Engineering, Technology and Systems, Plovdiv, Bulgaria, 15–17 May 2025.
Eng. Proc.2025, 100(1), 37;https://doi.org/10.3390/engproc2025100037
This article belongs to the Proceedings The 14th International Scientific Conference TechSys 2025—Engineering, Technologies and Systems
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Abstract

The study of traffic parameters in cities is the basis for making adequate decisions related to the organization and regulation of traffic. This publication presents a study of one of the main parameters of transport flows, namely, its intensity. The study covers one of the busiest streets in the city of Sofia, which is part of the radial connection in the radial circular street network of the city, for the evening peak period of the day. Data analysis presents the influence of the intensity of transport flows at the intersections, which are formed by the intersection with other streets, on the load of the studied street. The share of the load of each transport flow at the individual intersections on the total load of the studied section was recorded for the subsequent assessment of the existing traffic management. The results have been provided to the relevant directorates in the structure of Sofia Municipality for information and use.

1. Introduction

Road traffic in cities is the subject of continuous research and analysis of the processes taking place. This is necessitated by the fact that all activities related to the introduction of a new organization, the reorganization of traffic in cities, determining the method of regulation, and the overall management of these processes depend on the values of the studied indicators. This is the reason why such studies are carried out in all parts of the world, as evidenced by the results presented by the authors of the studies in Vilnius, Lithuania [1] and Dhaka, Bangladesh [2]. This shows the comprehensiveness of the understanding of the need for such data in each country. An important issue in these studies was raised by Sayed et al. [2], emphasizing the importance of providing data for real-time measurements, which leads to timely decisions related to optimizing road traffic. This is also necessitated by the fact that some parameters are strongly influenced by all kinds of external factors. Meteorological conditions are such a factor, and researchers are constantly looking for the most accurate possible relationships between them and traffic parameters, especially in connection with changes in the intensity of traffic flows [3]. Others have also paid attention to the fact that changing one of these parameters leads to changes in others, in which particular attention is paid to the influence of traffic intensity on the number of vehicles that can pass through a certain section of the street network in a certain time [4]. Choudhury and Basak [5] and Singh et al. [6] use the theory of queues to assess the impact of traffic intensity on the processes in it, which other authors also use to assess its influence on the process of work at points important for the economy and security of the state [7]. This shows the many possibilities for determining and assessing traffic parameters using different approaches, theories, and models.
The main aspect of carrying out research related to establishing the necessary information about traffic parameters is the way in which it is carried out and, in particular, the technical means for achieving the goals. Here too, the possibilities are many, as evidenced by their diversity in numerous publications on the subject. Myat et al. presented an alternative to loop detectors, cameras, and radars using microphones and air quality sensors [8]. The authors of [9] proposed a similar approach, supplementing the development with an improvement in the Doppler sensor for recording the speed of vehicles. Other authors have proposed the use of IR sensors to determine the intensity of transport flows [10]. This approach can be supplemented by taking into account the reduction in the cost of their use, which is the essence of the proposal in [8], using systems developed by the authors in [11] from other areas of our life, which can be successfully applied in these studies. The main technologies used are image acquisition and subsequent processing to achieve the research goals. Grozev and Beloev [12] proposed the use of unmanned aerial vehicles for what in recent years has been established as a preferred method for some studies of transport flows. In addition, the necessary software products for the use of such images have also been proposed, such as the one presented by Dmyanov [13]. Maduro et al. [14], in turn, propose the use of corrected images to determine the speed of vehicles and the intensity of transport flows. The improvement of image acquisition technologies and their subsequent processing can be achieved by applying the developed methods, such as those presented by the authors in [15,16]. In the process of studying road traffic, the establishment of the parameters of pedestrian flows should not be neglected. Here, the developed methods and models for their safe crossing [17] should be taken into account, which are directly dependent on their defined critical speed, depending on the visibility zone [18] and their influence on the occurrence of road accidents [19]. For such a connection with the set goals, some authors, such as Miletiev et al. [20], propose a system for comprehensive monitoring of such intelligent transport systems, which uses artificial intelligence, which has already become an integral part of our lives.
Comprehensive solutions using traffic data provide several benefits for people. These include reducing travel time and traffic congestion [21,22]. Others combine the overall improvements achieved based on traffic research with a particularly high goal of reducing pollution from cars in cities. In this regard, Roosbroeck et al. [23] showed the influence of traffic intensity on pollution. In turn, Dimitrov and Damyanov [24,25] presented studies related to the change in the temperature of the exhaust gases of a gasoline-powered car and the temperature of car tires under different operating modes. This, in turn, can affect the level of harmful components emitted in the exhaust gases and fine dust particles emitted by car tires. This is directly related to the definition of risk zones in terms of air pollution from transport in cities. Based on such studies and those related to determining traffic parameters, the European Commission found a reduction in the harmful impact of transport [26]. As noted in this report, transportation is not a major source of pollution. Other sectors of the economy also contribute significantly to overall pollution, which is also a major reason for the energy transition in the Republic of Bulgaria and a reduction in the use of coal for electricity generation, for which the authors of [27] propose appropriate approaches.
Despite the impact of high traffic intensity on the overall life of people and its impact on indicators related to travel times, traffic congestion, pollution from transport, and others, it remains a key indicator that shows economic activity in the relevant regions and large cities [28].

2. Materials and Methods

The study of traffic may include determining the parameters of one or more of its indicators, such as the intensity, speed, density, and composition of transport and pedestrian flows, throughput capacity of street intersections and road junctions, identification of transport delays, and analysis of traffic accidents.
The present study is focused on establishing the values of the intensity of transport flows along one of the main streets in the city of Sofia. This is Simeonovsko Shose Blvd. It is part of a radial connection in the radial-circular street network of the city of Sofia, as a continuation of Stoyan Mihaylovski St. and connects the central part of the city with the outer ring of the Capital, formed by Okolovrasten Pat Str. (Figure 1).
Figure 1. Location of the surveyed part of the street network [29].
The studied section is 4.5 km long. It also includes part of Stoyan Mihaylovski Street at its intersection with Peyo K. Yavorov Blvd. The section intersects with other streets in the city’s street network at 23 different locations. The intersections formed by these intersections are mainly at one level, with the exception of two: the intersection with Okolovrasten Pat Street, where the intersection is organized at two levels with traffic light regulation on one level, and the intersection of Stoyan Mihaylovski Street with Peyo K. Yavorov Blvd., which is the beginning of the studied section. There are seven more intersections that are regulated by traffic lights. The rest have priority signs, with priority given to Simeonovsko Shose Blvd. as a higher-class street.
For the purposes of this study, the number of vehicles was counted from Peyo K. Yavorov Blvd. to Okolovrasten Pat St. between the intersections where traffic lights were used (Figure 2). This is assumed from the fact that the remaining intersections do not have a significant impact on the intensity of the studied section due to their low intensity on secondary streets, as proven by preliminary observations.
Figure 2. Layout diagram of the surveyed areas.
The designated sections for reporting the intensity of traffic flow are as follows:
-
Part 1—between Peyo K. Yavorov Blvd. and Nikola Gabrovski St.;
-
Part 2—between Nikola Gabrovski St. and Filip Kutev St. (Doctor G. M. Dimitrov Blvd.);
-
Part 3—between Filip Kutev St. (Doctor G. M. Dimitrov Blvd.) and Ekaterina Nedelcheva St.;
-
Part 4—between Ekaterina Nedelcheva St. and 21st Century St.;
-
Part 5—between 21st Century St. and Asen Raztsvetnikov St.;
-
Part 6—between Asen Raztsvetnikov St. and Prof. Vasil Arnaudov St. (Prof. Dr. Ivan Stranski St.);
-
Part 7—between “Prof. Vasil Arnaudov (Prof. Dr. Ivan Stranski St.) and “Yordan Radichkov St.” (Georgi Rusev St.) and
-
Part 8—between”Yordan Radichkov St. (Georgi Rusev St.) and Okolovrasten Pat St.
Traffic intensity was measured during the evening peak period between 17:00 and 18:00 on weekdays in April 2024. Preliminary studies have shown that the evening peak period has higher values than the morning peak, but with a shorter duration. This is the reason for the choice of the period and duration of the measurement. This includes determining the number of vehicles passing through the designated part of the studied section in different directions of movement. The measurements were carried out directly by an observer trained to perform them and record the data in a specially made form for this purpose (Appendix A.1). The composition of the vehicles was recorded during the study. This is caused by the passage of public transport, which consists of different types of buses, along the studied section, and its use for the passage of trucks to the neighborhoods that it connects. Therefore, the results are presented in reduced units. The composition of the vehicles was recorded using the types of vehicles defined in the regulatory framework of the Republic of Bulgaria with the relevant equivalence coefficients, as shown in Table 1.
Table 1. Coefficient of equalization 1 [30].
During the measurements, the passing vehicles were distributed in five-minute intervals to determine the unevenness of the intensity within the studied hour.
To determine the influence of the traffic load of individual traffic light-regulated intersections on the traffic intensity of individual parts of the studied section and to determine the intensity of the traffic flows that have the greatest impact on its load, traffic flow intensity values were determined for each intersection. A method with video recording of the intersection and profile counting for a period of 15 min during the evening peak period was used. For this purpose, the traffic flows of the traffic light-regulated intersections were designated by numbering consecutive intersections, as shown in Figure 3.
Figure 3. Numbering of traffic flows at traffic-light-controlled intersections in the studied area.

3. Results

After the observations and data processing, the following results were obtained for the transport flow intensity in the parts of the studied section indicated in Figure 1 by direction, as shown in Table 2.
Table 2. Results of the measurement to establish the intensity of transport flows in the individual parts of the studied section.
The values with detailed results, which also show the relationship between the composition of the transport flows and the results shown in Table 2, are presented in Appendix A.2.
The traffic loads at the individual intersections in the study area are presented in Table 3, Table 4 and Table 5. The results are averaged for one hour of the peak period. The detailed measurement data are presented in Appendix A.3.
Table 3. Measurement results for determining the traffic load at intersections 9, 10, and 11.
Table 4. Measurement results for determining the traffic load at intersections 12, 13, and 14.
Table 5. Measurement results for determining the traffic load at intersections 15, 16, and 17.

4. Discussion

The load on each part of the studied section is uniform in both directions, as can be seen from the results shown in Table 2. The exception is the section between Yordan Radichkov Street (Georgi Rusev Street) and Okolovrasten Pat Street, for which a difference of over 25% is observed in favor of those traveling from Okolovrasten Pat Street. This is mainly due to the larger number of vehicles that arrive from Okolovrasten Pat Street but deviate at the first intersection (Intersection 16), which can be explained by the preferred route of returning home for the residents of the neighborhood. This is also seen from the small number of vehicles arriving in the neighborhood, from the flow 15-16-06.
The data analysis shows that the parts of the studied section with the highest intensity values are between Peyo K. Yavorov Blvd. and Nikola Gabrovski St. (Part 1) and between Prof. Vasil Arnaudov St. (Prof. Dr. Ivan Stranski St.) and Okolovrasten Pat St. (Part 7 and Part 8). They differ in the load from the other parts by over 35%, with the busiest part (Part 1) reaching differences of over 80%. This is also due to the preferred routes of residents and workers in the neighborhoods along whose extension the studied section passes. For the other parts, it is striking that the intensity of the transport flows is relatively the same, with values of around 1000 PCU/h. This leads us to assume that the transport load of the individual intersections that form the parts of the studied section does not affect their load or that the transport flows that leave and enter these parts are of relatively equal intensity.
The influence of traffic flow from individual intersections on the loading of the sections in the studied section is expressed as follows:
-
The loading of Section 1 in the direction of Okolovrasten Pat Street is formed mainly by flows 01-09-10, which determines about 50% of the intensity in this direction of the section. It is noticeable that in the other direction, about 40% of the loading is formed by the flow coming from Nikola Gabrovski Street 02-10-09. In addition, there is no significant outflow of cars from flow 11-10-02, which is the reason for the significant increase in the value of the intensity of the traffic flow in this section.
-
The loading of Section 2 in the direction of Okolovrasten Pat Street, the cars coming from Nikola Gabrovski Street (flow 02-10-11), are about 10% of the loading of this section. In the direction of Peyo K. Yavorov Blvd., the same trend is observed with the incoming vehicles from flows 03-11-10 and 20-11-10. Observations show that the outflow of vehicles at Intersection 10 from flow 09-10-02 is significant, which is the reason for the reduction in the load in this part compared with Part 1.
-
The loads of parts 3, 4, 5, and 6 are characterized by the same trend, whereby, in both directions, they are formed by incoming flows within 10-15% of the total load. The outgoing flows at these intersections were in the same range as the total load. This is also the reason for the relatively equal values of the intensity of transport flows in these parts.
-
The intensity of the transport flows at Intersection 15, similar to Intersection 10, has an extremely high impact on the load of the individual parts before and after it. It turns out that about 50% of the flow in section 7 towards Peyo K. Yavorov Blvd. flows into this intersection (flow 16-15-05). However, approximately 40% of the load in Section 7 towards Okolovrasten pat Str. is formed by the incoming vehicles from flow 05-15-16. These facts contribute to the reduction of the intensity in Section 6 towards Peyo K. Yavorov Blvd., compared to the load in Section 7, as well as the reason for the increase in the intensity of the transport flows in Section 7 towards Okolovrasten pat Str.
The analysis of the unevenness of the intensity of the transport flows in the individual parts shows that the difference for the divided periods of five minutes within the studied hour varies between 30% and 40%. An exception to this is the transport flow from Part 3 in the direction of Peyo K. Yavorov Street, where the difference is smaller, within about 20%.

5. Conclusions

The study of the transport load on the section between Peyo K. Yavorov Blvd. and Okolovrasten Pat Str. shows the results that need to be used to improve the organization and regulation of traffic through the considered radial connection of the street network of the city of Sofia.
The results provide grounds for revising the number and type of phases of traffic-light-regulated intersections, which should be in line with the main directions of traffic flows. In this case, it is necessary to pay attention to the organization of traffic, which should provide the necessary lanes for them, which may lead to the reconstruction of some intersections. This will certainly lead to a revision of the operating times for individual signals and the compilation of new time diagrams. In this regard, and given the reported unevenness of traffic flows within the studied hour, it is necessary to build adaptive signal regulation of all traffic light-regulated intersections, some of which are included in such a traffic management system in the city.
The measured data and subsequent analysis were provided to the Municipality of Sofia for review and as a basis for making adequate decisions to improve traffic on the surveyed section.

Author Contributions

All authors contributed equally to achieve the results presented in this publication. Conceptualization: D.S., G.M. and P.P.; methodology: D.S., G.M. and P.P.; investigation: D.S., G.M. and P.P.; formal analysis: D.S. and G.M.; writing—original draft preparation: D.S.; writing—review and editing: G.M. and P.P.; visualization: D.S. and G.M. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

Not applicable.

Data Availability Statement

The data is contained within the article.

Acknowledgments

The authors thank the Research and Development Sector at the Technical University of Sofia for financial support.

Conflicts of Interest

The authors declare no conflicts of interest.

Appendix A

Appendix A.1

A form was developed for recording the results of the study.
Table A1. Form for recording the results of the study.
Table A1. Form for recording the results of the study.
Types of Vehicles/Intervals, minPassenger Car, Including Ambulance, Light Commercial Vehicle with Payload up to 800 kg, Minibus up to 12 Seats and SimilarMoped, CyclistMotorcycleTruck with Payload up to 5 t, Minibus over 12 SeatsTruck with a Payload of over 5 tBus or TrolleybusTractor Unit with Trailer, Articulated Bus or TrolleybusIntensity, VehIntensity, PCU
0–5
5–10
10–15
15–20
20–25
25–30
30–35
35–40
40–45
45–50
50–55
55–60
Total

Appendix A.2

The results of the study on the intensity of transport flows in the individual parts of the studied section.
Table A2. Traffic flow intensity from part 1 in the direction of Okolovrasten Pat Street.
Table A2. Traffic flow intensity from part 1 in the direction of Okolovrasten Pat Street.
Types of Vehicles/Intervals, minPassenger Car, Including Ambulance, Light Commercial Vehicle with Payload up to 800 kg, Minibus up to 12 Seats and SimilarMoped, CyclistMotorcycleTruck with Payload up to 5 t, Minibus over 12 SeatsTruck with a Payload of over 5 tBus or TrolleybusTractor Unit with Trailer, Articulated Bus or TrolleybusIntensity, VehIntensity, PCU
0–5151002001154156.5
5–10183101101187191.3
10–15132000202136143
15–20116004102123133.5
20–25154012001158162
25–30128001001130133.5
30–35167010102172177
35–40107100011110113.8
40–45135023101142148
45–50129102102135142.8
50–55147000203152162.5
55–60174001001176179.5
Total 17751843.4
Table A3. Traffic flow intensity from Part 1 in the direction of Peyo K. Yavorov Blvd.
Table A3. Traffic flow intensity from Part 1 in the direction of Peyo K. Yavorov Blvd.
Types of Vehicles/Intervals, minPassenger Car, Including Ambulance, Light Commercial Vehicle with Payload up to 800 kg, Minibus up to 12 Seats and SimilarMoped, CyclistMotorcycleTruck with Payload up to 5 t, Minibus over 12 SeatsTruck with a Payload of over 5 tBus or TrolleybusTractor Unit with Trailer, Articulated Bus or TrolleybusIntensity, VehIntensity, PCU
0–5121001202126135
5–10175002300180186.5
10–15140000003143150.5
15–20117012101121125
20–25123000002125130
25–30105103002111118.3
30–35136001101139144
35–40114010001116118
40–45107002102112120.5
45–50154104201163170.8
50–55148016000155160.5
55–60127013102134143
Total 16251702.1
Table A4. Traffic flow intensity from Part 2 in the direction of Okolovrasten Pat Street.
Table A4. Traffic flow intensity from Part 2 in the direction of Okolovrasten Pat Street.
Types of Vehicles/Intervals, minPassenger Car, Including Ambulance, Light Commercial Vehicle with Payload up to 800 kg, Minibus up to 12 Seats and SimilarMoped, CyclistMotorcycleTruck with Payload up to 5 t, Minibus over 12 SeatsTruck with a Payload of over 5 tBus or TrolleybusTractor Unit with Trailer, Articulated Bus or TrolleybusIntensity, VehIntensity, PCU
0–5981000009998.3
5–10781320108586.8
10–15691010107377.8
15–20760030007982
20–25700111007375
25–30940100009594.5
30–35118120001122122.8
35–40960010009798
40–45740121007881
45–50811000108384.3
50–55740110007676.5
55–60910011009395.5
Total 10531072.5
Table A5. Traffic flow intensity from Part 2 in the direction of Peyo K. Yavorov Blvd.
Table A5. Traffic flow intensity from Part 2 in the direction of Peyo K. Yavorov Blvd.
Types of Vehicles/Intervals, minPassenger Car, Including Ambulance, Light Commercial Vehicle with Payload up to 800 kg, Minibus up to 12 Seats and SimilarMoped, CyclistMotorcycleTruck with Payload up to 5 t, Minibus over 12 SeatsTruck with a Payload of over 5 tBus or TrolleybusTractor Unit with Trailer, Articulated Bus or TrolleybusIntensity, VehIntensity, PCU
0–5780120008182.5
5–10601111006465.3
10–15810021008487.5
15–20630002106671
20–25640210006767
25–30650110006767.5
30–35891100009189.8
35–40862000008886.6
40–45751020007879.3
45–50640211006871.5
50–55701000007170.3
55–60831100108686.8
Total 911925.1
Table A6. Traffic flow intensity from Part 3 in the direction of Okolovrasten Pat Street.
Table A6. Traffic flow intensity from Part 3 in the direction of Okolovrasten Pat Street.
Types of Vehicles/Intervals, minPassenger Car, Including Ambulance, Light Commercial Vehicle with Payload up to 800 kg, Minibus up to 12 Seats and SimilarMoped, CyclistMotorcycleTruck with Payload up to 5 t, Minibus over 12 SeatsTruck with a Payload of over 5 tBus or TrolleybusTractor Unit with Trailer, Articulated Bus or TrolleybusIntensity, VehIntensity, PCU
0–5920100109495.5
5–10104011000106106.5
10–15800110118489
15–20890230009496
20–25860210119195.5
25–309700101099102
30–35912000009391.6
35–40851100018889.3
40–45102011100105107
45–50920010109497
50–55891000019192.8
55–60841100108787.8
Total 11261150
Table A7. Traffic flow intensity from Part 3 in the direction of Peyo K. Yavorov Blvd.
Table A7. Traffic flow intensity from Part 3 in the direction of Peyo K. Yavorov Blvd.
Types of Vehicles/Intervals, minPassenger Car, Including Ambulance, Light Commercial Vehicle with Payload up to 800 kg, Minibus up to 12 Seats and SimilarMoped, CyclistMotorcycleTruck with Payload up to 5 t, Minibus over 12 SeatsTruck with a Payload of over 5 tBus or TrolleybusTractor Unit with Trailer, Articulated Bus or TrolleybusIntensity, VehIntensity, PCU
0–5820300008583.5
5–10740121007881
10–15101012100105108
15–20762140008385.1
20–25692141117987.1
25–30750201107981.5
30–35700111027582
35–40811100008381.8
40–45771011108082.3
45–50720100017476
50–55830120108790.5
55–60882010019294.1
Total 10001032.9
Table A8. Traffic flow intensity from Part 4 in the direction of Okolovrasten Pat Street.
Table A8. Traffic flow intensity from Part 4 in the direction of Okolovrasten Pat Street.
Types of Vehicles/Intervals, minPassenger Car, Including Ambulance, Light Commercial Vehicle with Payload up to 800 kg, Minibus up to 12 Seats and SimilarMoped, CyclistMotorcycleTruck with Payload up to 5 t, Minibus over 12 SeatsTruck with a Payload of over 5 tBus or TrolleybusTractor Unit with Trailer, Articulated Bus or TrolleybusIntensity, VehIntensity, PCU
0–5103000000103103
5–10980100009998.5
10–15970200009998
15–20105010011108112
20–259400210198104
25–30741020107881.3
30–35900211009495.5
35–40830111008688
40–4597000111100106
45–50102100000103102.3
50–55107022001112115.5
55–60790020108286
Total 11621190.1
Table A9. Traffic flow intensity from Part 4 in the direction of Peyo K. Yavorov Blvd.
Table A9. Traffic flow intensity from Part 4 in the direction of Peyo K. Yavorov Blvd.
Types of Vehicles/Intervals, minPassenger Car, Including Ambulance, Light Commercial Vehicle with Payload up to 800 kg, Minibus up to 12 Seats and SimilarMoped, CyclistMotorcycleTruck with Payload up to 5 t, Minibus over 12 SeatsTruck with a Payload of over 5 tBus or TrolleybusTractor Unit with Trailer, Articulated Bus or TrolleybusIntensity, VehIntensity, PCU
0–597013120104112
5–1096111001100102.3
10–15850150109298.5
15–20840330119298
20–25111021000114114
25–30821120008686.8
30–35751400108180.3
35–40830111018791.5
40–45840000008484
45–50770100107980.5
50–559110310197103.3
55–60870120109194.5
Total 11071145.7
Table A10. Traffic flow intensity from Part 5 in the direction of Okolovrasten Pat Street.
Table A10. Traffic flow intensity from Part 5 in the direction of Okolovrasten Pat Street.
Types of Vehicles/Intervals, minPassenger Car, Including Ambulance, Light Commercial Vehicle with Payload up to 800 kg, Minibus up to 12 Seats and SimilarMoped, CyclistMotorcycleTruck with Payload up to 5 t, Minibus over 12 SeatsTruck with a Payload of over 5 tBus or TrolleybusTractor Unit with Trailer, Articulated Bus or TrolleybusIntensity, VehIntensity, PCU
0–5880120119399
5–1096103000100102.3
10–15740210117983.5
15–20930110009595.5
20–25102001011105110.5
25–30890000008989
30–35680000106971
35–40741100017778.3
40–45911020109598.3
45–50630010016568.5
50–55771100007977.8
55–60641020116972.8
Total 1014976.5
Table A11. Traffic flow intensity from Part 5 in the direction of Peyo K. Yavorov Blvd.
Table A11. Traffic flow intensity from Part 5 in the direction of Peyo K. Yavorov Blvd.
Types of Vehicles/Intervals, minPassenger Car, Including Ambulance, Light Commercial Vehicle with Payload up to 800 kg, Minibus up to 12 Seats and SimilarMoped, cyclistMotorcycleTruck with Payload up to 5 t, Minibus over 12 SeatsTruck with a Payload of over 5 tBus or TrolleybusTractor Unit with Trailer, Articulated Bus or TrolleybusIntensity, VehIntensity, PCU
0–5910011109498.5
5–10107120101112114.3
10–15681121007375.3
15–20860000028893
20–259202201097100
25–30700111017478.5
30–35810010118489.5
35–40751100007575.8
40–45690111017377.5
45–50821010118690.8
50–55900100009190.5
55–60662010107071.6
Total 10171055.3
Table A12. Traffic flow intensity from Part 6 in the direction of Okolovrasten Pat Street.
Table A12. Traffic flow intensity from Part 6 in the direction of Okolovrasten Pat Street.
Types of Vehicles/Intervals, minPassenger Car, Including Ambulance, Light Commercial Vehicle with Payload up to 800 kg, Minibus up to 12 Seats and SimilarMoped, CyclistMotorcycleTruck with Payload up to 5 t, Minibus over 12 SeatsTruck with a Payload of over 5 tBus or TrolleybusTractor Unit with Trailer, Articulated Bus or TrolleybusIntensity, VehIntensity, PCU
0–5740111218088.5
5–10100000120103108.5
10–15770421118692
15–20792000018283.1
20–25571310106363.8
25–30580220116469.5
30–35641201106970.8
35–40700120017478
40–45711000207477.3
45–50641100006664.8
50–55590211016468
55–60670120117278
Total 897942.3
Table A13. Traffic flow intensity from Part 6 in the direction of Peyo K. Yavorov Blvd.
Table A13. Traffic flow intensity from Part 6 in the direction of Peyo K. Yavorov Blvd.
Types of Vehicles/Intervals, minPassenger Car, Including Ambulance, Light Commercial Vehicle with Payload up to 800 kg, Minibus up to 12 Seats and SimilarMoped, CyclistMotorcycleTruck with Payload up to 5 t, Minibus over 12 SeatsTruck with a Payload of over 5 tBus or TrolleybusTractor Unit with Trailer, Articulated Bus or TrolleybusIntensity, VehIntensity, PCU
0–5690040107480
5–10780320108486.5
10–15831221008990.8
15–20610120206671.5
20–25821311108991.3
25–309202211098102.5
30–35781111118489.8
35–409001300195100
40–45843001108990.4
45–50880320109496.5
50–55820001018488
55–609410201199104.8
Total 10451092.1
Table A14. Traffic flow intensity from part 7 in the direction of Okolovrasten Pat Street.
Table A14. Traffic flow intensity from part 7 in the direction of Okolovrasten Pat Street.
Types of Vehicles/Intervals, minPassenger Car, Including Ambulance, Light Commercial Vehicle with Payload up to 800 kg, Minibus up to 12 Seats and SimilarMoped, CyclistMotorcycleTruck with Payload up to 5 t, Minibus over 12 SeatsTruck with a Payload of over 5 tBus or TrolleybusTractor Unit with Trailer, Articulated Bus or TrolleybusIntensity, VehIntensity, PCU
0–5112004001117123.5
5–10142002010145149
10–15108002010111115
15–20901000009190.3
20–25780020108185
25–30130004010135141
30–35124011100127129
35–40118100000119118.3
40–45130031101136139.5
45–50128021011133137.5
50–55119111110124127.3
55–60122004001127133.5
Total 14461488.9
Table A15. Traffic flow intensity from Part 7 in the direction of Peyo K. Yavorov Blvd.
Table A15. Traffic flow intensity from Part 7 in the direction of Peyo K. Yavorov Blvd.
Types of Vehicles/Intervals, minPassenger Car, Including Ambulance, Light Commercial Vehicle with Payload up to 800 kg, Minibus up to 12 Seats and SimilarMoped, CyclistMotorcycleTruck with Payload up to 5 t, Minibus over 12 SeatsTruck with a Payload of over 5 tBus or TrolleybusTractor Unit with Trailer, Articulated Bus or TrolleybusIntensity, VehIntensity, PCU
0–5141002100144147.5
5–10118000010119121
10–15103000000103103
15–20132002121138148
20–25119011030124130.5
25–30110121110116118.8
30–35131004101137145
35–40102021001106108.5
40–4597111200102104.8
45–50128021020133137
50–55117012101122127.5
55–60136002010139143
Total 14831534.6
Table A16. Traffic flow intensity from part 8 in the direction of Okolovrasten Pat Street.
Table A16. Traffic flow intensity from part 8 in the direction of Okolovrasten Pat Street.
Types of Vehicles/Intervals, minPassenger Car, Including Ambulance, Light Commercial Vehicle with Payload up to 800 kg, Minibus up to 12 Seats and SimilarMoped, CyclistMotorcycleTruck with Payload up to 5 t, Minibus over 12 SeatsTruck with a Payload of over 5 tBus or trolleybusTractor Unit with Trailer, Articulated Bus or TrolleybusIntensity, VehIntensity, PCU
0–5127014000132135.5
5–10125001000126127
10–15101022011107112.5
15–2097011010100102.5
20–258710411094100.8
25–30871011009091.8
30–35117013111124132.5
35–40121000000121121
40–4595013100100104
45–50103001000104105
50–55114112010119121.8
55–60860201008989.5
Total 13061343.9
Table A17. Traffic flow intensity from Part 8 in the direction of Peyo K. Yavorov Blvd.
Table A17. Traffic flow intensity from Part 8 in the direction of Peyo K. Yavorov Blvd.
Types of Vehicles/Intervals, minPassenger Car, Including Ambulance, Light Commercial Vehicle with Payload up to 800 kg, Minibus up to 12 Seats and SimilarMoped, CyclistMotorcycleTruck with Payload up to 5 t, Minibus over 12 SeatsTruck with a Payload of over 5 tBus or TrolleybusTractor Unit with Trailer, Articulated Bus or TrolleybusIntensity, VehIntensity, PCU
0–5118012100122125
5–10148001110151155.5
10–15161002010164168
15–20165002010168172
20–25137022000141142
25–30154002210159166
30–35111011010114116.5
35–40132113000137138.8
40–45114001000115116
45–50127011110131135
50–55136001000137138
55–60142003110147153.5
Total 16861726.3

Appendix A.3

Results of the study on the traffic load of the traffic light-controlled intersections in the study area.
Table A18. Traffic flow intensity at intersection 9.
Table A18. Traffic flow intensity at intersection 9.
Types of Vehicles/Traffic Flow NumberPassenger Car, Including Ambulance, Light Commercial Vehicle with Payload up to 800 kg, Minibus up to 12 Seats and SimilarMoped, CyclistMotorcycleTruck with Payload up to 5 t, Minibus over 12 SeatsTruck with a Payload of over 5 tBus or TrolleybusTractor Unit with Trailer, Articulated Bus or TrolleybusIntensity, Veh/hIntensity, PCU/h
08-09-105160000012528558
08-09-19480000004848
08-09-01336000000336336
10-09-0866000240012696750
10-09-01936004800129961074
10-09-19108000000108108
01-09-19120000001212
01-09-08660000000660660
01-09-10768000000768768
19-09-01000000000
19-09-10336000000336336
19-09-08000000000
Total 44884650
Table A19. Traffic flow intensity at intersection 10.
Table A19. Traffic flow intensity at intersection 10.
Types of Vehicles/Traffic Flow NumberPassenger Car, Including Ambulance, Light Commercial Vehicle with Payload up to 800 kg, Minibus up to 12 Seats and SimilarMoped, CyclistMotorcycleTruck with Payload up to 5 t, Minibus over 12 SeatsTruck with a Payload of over 5 tBus or TrolleybusTractor Unit with Trailer, Articulated Bus or TrolleybusIntensity, Veh/hIntensity, PCU/h
09-10-1190004812000960948
11-10-096960024000720744
11-10-02132000000132132
09-10-0238412000036432513.6
02-10-111080012000120132
02-10-0954001200012564588
Total 29283057.6
Table A20. Traffic flow intensity at intersection 11.
Table A20. Traffic flow intensity at intersection 11.
Types of Vehicles/Traffic Flow NumberPassenger Car, Including Ambulance, Light Commercial Vehicle with Payload up to 800 kg, Minibus up to 12 Seats and SimilarMoped, CyclistMotorcycleTruck with Payload up to 5 t, Minibus over 12 SeatsTruck with a Payload of over 5 tBus or TrolleybusTractor Unit with Trailer, Articulated Bus or TrolleybusIntensity, Veh/hIntensity, PCU/h
10-11-1263601212000660666
10-11-20480000004848
10-11-03168000000168168
12-11-1084000361200888942
12-11-0328812000120312327.6
12-11-20180000000180180
20-11-0331201212000336342
20-11-12840000008484
20-11-10600000006060
03-11-203840024000408432
03-11-10600000006060
03-11-12336002412012384456
Total 35883765.6
Table A21. Traffic flow intensity at intersection 12.
Table A21. Traffic flow intensity at intersection 12.
Types of Vehicles/Traffic Flow NumberPassenger Car, Including Ambulance, Light Commercial Vehicle with Payload up to 800 kg, Minibus up to 12 Seats and SimilarMoped, CyclistMotorcycleTruck with Payload up to 5 t, Minibus over 12 SeatsTruck with a Payload of over 5 tBus or TrolleybusTractor Unit with Trailer, Articulated Bus or TrolleybusIntensity, Veh/hIntensity, PCU/h
11-12-1312362424120121213201357.2
11-12-21000000000
13-12-11105604800121211281158
13-12-211680120000180174
21-12-131800012000192204
21-12-11120000001212
Total 28322905.2
Table A22. Traffic flow intensity at intersection 13.
Table A22. Traffic flow intensity at intersection 13.
Types of Vehicles/Traffic Flow NumberPassenger car, Including Ambulance, Light Commercial Vehicle with Payload up to 800 kg, Minibus up to 12 Seats and SimilarMoped, CyclistMotorcycleTruck with Payload up to 5 t, Minibus over 12 SeatsTruck with a Payload of over 5 tBus or TrolleybusTractor Unit with Trailer, Articulated Bus or TrolleybusIntensity, Veh/hIntensity, PCU/h
12-13-149961201200010201023.6
12-13-04228000000228228
14-13-1299604824001210801110
14-13-04120000001212
04-13-12108000000108108
04-13-14960120000108102
Total 25562583.6
Table A23. Traffic flow intensity at intersection 14.
Table A23. Traffic flow intensity at intersection 14.
Types of Vehicles/Traffic Flow NumberPassenger Car, Including Ambulance, Light Commercial Vehicle with Payload up to 800 kg, Minibus up to 12 Seats and SimilarMoped, CyclistMotorcycleTruck with Payload up to 5 t, Minibus over 12 SeatsTruck with a Payload of over 5 tBus or TrolleybusTractor Unit with Trailer, Articulated Bus or TrolleybusIntensity, Veh/hIntensity, PCU/h
13-14-151080001212121211281212
13-14-22264000000264264
15-14-1381602412000852852
15-14-2221600001212240294
22-14-15156000000156156
22-14-13180000000180180
Total 28202958
Table A24. Traffic flow intensity at intersection 15.
Table A24. Traffic flow intensity at intersection 15.
Types of Vehicles/Traffic Flow NumberPassenger Car, Including Ambulance, Light Commercial Vehicle with Payload up to 800 kg, Minibus up to 12 Seats and SimilarMoped, CyclistMotorcycleTruck with Payload up to 5 t, Minibus over 12 SeatsTruck with a Payload of over 5 tBus or TrolleybusTractor Unit with Trailer, Articulated Bus or TrolleybusIntensity, Veh/hIntensity, PCU/h
14-15-16792012240120840882
14-15-23240000000240240
14-15-05600000006060
16-15-14924000000924924
16-15-0552801224000564582
16-15-23600000006060
23-15-052412000003627.6
23-15-16360000003636
23-15-14360000003636
05-15-23240000002424
05-15-14168000000168168
05-15-163840012000396408
Total 33843447.6
Table A25. Traffic flow intensity at intersection 16.
Table A25. Traffic flow intensity at intersection 16.
Types of Vehicles/Traffic Flow NumberPassenger Car, Including Ambulance, Light Commercial Vehicle with Payload up to 800 kg, Minibus up to 12 Seats and SimilarMoped, CyclistMotorcycleTruck with Payload up to 5 t, Minibus over 12 SeatsTruck with a Payload of over 5 tBus or TrolleybusTractor Unit with Trailer, Articulated Bus or TrolleybusIntensity, Veh/hIntensity, PCU/h
15-16-17111612012012011521179.6
15-16-06720000007272
15-16-24000000000
17-16-15128402448120013681422
17-16-06324000000324324
17-16-24000000000
06-16-154800001206084
06-16-171560012000168180
06-16-24000000000
24-16-06000000000
24-16-17000000000
24-16-15000000000
Total 31443261.6
Table A26. Traffic flow intensity at intersection 17.
Table A26. Traffic flow intensity at intersection 17.
Types of Vehicles/Traffic Flow NumberPassenger Car, Including Ambulance, Light Commercial Vehicle with Payload up to 800 kg, Minibus up to 12 Seats and SimilarMoped, CyclistMotorcycleTruck with Payload up to 5 t, Minibus over 12 SeatsTruck with a Payload of over 5 tBus or TrolleybusTractor Unit with Trailer, Articulated Bus or TrolleybusIntensity, Veh/hIntensity, PCU
16-17-184560000120468492
16-17-257200240000744732
16-17-07312000000312312
18-17-16168000000168168
18-17-071440012000156168
18-17-251080024000132156
07-17-25000000000
07-17-167800012000792804
07-17-18276000000276276
25-17-07000000000
25-17-18960000009696
25-17-165520036000588624
Total 37323828

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