Classification Characteristics of Some Roads in Karbala City

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Introduction Traffic congestion in cities is one of the big-gest transportation problems. Traffic jams are very intrusive activities for people and arise owing to the high degree of saturation of traffic flow. Because of the increased trip duration, congestion will have a detrimental effect on drivers and other road users. A population with a wide range of activities leads to a mobility flow that requires suitable roads [1-5]. The effects of street network design on congestion levels and characteristics differ greatly in street network design [6]. In terms of accidents, delays and CO2 emissions, the operational efficiency of urban street networks has a significant impact on the sustainability of urban road transport. As a result, governments must regularly inspect road networks and manage urban traffic patterns [7; 8]. The quality of traffic flow must be evaluated to find better solutions to control the increase in traffic demand [9-11]. It is necessary to assess the quality of traffic flow in order to find the best solutions to control the growth in traffic demand [12; 13]. Transportation operations can have both positive and negative effects. Traffic jams in city centers, including Palembang, are one of the undesirable consequences of transport activities. Congestion leads to a significant loss of travel time, which takes a long time and slows down, as well as financial, health and environmental consequences, such as exposure to air pollution caused by car exhaust emissions [14]. According to INRIX, lost time, wasted fuel, and carbon emissions in the 25 cities evaluated in the United States would cost drivers an estimated $480 billion over the next ten years [15]. The Highway Capacity Manual provides de-tailed instructions for estimating the capacity and service levels based on speed and other factors. Correction factors for estimating throughput ac-cording to various parameters are provided if the HCM handbook does not include lateral friction parameters for determining throughput and service level [16, 17]. With regard to access control, which is considered a key urban traffic issue, statistical correlations between travel speed and related vari-ables have been documented. It is used to measure traffic congestion and quality of services on urban highways. In addition, speed regulation for ac-cessibility purposes has contributed to improving the safety and efficiency of road network [18]. Reliability is one of the most important indicators of transport system efficiency and service quality. The large variance in travel time has become a problem for both travelers and transport manage-ment companies. Reliability indicators are increas-ingly used to assess traffic jams and unexpected changes in travel time [19]. Data from an in-vestigative vehicle for 200 compounds in Beijing, China were analyzed. This study examines urban expressways, auxiliary highways, main roads, and secondary roads. First, the time distributions of the passages of various DOW are studied. The results of tests for compliance with various distributions have shown that a logarithmically normal distri-bution can provide higher acceptance indicators for different time periods and types of roads than other distributions. In addition, four reliability indicators (travel time per unit distance, coefficient of variation, buffer time index, and punctuality level) were used to investigate the patterns of travel time variability for various. The results showed that on weekdays, urban expressways, auxiliary roads, and important highways exhibit constant and distinct morning and afternoon peaks [20; 21]. 1. Research area The city of Karbala is a famous city in the Islamic world. It is known for its religious signif-icance. The shrines of Imam Hussein and his brother Abbas can be found in the ancient city or in the city center. It is located approximately 110 km south-west of Baghdad. The study area is located in the center of Karbala Province, where this study examines a group of urban roads connecting central commer-cial areas with industrial, commercial, residential, and educational areas with high population density. Figure 1 shows the research area where embedded segments and street nodes were identified. These segments are then displayed. Table 1 lists the main characteristics of the street segments studied, such as the local street name, segment length, and number of lanes. These characteristics were collected in this study based on a field survey. 2. Methodology Segmenting of urban street. The methodology includes the definition of the study area, which is a network of urban roads in the Karbala province. The primary objective of the fieldwork was to con-duct surveys and administer questionnaires on a street-by-street basis to identify the periods of peak traffic. The subsequent step involves the distribut-ion of relevant data. The volume of traffic is deter-mined by recording cameras, whereas the speed information is described by the free flow rate in each network segment. The classes were then deter-mined using the Speed Gun device, and the average speed of movement for each segment in the net-work was calculated. The appropriate service level (LOS) is then calculated using HCM2000 [22]. Figure 1. The selected research area S o u r c e: Karbala Carte, Street Views. Available from:https://www.istanbul-visit.com/carte/iraq/karbala-plan.asp (accessed: 12.06.2024) Table 1 Detailed information about the roads in the study area Road Name Segment NO. Lane number / direction Length, m Fatima Al-Zahraa Street 1 3 234 2 443 3 790 4 811 5 418 6 269 Al-Iskan Street 1 3 1430 2 1380 Ramadan Street 1 3 1670 2 1710 S o u r c e: make by H.S. Khudhair, H.A.E. Al-Jameel, V.N. Konoplev, A.R. Asoyan 3. Results and discussion 3.1. Determine the road class basedon the free flow speed (FFS) The free-flow speed (FFS) is the average speed of traffic flow when there is not enough traffic to influence drivers’ decisions about speed, and when traffic control at an intersection is either absent or located at a distance that does not allow the Speed Gun device to be installed. It is used to determine the FFS, as shown in Figures 3-6. 3.2. Determine the level of service (LOS) of a road After classifying each segment based on the FFS, city streets were evaluated using the average travel speed (ATS), which is one of the most fundamental indicators of service on city streets. It is calculated by collecting travel time data in the field. Table 2 illustrates the criteria for urban streets depending on their class and average speed. There are six levels of service, from USA (free work and absolutely free maneuvering) to the USA (congested traffic), when the need for traffic exceeds the capacity of the street (Figure 2) [23]. Figure 2. Segment length diagram(adapted from HCM 2010). S o u r c e: Manual HC, HCM2D10 [6] Figure 3. FFS for Fatima Al-Zahraa Street,segments 1, 2,5, and 6 S o u r c e: make by H.S. Khudhair,H.A.E. Al-Jameel, V.N. Konoplev, A.R. Asoyan Figure 4. FFS for Fatima Al-Zahraa Street,segments 3 and 4 S o u r c e: make by H.S. Khudhair,H.A.E. Al-Jameel, V.N. Konoplev, A.R. Asoyan Figure 5. FFS for Al-Iskan street, segment 1 and 2 S o u r c e: make by H.S. Khudhair,H.A.E. Al-Jameel, V.N. Konoplev, A.R. Asoyan Figure 6. FFS for Ramadan street, segment 1 and 2 S o u r c e: make by H.S. Khudhair,H.A.E. Al-Jameel, V.N. Konoplev, A.R. Asoyan Table 2 LOS of urban road based on FFS and ATS from HCM 2000 Urban street class I II III IV Range of FFS, km/h 90 to 70 70 to 55 55 to 50 55 to 40 LOS Average travel speed (ATS), Km/h A > 72 > 59 > 50 > 41 B > 56-72 > 46-59 > 39-50 > 32-41 C > 40-56 > 33-46 > 28-39 > 23-32 D > 32-40 > 26-33 > 22-28 > 18-23 E > 26-32 > 21-26 > 17-22 > 14-18 F ≤ 26 ≤ 21 ≤ 17 ≤ 14 S o u r c e: make by H.S. Khudhair, H.A.E. Al-Jameel, V.N. Konoplev, A.R. Asoyan Table 3 LOS according to FFS data (using HCM 2000) Road name Seg. no. FFS, km/hr Class by FFS ATS, Km/hr LOS Fatima Al- Zahraa Street 1 72.2 I 12 F 2 58.5 II 24 E 3 44.6 IV 17 E 4 43.6 IV 12 F 5 58.1 II 10 F 6 67.5 II 16 F Al-Iskan Street 1 69.6 II 13 F 2 65.6 II 28 E Ramadan Street 1 80 I 42 C 2 78.2 I 26 E S o u r c e: make by H.S. Khudhair, H.A.E. Al-Jameel, V.N. Konoplev, A.R. Asoyan Conclusions The analysis of Karbala roads has shown the following: 1. The length of urban roads of the first category is 25% of the total length of the number, and the remaining part of the roads belongs to the second category. 2. The structure of city streets according to the level of maintenance is characterized by 25% when working with LOS C; 31.25% when working with LOS T; 12.5% when working with LOS E; 31.25% when working with LOS Fastidios. 3. The assessment of traffic efficiency by the ratio (o/n) shows that the level of maintenance of street sections is: 50% of the segment’s operating with LOS C; 18.75% of the segments working with LOAD; 25% of the segments working with LOS E; 6.25% of the segments working with LOS F. 4. According to the HCM 2000 methodology, all the considered sections of Fatima Al-Zahra and Al-Iskan streets operate under conditions of traffic disruptions, while Ramadan Street sections operate at their maximum capacity.

About the authors

Hayder S. Khudhair

RUDN University

Email: hyder.s@uokerbala.edu.iq
ORCID iD: 0000-0002-6833-7780

Postgraduate student of the Department of Engineering and Transport Technologies, Academyof Engineering

Moscow, Russia

Hamid Athab E. Al-Jameel

University of Kufa

Email: hamid.aljameel@uokufa.edu.iq
ORCID iD: 0000-0002-1367-4421

Doctor of Technical Sciences, Professor of the Department of Civil Engineering, Facultyof Engineering

Kufa, Iraq

Vladimir N. Konoplev

RUDN University

Author for correspondence.
Email: konoplev-vn@rudn.ru
ORCID iD: 0000-0003-1662-6254
SPIN-code: 3876-1534

Doctor of Technical Sciences, Professor of the Department of Engineering and Transport Tech-nologies, Academy of Engineering

Moscow, Russia

Artur R. Asoyan

RUDN University

Email: asoyan-ar@rudn.ru
ORCID iD: 0000-0002-1976-9376
SPIN-code: 1020-5089

Doctor of Technical Sciences, Professor of the Department of Transport, Academy of Engineering

Moscow, Russia

References

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