Traffic Growth rate and Composition of Dhaka-Chittagong Highway (N-1) of Bangladesh: The Actual situation

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1 Traffic Growth rate and Composition of Dhaka-Chittagong Highway (N-1) of Bangladesh: The Actual situation MOHAMMAD AHAD ULLAH 1, DR. MD. SHAMSUL HOQUE 2, DR. HAMID NIKRAZ 3 Department of Civil Engineering 1,3 Curtin University, 2 Bangladesh University of Engineering and Technology (BUET) 1,3 Western Australia, 2 Dhaka 1,3 AUSTRALIA, 2 BANGLADESH 1 m.ullah2@student.curtin.edu.au, 2 shoque@ce.buet.ac.bd, 3 H.Nikraz@curtin.edu.au Abstract: - In transportation planning and operations, analysis of traffic growth pattern and traffic composition carry great significance. Developing countries like Bangladesh has serious shortcoming in performing such analyses due to unavailability of required traffic data. In recent years ministry of communication of Bangladesh has established computerized toll plaza in different National Highways of Bangladesh such as Dhaka-Chittagong highway (N-1) that is one of the most vital highway of Bangladesh. Since the opening of computerized toll plaza on Meghna and Gomoti bridges along N-1 corridor in 2004, the toll collectors have been recording and preserving round-the-year continuous flow data in a systematic manner. The study has taken this prospect of utilizing four years of flow data along the corridor from the year 2006 to 2009 and has performed a traffic growth pattern and composition analyses. From the analyses, it has been found that the yearly growth of total traffic is about 21.03%, which is much higher than the factor presently used by transport authorities in Bangladesh. Besides, vehicle class wise traffic growth factors are analyzed and numbers of heavy vehicles like trucks are increased 1.5 times during the four year period. Moreover, traffic composition, particularly the proportion of heavy vehicles in a traffic stream, is a very important parameter of traffic flow. The average percentage of trucks are found from 2006 to 2009 is 34.40%. These figures can be more precisely obtained up to higher level of confidence by populating more traffic data into the framework established during this study. The transport authorities should take necessary actions for preserving longer period of continuous flow data in order to perform such analysis at a precise level. By using actual traffic growth and composition pattern curves and factors, it is possible to design more efficient highways in Bangladesh. Key-Words: - Traffic growth factor, Traffic volume, Traffic composition, National highway, vehicle class percentage. 1 Introduction In developing countries like Bangladesh, growth rate of traffic is a normal incident. Substantial agricultural and economic growth in different sectors during the last two decades caused significant increase in passenger and freight movement for the whole country. From the transportation point of view, it is of great importance to analyze the pattern of actual traffic growth trends in all prime highway locations in a country. Traffic growth rate is a vital parameter for prediction of future traffic demand and therefore carries significant importance in terms planning, designing of new highway facilities, as well as operation and maintenance of existing facilities, toll collection and other related issues. For the analysis of traffic growth pattern, long duration continuous traffic flow data along a specific location of highway is required [1]. Considering the economic status of Bangladesh, it is quite understandable that, this is an expensive task for the government to take up the initiative to set up permanent traffic counting stations at important locations, since the measure requires high fixed and running cost. As a result, the highway authority has never been able to record and preserve the continuous traffic flow data by which an authentic traffic growth pattern or rate could be analyzed. The required design parameters used by the transport authorities, designers, consultants, planners have been assumed on the basis of short counts, or less accurate data, which may lead to inefficient geometric and structural design ISBN:

2 of highways. Therefore, the need for continuous traffic data and its proper analysis to obtain actual growth pattern is easily understood. For example, the Roads and Highways Pavement Design Guide 2005 sets a 10% growth rate for the national highways [2]. The compatibility of this value with the actual growth rate can only be compared, if true growth rate analysis can be made on the basis of actual continuous traffic flow data. Since the commencement of operation of Meghna- Gomoti Bridges in 2004, according to the toll collection, bridge operation and maintenance agreement with the Roads and Highways Department of Bangladesh, the toll operators have been systematically recording and preserving daily traffic flow data along with the toll collection information. Gaining access to the traffic flow database, this study has effectively utilized the opportunity to analyze four years of daily traffic flow data on the Meghna-Gomoti Bridges and performed a traffic growth pattern and composition analysis on the corridor, which has given a broader understanding over the actual traffic growth pattern and composition on the corridor. 2 Objectives and Scope of the Study The main objective of this study is to analyze yearly traffic flow data on a selected highway corridor to obtain the growth pattern and traffic composition of traffic. The growth rates and composition of total vehicle as well as various vehicle classes are also to be determined. This study has been performed on Meghna-Gomoti Bridges traffic data, which is the entry and exit point of Dhaka-Chittagong highway (N-1) corridor. Therefore, the growth pattern analysis has been rendered for the selected corridor only. The corridor selection has been mainly governed by the availability of sufficient amount of high quality data. 3 Literature Review Study on traffic flow pattern and its variability over time carries a great importance to understand the characteristics of a traffic stream. Analysis of traffic flow pattern from existing data is performed to determine important characteristics of traffic flow that are used in geometric & structural design of highways, traffic monitoring programs, roadway maintenance and operation, economic evaluation, traffic flow prediction, highway financing, evaluation of safety programs and many other related decision making. While transport authorities and agencies in many developed countries extensively record traffic flow data through short counting as well as continuous counting stations in order to monitor their trend of traffic growth and changes in traffic characteristics, but not many studies have been performed in Bangladesh on traffic characteristics. Previously performed studies in Bangladesh on related topic reveals that similar studies was carried out by Roads and Highways Department, as a part of Development of Geometric Design Standards in 1994, on some important highways [1]. Muhibur Rahman performed studies on Vehicular Flow Pattern on Jamuna Multipurpose Bridge Access Road in 2002 [3]. Hamid-Uz-Zaman completed another study in Traffic Flow Characteristics and Modeling for Estimation of AADT in selected Rural Highways in 2006 [4]. Mohammad Ahad Ullah carried out research on Evaluation of Pavement Design Parameters for National Highways of Bangladesh [5]. In addition, guidelines are followed for analysis of traffic characteristics from Traffic Monitoring Guidelines 2001, published by Federal Highway Administration of U.S. Department of Transport, which have been helpful for this type of research [6]. 4 Data Collection The traffic data that has been used in this study for the growth pattern analysis is primarily collected by the Operation and Maintenance Companies of Meghna- Gomoti Bridges. From the year 2006 to 2009, traffic flow daily data have been collected by the toll operators RCL and MBEL-ATT JV. The traffic data has been recorded by the operators by direct entry from the toll plaza and they have been electronically preserved at the main database. These flow data have then been collected from the operators with official permission from Roads and Highways Department of Bangladesh and have been used in this study to perform the required analysis. From the analysis of flow pattern in different time scales, the data has resulted repetitive nature of flow patterns, which refers that the selected corridor is stable from traffic flow point of view and the traffic data are reliable. ISBN:

3 5 Data Analysis and Findings In this study, growth pattern of total traffic as well as individual vehicle classes have been analyzed. ly growth factor of total traffic has also been determined. The following sections discusses the traffic growth trend and rates in light of the data analysis. 5.1 Growth rate of total traffic From the analysis of the yearly traffic volume on Meghna-Gomoti Bridges, it has been revealed that the amount of traffic is increasing at a fairly constant rate. In 2006, the total bi-directional traffic volume was 3,206,277 while it reached almost 5.6 million in the year Table 1 shows the bi-directional flow volume of each vehicle class as well as total traffic on Meghna-Gomoti Bridges from 2006 to From Figure 1, it can be seen that the total traffic is increasing every year at a significant rate and the pattern maintains almost linear growth of traffic. From the calculation of yearly growth rate, as shown in Table 2, it can be seen that, yearly increase in traffic during the study period has ranged from 10% to 18% per annum and the average growth factor of total traffic from 2006 to 2009 is 21.03% per annum. Table 1: ly Bi-Directional Traffic Volume on Dhaka-Chittagong Highway (N-1) ly Bi-Directional Traffic Volume Motor Cycle 9,743 22,729 36,975 46,896 Scooter/ Tampo Car/Jeep Micro/ Pickup Minibus /Coaster Bus Truck Trailer Toll Free Vehicle Vehicle Fig. 1 ly traffic growth on Dhaka-Chittagong Highway (N-1) Table 2: ly Growth Rate of Traffic ly Volume (Both way) Growth Factor ,210, ,313, ,732, ,632, Average Growth Factor 21.03% It can be observed in Table 2 that, the growth rate of total traffic in 2007 was 34.37%, which is much higher than following years. Therefore, it can be concluded that the traffic growth trend along this corridor is not yet stable. It is to be mentioned here that, economic growth is not the only governing issue against this growth pattern, but also political stability, government policy, availability of alternate route, shifting of traffic to the study corridor play important roles in this regard. Notwithstanding, since the corridor does not have any alternate route, it may be assumed that, the actual growth pattern has been truly reflected in the analysis. It is therefore observed that the growth rate used by the Roads and Highways Department s Pavement Design Guide 2005 is significantly lower than that obtained in this study. However, populating more yearly traffic data into the analysis framework for another 5-6 years may reveal a better understanding of the actual growth factor of traffic along the corridor. 5.2 Classified vehicular growth rates From the preceding discussion, it has been found that the growth rate of total traffic on the Meghna-Gomoti Bridges corridor is 21.03% per annum. It is also evaluated that different vehicles classes have different growth factor. Figure 2 shows the growth pattern of each individual vehicle class. It is observed from the ISBN:

4 Figure that the main predominant vehicle classes viz. Trucks are increasing at a quite steep rate while the rest of the classes did not increase to considerable extent during the study period. Fig. 2 Vehicle class wise yearly flow on Meghna- Gomoti Bridges Table 3: ly Bi-Directional Volume of Buses Mini Bus/ Coaster/ Bus Buses Mini Truck , , , , ,413 1,251, , ,618 1,239, , ,149 1,324,119 Average 515, ,530 1,186,197 Table 4: ly Bi-Directional Volume of Trucks Truck Trailer Trucks & Trailers ,182,337 47,491 1,229, ,459,489 89,800 1,549, ,594, ,870 1,696, ,876, ,995 1,992,193 Average 1,528,133 88,789 1,616,922 In Table 3, the yearly bi-directional volume of Buses on Meghna-Gomoti Bridges are given. It can be observed that, the total number of mini bus/coaster/mini truck have increased and also, the total number of bus has increased 1.5 times from 2006 to In 2006, total bi-directional volume of Bus was 497,938 while it increased to almost one and half times number 788,149 in The average rate of growth of Bus is 17.32% per annum. It is to be mentioned here that a large number of mini buses was replaced by introduction of luxury chair coaches in the concerned years. This might have been caused by banning of old, unfit small buses on road, which in turn was replaced by new chair coaches. The demand of luxury buses capable of cutting down travel time along the Dhaka-Chittagong highway might have caused this as well. In the case of Trucks, which is presented in Table 4, is found that Truck contains the highest percentage of traffic on N-1 corridor. In the year 2006, total volume was 11,82,337 and it increased to more than 1.5 times during the next four years. Although due to consequent increase in total traffic, the growth in annual percentage is declining. From 2006 to 2009, the percentage has dropped from 36.77% to 33.31%. Ineffectiveness of axle load control station has promoted excess load carried by these truck frequently. Hence, the Dhaka-Chittagang highway is suffering extremely heavy loads then their design load. The percentage of trailer is very nominal with respect to traffic stream in N-1 corridor, but the number of trailers is increasing very rapidly. In 2006, the total number of trailers is found 47,491 and the number has increased to 115,995 in From the above discussion, it has been found that, heavier vehicle viz. Buses and Trucks are increasing at a higher rate than the total vehicles, which is clearly an indication of increased economic growth and transport demand. Considering the importance of heavy vehicles in terms of geometric and structural design of pavement, the highway engineers while designing new facilities should consider their true growth rates of traffic. ISBN:

5 5.3 Heavy Vehicles Percentage Percentage of heavy vehicles refers to the percentage of truck and bus in a traffic stream. Heavier vehicles cause more damage to the roadway. For this reason, this is an important parameter for structural design of highway. Moreover, higher proportion of larger sized vehicles is important in the aspect of geometric design of highways as large vehicles are critical for the design of grade, turnings, road width, warrant for curve widening and auxiliary lane at vertical curve etc. The following section discusses the proportion of heavier vehicles on Meghna and Gomoti bridges flow and their travel pattern. Fig. 3 Traffic composition pattern on Meghna- Gomoti Bridges (in percentage of total vehicle) In Fig. 3, vehicle class percentages on Meghna- Gomoti bridges are shown. It is found that, truck has the highest percentage in the traffic stream. In 2006, the percentage was 36.77% and during the next years the proportion is almost same. The average percentage of truck from 2006 to 2009 is 34.40%. The second highest percentage of vehicle class is Micro/Pick-up, the proportion of which was 14.20% in 2006 and 17.66% in The average percentage of Micro/Pick-up from 2006 to 2009 is 15.75%. The third highest contributing class to the total traffic flow is bus. In 2006, its percentage was 15.60% and it became 13.99% in the year of 2009, the average is found to be 15.12%. The fourth highest vehicle class is Car/Jeep, which has 13.53% in 2006 and 13.42% in 2009 making average from 2006 to 2009 is 13.26%. Analyzing the traffic flow data on Meghna-Gomoti bridges from 2006 to 2009, it is found that these three pre-dominant vehicle classes comprise of total 78.53% of total traffic flow. Rest 21.47% is shared between minibus/coaster/mini Truck (11.82%), motorcycle (0.61%), scooter/tampu (2.95%), trailer (1.94%) and toll free (4.15%). It is seen from the graph that the percentage of heavier vehicles especially Truck is increasing every year and lighter vehicles are decreasing Truck percentage In Meghna and Gomoti bridges, according to the vehicle classification system used by the operators, vehicle having capacity of 5 ton to 8 ton are classed as trucks. This class is most common in Bangladesh and hence contributor of the highest percentage of traffic. Also, some trucks capacity is more than 8 ton and usually possesses more than two rear axles. It is observed from field survey that the toll collectors are often confused about the classification between the trucks falling near to boundary conditions. However, from the analyses of traffic flow data from 2006 to 2009 on Meghna and Gomoti bridges, taking the average of these years, it is found that the percentage of all classes of trucks 36.34% of total vehicle. Among this, the percentages of trucks and trailers are 34.40% and 1.94% respectively which is shown in Table 5. Table 5: Truck Percentages on Meghna-Gomoti Bridges (Both Direction) Truck Trailer Trucks & Trailers % 1.47% 38.24% % 2.08% 35.91% % 2.15% 35.84% % 2.06% 35.37% Average 34.40% 1.94% 36.34% Date Source: RCL, MBEL-ATT JV Bus percentage Buses passing through Meghna and Gomoti bridges are classified into two groups namely Mini Bus/ Coaster/ Mini Truck and large Bus are called Bus. ISBN:

6 Buses having capacity of 30 seats of less are classed as mini bus and buses having more than 30 seats capacity are classed as Bus. Table 6: Bus Percentages on Meghna-Gomoti Bridges (Both Direction) Mini Bus/ Coaster Bus Buses % 15.60% 29.06% % 15.77% 29.01% % 15.12% 26.19% % 13.99% 23.51% Average 11.82% 15.12% 26.94% Date Source: RCL, MBEL-ATT JV. It is seen from table 6 that total 26.94% of total annual flow (taking average from 2006 to 2009) comprises of buses. Among this, 15.12% is bus and 11.82% is mini bus. It can be seen that the percentage of bus has slightly decreasing with respect to total traffic (15.60% in 2006 and 13.99% in 2009). The growth factor of bus from the year 2006 to 2009 is found 36.65%, 5.17%, and 10.14% respectedly. The percentage of bus has increased every year at an average rate of 17.32% per annum. 6 Conclusions and Recommendations Four years of data is not sufficient to reliably analyze the actual growth pattern of traffic in a major highway like Dhaka-Chittagong highway in Bangladesh. However, this study has taken this attempt because presently no further continuous count data is available along this corridor. From the analyses performed in this study, a generalized idea of traffic growth trend in the selected corridor has been discovered. By proper preservation of round-the year traffic data and populating more years of data within this present framework, a more generalized traffic growth pattern analysis can be made possible along this highway. In this regard, the following recommendations are suggested which would be largely beneficial for future analysis of traffic growth patterns in Dhaka- Chittagong highway in Bangladesh. Corridor specific traffic growth factor should be established which will help to measure future traffic demand. Class wise vehicular growth factors should be considered and the same should be regularly updated using recently data. Initiative may be taken to instruct all Highway toll operators to keep flow records in hourly basis. A valuable traffic database can be generated in every corridor by introducing this technique. A specified data collection and preservation system in electronic format may be introduced by RHD to ensure proper data collection in tolled bridges without spending any money for data collection purpose. Transport authorities, agencies should formulate frameworks for collecting and preserving long duration traffic data obtained from the toll plazas. References: [1] Development of Geometric Design Standards, Road Material and Standards Study Bangladesh, 1994, Volume VIIA, Roads and Highways Department, GOB. [2] Pavement Design Guide, Roads and Highways Department, 2005, Ministry of Communication, Government of Bangladesh. [3] Rahman S.K., Study of Vehicular Flow Pattern on Jamuna Multipurpose Bridge Access Road, 2002, Dept. of Civil Engineering, MIST. [4] Zaman H.U., "Traffic Flow Characteristics and Modeling for Estimation of AADT in Selected Rural Highways", 2006 Dept. of Civil Engineering, BUET. [5] Ullah, M. A., Evaluation of Pavement Design Parameters for National Highways of Bangladesh, 2012, Department of Civil Engineering, BUET. [6] Traffic Monitoring Guidelines, Federal Highway Administration, 2011, U.S. Department of Transport. ISBN: