Performance assessment of road transport network of the Republic of Serbia in a context of information scarcity. -Summary- Andrej Manić

Transcription

1 Performance assessment of road transport network of the Republic of Serbia in a context of information scarcity -Summary- Andrej Manić November 2012

2 Development and improvement of transport infrastructure in the region of Western Balkans plays a key role in regional development and also facilitates regional integration as well as integration into Trans-European Transport Network (TEN-T) and Pan-European Corridors. Western Balkans, at present, is a region undergoing a long process of transition and without a modern transportation system it will continue to lag behind its EU neighbors in economic development. One of these countries is Serbia, and it is facing significant challenges and needs to restore and expand its transport network, and while doing so, ensure integration into the main European transport corridors, and also to promote balanced regional development and good accessibility for the entire country. The main goal of this dissertation, firstly, was to critically examine the present state of road transport infrastructure network. In this sense, it was necessary to create a road transport model of Serbia for further assessments for example, transport policy interventions. With the model in hand we can suggest interventions in order to improve the transport network in accordance with the countrywide transportation master plan defined by the Serbian Ministry of Transport (Ministry of Infrastructure of the Republic of Serbia 2009) and create a forecast and scenario analysis for some time horizon. At present, the transport network of Serbia is not evenly distributed in terms of accessibility (Laketa et al. 2011). The work also aims to measure those variations and to test whether the future plans pay attention to linking insufficiently accessible parts of the country, and what will be possible future benefits. Key performance indicators, such as quantity and quality of transport infrastructure, as well as travel time/distance to the regional centers play crucial role in this evaluation. For the purpose of examining transportation related issues and for transport planning in general, specific types of models have been developed over the years; most common are travel demand models or traffic models. These are designed to evaluate transport supply and demand. Years of experimentation and practice in the past 50 years has led us to a general structure of a transport model that is often referred to as the classic transport model. It is a sequential 4-step model, containing the following steps: Trip generation, Trip distribution, Modal split and Assignment. The four step model is the primary tool for forecasting future demand and performance of a transportation system, typically defined at a regional or subregional scale (McNally 2007). In short, we can state that the present state-of-the art regarding transportation modeling has the following highlights: For the trip demand: evolution towards the activity-based model. For the trip assignment: evolution towards simulation techniques For the interfaces with other tools : o GIS for developing and applying transportation forecasting models, o combination of land use and traffic models, o linkage between traffic model and pollutants emissions model There has been limited previous experience in regional traffic forecasting for Western Balkans. Most of the studies to assess the situation of the regional transport network were undertaken or at least supported by the European Commission. The fact is that there is not sufficient data on

3 the region, and that the data is often incomplete or obsolete. However, it is evident that in the recent years more and more focus is given to this issues; a good proof of that is the forming of South-East Europe Transport Observatory (SEETO South-East Europe Transport Observatory 2011), and also the delivery of two large scale studies, first the Transport Infrastructure Regional Study in the Balkans (TIRS) in 2002., which was later followed by Regional Balkans Infrastructure Study (REBIS) (European Commission 2003). The Regional Balkans Infrastructure Project-Transport (REBIS) was started with the purpose of assisting Balkan countries in the developing of coordinated strategies for transport development. In order to create a valid starting point for the assessment of future projects, a traffic forecasting model was created, and projections made for up to the year In a moderate growth scenario, road traffic will increase by %; rail traffic will grow at a much slower pace: 40-60%; growth in inland waterway transport is estimated to % and air traffic at %. By the end of the period, vehicle ownership and trip rates will have reached the levels which are currently found in many West European countries (European Commission 2003). What is also worth noting is the fact that the key input parameters in the mentioned forecast model were present and assumed growth rates of GDP and population. And according to study, modal split between road and rail traffic will continue to change in favor of road traffic, increasing from 87%- 92% to 92%-94% over the next 25 years; for freight the increase of road traffic will be from 79%-95% to 88%-98% (European Commission 2003). Serbia holds a very good position due to the proximity to EU, the rest of South-East Europe, and in extent to the Middle East. It borders the EU at the Hungarian, Bulgarian, and Romanian state lines. With the total road length of about km (Government of the Republic of Serbia 2007), the road network in the Republic of Serbia is well-developed, although its quality is reduced due to insufficient investments and inadequate maintenance in the period If we compare the population density (inhabitants per km 2 ) with the road network length (km), we can conclude that, at present, the network is sufficiently developed, but the accessibility varies greatly between regions, which is a factor that must be addressed in the near future: Figure 1: Development of road network and accessibility levels

4 In 2010, the first major step towards development of modern transport system occurred, in the creation of General Master Plan for Transport in Serbia (GMTS) until Critical to Serbia s transport sector are the ten Pan-European Transport Corridors, which were defined at the second Pan-European transport Conference in Crete, March They are designated as routes in Central and Eastern Europe that required major investment in the next decades. Figure 2: Pan European Corridors Regarding Serbia, Corridor X forms the backbone of the country s transport, as it connects Austria, Hungary, Slovenia, Croatia, on one side, with Bulgaria, Macedonia, Greece and Turkey on the other. The two branches of the Corridor (one from Croatia, another from Hungary) meet at Belgrade, run together south-east until the city of Niš, and then branch out, one towards Greece, and other towards Bulgaria. Furthermore, Corridor X is connected with Corridors IV, V, VII and VII. This Corridor, with its basic direction from Salzburg to Thessaloniki, connects eight states; of the total length (2.360 km), through Republic of Serbia flows 874 km (37% of corridor); and of the total international land transport of Serbia, more than 77% of goods are transported through routes on Corridor X. Recently, a new corridor was proposed, Corridor XI, which stretches diagonally through Serbia, from North-East, to South-West. It is intended to connect Romania, through Serbia and Montenegro, to Italy. It is known that this will pass through Belgrade and will incorporate the Belgrade (Serbia) - Bar (Montenegro) highway. It is often referred to as the Belgrade- South Adriatic, since it will also incorporate Montenegrin port of Bar, linking Corridor IV in Romania with Bari in Italy. This route holds high significance for Serbia, but also for the region. In order to start developing the 4-step model, we had to correlate GDP per capita with the number of daily trips per inhabitant. Based on the Technical Report on Kazakhstan (Macário et al. 2012), we used the trip generation logistic function calibrated for a benchmarking analysis of 71 European cities based on the database from the UITP (Union Internationale des Transport Publics). This mobility variable was estimated through the GDP per capita projections. Serbia is divided into districts which are the further subdivided into municipalities. Therefore, for every municipality in Serbia the following data has been obtained: total population, active population and number of households. With this data collected in represented in table form, we needed another key figure, GDP. We have obtained average salaries for each municipality, sorted from the highest to the lowest, and created an earning factor - θ. The zone with the highest average 4

5 salary (New Belgrade) became the reference level with θ = 1, and all other zones had lower factors (0,9; 0,87; 0,64, etc.) translating the ratio between each of these zones and the highest income zone: Equation 1: Revised trip generation formula With the average household size in Serbia standing at 3,02 persons the average number of trips per day per household was calculated at 4,75. This resulted in overall number of trips per day for the entire country to be These are total trips by all modes available to any zone. The next step in the process was to create the transport network through which the generated traffic will be assigned. Traditionally, transport networks have been modeled in a relatively coarse manner. In this case, the construction of the network proved to be very time consuming, as the only road data available online was of poor quality, hence it was decided to create the network manually, using GIS data as background. Before starting the mapping process, TIRS study (Louis Berger S.A. 2002) was consulted to help in categorizing the road network. Once we had the network, along with distance and impedance matrices calculated, we could go further and proceed with trip distribution. This step was performed using the common Gravity model. In this case, the bigger the zone (in terms of population and employment) the more travel will be between them and the further apart zones are, the less travel there will be between them. Here, the generator is the population of the zone, while the attractor is the number of employed persons in a particular zone; and the amount of pull between each O-D pair is represented through number of trips. This gave us the first initial matrix of tips, but we needed to divide it into two; one for the private cars and another for the freight. As we didn t have addition information on industrial activity and freight itself, we made an assumption stating that of all trips 95% is private and 5% freight; with 1 unit of freight vehicle accounting for 3 personal vehicles. The next steps were modal split and assignment. One of the main problems we have encountered while creating the model is the fact that we didn t know what is actual percentage of the trip matrix that actually loads the road network links. When running the model for the first time, the load on links for inter-zonal trips was far above the capacities. This is due to road modal share, to the occupancy rates of cars and overestimates of trip generation. As we have adopted capacity values from the TIRS study, the only solution was to calibrate number of trips. This was done by trial and error; as we have obtained official counts of traffic from the Putevi Srbije (Roads of Serbia) Government Agency, we compared the counts with our results and concluded that the pattern of traffic matches the pattern from the counts, but the trip numbers are too high. In other words, the model was performing satisfactory, but we had a scaling problem. This could be solved by dividing the entire matrix by uniform factor, and so lowering the level, but not changing the trip pattern. After various trials we concluded that 15% matrix load match the observed counts in the manner that is the most acceptable of all. This can be 5

6 graphically represented on the following figure, where on the left we have model results and on the right the official counts (using the same color coding): Figure 3: Comparison of AADT from the model (L) and from the counts (R) Next, in order to better understand and analyze the transport network and the demand forecast, 3 different versions were examined: Present state (2012) Future state without network improvements (2027) Future state with network improvements (2027) Here we needed to estimate growth rate of GDP, which is crucial element in forecasting future demand. In other words, we used growth factor method. Because one of the main goals of the Government is to balance out differences in development between regions, the lower limit of θ was set to 0,7. In other words, this simulates that in 15 years, difference in earning between any two regions in Serbia will not be more than 30%. What becomes apparent, according to the formula used, is that the differences in total trip numbers will not vary greatly between scenarios, and will not grow significantly comparing to 2012, less than 10. After analyzing the 3 scenarios we concluded that the difference between them is not sufficient for separate analysis. Based on that, and the planned projects from GMTS, we proceeded to performance analysis and differential comparison of the state in 2012 and future states in The following figure shows the Levels of Service (LOS) for the network, according to HCM adopted level categorization: 6

7 N Figure 4: Road network (L) and LOS 2012 (R) Most of the links show that the LOS is satisfactory, while the main problems identified are roads leading to the main cities; especially Belgrade, Novi Sad, Niš, Kragujevac and Požarevac. Others include the primary road M-22.1 that connects Belgrade and Novi Sad, section of primary road M-21 connecting the cities of Ruma and Šabac, and section of primary road E-761 (Pojate- Preljina) connecting Čačak, Kraljevo, Trstenik and Kruševac. These issues match to the ones carried out in previous studies. Furthermore, it goes in line with the preceding facts, that the amount of traffic still has not reached even 50% of the level in Also, we concluded that, at present, the accessibility is not satisfactory, especially at the regions that are located along or close to the border with neighboring countries. For comparison, planned projects are implemented in the network, resulting in upgrading some existing links and creation of new ones, and by updating trip matrices using forecasts and growth rates, the demand side was also updated. The difference in road network can be seen on the following figure: N Figure 5: Network comparison, 2012 (L) and 2027 (R) 7

8 Percetage of total links With the network improved, and new demand inserted into the model, the comparison in terms of accessibility was carried out. 2 hours isochrones were created starting from Belgrade, Novi Sad and Niš, in order to see the difference in isochrones reach on the loaded network: N Figure 6: Comparison in accessibility from 3 main cities, 2012 (L) and 2027 (R) From this comparison we concluded that the accessibility problems have been mitigated with partial success, at least from this perspective. The districts in the West and South-West will witness significant improvements due to the motorway that will pass through the region, along with the upgrading of the primary roads. Still, very little improvement is visible in the East, due to the fact that none of the proposed projects pass through this region. This issue should be investigated further. Regarding volume/capacity levels, absolute values here are less important, especially because of the difficulty to determine precise link capacity values. What should be more carefully examined is the difference or shift between scenarios, and the increase of the number of links with high saturation. 70% 60% 50% 40% 30% 20% 10% 0% with improvements no improvements Saturation levels Figure 7: Link saturation comparison 2027, with and without improvements 8

9 Recalling the main objective of the dissertation, it was intended to critically examine the present state of the Serbian road transport infrastructure network and analyze the possible outcomes from new projects programmed for the near future. Here, we have built a detailed and accurate model of the road network and simulated satisfyingly a very complex reality in a context of information scarcity. In fact, we managed to capture and recreate some of the crucial aspects of the present situation and to give valuable information and contribution to identify some existing problems and foresee those that will probably remain even after the projects are installed, eventually. The results and values obtained with the present research should not be considered in absolute terms, but more as general indicators of present and future traffic patterns. The issues with scaling, capacities and actual number of trips on the network also suggest that these conclusions should be regarded in relative or comparative terms; e.g. how does present state compare to the future one, or how improved network will be able to satisfy future demand, comparing to the network with no improvements. Still, the model shows and confirms statements from previous studies, regarding possible bottlenecks, and issues with accessibility. Also, it acknowledges the importance of Corridor X, which serves as a backbone to whole transport system of the country. As was mentioned in the previous studies, and confirmed in this one, the characteristics of the transport network can be summarized as: A network with a valuable strategic position, and a lot of unused capacity and potential for economic fostering; Comparing to the population, the network has adequate road density; Capacities of the network are generally sufficient, except on the links mentioned; and Accessibility is a weak point, especially in regions along the borders. Regarding trip forecasts, the formula used led us to conclude that the overall number of trips will not rise more than 1/5 of the present volumes. Still, without improvements, those links that are already saturated will experience additional buildup of negative impacts. Also it became apparent that different GDP growth rates (1%, 3% and 5%) did not evidence sufficient differences and therefore the neutral (middle) scenario was adopted for further comparative analysis. The majority of the planned projects have a good level of future demand supporting them. It is apparent that, in order to catch up with EU norms and standards, a thorough modernization of the network is needed, especially in the case of new motorways. Without good connections between regions, as well as between Serbia and the neighboring countries, many districts are under threat to be excluded from the main traffic flows. This would only aggravate the present condition, where the difference (in terms of earnings and standard) between certain regions is very high, up to 4 times. The projects will improve average travel time through network with certain region experiencing much higher benefits. Furthermore, no region would suffer from these undertakings. In that sense, big majority of projects are justified. Regarding accessibility, the results show that the future project will help the overall situation, but there will 9

10 still be certain regions that will show signs of low accessibility. The improvement in average travel time to a certain district from all others is about 10%, with the individual improvements ranging from 4% to 19%. Further improvements are necessary, in order to bridge the gap between regions, in terms of development, income and movement of goods and people. Transport network exhibits vulnerable points, mostly on bridges in the capital. This however, is likely to be successfully addressed with the future completion of bypass motorway. Utilization of motorways on corridor X is and will remain very high, stressing the need to quickly complete the missing links and integrate it into European networks. This will further facilitate trade and generate economic activities. Future Corridor XI, stretching from Romanian to Montenegrin border, will be of high value as it will intersect Corridor X near Belgrade, which could lead to a creation of a transport hub and attract investment. For other links, careful examination of future demand is needed when considering upgrade; sometimes it will be sufficient to modernize a present road, and maintain it well, as opposed to investing into a higher category road. On the side note, we would like to stress the importance of good accessibility and balanced social equity throughout the county, especially on the bordering regions. This is even more important in Serbia, due to the fact that there is a number of ethnic minorities living at the bordering regions that need to be better integrated in the society, increasing social welfare and the overall quality of life for all the inhabitants. Research limitations, and way to deal with them, are probably of equal importance as the results presented. Thorough the modeling process, we have encountered many obstacles, which need to be acknowledged. We have aimed to create a starting point in road transport model of Serbia, which can later be upgraded and expanded. Here, we will list various limitations encountered and ways in which these issues were overcome. Data; Model is extremely dependent on data availability. Ultimately, no matter how sophisticated the model is, if the data is missing, incomplete or corrupted, the end results will be poor. We have faced to types of data problem: statistical and geographical. The statistical problem related to lack of data regarding trips and land use. If the land use information was available and clear, distribution would be more accurate. In this case, population and employment were used as a proxy to determine generators and attractors of trips. The geographical problem, however, was more demanding. Fortunately good GIS data was obtained for the zoning system, but the only road network available was of very poor quality. The only way, at the time, to solve this problem was to create a network manually, following the maps obtained from ArcGIS. This was a tedious process, but it ensured that the entire network had the same accuracy and level of detail. If a GIS data bundle would be available (like zones, links and nodes) this would significantly increase the accuracy of the entire model, at least for future work. 10

11 Exact impedance and volume delay functions; from the previous studies, no information was given in the formulas used in the model. Usually, these types of functions are calibrated to accurately depict a region, and they differ from country to country. We adopted standard ones, and with some trial and error adjusted them slightly to give more satisfactory results. Network design problems; there were many assumptions and approximations that were necessary, mainly due to lack of data or sheer dimension of the issues. Firstly, and it was mentioned previously, the issues with capacity. Actual capacity can differ greatly from a starting default value (e.g veh/h/lane) due to gradients, existence of crawler line geometry of the road, signalization, etc.. These can have considerable impact, and needs to be included if the model is to be upgraded. Special consideration should go to type of terrain the road goes through, and this should influence capacities. Furthermore, as Serbia has two distinct geographical areas; North, which is completely flat and South, which is mostly hilly and mountainous terrain, the differences in network performance between regions would be even more distinct. Transit (external) trips; Modeling transit trips can be quite different from modeling inner trips. So different, that it may require a separate sub-model to describe these types of movements. In this thesis, due to various restrictions, a broad simplification had to be applied. The only data available were the counts at the border crossings, which gave us a general idea how the flows work and what are the volumes. In the future scenarios, these volumes were increased using growth rates for all trips. Freight; as with transit trips, freight traffic requires a separate sub-model in order to be realistic and accurate. As very little data was available, and also due to the fact that a relatively small percentage of all traffic is freight, general simplification was applied; a 5% of all trips was considered to be freight, and a unit of freight was set to be equal to 3 personal car units. If land use data was available, greater accuracy could have been achieved. Finally, is necessary to provide some leads for future work. As the model at hand needs additional refinement and improvement, we will list possible directions in which the future research should go: Acquiring of a more accurate GIS data for road network, preferably from and official source; Reassess network capacities using additional data (geometry, gradient, crawler lines, etc.) Creation of a sub-model for external transit trips, with separate growth rate functions more adapted to international economic relationship trends between different bordering countries; Creation of freight sub-model, using accurate land use data regarding industry; and Considering performing a strategic environmental impact assessment, focusing on major aspects, e.g. air emissions, biodiversity, protected areas, among a few others. 11