FACILITY-BASED OPTIMAL RURAL ROAD-NETWORK DESIGN

Abstract

Transportation provides the basic infrastructure for all round development and it can be deemed to be the precursor of all forms of development activities. Among all the modes of transport, socially and culturally, road transport permits a higher degree of personal contact and social integration than do trains which pass or planes that fly overhead. Road transport has greater potential for involving more people in a wider variety of endeavours than any form of transport has. A large proportion of the population of India lives in villages or rural areas. The rural population is estimated as 68% of the total population in India. The existing communication facilities, in about 44% rural areas of India, are.still earth tracks and non-motorable foot-paths. In their present form, these tracks are not suitable for motorised traffic generated by various rural development schemes. During fair weather, these tracks cater to the rural traffic to an extent, but during the rainy season, they become muddy, slushy, slippery and practically unusable. The task of providing an adequate rural road network to cater the needs of 0.6 million villages throughout India is gigantic. Despite the ever increasing attention to the issue of rural roads and several national and regional programmes for their development, only about 56% of the villages are yet connected by roads. Large deficiencies in the connectivity available in the rural areas or to villages are undoubtedly due to paucity of funds, as well as, the adhoc approaches adopted to provide rural roads and the consequent sub-optimum designs of networks. After a careful review and critical analysis of research work carried out during the last thirty years in India and abroad, the need for the planning model for rural-road network-design, suitable for Indian condition, becomes all the more vital. In India, the research work carried out so far, could not provide any concrete approach, a practical model or a rational solution for the rural network planning. Most of the approaches are adhoc and not related to the socio-economic condition or the actual trip-pattern of the region. Those approaches which partially use some of these parameters, are also based on adhoc relationships. Furthermore, no model could be applied for the planning of any rural area in India, in real sense. The reason is the use of adhoc values of various parameters and unexplained complexity of these models. So a network model is needed in India, which should incorporate the actual trip-pattern phenomenon, depicting socio-economic parameters and facilities easily available in the villages of India. For this purpose, district Ghaziabad in Uttar Pradesh was chosen for the study. Thirtytwo villages of different population levels were selected in four tehsils (sub divisions) of Ghaziabad district namely Hapur, Dadri, Modinagar and Ghaziabad. Ghaziabad is comparatively a more developed sub-division while Hapur, Dadri and Modinagar are average developed rural areas, truly representative of Indian Scenario. To incorporate the effect of highly rural areas, three villages of kotputli subdivision of Jaipur district in Rajasthan State of India, were also included, to make it a more representative data set. So the total number of villages surveyed is 35. A location map of the study areas has been included in the thesis. In each village about 20 families of different sizes and socio-economic status, selected randomly, were interviewed. In all, 711 families and 4255 persons were surveyed. These numbers are found to be quite reasonable in view of the fact that it is a very difficult and timeconsuming process in rural areas of India, where any data is not available and contacting identified households is rather tough. The very first objective of this study was to know the prime factors which are responsible for inter-village or village-town trip generations. For this purpose, various trips are classified as per purpose for trip making. It shows that out of total actual trips, 42% trips are education centre bound or study purpose trips. It is far ahead from domestic purpose occasional trips (17%), service bound trips (16%) and business bound trips (16%) . It shows the major share, dominance and a need to base the plan of roads on education. The total trip-lengthwise distribution confirms the need to pay attention to education bound trips. The destination of education bound trips is always education centre which may be situated in a nearby area or at the nearest market centre/town, as per the prevalent practice in rural areas of India. It is observed that 92.79% trips either terminate at market centre or education centre. So, if a network is planned with the objective to connect the villages to education centre and the nearest market centre/main road, then it will possibly be the most efficient network. The analysis shows that the age group of 11-15 has the maximum trips per person per month as 26.45 followed by 16-20 years age group and then by 21-30, 31-40 and 41-50 years. Almost the same trend is repeated if instead of trips per person per month, trip-length per person per month is the criterion. The age group 11-15 years is having maximum triplength/ person/month as 237.35 km. It is again followed by the age groups 16-20, 21-30, 31-40 years. Interestingly, the leading age groups, i.e., 11-15 and 16-20 years are the age groups of students. All this information and discussion emphasizes that the education is a major cause for trip generation. With this background, it becomes obvious to ascertain the effect of road accessibility to education centre on the education level of a village. The education level for a particular standard may be defined as the number of persons studying or have studied in that particular standard to the total number of persons surveyed. In this analysis, three standards have been chosen, i.e., Junior High School, High School and Intermediate College (Senior Secondary Schools) to calculate the education levels. Primary Schools are not included for the analysis purpose, because almost all the villages, in India, have IV primary schools within the village and so no inter-village trips are generated due to the desire of this education level. Degree colleges (University education level) are also not included because degree colleges are not available in village clusters. Here it is observed that as the distance from the education centre increases, the education level starts dropping. The slope of the curve is maximum for Junior High School standard and minimum for Intermediate college (senior secondary school) standard. These curves can be used as nomograms till a country wide survey and results are available for reference. After analysing the data, it is concluded that education is the prime parameter which is responsible for trip generation. If a education centre is available in nearby areas of a village and it is well connected by an allweather road, the village is likely to have a better level of education with an increase in trip generation rate, as well as, education in the area. It is also to be noted that the dominance of the education centre bound trips is due to the fact that the frequency of these trips is generally 20-30 to and fro. On the other hand, trips for other purposes, like domestic trips, are once or twice a month only. Personal relation or social trips which come under occasional trips, are also of low-frequency. One of the important goals of a transport design effort is a balanced network that meets the needs of the population in most effective manner. In aggregate, 92.79% trips can be covered, if the networks are designed to connect all the villages to a nearest market centre/main road through routes which provide minimum required accessibility to education centres. Here the minimum required accessibility means the maximum permissible distance from a education centre for each standard which may be specified by the planner. This distance may be approximately fixed by having an idea from nomograms (figures) after choosing a particular education level. This procedure will automatically give a preference to the routes which have an education facility on the way to market centre. It will remove the prevailing adhochism in the planning strategies to give weightages to various facilities available in the villages. A check on maximum permissible distance from the education centre is a better way than to arbitrarily assign some weightages. It is an easy approach and meets the needs of 92.79% trips. The following logics are used for developing the computer program for the present study: (1) The flow of trips is taken as flow of water with storages of water at all connected points. This water has to reach each and every village node irrespective of the source, i.e., it can come from any connected node. The approach of "Minimum Spanning Tree" is adopted for this purpose. (2) The iteration procedure starts simultaneously with all the connected nodes, and all the links emanating from these nodes, are considered. The link of minimum construction cost per person served is chosen. (3) The chosen link is checked for the distances from Junior VI High School, High School and Intermediate College (Senior Secondary School). These distances should not be more than maximum permissible distances from these centres respectively. If it is not so, then the next link of higher construction cost is chosen and checked. This iteration process is repeated till a link, which is within the limits of these maximum permissible distances, is found. (4) Now the new node is also considered as connected node. This process is repeated till all the nodes are connected. The computer program is developed in TURBO C language. It is a simple and compact program. The inputs include the topographical maps, published by the Survey of India Department, available at various scales. For planning purpose at village level, maps of two scales are required. These scales are 1:250,000 and 1:50,000. The maps of 1:250,000 are required for identifying and dividing the area into various suitable frames (zones), each consisting of 40-60 villages with main roads atleast as one of its boundry. The 1:50,000 maps are used for locating the available cart-tracks, earth tracks, etc. Using these maps, the relative position of the villages is fixed and transferred to the files. The length of the available cart-tracks/earth tracks is also measured from these topographic sheets. Census Records, published by the Census Department of India, are also used to know population of the villages and various facilities available in the villages. The market centres and towns are also identified by these records. The data, regarding existing roads in the VII area, is collected from PWD and other local agencies, invoved in rural road construction. Input Data is given in two files. Data.Txt is the file which contains node numbers, village names, population, connectivity status, school availability in the villages, link number, connecting nodes, length of links, cost of links and type of links. This file contains factual information, and once prepared, doesn't need any change during iterations. The second file is School.Txt which contains node-numbers, distance of- the connected nodes from schools, i.e., from Junior High School, High School and Intermediate college (Senior Secondary School) respectively. These values are also fixed. In the last, this file contains maximum permissible distances from Junior High School, High School and Intermediate College. These values are chosen from the nomograms (Figures), developed in this doctoral programme. The model checks the distances from three specified points. It has the flexibility to base the design on any other parameters instead of education, like health centre, bank, post office, police station, etc. The emphasis of this research work is to develop a technique, for rural road network design, which can be easily used in India. For a wide scale application of this expert system (model), it is further developed as a menudriven user-friendly computer-aided design model in such a manner that the data entry can be done by even a beginner or local engineer/planner/network designer, obviating the need of an computer expert. VIII The Garhmukteshwar subdivision, about 75 km away from New Delhi, was selected for the study and for validation of the computer model, developed in this doctoral programme. Ganga (Ganges) , one of the major rivers of India and a few canals pass through this area. This area is divided into four zones called frames so that every frame is surrounded by main roads on two sides. The network, designed by using this model, is efficient in following respects: (i) Each and every village has one and only one route to reach the market centre/main road giving no chance to multiplicity of links to some villages. (ii) All the existing roads have been incorporated, as far as possible, in the optimal network. (iii) All the villages have the Junior High Schools, High Schools and Inter College (Senior Secondry School) within 14, 20 and 20 km distances respectivey. (iv) The proposed construction cost in terms of length of new construction, when the education parameter is considered, comes out to be 85.85 km for the whole subdivision, which is just 11.28% more than the cost when education parameter is not considered. (v) Direct links are available for 96% trips in the Garhmukteshwar subdivision, if the network, designed by this proposed model, is used. These results validate the model and prove its usefulness. (vi) Finally, it is the best developed state of the art model till today. IX