Journal of International Academic Research for Multidisciplinary
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1 Journal of International Academic Research for Multidisciplinary
2 Editorial Board Dr. Kari Jabbour, Ph.D Curriculum Developer, American College of Technology, Missouri, USA. Er.Chandramohan, M.S System Specialist - OGP ABB Australia Pvt. Ltd., Australia. Dr. S.K. Singh Chief Scientist Advanced Materials Technology Department Institute of Minerals & Materials Technology Bhubaneswar, India PROF.Dr. Sharath Babu,LLM Ph.D Dean. Faculty Of Law, Karnatak University Dharwad, Karnataka, India Dr.SM Kadri, MBBS,MPH/ICHD, FFP Fellow, Public Health Foundation of India Epidemiologist Division of Epidemiology and Public Health, Kashmir, India Dr.Bhumika Talwar, BDS Research Officer State Institute of Health & Family Welfare Jaipur, India Dr. Tej Pratap Mall Ph.D Head, Postgraduate Department of Botany, Kisan P.G. College, Bahraich, India. Dr. Arup Kanti Konar, Ph.D Associate Professor of Economics Achhruram, Memorial College, SKB University, Jhalda,Purulia, West Bengal. India Dr. S.Raja Ph.D Research Associate, Madras Research Center of CMFR, Indian Council of Agricultural Research, Chennai, India Er. R. Bhuvanewari Devi M.Tech, MCIHT Highway Engineer, Infrastructure, Ramboll, Abu Dhabi, UAE Sanda Maican, Ph.D. Senior Researcher, Department of Ecology, Taxonomy and Nature Conservation Institute of Biology of the Romanian Academy, Bucharest, ROMANIA Dr.Damarla Bala Venkata Ramana Senior Scientist Central Research Institute for Dryland Agriculture (CRIDA) Hyderabad, A.P, India PROF.Dr.S.V.Kshirsagar,M.B.B.S, M.S Head - Department of Anatomy, Bidar Institute of Medical Sciences, Karnataka, India. DR ASIFA NAZIR, M.B.B.S, MD Assistant Professor Dept of Microbiology Government Medical College, Srinagar, India. Dr.AmitaPuri, Ph.D Officiating Principal Army Inst. Of Education New Delhi, India Dr. Shobana Nelasco Ph.D Associate Professor, Fellow of Indian Council of Social Science Research (On Deputation}, Department of Economics, Bharathidasan University, Trichirappalli. India M. Suresh Kumar, PHD Assistant Manager, Godrej Security Solution, India. Dr.T.Chandrasekarayya,Ph.D Assistant Professor, Dept Of Population Studies & Social Work, S.V.University, Tirupati, India. Dr. Vijay Pithadia, Ph.D, Director - Sri Aurobindo Institute of Management Rajkot, India.
3 GRAVITY MODEL CALIBRATION AND USE IN TRIP DISTRIBUTION ABSTRACT S.ZALA KARTIK* DR. L. B. ZALA** PROF. A. A. VANKAR*** *M.E. Student, Dept. of Civil Engineering, B.V.M Engineering College, Gujarat, India **Head, Dept. of Civil Engineering, B.V.M Engineering College, Gujarat, India *** Dept. of Civil Engineering, B.V.M Engineering College, Gujarat, India As the society evolves it generates transport demand. An estimate of the volume of trips between zones is a necessary step in transportation studies. The classical transportation planning methods are based on simple extrapolation of trends. Mathematical model like Gravity model in which the spatial configuration of destinations are incorporated in the modelling process (Veenastra S. A., T. Thomas & S. I. A. Tutert, 2010). This paper presents a model for trip distribution for Anand agglomeration using Gravity model. This model is also applicable for all the Indian cities which have population range nearby Anand agglomeration population. This model is applied on the real set of data on persons trips generated and persons trips attracted in all zones of Anand agglomeration, which in turn gives satisfactory results which can be applicable in current and future scenarios. KEY WORDS: Gravity Model, Trip Distribution, Calibration of Gravity Model, Anand Agglomeration, Travel Time, Travel Distance, Travel Cost. INTRODUCTION The different steps of Urban Transportation planning (Shivendra Goel, J. B. Singh, Ashok K. Sinha, 2012) are trip generation, trip distribution, and mode choice and traffic assignment. Brief description is presented in following paragraph Trip generation is the first step in the conventional four step urban transportation planning process, widely used for forecasting travel demand. It predicts the number of trips originating in or destined for a particular zone. Urban area is divided into several zones which are the clusters of household and socio-economic activities. 411
4 Trip distribution is the second step in the traditional four step urban transportation planning process. This step matches trip makers origins and destinations to develop a Trip O D Matrix Table. This matrix displays the number of trips going to destination. Gravity model is widely used for trip distribution analysis. Different trip distribution models (Kadiyali L. R, 2008, Juan de Dios Ortuzar, Luis G. Willumsen, 2006, Khisty & Lall, 2012) Uniform Growth Factor Method Average Growth Method Fratar Method Furness Method Detroit Method Gravity Model Intervening Opportunity Model Modal choice analysis is the third step in the conventional four step urban transportation planning process. Mode Choice Analysis allows the modeller to determine which mode of transport will be used. Traffic assignment concerns the selection of routes between origins and destinations in transportation networks. It is the fourth step in the conventional urban transportation planning process. Fig.1. shows four step urban transportation planning. Land use Data Trip generation Zone to Zone Travel Time, Cost, Distance, etc Trip distribution Mode choice Traffic assignment Fig.1. Four Step Transportation Planning Process 412
5 OBJECTIVES The aim of present study was to Calibrate Gravity Model for Anand Agglomeration. The objectives identified are: To prepare GIS database. To carry out house hold survey for tips and socio economic data. To prepare OD matrix for trips. To do gravity model calibration for various trips classes using Trans CAD software. STUDY AREA The study area need not be confirmed by political boundaries, but bounded by the area influenced by the transportation systems (Mathew T. V., Krishna Rao K. V., 2006). In short, study area should be defined such that majority of trips have their origin and destination in the study area and should be bigger than the area of interest covering the transportation project. The location of Anand Agglomeration is latitude North and longitude East. The location map is provided as fig.2. Fig.2. Study Area Location Map 413
6 The study area is sub divided into smaller areas called zones. The purpose if such a sub-division is to facilitate the spatial quantification of land-use and economic factors which influence travel pattern the data collected on individual household basis cannot be conveniently considered and analysed unless they are aggregated into small zones which reflect the average characteristics of the individual households. Sub division into zones further helps in geographically associating the origins and destinations of travel (Kadiyali L. R., Lal N. B., 2011). The following zoning criteria have been used for zoning. The criteria are compiled from experience in several practical studies (Juan de Dios Ortuzar, Luis G. Willumsen, 2006). Zoning size must be such that aggregation error caused by the assumption that all activities are concentrated at the centroid is not too large. The zoning system must be compatible with administrative divisions, particularly with census zones; this is probably fundamental criterion. Zones should be as homogeneous as possible in their land use and/or population composition; census zones with clear differences in this respect should not be aggregated, even if they are very small. Zone boundaries must be compatible with cordons and screen lines and with those of previous studies. The shape of the zones should allow an easy determination of their centroid connectors; this is particularly important for later estimation of intra-zonal characteristics. Zones do not have to be of equal size they could be of similar dimensions in travel time units, therefore generating smaller zones incongested than in uncongested areas. Keeping above criteria the Anand Agglomeration area is divided into 17 internal zones and 7 external zones. The zoning map is shown in Fig.3 help of TransCAD software. 414
7 Fig.3. Zoning of Anand Agglomeration Area Table 1. Zone Attributes ZONE NO ZONE NAME TOTAL HH NO OF MALE NO OF FEMALE TOTAL POPULATION 1 RAILWAY STATION MOGARI NEW V.V.NAGAR ISMAIL NAGAR ANAND NAGARPALIK HADGOOD JALARAM TEMPLE NEW BUS STAND FT ROAD D.Z.PATEL SCHOOL D MART PURSHOTTAM NAGAR LAXMI THEATRE BIG BAZAR & TOWN BAKROL GAM V.V.NAGAR KARAMSAD N N E N W S S E S W W
8 In zone attributes No. of household in that zone, No. of male in that zone, No. of female in that zone and No. of total population is taken which is collected from the Anand Municipality as well as from the census2011 data. DATA COLLECTION Data collection is the process of gathering the required information for each selected unit in the survey (Fellegi, 2003). In the first step collected map of study area with zonal boundary and population of each zone. The questionnaire format prepared for house hold interview. This process is expensive, time consuming, require extensive men power and has a direct impact in data quality. The data collection need: (1) Socio-economic data in which income, vehicle ownership, family size etc included. (2) Travel data in which number of trips made by each member of the house hold, the direction of travel, destination, the cost of travel and travel time is taken. DATA PREPARATION After collecting the raw data, because of various errors in the survey both in the selection of sample households as well as error in filling details, data preparation is needed. DATA CORRECTION After preparing the raw data it has to be corrected it by four different ways. (1) House hold size correction. (2) Socio-demographic correction. (3) Non-response correction. (4) Non-reported trip correction. The corrected data is given in form of table
9 Table 2. Sample Data Form No. Name Trip No. Starting Time Ending Time Travel Time Travel length (km) Origin Destination Cost 1 SALIMBHAI 1 07:45 08:00 0: SALIMBHAI 1 18:20 18:35 0: SALIMBHAI 1 18:55 19:05 0: NAZIA 1 09:45 10:00 0: NAZIA 1 10:20 10:35 0: IQBAL 1 09:00 09:20 0: IQBAL 1 09:50 10:00 0: MEHRUNBEN 1 10:00 10:10 0: MEHRUNBEN 1 10:40 10:50 0: AKRAM 1 07:45 08:00 0: AKRAM 1 11:45 12:00 0: MUSKAN 1 07:45 08:00 0: MUSKAN 1 13:15 13:30 0: H.M.SAIYAD 1 09:30 10:15 0: H.M.SAIYAD 1 17:30 18:15 0: INYAT 1 08:45 09:00 0: INYAT 1 17:45 18:00 0: JURKHAN 1 07:00 07:10 0: JURKHAN 1 11:45 12:00 0: FARUKH 1 09:00 09:15 0: FARUKH 1 13:00 13:15 0: FARUKH 1 14:00 14:15 0: FARUKH 1 19:00 19:15 0: Source: HH Interview Survey, 2013 METHODOLOGY The gravity model is synthetic model in which an attempt is made to discern the underlying causes of movements between places, and relationships are established between trips and measures of attraction, generation and travel resistance. Synthetic models have an important advantage that they can be used not only to predict future trip distribution but also to synthesis the base year flows (Mathew, 2006). Gravity model is used to distribute trips from origin zone to each destination zone in the region. It is based on Newton s law of gravity, which describes the gravitational force between two bodies. The number of trips between zones in transportation models is a function of the attractiveness of a zone and the travel impedance between zones. 417
10 Tij = Kij * Oi * Dj * F(dij) Where, Tij = The number of trips produced in zone i to zone j, Kij = ri * sj, Oi = Total number of trips generated in zone i, ri = Row balancing factor sj = Column balancing factor Dj = Total number of trips attracted in zone j, F(dij) = Friction factor. The gravity model in this application will apportion the trips produced at each production zone among attraction zones according to the attractiveness of each zone and the disutility of travel each trip interchange. This application is doubly constrained, which means that the trips produced from and attracted to each zone are consistent with the input assumption on trips. The basic frictional formula for the friction factors are given by the deterrence function as follows: Fig.4. Deterrence Functions Where, b value depends on the trips purpose (Modi et al, 2011) Table 3. b values for different purpose Trip Purpose b value Work Shopping Recreational Other Purpose
11 ANALYSIS The decision to travel for a given purpose is called trip generation. The decision to choose destination from origin is directional distribution of trips forms the second stage of travel demand modelling. Trip distribution is determined by the number of trips end originated in zone-i to number of trips end attracted to zone-j, which can be understood by the matrix between zones. The matrix is called origin destination (O - D) matrix. From the House Hold interview survey for study area zones the trip distribution O D matrix is prepared with the help of SPSS Statistics 17.0 software. Table 4, represents the observed O - D matrix. Table 4. Observed Trip Based O D Matrix Distance matrix, Travel Time matrix and Travel Cost matrix are prepared using questionnaire format data with the help of SPSS Statistics 17.0 software, shown in Table 5, Table 6 and table 7 respectively. 419
12 Table 5. Travel Distance Matrix (Travel Distance in km) Table 6. Travel Time Matrix (Travel Time in minutes) 420
13 Table 7. Travel Cost Matrix (Travel Cost in rupees) The desire line diagram for observed trips are prepared with the help of transcad software using observed O D Matrix and is given in Fig.5. Fig 5. Observed Desire Line for Anand Agglomeration 421
14 CLIBRATION OF GRAVITY MODEL Gravity Model Calibration tool from TransCAD matrix is used for calibration of gravity model using distance, time and cost attributes and 4 iterations. The calibrated exponent values are shown in Table 8. Table 8. Calibrated exponent values Sr No. Trip Purpose Using Travel Time (min.) UsingTravel Distance (km.) Using 1 Business Service Home CONCLUSION Cost (rs.) Travel The desire lines for trips have been shown in fig. 5 shows that dominant traffic directions are: 1. Zone 15 (Bakrol Gam) to zone 1 (Railway Station) via from zone 16 (V. V. Nagar), zone 14 (Big Bazar & Town Hall) and 2. Zone 17 (Karamsad) to zone 5 (Anand Nagarplaika) via from zone 16 (V. V. Nagar) and zone 14 (Big Bazar &Town Hall). 3. The value of exponent is different for different cost attributes. REFERENCES 1. Fellegi. I. P., October 2003, Survey Methods And Practices, Ottawa, Canada. 2. Juan de Dios Ortuzar, Luis G. Willumsen, August 2006, Modelling Tranport, John Willey & Sons, LTD, 3rd Edition, Reprinted with Corrections. 3. Kadiyali, L. R. and Lal, N. B., 2011, Traffic Engineering and Transport Planning, Khanna Publishers, 9th Reprint. 4. Khisty C. J and Lall B. K., 2012, Transportation Engineering An introduction, PHI Learning Privated Ltd., 3rd Edition. 5. Mathew T. V., Krishna Rao K. V., 2006, Introduction to Transportation Engineering Trip Distribution, NPTEL. 6. Mathew T. V., Krishna Rao K. V., 2006, Introduction to Transportation Engineering Traffic data Collection, NPTEL. 7. Modi K. B.,Dr. Zala L. B.,Dr. Umrigar F. S. Dr. Desai T. A., May 2011, Transportation planning models : A review, National Conference on Recent Trends in Engineering & Technology. 8. Shivendra Goel, Singh J. B., Sinha A. K., March 2012, Trip Distribution Model for Delhi Urban Area Using Genetic Algorithm, International Journal of Computer Engineering Science. 9. Veenstra S. A., Thomas T., Tutert S. I. A., 2010 T,rip Distribution for Limited Destinations: A case study of grocery shopping trips in the Netherlands, Transportation. 422
Journal of International
ISSN 2320-5083 Journal of International Academic Research for Multidisciplinary A Scholarly, Peer Reviewed, Monthly, Open Access, Online Research Journal Impact Factor 1.393 VOLUME 1 ISSUE 11 DECEMBER
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