CHAPTER 1INTRODUCTION11 GENERALGeographic information ie Essay

CHAPTER 1

INTRODUCTION

1.1 GENERAL

Geographic information (i.e.., land information, spatial information) is information that can be associated with a place name, a street address, section/township, a zip code, or coordinates of latitude and longitude.

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A multitude of government functions require geographic information; at least 70 percent of all information used by local governments is geographically referenced. For example, property records and assessment, planning and zoning, permit tracking, natural resource management, infrastructure and transportation management, economic development planning, and health safety.

All of these applications consider the location of certain features on the landscape in relation to other features.

For instance, in assessment, the location of soil types relative to property parcels is considered, whereas in planning and zoning, the location of animal confinement facilities relative to residential areas might be relevant. A geographic information system (GIS) allows the user to examine and visualize these relationships.

A “geographic information system” (GIS) is a computer-based tool that allows you to create, manipulate, analyze, store and display information based on its location.

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GIS makes it possible to integrate different kinds of geographic information, such as digital maps, aerial photographs, satellite images and global positioning system data (GPS), along with associated tabular database information (e.g., ‘attributes’ or characteristics about geographic features).

Using GIS, you can incorporate all of this information into a single system and execute common database operations. For example, GIS allows you to perform statistical analysis or spatial queries, to explore ‘what-if’ scenarios, and to create predictive models. GIS has shown great application in a number of field including transportation.GIS capabilities including integration of geographical spatial-analysis and cartography.The various advantages of

1.2 OBJECTIVE

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By using Geo-spatial technology,

• To reduce the traffic.

• To provide alternate measures to reduce congestion.

• To help in accident minimization.

• To ensure efficient and smooth flow of traffic.

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1.3 PURPOSE AND NEED FOR STUDY

• Traffic management analysis is one of the most important aspect in the field of civil engineering.

• The proper road network, knowledge on traffic conditions and accident location is important for an efficient environment.

• Studying and accessing, will helps in reducing an accident and ensure smooth flow of traffic.

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• It helps in road facilities(routes),priority for road expansion.

• Helps in planning and designing existing and new facilities of traffic operation on road.

1.4SITE LOCATION

Figure 1.1 Google earth image of selected zone

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CHAPTER 2

LITERATURE REVIEW.

2.1 GENERAL

Literatures from the reputed national and international journals were studied for the study on the use of GIS for the management of traffic systems. The suggestions made by authors were taken into considerations. The valuable parameters over the recent years were reviewed and considered in this project.

2.2 LITERATURE REVIEW

Guisoppe Chills et al (2018) done an analyze on rural landscape by using GIS and made the historical maps combined with modern digital cartography and remote sensing images to achieve targeted rural landscape planning in Southern Italy

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Dong Bin Shin et al (2018) studied on Development of Geo-spatial Big data service system based on 7V in Korea which enormously increasing open government data ,smart devices and location based services to secure technology to store , manage , analyze and deliver service. The concept and characteristic of GSBD were implemented a 7V based GSBD system to Analyze the changes in South Korea territory and Pilot system for a GSBD service supporting it.

Yu-Ming Wang et al (2018) done a research with respective Analyze by using GIS and they controlled the Traffic Accident in Nantou Country. Then they found the time of accident takes place and the current location where the accident takes places using the application of Geographic Information system.

H.Ebru colak et al (2018) determined the intensity of traffic due to accidents(Hotspot region) using GIS and Hotspot Analysis based on network spatial weight to determine spatial statics of traffic accidental in Rige ,Turkey using two method of hotspot analysis , Network spatial weights to identify black spot for traffic safety and Kernel Density to identify traffic accidents.

Helen Thompson et al (2016) is an Overview done on Geo-spatial Method used in Uni –inteptional injury epidemiology to detect Socio economic and physical environmental factors which associates with injury incidence which applied in uni intentional injury epidemiology studies using Geo spatial epidemiology methods such as mapping,clustering and ecological analysis.

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H.Sebnem Duzgun et al (2014) is about the Spatial Analysis of Two wheeled vehicles Traffic crashes took placed in osmaniye ,Turkey they have used GIS with statistical analysis method for accidental and Analyzed the road traffic accidents according to vehicle types and done Chi-square test for non-spatial analysis kernel density and K-Function for existence of clustering of hotspot and executed through (SANET)spatial analyzes on network.

A.Petrosino oliver (2013) studied on Road Traffic conflict Analysis from Geo referenced stereo sequences, It exploits traffic conflict analysis,stereo system and traffic and this Technique done by adapting driver interacts behavior with respective vehicle road characters, traffic control device and environments.

F.Benjamin ZHAN et al (2012) studied the effects of real time traffic information system on traffic performance under different network system. It Investigate the real time Traffic information system (RTTIS)Traffic network ,Traffic efficiency and optimization of urban traffic and the investigation of (RTTIS) is done under parallel Grid and Ring Networks.

Nuvolone et al (2011) examines the affected respiratory health status. Geographical inform system and environmental epidemiology a cross- sectional spatial analysis of effect of traffic- related air pollution on population respiratory health status which points out the effect of traffic related air pollution on respiratory health status and also highlights value of added GIS in environmental health research.

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CHAPTER-3

METHODOLOGY

3.1 GENERAL

The methodology adopted in our project work is illustrated in the flowchart 3.2. The methodology indicating the various salient activities involved in studying GIS used in the management of traffic systems from Perungalathur to Guduvancheri zone.

3.2 STUDY AREA

The Selected Zone is from Perungalathur to Guduvancheri which covers a total area of 27.05 Km2.The Total Population in the particular zone is 127414 and The Total household present in the area is 32587.The above information are collected from the source

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Figure 3.1 Site location (a)

Figure 3.2 Site location (b)

Figure 3.3 Schematic representation of methodology

3.3 RECONNAISANCE SURVEY

The act of scouting or exploring (especially military and survey) to gain information about a particular location is known as reconnaissance.Location chosen for this project is from Perungalathur to Guduvancheri. It is in Chennai; it is located in such a way that it connects to all the major location.

Some of the companies like Chain System India Private Limited, Accenture Pvt. LTD, Sybrant Technologies, Take Solutions, Team Pvt. LTD, Trianz, Redington Gulf FZDE, Gateway Office Parks, HTC Global Services India Pvt. LTD, Writers Information Management Services which are seen near this location and Institution like BSA CRESCENT Institute of science and technology, Kilakarai Bukhari Aalim Arabic College, Crescent school, Sri Sankara Vidyalaya Matriculation School, Sri Sankara global academy are also present near the zone which results in traffic in the morning because of the institutional busses.

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Highly populated places like Anna Zoological Park, VGP ground, Government Hospital, Guduvancheri, Fish Market are located around the zones, because of this there will be constant movement of people and vehicles all the time. Also there are a lot of industries (IT and manufacturing), Banks, Schools, car and bike showrooms located near the study area.

3.5 IDENTIFYING REASON FOR TRAFFIC

Bus stop occupies a little portion of the main road and creates chaos and problems for the commuters and decreases the smooth flow of traffic. Most of the roads around this junction are not fully constructed which forces the commuters to take a particular road which increases the traffic at Perungalathur and Urappakam. There are a lot of pot holes in the roads which decreases the efficiency of movement of traffic flow. Also there are a lot of commercial areas around Vandalur and Guduvancheri; therefore there is constant movement of people from one place to another.

3.7 TRAFFIC VOLUME COUNTING

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Traffic counting can be done in two ways Manual and video counting. In manual counting we have to be physically present at the site and note down the number of vehicle travelling. In video counting we can just place the camera at a particular place and we can count it at end of the day.

For this project the traffic counting is done only during the peak & non-peak hours in the mornings, afternoon and evening, manual counting is adopted here for completion of the project.

3.8 NOTING DOWN WHERE THE VEHICLE IS TRAVELLING

Different types of vehicle travel in different directions. Noting down the direction in which the vehicle is travelling and the type of vehicle is also a key component required for completing the project.

3.9 DIFFERENTIATING THE TYPE OF VEHICLE

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In a road there will be various types of vehicles travelling i.e. two wheeler, three wheelers, Light mode vehicles(LMV) like cars and Heavy mode vehicles (HMV) like Busses and trucks etc. Differentiating and noting down of each of these vehicles is a very important aspect which will help us determining the volume of traffic in a particular direction.

3.11 IMPLEMENTING THE DATAS IN GIS

All the observed and recorded data’s are added to GIS. A Georeferenced data is used in GIS and digitization of the road network was done on top of it; The attributes such as width of the road, no of lanes and whether the road is one way or two way was added to the GIS data. Once all the spatial and non spatial information was added the traffic analysis and the accident hot spot analysis can be performed in GIS.

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CHAPTER 4

RESULTS AND DISCUSSIONS

4.1 VEHICLE VOLUME COUNT

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We count the number of vehicles passing through the GST Road to have a better knowledge and understanding about the reasons for the traffic and congestion. These counting are done during the peak & non-peak hours and it is done for three week days i.e,Tuesday,Wednesday,Thursday

VEHICLES 7.30-9.30

AM

(PEAK) 10.30-11.30

AM (NON PEAK) 2-3.30

PM (NON PEAK) 6-7.30

PM

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(PEAK) TOTAL VEHICLES

PEAK NON PEAK

2W 471 458 439 495 966 897

3W 126 91 119 115 241 210

LMV 828 670 630 735 1563 1300

HMV 912 205 212 255 1167 417

Table 4.1 Collective data on number of vehicles in Perungalathur

Figure 4.1 Perungalathur Hotspot

VEHICLES 7.30-9.30

(PEAK) 10.30-11.30

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(NON PEAK) 2-3.30

(NON PEAK) 6-7.30

(PEAK) TOTAL VEHICLES

PEAK NON PEAK

2W 1082 781 925 973 2055 1706

3W 625 386 409 416 1041 795

LMV 1328 1164 1227 1315 2643 2391

HMV 1395 1147 1213 1346 2741 2360

Table 4.2 Collective data on number of vehicles in Vandalur

Figure 4.2 Vandalur Hotspot

VEHICLES 7.30-9.30

(PEAK) 10.30-11.30

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(NON PEAK) 2-3.30

(NON PEAK) 6-7.30

(PEAK) TOTAL VEHICLES

PEAK NON PEAK

2W 854 607 415 928 1782 1022

3W 610 302 437 495 1105 739

LMV 1825 1045 1532 1634 3459 2577

HMV 1084 716 640 1145 2229 1356

Table 4.3 Collective data on number of vehicles in Urapakkam

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Figure 4.3 Urapakkam Hotspot (a)

Figure 4.3 Urapakkam Hotspot (b)

4.2 CALCULATION:

Capacity , c = (1000 * v) / s

v = Speed in Kmph

s = average spacing between successive moving vehicle

s = L + 0.78 * v * t + (v2 / 254f)

= 5.0 + 0.78*2.5*50 + (502 / 254*0.5)

= 122.185m

C = (1000*50)/122.185

= 410 Vehicles per hour per lane

Source: Highway engineering by Khanna & Justo

According to IRC: 73-1980, the equivalency factors for different types of vehicles are given:

S.NO VEHICLE TYPE EQUIVALENCY FACTOR

1 Passenger car, tempo, auto-rickshaw, or agriculture tractor. 1

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2 Cycle, motor cycle or scooter 0.5

3 Truck, bus, or agricultural tractor trailer unit. 3

4 Cycle rickshaw 1.5

5 Horse- drawn vehicle 4

6 Bullock cart 8

Table 4.4 EQUIVALENCY FACTOR TABLE

Table 4.5 PCU AND V/C RATIO

Analysis:

• The v/c ratio should be lesser than 1 for a normal flow

• The calculated v/c ratio of Perungalathur ranges between 2.609 to 4.683

• The calculated v/c ratio of vandalur ranges between 9.039 to 10.516

• The calculated v/c ratio of urapakkam ranges between 6.418 to 9.871

• From the above analysis the v/c ratio is more than 1 which indicates the congestion of traffic in that particular area

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4.3 ANALYSIS USING GIS

A geographic information system (GIS) is a computer system for capturing, storing, checking, and displaying data related to positions on Earth’s surface. GIS can show many different kinds of data on one map. This enables people to more easily see, analyse, and understand patterns and relationships.. By the use of GIS the georeferencing, spatial reference, digitizing and hotspot analysis for accidental zones have been done.

4.3.1 Georeferencing

It is the process of assigning real world coordinates to each pixel. Many times these coordinates are obtained by doing surveys- collecting coordinate with a GPS device for a few identifiable features in the image or the map. Here the georeferencing is done.

S.NO LOCATION LONGITUDE LATITUDE

1 OLD PERUNGALATHUR 80.53743 12.55613

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IRUMBULYUR 80.63713 12.55050

PEERKANKARANAI 80.63134 12.54196

SRINIVASA NAGAR 80.53169 12.54293

2 OTTERI 80.42829 12.53830

VANDALUR ZOO 80.51291 12.53415

CRESCENT CAMPUS 80.51236 12.52344

D.S.NAGAR 80.42464 12.52386

3 URAPAKKAM FLY OVER 80.42292 12.52922

VGP 80.44559 12.52977

AMBIKA NAGAR 80.44807 12.51534

URAPAKKAM RAILWAY STATION 80.42370 12.51530

Figure 4.6 Georeferencing of selected zones

4.3.2 Digitisation

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It is the process by which coordinated from a map, image, or other sources of data are converted into digital formats. This method involves scanning a map or image into a computer. The digitizer then traces the points, lines and ploygons using digitizing software.

Here the green lines indiciate the roads and red point indicate the hotspot region as shown in the following figures

Figure 4.4 Digitising of Perungalathur zone

Figure 4.5 Digitising of Vandalur zone

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Figure 4.6 Digitising of Urapakkam zone

4.4 RECOMMENDATION

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CHAPTER 5

CONCLUSION

The growing complexity of urban Traffic requires the use of advanced tools and various types of analysis which could simulate the traffic in real time.

Although there are sufficient tools to analyse the results, in this project we have tried to demonstrate the compositional method for modelling and performance evaluation of complex traffic situations by using GIS.

By the help of GIS, the georeferencing, digitising and hotspot analysis for zones are done.

From the above results, it is known that due to heavy movement of vehicles, major traffic takes places at the Perungalathur,Vandalur,Urapakkam and Guduvancheri junctions as per the survey. Due to increase in traffic volume many accidents may occur. Also the bus stand is pretty close to the road, therefore some of the buses get parked on the side of roads.

In order to reduce the traffic volume and to minimize the accidents, the alternative measures are provided. The vehicle count is also done in the selected routes and this shows that the vehicles moving in that direction are only a few and these roads can be utilised more, if they are well constructed and maintained.

REFERENCE

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[4]. Greibbe et al, 1999. “Speed Management in Urban Areas, A framework for the planning and evaluation process”, Report no. 168, pg 9-13.

[5]. Jacobs G. D; A. Aeron-Thomas, Gururaj. G, F .Rahman and B. Sexton (eds) (2004) ‘The involvement and impact of road crashes on the poor: Bangladesh and India case studies’. Global Road Safety Partnership.

[6]. Jha M., S. Madanat, et al, 1998. Perception updating and day-to-day travel choice dynamics in traffic networks with information provision. Transportation Research Part C: Emerging Technologies 6(3): 189-212. [7]. Johnson Keith R (1999) Building a Transport GIS in Manipur, Secretary, Government of Manipur, Manipur, India.

[8]. Joseph Owusu, Francis Afukaar and B.E.K. Prah, “Urban Traffic Speed Management: The Use of GPS/GIS” Conference proceeding, Shaping the Change XXIII FIG Congress Munich, Germany, October 8-13, 2006.

[9]. Katsikopoulos, K.V., Fisher, D.L., Duse-Anthony, Y. Duffy, S.A., (2002), Risk attitude reversals in drivers’ route choice when range of travel time is provided. Human Factors 44(3): 466-473.

[10]. Lam, T.C., Small K.A. (2001). The value of time and reliability measurement from a value pricing experiment. Transportation Research part E: Logistics and Transportation Research Part A: Policy and Practice 34(4): 243-260

[11]. Monahan, Torin. 2007. “War Rooms” of the Street: Surveillance Practices in Transportation Control Centres.The Communication Review 10 (4):367-389.

[12]. RegInald Souleyrette and Sitansu Pattnalk, (2003), ?Designing a traffic maintaining program using land use change detention‘. 6th Annual conference and exhibition on GIS, GPS A.P and R.S January 28-3 1.