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GIS datatbase for Chennai city roads and strategies for improvement

GIS Analyst (Trainee), IIC Technologies Pvt. ltd., Hyderabad –500 482
Tel: 91-040-3354356

M.E (Urban Engg.), Anna University,Chennai –25.

In India various problems related to road network can be identified as inadequate capacity, congested city roads, safety, lack of way side amenities, poor riding quality etc. One of the major problems in preparing the road network improvement strategy is the lack of large volume of data needed for it. And even if it is available, the problem is how to manage and access the data. As the different informations are scattered at different agencies, it is a severe problem for the respective organisations to make any decision on the road network problem. Every time it is mandatory for those organizations to start from scratch in planning and executing of their work. Considering the complexities in developing, updating and processing of transport related data there is an urgent need to adopt new concepts on information technology in design and development on information system for the road network. The application of GIS in particular has relevance to road network due to the spacially distributed nature of road related data. Thus, GIS technology provides coreframework for an integrated information system on transportation.

Chennai, the capital of Tamil Nadu has grown from a tiny fisherman’s hamlet during the 17th Century to the fourth largest metropolis in India. It is housing a population of 6 million which is expected to grow to 10 million in the near future. The Chennai metropolitan area(CMA) covers an extent of 1172 sq.kms of which the city municipal administration area extends to 172 The major road network in the metropolitan area is of ring and radial pattern with 5 radial arterials and one Inner Ring Road(IRR). Also it is proposed to construct one Outer Ring Road (ORR) and a by-pass road. The major roads are listed below:
  1. NH 5 on the North West towards Calcutta
  2. NH 4 on the South West towards Bangalore
  3. NH 45 on the Southern Direction towards Madurai
  4. Thiruvallur High Road parallel to NH 4
  5. Inner Ring Road from Kathipara to NH 5.
The rapid growth of population and increasing number of motorised and non-motorised vehicles put the city’s road network into a complex problem. In the existing social scenario, the urban planner is forced to manage the existing facilities rather than to develop new facilities. Due to the spatial distributed nature of transportation related data, GIS technology provides the core frame work an integrated traffic information system.

The objectives of the study are:
  • To develop a database for Chennai City using GIS
  • To identify the critical links for Chepauk Zone re quiring immediate attention.
  • To propose improvements for the critical links.







Study of Methodology AHP - Analytical Hierachy Process

Methodology for Analysis

Database Development for Chennai City
The road network of Chennai City is digitised using PC ArcInfo. The source of the map is survey of land record map. This map is drawn based on Survey of India map and its scale is 1:33,000. The road network of Chennai City is digitised by considering all the roads in the map. Total of nine spatial locations were identified as control points to project the map in to its real world co-ordinates. The concept of geographic database, is to structure the data according to certain number of logical rules. The geographic database of Chennai City is conceived and elaborated under the GIS Arc/Info Software. The Structure of database is shown in the figure below.

The minimum road width for the development of database is taken as 12m width. The reason of choosing 12m width is, as per detailed development plan, only roads with more than 12m width is considered as Public Roads. Hence three levels of road network is taken as follows:
  1. I Order Roads -  road width of more than 24 m
  2. II Order Roads -  road width of between 18 m – 24 m
  3. III Order Roads -  road width of between 12 m – 18 m.
Hence, Database is developed for all the above road network level. The database is developed for road length of 7. 35 km in I Order roads, 16.79 km in II Order roads and 85.08 km in III Order roads. The data in the database are also categorized as Group 1 and Group 2. The purpose of this classification is that only Group 1 data is used for further analysis in this work. For all the above development, Simple Macro Language(SML) have written for graphical user interface(GUI) .Road network level and its database for Chennai City are shown in the form of maps as below.

Identification of Critical Links
After developing the road network database for Chennai City, Chepauk area is taken as study area for the analysis. The Chepauk comes under the planning division of 11, unit no.2 in Detailed Development plan prepared by Chennai Metropolitan Development Authority. The approximate extent of the land is 47 hectare. A map showing the database of the study area is shown below.

The critical link among the selected stretch is identified based on model generated by Analytic hierarchy process (AHP) technique. The composite index is found by using the model and AHP technique is used to generate scores for the factors that are considered for analysis. The composite index for various are generated by the model and the lowest model value indicates the critical link of the selected study area. Also, the positive and negative impact of the factors towards the objective of the work is taken in to account in deriving the model value. Critical links are identified by considering the following factors.
  1. Carriage way width
  2. Footpath width
  3. Volume on the road
  4. Capacity of road
  5. Average Speed
  6. Percentage of Slow Moving Vehicles.
Model Development and its Application
For the present study, the spatial- AHP technique (integrating the GIS database in the AHP frame work) is applied to find the relative importance weight (RIW) for each decision factor. The composite index for each road is determined by aggregating the relative importance weights at each level of the hierarchy. The RIWs are normlsed eigenvectors corresponding to the maximum eigenvalues of the pairwise comparison matrices constructed at each level of the decision hierachy. The RIW assigned to each hierarchy element is deremined by normalising the eigenvector of decision matrix.

Eigenvector values are eatimated by multiplaying all the elements in a row and taking the root of the product, where in is the number of row elements. Normailsation of the eigen vector is accomplished by dividing each eigen vector element by the sum of the eigen vector elements of the decision matrix. After finding the relative importance of various factors, a model is developed for finding a composite index for various roads which assists in identifying the critical links.

The scores for each factor on scale of 9 are as follows :
Carriageway width - 5.50
Footpath width - 1.89
Volume/Capacity ratio - 1.57
Average speed - 0.68
Percentage of SMV - 0.35

The above model is then developed and fed in the PC ArcInfo. The Model equation is as follows:

5.5Ri1 + 1.89Ri2 + 1.57Ri3 + 0.68Ri4 + 0.35 Ri5           ( Eq.1)

Ri1-5 - standard value for jth parameter for route i
i - S elected rotes from 1 to n

The index value for various stretches is obtained by above formula. The values are stored in “TABLES” and the positive and negative impact of decision factors is taken in to account. Then the critical links is identified based on the index value in such a way that lower the index value the link is more critical.

Rank No Carriage
way width
of SMV
Final Index
1 66.00 2.83 2.83 1.23 22.15 22.01 70.57
2 56.59 3.57 3.40 1.62 19.96 6.72 75.19
3 84.15 2.83 2.83 1.14 22.72 21.93 89.46
4 66.00 2.83 0.00 0.53 34.38 12.41 90.26
5 79.75 2.83 2.83 1.43 20.95 10.85 94.09
6 82.50 3.40 3.40 0.81 25.43 6.28 107.65
7 94.05 3.91 3.91 0.87 24.84 4.77 121.07
8 90.75 6.23 4.53 0.53 34.05 12.48 122.62
9 104.5 2.83 4.72 1.93 16.84 3.25 123.74
10 110.00 5.48 5.48 1.27 20.40 9.43 130.68
11 102.30 4.53 5.67 0.88 23.00 3.95 130.73
12 123.75 5.67 3.40 0.63 25.90 3.59 154.50
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