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Scaling Laws in Chennai Bus Network

Atanu Chatterjee,Gitakrishnan Ramadurai

Published 2015 in arXiv: Physics and Society

ABSTRACT

In this paper, we study the structural properties of the complex bus network of Chennai. We formulate this extensive network structure by identifying each bus stop as a node, and a bus which stops at any two adjacent bus stops as an edge connecting the nodes. Rigorous statistical analysis of this data shows that the Chennai bus network displays small-world properties and a scale-free degree distribution with the power-law exponent, = 3:8. I. INTRODUCTION A. Chennai Bus Network Chennai is one of the metropolitan cities in India with a structured and a close-knit bus transport network. The Chennai bus network (CBN) is operated by the Metropolitan Transport Corporation (MTC), a state government undertaking. Spanning an area of 3,929 sq. km and with over 800 routes sprawling across entire Chennai, this extensive network also boasts of the largest bus terminus in Asia. With the population of the city being the sixth largest in the country, this medium of transport is most widely used for day-to-day commutation. The reason that the bus network, in general, achieves this favourable status lies primarily in two factors: (i) cost, and (ii) penetration. With high volume of commuters flowing through this network each day, the cost of travel per day, per person becomes significantly low. Although, this is a parameter which is usually met by every other public transport system, the penetration factor is the one which significantly makes bus networks the prime mode of transportation in cities. A high penetration effect exhibited by a bus network enables a person to travel between any two points in the city very easily which is in contrast to other public modes of transportation, where geographical constraints associated with the network layout are much higher in number. Thus, bus transportation allows flexibility in travel. A natural question arises here; what is the least number of buses one should change to go from one place to another? Or more precisely, why do we require changing buses at all? To answer these questions, we need to look at a more abstract and networked structure of the bus routes, and argue based on its various statistical properties. B. Complex Networks: overview

PUBLICATION RECORD

  • Publication year

    2015

  • Venue

    arXiv: Physics and Society

  • Publication date

    2015-07-08

  • Fields of study

    Geography, Physics, Computer Science, Engineering

  • Identifiers
    arXiv 1508.03504
  • External record

    Open on Semantic Scholar

  • Source metadata

    Semantic Scholar

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