Abstract

We develop a methodology to estimate robust city level vehicular mobility indices, and apply it to 154 Indian cities using 22 million counterfactual trips measured by a web mapping service. There is wide variation in mobility across cities. An exact decomposition shows this variation is driven more by differences in uncongested mobility than congestion. Under plausible assumptions, a one standard deviation improvement in uncongested speed creates much more mobility than optimal congestion pricing. Denser and more populated cities are slower, only in part because of congestion. Urban economic development is correlated with better (uncongested and overall) mobility despite worse congestion.

Highlights

  • Using a popular web mapping and transportation service, we generate information for more than 22 million counterfactual trip instances in 154 large Indian cities.1 We use this information to estimate a number of indices of mobility of motorized vehicle travel in these cities

  • When ranking cities by uncongested mobility, we find that the five slowest cities in the absence of traffic are all in Bihar and 17 of the 20 slowest cities are in the poor northeastern part of India

  • We propose a novel approach to measuring vehicular mobility within cities, and decomposing it into uncongested mobility and a congestion factor

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Summary

Introduction

Using a popular web mapping and transportation service, we generate information for more than 22 million counterfactual trip instances in 154 large Indian cities. We use this information to estimate a number of indices of mobility (speed) of motorized vehicle travel in these cities. Using a popular web mapping and transportation service, we generate information for more than 22 million counterfactual trip instances in 154 large Indian cities.. Using a popular web mapping and transportation service, we generate information for more than 22 million counterfactual trip instances in 154 large Indian cities.1 We use this information to estimate a number of indices of mobility (speed) of motorized vehicle travel in these cities. We examine how indicators of urban economic development and other city characteristics correlate with mobility, uncongested mobility, and congestion delays. Indicators of urban economic development such as faster recent population growth, higher income levels, and higher motorization rates are generally associated with better overall mobility despite worse congestion. We rely on a wide variety of sources including the census of India, OpenStreetMap, and satellite imagery

City sample
Trips data
City-level data
A general conceptual framework
Measuring mobility
Disentangling two sources of mobility
Descriptive statistics
Trip regressions
20 Largest cities
Density
Comparing mobility indices
Decomposition
Correlation of mobility with city characteristics and urban development
Transit and walking
Conclusions
Findings
Primary Roads

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