[Paper Review] Congestion costs incurred on Indian Roads: A case study for New Delhi

Neema Davis, Harry Raymond Joseph+2 more|arXiv (Cornell University)|Aug 5, 2017

Transportation Planning and Optimization17 references18 citations

TL;DR

This study analyzes congestion in New Delhi using GPS data from taxis to quantify economic costs, estimating marginal and total congestion costs across productivity loss, pollution, accidents, and fuel wastage. It projects total congestion costs to reach $14.7 billion annually by 2030, with productivity loss from buses being the dominant factor, highlighting the need for dedicated bus lanes and intelligent traffic systems.

ABSTRACT

We conduct a preliminary investigation into the levels of congestion in New Delhi, motivated by concerns due to rapidly growing vehicular congestion in Indian cities. First, we provide statistical evidence for the rising congestion levels on the roads of New Delhi from taxi GPS traces. Then, we estimate the economic costs of congestion in New Delhi. In particular, we estimate the marginal and the total costs of congestion. In calculating the marginal costs, we consider the following factors: (i) productivity loss, (ii) air pollution costs, and (iii) costs due to accidents. In calculating the total costs, in addition to the above factors, we also estimate the costs due to the wastage of fuel. We also project the associated costs due to productivity loss and air pollution till 2030. The projected traffic congestion costs for New Delhi comes around 14658 million US$/yr for the year 2030. The key takeaway from our current study is that costs due to productivity loss, particularly from buses, dominates the overall economic costs. Additionally, the expected increase in fuel wastage makes a strong case for intelligent traffic management systems.

Motivation & Objective

• To provide statistical evidence of rising congestion levels in New Delhi using one year of GPS traces from taxis.
• To estimate marginal and total economic costs of congestion, including productivity loss, pollution, accidents, and fuel wastage.
• To project congestion costs through 2030 under current growth trends.
• To evaluate the impact of two-wheelers on congestion and its economic implications.
• To recommend policy interventions such as dedicated bus lanes, intelligent traffic systems, and carpooling incentives based on cost-benefit analysis.

Proposed method

• Used GPS traces from taxis to compute average daily speeds and detect trends in vehicular congestion over time.
• Applied the Kolmogorov–Smirnov test to statistically validate a decline in average speeds between 2013 and 2014.
• Calculated marginal congestion costs using three components: productivity loss, air pollution, and accident-related expenses.
• Estimated total congestion costs by adding fuel wastage to marginal costs.
• Projected future costs using vehicle growth projections and assumed constant parameters, with adjustments for rising fuel use and emissions.
• Recomputed cost parameters (A1j, A2, A3, A4) from prior studies to reflect current conditions, acknowledging temporal changes.

Experimental results

Research questions

• RQ1 Has vehicular congestion in New Delhi increased significantly between 2013 and 2014, based on GPS data from taxis?
• RQ2 What are the marginal and total economic costs of congestion in New Delhi, broken down by productivity loss, pollution, accidents, and fuel wastage?
• RQ3 How will congestion costs in New Delhi evolve by 2030, and which factors will dominate the cost structure?
• RQ4 What is the relative economic impact of buses versus cars in terms of congestion costs, and how does this affect policy recommendations?
• RQ5 To what extent do two-wheelers influence congestion cost estimates, and why is their inclusion critical in urban traffic modeling?

Key findings

• The average speed of taxis in New Delhi declined significantly from 2013 to 2014, with statistical evidence (Kolmogorov–Smirnov test) confirming a significant drop in speeds.
• Productivity loss from bus travel dominates the total congestion cost, accounting for the largest share of economic burden.
• Total congestion costs in New Delhi are projected to reach $14,658 million (or $14.7 billion) per year by 2030.
• The marginal cost of adding one vehicle kilometer (vkm) of bus travel is projected to approach that of car travel by 2030, indicating network saturation.
• Fuel wastage is expected to increase substantially, making intelligent traffic management systems a high-priority intervention.
• Accident-related costs contribute only marginally to total congestion costs from a macroeconomic perspective, despite high personal and social impacts.