Ride-Hailing & Traffic Congestion

Research suggests that India’s cities may have too many ride-hailing cabs for their own good. Rather than easing congestion, as one might expect, empty cars cruising in search of passengers—a phenomenon known as “deadheading”—could be making traffic worse.

Dynamic pricing, real-time tracking, and technology that anticipates customer needs are the hallmarks of ride-hailing apps like Uber, Ola, and Rapido. These services have become second nature to commuters, even beyond India’s tier-1 cities. Yet, as revealed in our study, ‘The Impact of Ride-Hailing Services on Congestion: Evidence from Indian Cities,’ their presence may not be as benign as the platforms claim.

These companies promote themselves as more than just convenient; they claim to be sustainable modes of urban transportation. Yet, governments have often been cautious, with some considering regulation due to their role in traffic congestion.

But regulation should not be driven by assumptions alone. That is where our research comes in—to pinpoint the effect of app-based cab services within an already complex transport network.

A natural experiment on the streets

A straightforward way to assess the impact would be to measure travel time between two destinations and observe what happens when there are no such cabs on the roads. But how does one remove them from the roads to measure the difference?

In this study, my co-researchers Deepa Mani, Rahul Telang, and I used Google Maps to track changes in travel times across Mumbai. We monitored travel times every half-hour between various sets of origins and destinations over a period of 8 to 10 months.

A rare opportunity presented itself to us in October 2018, when Ola and Uber drivers went on strike in Mumbai. For a brief window, this created an opportunity to observe traffic patterns without these cabs, whilst other factors like private vehicles, pedestrians, and public transport remained largely unchanged.

To strengthen our analysis, we compared Mumbai’s traffic data with that of Pune, a city where no such strike occurred. This difference-in-differences approach helped isolate the effect of ride-hailing services. When the strike took place, Mumbai’s traffic congestion dropped significantly, whereas Pune saw no comparable change.

Not one city, not one pattern

The reduction in congestion was not uniform. We saw variations depending on which part of the city we examined.

The reduction was much greater in the central areas of the city that typically experience major congestion. The effects were much less pronounced in the outer areas of the city. That could be explained by the fact that Uber and Ola cabs tend to concentrate in the bustle of the city, where they have higher chances of finding rides.

There was also a difference according to the time of day. The drop in congestion was higher during mornings and peak evening hours because that is when most cabs would be on the streets.

The results were two-pronged in terms of numbers:

1. When we averaged the effect of Ola-Uber removal across the entire city and across all times, we found the congestion reduction to be around 3.5%.
2. When we narrowed down to the most congested parts of the city and peak hours, the reduction was between 10 and14%.

The analysis was replicated for other cities like Delhi and Bengaluru, using similar methods, as those cities too experienced Ola-Uber driver strikes at different times. Similar effects on congestion were observed in these cities. This meant the results could be generalised and become more actionable.

When cabs are headed nowhere

But here is another key question: What explains this reduction of congestion when such cabs are off the roads? Isn’t the more rudimentary thought that these cabs reduce use of private vehicles, hence reducing congestion and pollution?

One reason we found was that many such cabs would be empty whilst looking for passengers. That is something India-specific. Deadheading, or ‘headed nowhere’, is a classic term in transportation for cars driving around empty.

This is the most wasteful form of congestion because no one benefits from it.

Another reason there was reduced congestion during the strike days was the opening of shorter routes or “shortcuts”. Let us say you needed to go from point A to point B. If the route was through a congested centre of the city, then you would rather take a longer route that would have less traffic. That would increase the distance and even the travel time, but you would not be stuck in traffic as such. But when Uber and Ola were off the streets, the shorter routes opened without the congestion.

How it saves money

Yet another noteworthy observation of the study was that a sizeable number of people using ride-hailing services would otherwise have resorted to using the usual public transport, such as buses or the metro. We saw that when Uber and Ola went off the roads, the ridership for metro services increased in Delhi. We used data from the Delhi Metro for this.

That provided evidence that although Uber and Ola claimed and promised that they would put more people in fewer rides, in fact they may have been attracting people who would have otherwise used shared public transport. In that sense, it was leading to an increase in vehicle miles.

This travel-time reduction had to also be quantified, for which we used public surveys to get a sense of how many trips people would make in a day. That would be their average distance travelled. We found that the congestion relief benefit, due to absence of ride-hailing services, translated to around 1.5 to 2 million dollars per day.

Benchmarking: Strike vs odd-even

We also did some benchmarking against other events that may have removed many vehicles from the roads. One such event was the odd-even experiment introduced by the Delhi government in 2016.

Mainly to counter vehicular pollution, the Delhi government had mandated that vehicles with odd or even registration numbers would alternatively be allowed on the roads. This also had reduced congestion significantly as people resorted to carpooling or public transport.

We compared its effect with the effect of the Ola-Uber strike, and found that during the strikes, the reduction in congestion was 60-80% of the reduction seen during the odd-even experiment period. This was a substantial figure, further underlining that app-based cabs are a major factor in congestion.

Cues for policymakers

The findings of our research have significant implications for policymakers as they can now weigh the pros and cons of the cabs. Overall, we found that whatever benefits these cabs offer, there is no denying that they come at a certain cost towards traffic congestion and other related factors.

The question is not whether these services should exist, but how many such vehicles a city can sustain efficiently. Our findings suggest that there are more ride-hailing vehicles operating in these cities than is socially efficient, the caveat being that policymakers must weigh the costs and benefits before making a blanket call.

The deadheading-related findings, which show that cabs may just be going around unoccupied, awaiting rides while being on the move, suggest that it may be possible to reduce congestion without drastic measures.

Author: ISB Editorial Team