Solving Traffic Problem in Bengaluru

Abhi Chatterjee
20 min readApr 26, 2021

Frustrated with Bangalore traffic? My research reveals some interesting findings…

Bangalore… one of the fastest growing cities, also known as India’s Silicon Valley, and a house of more than two million IT workers.

Bengaluru, as it has been officially called since November 2014, is the hub of the US$ 45 billion information technology sector that contributes nearly 38% to India’s GDP.

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In fact, Bangalore has become such a powerful city that foreigners dread the term Bangalored- which means losing your job in the west. People from all over India flock here to get a job, earn a good living and enjoy a decent lifestyle. The expansion has been so great that it has grown twice its size in the past 40 years.

However, this rapid expansion has come at a hefty price. There has been a 6000% increase in the number of vehicles on streets since 1990. And this humongous rise in vehicles have given rise to monstrous traffic. This problem has now become so great that people have started getting anxiety attacks from just the thought of driving to work.

In last 15 years, the rate of movement of traffic has come down from 40 km/hour to 9 km/hour.

But.. wait a second, do you think population is the reason for this distressing condition of traffic? Or is it something else? Our research reveals some interesting findings.

Is population the reason?

I started with asking myself a question, if population is the reason for traffic, then cities with the highest population densities should suffer from similar problems.

The below picture shows live traffic in four most populated cities in the world on a Saturday evening.

Live traffic in four cities with highest population densities

Following are the stats for people living per sq. km for the four cities:

1. New York : 10,200 people/km²

2. Washington : 9,800 people/km²

3. Chandigarh : 9,500 people/km² (approx.)

4. Bangalore : 6,000 people/km² (approx.)

However, when I observed the traffic condition in the other three, they showed almost no signs of traffic congestion. And on the contrary, Bangalore, which has lesser population density than the other three, was traffic blocked.

Is city plan the reason?

Once the population was eliminated from the list, I jumped to the next probable cause.

I studied the plans of the above four cities and it revealed some intriguing findings.

I observed that all the well planned cities in the world followed a Grid pattern where the roads run parallel and across each other. While Bengaluru followed a Star pattern. (except in layout areas)

New York has Grid pattern. Whereas, Bangalore has Star pattern.
New York has Grid pattern. Whereas, Bangalore has Star pattern.

Grid pattern has an inherent benefit, that to go from point A to point B, you have multiple paths and the traffic gets distributed.

Grid distributes traffic in multiple paths
Grid distributes traffic in multiple paths

Whereas, in the Star pattern there is almost always just one (or two) main ways to go from point A to point B which congregates the traffic coming from sub-streets onto one main road.

Star congests traffic in single path

Star pattern is the result of rapid-unplanned growth. And the worst part is the main roads are not wide enough to accommodate the traffic coming from various sub-streets. This causes huge traffic jams on main roads while internal streets remain completely desolate — ineffective distribution of traffic.

Any other reasons?

Other than these, I also found some other reasons which contribute significantly in making Bangalore traffic worst.

  1. Common Office/School timings: School and offices use busses for their employees and students respectively. These busses come on the streets at similar timings and cram the traffic.
  2. Cars: Most IT professionals use cars to travel to work. This takes up a lot of space per person on already narrow streets.
  3. Ineffective public transport: The reason people use cars is because, the public transport is inefficient.
  4. Vicinity of IT parks: Major IT parks in Bangalore are located on single belt, which makes the matters worse on the Bangalore roads.
  5. Us: Yes. Even we are responsible. I agree, there is inefficient traffic management; but if we would follow road discipline ourselves, the situation could become a lot better.

With 7.5 million vehicles on roads every day, how do we handle the situation?

Simple Solution

The only way to handle the current traffic problem is a well-connected metro/public transport system. I do agree with the point, and in fact, a well-connected metro network would alleviate the traffic problem and is a necessity, however at the same time, I also believe thinking of it as the only solution would limit us to this belief and would prevent us from looking into other ways of handling the problem.

Different Vehicles, Different Affordances

Footpath often serves as a two-wheeler lane nowadays
Footpath often serves as a two-wheeler lane nowadays

Have you ever come across this scene? If you live in Bangalore and ride a two-wheeler, I’m pretty sure atleast once you would have participated in the activity as well!

Two-wheelers continue to dominate the Bengaluru roads, accounting for 70% of its total vehicular population, followed by cars (19%).

Heavy vehicles like buses, trucks, and cars prevent smaller vehicles like two-wheelers from moving past. Two-wheelers can afford to pass through smaller spaces in traffic congestion. But having just one common lane for all the vehicles; riders often cut through dangerously between the trucks and cars to move speedily. I have often come across situations where, as soon as the riders find a little gap between the heavy vehicles, they keep moving past the heavy vehicles, stopping them from moving ahead. This impedes the traffic behind them and creates a blockage. And when there is not enough space to cut through, riders often drive on the footpaths making it unsafe for both, the rider and the pedestrians.

In Bangalore, we have different types of vehicles and both have their own affordances. The vehicles which are smaller can move faster and should not be made to wait due to the vehicles which afford more space and move slowly. In this case, creating something as simple as a psychological separation for two-wheelers (wherever possible) can significantly improve the situation.

Example of psychological constraint

Two-wheelers, autos move faster compared to four-wheelers, buses and trucks; so, it would help if we have separate lanes, so they can move quickly without blocking the traffic and riding dangerously.

Now the question is, will this thing actually work and will people actually follow it? Many of the things that work in other countries fail when implemented in India, or people use it in a completely different way. So, the only way of knowing is to try it out!

Exasperating Traffic, Intelligent Traffic Lights.

Traffic jam due to ineffective traffic lights

In a study conducted by Stockholm Transportation Dept, it was found that traffic congestion shows an exponential nature.

That means, traffic congestion at one junction, propagates exponentially. Fortunately, it works the other way as well. If you clear a certain part of congestion, the traffic clears up faster than you would expect.

Initially, traffic lights were introduced to ease congestion and bring order on what otherwise would be a dangerous intersection of roads. But believe it not, traffic lights nowadays are causing much of the traffic jams.

In fact a new research by DailyMail suggests that much of the traffic jams are caused by traffic lights.

When all of the traffic lights went out on one of the most heavily trafficked roads in Britain the traffic moved smoother with lesser congestion.

Ineffective traffic signals cause more nuisance than service.

One way to look at it is this- Quantum theory of Traffic

Traffic moves in quants or chunks. And every chunk has its own momentum. The more often this momentum is altered, the slower it moves and the slowness is caused by the change, not the number. Which means, if you are traveling on a straight road with five to six traffic signals on the way, the signals should be designed in such a way that when one chunk of traffic leaves one signal, the signal ahead of it becomes green when the chunk reaches there.

We need traffic signals that collect data from all directions and adjust the signal timing accordingly so, chunks of traffic flow smoothly on the roads without much alteration in the momentum. It is referred to as Intelligent Traffic System (ITS).

This system has been implemented in Japan and has given positive results.

( Good news: India is soon going to import ITS technology from Japan and implement it in 29 junctions in Bangalore to test out the system. )

Varying Traffic, Adaptable Lanes.

This concept is purely a result of personal observation. Usually, I have observed, most of the traffic flows in one direction. As a result, one of the lanes is heavily populated and the other very little.

On the roads where there is no physical separation between the lanes, the lane in which traffic is greater pushes the vehicles and takes up space in the other lane. However, when the width of the lanes is fixed, results in heavy traffic on one side and very little on the other.

This behavior could be the result of several factors like common office timings, vicinity of tech parks etc.

How about having adaptable lanes that alter their width and give more space to the lane which has more traffic density according to the time of the day.

Lanes adapt according to traffic density at different times in the day

This will help to better utilize the existing real estate, as traffic on both sides doesn’t require equal space all the times.

This idea is still in its conceptual level and I haven’t yet explored the implementation details. A similar concept referred to as Modular Lanes exists but the idea is still in its infancy.

Digital solution

One solution to traffic congestion is smart mobility. Smart mobility is the concept of connecting the elements of a city’s transportation system to the cloud. Data from each element — vehicles, traffic signals, people, roads, and maps-is collected, combined, and analyzed to optimize the flow of vehicles in the city.

If we drill down on how cities are using smart mobility to reduce traffic congestion today, we see best practices emerge. Let’s look at six key items that cities should embrace to enable smart mobility solutions.

To learn how Microsoft can help you get started with smart mobility, explore these resources.

Connected infrastructure

One criterion required to enable smart mobility to reduce traffic congestion is connected infrastructure. The different parts of a city’s transportation system need to be connected to the cloud: traffic lights, cars, buses, trains, bikes, people, maps, and even roads. This Internet of Things (IoT) approach allows location, speed, capacity, and other data to be collected, stored, and analyzed. Wilson Parking recently invested in connected infrastructure to decrease congestion for drivers using the new Hong Kong-Zhuhai-Macau Bridge. The city of Taipai has launched an initiative to connect 150,000 streetlights.

Access to data

Another criterion is access to data. Cities continuously collect and produce large quantities of data for planning, production, and decision-making. Sharing this data with the private sector can help accelerate smart mobility solutions. The City of Denver creates a holistic data environment that brings together data from multiple siloed sources to meet its smart mobility goals. Helsinki, Finland, opened access to city GIS transportation data.

Alternative transportation

A third criterion is offering compelling options to the “one car, one driver” model. For smart mobility, alternative options would need to be connected to the cloud:

  • Bicycle commuting: ideal for commutes of a few miles
  • Carsharing: rent cars by the minute or by the hour
  • Ridesharing (carpooling): make use of the empty seats already in the system
  • On-demand ride services: use personal vehicles to offer transportation services
  • Buses and trains: reimagining existing transportation by integrating them into end-to-end trip plans, including how to travel the last mile home

Autonomous vehicles

A fourth criterion required to enable smart mobility to reduce traffic congestion is the evolution of autonomous vehicles. While still in development, autonomous vehicles are cars or trucks in which human drivers are not required. These vehicles use sensors and software to control, navigate, and drive the vehicle. The use of autonomous vehicles to reduce traffic congestion depends on public policy. For example, self-driving cars could connect transit hubs, provide public transit services to communities not currently served, and be used to improve public transportation.

Traffic management

Traffic management is ultimately at the heart of reducing congestion. The new Hong Kong-Zhuhai-Macau bridge is a modern-day marvel that has forever changed traffic patterns across one of Asia’s fast-growing areas. Recent estimates say daily volume on the world’s longest sea bridge will reach 29,100 vehicles by 2030 and 42,000 vehicles by 2037. Wilson Parking enables drivers to pre-book spaces on the bridge, resulting in smoother traffic flows. The City of Denver uses its capabilities to take a proactive approach to transportation optimizations, for example, by enabling real-time adjustments to traffic flows in the case of accidents or other disruptions.

Mobility as a Service (MaaS) Applications

Mobility as a Service (MaaS) applications complete the smart mobility picture. The vision of MaaS is to make it easier and less expensive for car drivers and passengers to travel via alternative forms of transportation. MaaS applications enable travelers to plan trips based on their priorities and preferences. Microsoft is working with companies like Moovit and TomTom to offer critical real-time data to MaaS application providers, enabling them to deliver compelling applications.

By connecting traffic lights, vehicles, people, and roads to the cloud, sharing data, embracing alternative modes of transportation, and building traffic management systems, cities like Hong Kong, Taipei, and Denver are experiencing success and leading the way for other cities. As travelers adopt MaaS applications, they will increasingly choose mass transit options over driving on their own. The advent of autonomous vehicles will eventually help reduce traffic congestion even further.

What is Intelligent Transport System and how it works?

With the conception of smart city transmuting cities into digital societies, making the life of its citizens easy in every facet, Intelligent Transport System becomes the indispensable component among all. In any city mobility is a key concern; be it going to school, college and office or for any other purpose citizens use transport system to travel within the city. Leveraging citizens with an Intelligent Transport System can save their time and make the city even smarter. Intelligent Transport System (ITS) aims to achieve traffic efficiency by minimizing traffic problems. It enriches users with prior information about traffic, local convenience real-time running information, seat availability etc. which reduces travel time of commuters as well as enhances their safety and comfort.

Intelligent Transport System (ITS) aims to achieve traffic efficiency by minimizing traffic problems. It aims to reduce time of commuters as well as enhances their safety and comfort.

The application of ITS is widely accepted and used in many countries today. The use is not just limited to traffic congestion control and information, but also for road safety and efficient infrastructure usage. Because of its endless possibilities, ITS has now become a multidisciplinary conjunctive field of work and thus many organizations around the world have developed solutions for providing ITS applications to meet the need.

One such example is the city of Glasgow. In the city, Intelligent Transport System gives regular information to the daily commuters about public buses, timings, seat availability, the current location of the bus, time taken to reach a particular destination, next location of the bus and the density of passengers inside the bus.

Iain Langlands, GIS and Data Manager, Glasgow City Council explains, bus operators in the city have the sensors in their buses. So, if the bus is going to be early to the next bus stop the bus is temporarily and very slightly is slowed down at the red light little longer than it should be to make sure the bus is on time and do not ahead of the schedule”. The system has been designed so smartly that passengers and even drivers are unaware of the delay as they are very little delays.

Application areas of Intelligent Transport System

The entire application of ITS is based on data collection, analysis and using the results of the analysis in the operations, control and research concepts for traffic management where location plays an important role.

Here sensors, information processors, communication systems, roadside messages, GPS updates and automated traffic prioritization signals play an imperative role in the application of:

1- Advanced Traffic Management System

2- Advanced Traveler Information System

3- Advanced Vehicle Control system

4- Advanced Public Transportation System

5- Advanced Rural Transportation Systems

6- Advanced Commercial Vehicles Operations system

How Intelligent Transport System works?

Traffic Management Centre (TMC) is the vital unit of ITS. It is mainly a technical system administered by the transportation authority. Here all data is collected and analyzed for further operations and control management of the traffic in real time or information about local transportation vehicle.

Well-organized and proficient operations of Traffic Management Centre depends on automatized data collection with precise location information than analysis of that data to generate accurate information and then transmitting it back to travelers. Let’s understand the entire process in a more detailed way.

Data collection: Strategic planning needs precise, extensive and prompt data collection with real-time observation. So the data here is collected via varied hardware devices that lay the base of further ITS functions. These devices are Automatic Vehicle Identifiers, GPS based automatic vehicle locators, sensors, camera etc. The hardware mainly records the data like traffic count, surveillance, travel speed and travel time, location, vehicle weight, delays etc. These hardware devices are connected to the servers generally located at data collection centre which stores large amounts of data for further analysis.

Data Transmission: Rapid and real-time information communication is the Key to proficiency in ITS implementation so this aspect of ITS consists of the transmission of collected data from the field to TMC and then sending back that analyzed information from TMC to travelers. Traffic-related announcements are communicated to the travelers through internet, SMS or onboard units of Vehicle. Other methods of communications are dedicated short-range communications (DSRC) using radio and Continuous Air Interface Long and Medium Range (CAILM) using cellular connectivity and infra-red links.

Data Analysis: The data that has been collected and received at TMC is processed further in various steps. These steps are error rectification, data cleaning, data synthesis, and adaptive logical analysis. Inconsistencies in data are identified with specialized software and rectified. After that data is further altered and pooled for analysis. This mended collective data is analyzed further to predict traffic scenario which is available to deliver appropriate information to users.

Traveler Information: Travel Advisory Systems (TAS) is used to inform transportation updates to the traveling user. The system delivers real-time information like travel time, travel speed, delay, accidents on roads, change in route, diversions, work zone conditions etc. This information is delivered by a wide range of electronic devices like variable message signs, highway advisory radio, internet, SMS, automated cell.

With urbanization expanding with speedy stride, number of vehicles on road is also increasing. Combination of both in return puts enormous pressure on cities to maintain a better traffic system so that the city keeps on moving without any hassle. For the purpose application of Intelligent Transport System is the only solution. ITS is a win-win situation for both citizens and city administrators where it provides safety and comfort to citizens and easy maintenance and surveillance to city administrators.


Intelligent Transport System is being applying to bundle of area such as

  • BIS — Bus Information System
  • AFC — Automatic Fare Collection
  • FTMS — Freeway Traffic Management System
  • ETCS — Electronic Toll Collection System
  • ATES — Automatic Traffic Enforcement System
  • PIS — Parking Information System
  • NTIC — National Traffic Information Center
  • C-ITS -Cooperative ITS

Here I only cover Bus Information System as short period of time

BIS — Bus Information System

My main goal is to improve the experience of bus users; we will offer a technological solution to increase the users’ satisfaction towards accessibility during the bus trip as well as when waiting for the bus to arrive.

Although the accessibility conditions for people with reduced mobility have been improved by the public transport service by upgrading the buses’ platforms and by offering assigned seats, the number of users has decreased every year.

The problem

The bus system in Bangalore is relatively hard to navigate, especially for commuters whose destination is outside of the heavily served downtown area. The buses are also often delayed and full, due to weather and traffic.
The applications and website currently available for commuters to plan their trips seem to be lacking important services.


My research process begins with an exploration focused on the user. Every question I could think of, related to these three topics, I wrote on post-its and stuck them to the wall. This is how I started to lead our investigation. Some of the questions:

  • How is the user experience with the app?
  • Which problems does a disabled person face when travelling?
  • Does the company offer good technological services?
  • Does the competition have specific services for disable people?

Desktop research

By doing a desktop research based on the competition, I collected data of alternatives transportation to the bus, such as VTC, taxis and other kinds of public transport. I also gathered information of mobility apps and disabled people oriented apps.

I concluded that almost every public transport service in the country offers the same solutions for people with reduced mobility, such as assigned seats, reserved platforms and ramps for wheelchairs.

On the other hand, I found many apps committed to disabled people, and none of their functions are contemplated in the EMT Madrid’s app.

VTC, taxis and every car sharing service present direct competition to the EMT due to their capacity of covering the users’ routes extensively.

Qualitative research

Following my investigation, I collected opinions and comments from users in numerous blogs and EMT’s social networks. I found several claims for malfunction of the ramps, and other comments such as ‘buses rarely have their sound system on’.

Safari in the bus.

In order to extend my qualitative investigation, I made a safari to the EMT buses. On a rainy day I studied the user’s experience using public transport. I witnessed some problematic situations, for example, a senior citizen couldn’t get to the central platform because the bus was highly crowded. Other elderly people weren’t able to reach the reduced mobility assigned seats, and had to travel standing since there was no other option. Furthermore, the information screen set in the front of the bus couldn’t be seen from the back, and in other cases it’s not even turned on.


To better understand the general experience of EMT users, I created a questionnaire through Google Forms. The following graphics represent the experience and interaction of the users with the public buses. First, I can see that a big percentage use this transport occasionally. Secondly, that most of the people get their information through the EMT app. And finally, that people use this form of transportation to get to their working places, schools/universities and for leisure.

User Personas

Based on all the information collected in the qualitative and questionnaire research, I generated two User Personas.

User Journey

Following the research and with the personas it was helpful to map the journey of a commuter. The journey does not follow a single identified persona, but I kept it at a higher level to help in identifying the common pain points and challenges for all users.

I used the identified pain points in the journey to start the ideation process for services that would address these challenges.


Following the research and the journey mapping, as well as researching similar case studies for other cities and other transport app , I put together a list of potential features and services that could improve the overall experience.

The following are some of the most important services identified to improve the transit experience:

  • Search by destination: From the research and experience this is the most obvious need. Users should not know the bus stop names or bus numbers but be able to search for routes by destinations. This can be through an integration with other map services.
  • Recording frequent destinations rather than frequent buses. Allowing the user to save destinations they frequently go to, to find optimal routes to them, depending on time and conditions at that time.
  • Notifications: User can chose to receive notifications, to be notified when they need to start to go to the station, or when they need to be alerted to leave the bus.
  • Stop Alert: The buses right now require passengers to alert the driver when they need to leave the bus. To avoid commuters being stranded in stations where the bus doesn’t stop, there could be a way to alert the bus driver to stop in stations for people to get on the bus as well. This would also optimize stopping times and potentially reduce delays.
  • Crowdedness level: This can also alert commuters when there is a chance that a bus will not stop. Commuters if not in a hurry could also chose to take later buses to find seats. This feature would be also be extremely useful for commuters in wheelchairs, or with strollers who require the extra space.
  • No show or late bus report: this is feature that can help commuters feel more in control, when there are delays or issues with the bus schedule. They can that way contribute to troubleshooting and potentially optimizing the bus routes and schedules.
  • Stations GPS trackers: Using mobile devices in cold or stormy weather is always a problem. Since the GPS tracking information is already available, small displays in the bus station to show when the bus is expected to arrive could help commuters in planning their trips in any condition. This is especially important for commuters with limited or no data options, as well as seniors.

These (and some more) features were prioritized according to their impact on the experience as well as how much they would be expected in the service.

This prioritization would help in identifying the minimal viable product and guide the design of the user experience for a digital service.
For a good experience obviously the expected features should all be available and therefore higher prioritized than unexpected features. High impact features should also be prioritized higher than low impact ones to make sure the most important needs of users are addressed satisfactorily.

User Flows

I chose to focus on two key user flows that I think represent the most frequent and pressing needs for a friendly and efficient transit experience:

This use case includes using the planner. The user open the app and enters their destination to view alternative routes. Frequent destinations should be easily accessible on their home screen, however would start a real-time search for optimal routes with the current conditions.
The user can compare the alternative route and view the details of it.
At every step the user also has the option to turn on notifications. The notifications are either to let them know when they need to start to go to the bus station.
Additionally they can chose to turn on get off notifications, if they have started their trip.

Nearby Stops

The second user flow is when the user is more familiar with the bus system and uses the service to find out which buses are available near by.

The home screen already shows a list of near by bus stops, or the user can chose to select a stop from the map. When the user views a specific stop the buses are listed according to their arrival time. The user can find more information about the specific location and the stops of each bus.

Key Components

The key proposed improvements and features, are for the most part in the information that the user can view about their route or their bus. Therefore I focused on the defining the key components and the information in them. The bus and route cards can be reused in different contexts within a service.

Bus Card

Route Card

Screen designs

The case study did not include the full design of the app, but focused primarily on research and ideation. The above screens aim to show the proposed visual style.



Abhi Chatterjee

UX Designer at Dubai Municipality specialised in User research & Interaction Design