Driver Behavior and Profiling — The Driver Centric Approach

Published in
6 min readOct 7, 2018


Sharing economy, reduction in the personal vehicle ownership, electric vehicles are the revolutionary terms of Indian transportation industry. The time has started where the whole is world is sighting changes in how we commute. World is moving towards shared, safer and smarter ways of transportation. Whenever it comes to commute, the safety of the commuters comes first and whoever is providing the shared services, the safety is gonna be the key differentiator for them in the market penetration.

Driving safety is one of the most critical but under look aspect in India as Indian roads are considered to be one of the most dangerous roads around the world and lots of lives are being taken by mistakes made by drivers. Out of all, 78% of accidents are happened due to driver’s mistakes like distraction, rash driving in darks and in higher speeds.

Indians have unique traffic sense and driving skills. Unique traffic sense because we Indian take traffic rules very casually and despite huge traffic rules violations, lots of Indians always come home back after the battle on the road. Foreign countries have already started learning to deal with robot vehicles, driving on the public roads on their own, but here in India, it’s difficult to drive with among human drivers and this has to be fixed to pave the way for the emerging technology to penetrate to Indian roads. The sole motto of Autonomous Vehicles are to make driving safer as humans can violate the traffic rules but robots learn not to violate and once they learn rules, they tend to follow it. So how do we fix it and make Indian roads ready for Robot vehicles and till that time India needs to learn the important and critical aspect of driving safe and make roads safer for people to commute.

In the current condition, the companies, the people who has got the technology and ability solve a problem has to come forward and fix it. We at @drivebuddyAI has found a way to contribute our skills and knowledge of technology to fix the bugs of driving safety and making people aware about their driving and educate them who’re most responsible for keeping the roads safer.

drivebuddyAI, aimed to make Indian roads smarter and safer, has devised a solution, and the solution is developed with artificial intelligence. When we talk about shared mobility, public vehicles, self-driven vehicles, chauffeur driven vehicles, the providers of these services needs to keep their assets i.e. drivers and vehicles safe and that is one of the challenge. And this comes to fleet owners to take care of their vehicles, the existing market is already aware of GPS tracking based solutions which allows the fleet owners to track the location of the vehicle and these services do help the owners to understand how a person is driving based on the speed data comes from the vehicle. But these data are calculated on very superficial level and lack accuracy and context. Identifying how a person is driving and evaluating the person for his driving skills required lots of data points and context to all the points captured. Driving behavior and evaluation itself is a industry and huge numbers of companies have derived their own equations for that. There’s no standard available around and every evaluator has their own set of equations based on the data points they have.

How this matters to the Autonomous Vehicles and future of transportation???

This one has to be answered and I believe there’s a direct relation of driving behavior of human driver with robot driver. To make robot drive itself on Indian roads or tough conditions, it has to pass through the rigorous training of all different and unique traffic scenarios which might come across while driving on Indian roads. How do a robot driver learns it?? The answer is, it has to be learned from the human drivers, their mistakes & their skills. If a robot driver understands the typical behavior of a human driver, it can ultimately drive along with human driver on the same road. And this is the future.

drivebuddyAI — Contextual driving behavior

drivebuddyAI, an AI enabled hardware & cloud based platform. The product developed in India and for Indian roads to understand how Indian drivers are driving to make it possible to have robot drivers drive on Indian roads.

How do we do that?

We work with lot of fleet owners as we see a huge growth in sharing mobility and fleets are now becoming more organized and they promise safety to the users. Employee transportation, vehicle rental services, logistics and commercial vehicles need to have a driving safety in place and to provide a better customer experience, the driver with whom the users are driving needs to be evaluated to provide better services. drivebuddyAI, works with these fleet owners to help them understand how their drivers are driving in all different conditions. drivebuddyAI, hardware platform, a camera fitted device, continuously monitors the on road conditions while driving with the precision location sensors to locate the vehicle. The device looks for forward collision events and alerts the driver if it drives close to the front vehicle with keeping shorter distance. It also checks for the lane keeping and over speeding like scenarios to make sure to avoid critical crash like situations and even if driver reacts lately the impact of the crash could be reduced with prior collision alerts. The device comes with optional driver facing camera, monitors driver distraction and drowsiness. The device having IoT capabilities, transfer all the data to the cloud based analytics platform. The cloud platform analyzes the driving data captured along with the video. The cloud platform finds out the anomalies in the whole driving duration in terms of

  • Over speeding
  • Acceleration
  • Sudden breaking
  • Overtaking
  • Collision Avoided
  • Distracted driving
  • Traffic sign violations
drivebuddyAI — Driver report dashboard, showing anomalies via Contextual Video Events

These are all contexts which are analyzed with the sensor based data, their pattern along with the CNN based deep learning model to identify anomalies in on road events, and provides a visual context to the the event captured. This provides a clear visible picture for fleet owner about the driver and reduces the chances to have a guess work or investigation for finding out the reasons for such anomalies.

The visual context enhances the transparency between the driver and a fleet owner which results in improved efficiency of the fleet to have more safer and smarter trips for fleet owner and ultimately leads to better business.

drivebuddyAI — Driving pattern dashboard showing trends of driving over the month period

This is how we demonstrate the driving behavior of the driver for fleet owner, which clearly indicates the trends. Trends gives the clear picture of the driving pattern of the driver over the time period.

The driver centric approach

Typical tracking systems are the systems which only involves the fleet owner and driver has no role in that. Drivers do have a mindset of spying behavior of a fleet owner and specifically in India, drivers do try to damage the systems which they feel, they are being tracked with. drivebuddyAI, as the name suggests, we try to associate with driver as well, first we make driver educate about the product, what are the alerts generated for, where it’ll be an assistance for them while driving. Once education of driver for in-vehicle device is done, we gather driver & fleet owner together to make both of them understand how video is being displayed and how do we find anomalies. The product education is essential part of the product as the system is developed for a driver to keep the driver and vehicle safer and for fleet owner to provide insights about the driver’s driving performance.

We have started working with fleet owners in India to make driving safety and utilization of available technology to serve the nation for reducing the number of accidents and as I mentioned earlier, to make vehicles of tomorrow to make wise decisions to use technology in a smarter way.

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Entrepreneur, Startup Founder & CEO @drivebuddyAI. Learning from human drivers for the future drivers.