A closer look at the motor vehicle accident statistics around the world shows that driver drowsiness and distraction are some of the major risk factors to road safety today. As road traffic injuries and death have been showing an incremental trend over the years, it is high time we address this issue.
The source of driver distraction, in most cases, is within the vehicle itself. Activities that distract the driver include texting or talking on the phone, reaching out to the back seat, playing music on the infotainment system, etc. while driving.
With the increase in the use of smartphones and hands-free devices connected to phones, driver cognitive load and distraction that affects driving behavior is also on the rise.
With advancements in automotive technology, new-age monitoring apps are available for driver drowsiness detection and identification of driver distraction activities.
This is an account of our proprietary driver drowsiness and distraction detection app, Drivesafe.
Project DriveSafe – Real-time Driver Drowsiness & Distraction Detection
The Innovation Lab at Embitel has been buzzing with activity as our engineers tried to develop a solution that keeps a check on cognitive distraction, i.e., activities that take a driver’s mind off the road.
Our work on this project was initiated at the beginning of 2020 when we designed a Python-based machine learning algorithm that analyzes driver movements, identifies each activity, and sends alerts based on the results.
The next step was to identify the most optimum end-user application that would relay these messages to the driver.
The pandemic lockdown ceased to deter our enthusiasm to see this solution through to the end, and we came up with a great idea!
We decided to develop DriveSafe, an intuitive Android-based app that would use the existing hardware of the user’s mobile app to assess their attentiveness while driving. The app that was designed captures images of the driver at pre-defined intervals to act as input to the machine learning algorithm within.
Key features of DriveSafe:
- Driver Distraction Detection
- The intensive training given to the algorithm ensures that it identifies the driver’s activity with a great degree of accuracy.
- Currently, we have identified 16 activities that the driver could be engaged in. This includes 15 driver distraction activities such as using a mobile phone for calls, texting, taking selfie on a phone, adjusting makeup, talking to passengers, reaching to the back seat, smoking, reaching for the audio system to play music, and more. The focused activity identified is the driver looking at the road while driving.
- The activity is analyzed through the hand movements of the driver as well. Hence, the camera should be positioned at a 45-degree angle to the direction in which the driver is facing.
- The driver can pre-configure the app settings so that his/her images are captured at periodic intervals throughout the journey. This interval for photo capture can be configured up to milliseconds.
- The user can also configure the resolution of the images captured. Additionally, he/she can configure whether all images captured need to be retained on the device after processing.
- After analysis of the images, if the algorithm finds that the driver is engaged in a distracting activity, it sends a visual notification on the phone in the form of a text image. It also sends an audio notification to alert the driver.
- The solution can be customised to integrate a cloud server to which the alert messages can be sent. Integration of this functionality could open up a wide range of business use cases for which this solution can be deployed.
- We designed the solution to be scalable so that it can be customised to incorporate various other modules or driver distraction activities based on our customer’s unique requirements.
- Driver Drowsiness Detection
- Currently, our driver behavior app performs image analysis using pictures captured from the mobile camera positioned at the side of the driver (45 degrees from the front of the driver’s face). For detecting driver drowsiness, it is necessary to install the camera at the front of the driver. When the camera is at the front, it is possible to analyze the eyes of the driver and detect drowsiness.
- Our app is scalable to include driver drowsiness detection feature as well. The same algorithm can be used for this purpose; only the model needs to be trained with different data to accomplish this feature.
Business Use Cases for Our Distracted Driver Detection App
Embitel’s driver drowsiness and distraction detection app can be the solution for a large spectrum of business use cases:
- Driver assistance – When there is a need to offer some assistance to the driver to help him/her stay attentive on the road, DriveSafe would be the perfect solution. While using this app, if the driver is drowsy or distracted, they receive a real-time notification that helps them focus on the road and drive safely.
- Insurance companies – Our driver drowsiness detection app can be beneficial to insurance companies in identifying the primary reason for a road mishap that precedes an insurance claim. If there was an accident, the insurer can easily analyze the driver activity at that point of time to take a judicious decision.
- Cab aggregators – Embitel’s driver distraction detection app helps cab aggregators track their drivers’ behavior for streamlining operations. Driver activities such as smoking, texting, excessive use of music system, etc. can be of interest to such companies.
Data Security Aspects of Driver Drowsiness & Distraction Detection App
Currently, all computations and predictions are performed locally on the driver drowsiness detection app. There is no need for internet connectivity for app functioning.
In the future, if a module is integrated to connect to an external server to transfer driver alerts for analysis, the data will be stored locally and transmitted to the server when there is connectivity.
Hence, there will be no data loss or threat to security from this architecture. In such a scenario, the security aspects of the solution will also rely completely on the network security.
Overcoming Challenges
This project was sparked by a unique “Eureka moment” and fueled by an undying urge to craft a solution quickly. As with such kind of projects, we had to face some challenges along the way. One that we are particularly proud of overcoming is the sudden change in operations when we adopted a work-from-home policy during the pandemic lockdown.
Today, we are thrilled to announce the successful completion of the development activities of this project, as planned before the lockdown. This is a feather in the cap of the engineering team that worked onthe driver drowsiness and distraction detection app project. And clear evidence of their dedication and passion to break barriers and deliver exciting solutions for the future!
FAQs
Q1. What is a cognitive distraction?
Ans- Any kind of activity that puts a mental load or demands the attention of the driver and takes their focus away from the road is classified as cognitive distraction. A few examples of cognitive distraction in drivers are –
- engaging in a hands-free conversation over a phone
- excessively using voice assist features on the infotainment system
- following navigation directions from infotainment by constantly glancing at the screen
Q2. Can heart rate be used to detect drowsiness?
Ans- Yes, it is possible to detect driver drowsiness by monitoring their heart rate. Heart Rate Variability (HRV) signal that is available from surface electrocardiogram shows variations in autonomous nervous system activity during episodes of stress, drowsiness or extreme fatigue. These alterations in HRV signals can detect driver drowsiness.
To learn more about the vital signs that play a role in defining a driver’s health, check out our article – IoT-driven Driver Health Management Systems
Q3. How does driver drowsiness detection work?
Ans- A driver drowsiness detection app is based on machine learning algorithms that identify lack of driver alertness by capturing how they look or their vitals.
The app uses images captured by a dashboard camera or the driver’s smartphone mounted on the dashboard. The camera captures images of the driver continuously while the ML algorithm checks for signs of fatigue like blinking, head and hand movements. Sometimes, the path taken by the car is also monitored to see if there are mild deviations from the course or unexpected steering actions.
The app then issues a visual and audible alarm to notify the driver. High-end driver drowsiness monitoring apps can be linked to the vehicle’s navigation system. Using the navigation data, the app can inform the driver of nearby places where he can freshen up or have a cup of coffee.
Q4. How accurate is drowsiness detection using the DriveSafe app?
Ans- The DriveSafe app PoC has been developed after intensive training of the ML algorithm. This ensures that the app detects driver drowsiness and distraction to a high degree of accuracy, and can be further optimised based on customer requirements.
Q5. Does the app require additional hardware?
Ans- The app primarily relies on the sensors already present in smartphones, such as the front-facing camera, accelerometer, and gyroscope, to detect driver behavior. No additional hardware is typically required, making it convenient for users to install and use.
Q6. Can the app be used by commercial drivers or fleet operators?
Ans- Yes, the app can be beneficial for commercial drivers and fleet operators concerned about the safety of their drivers and vehicles. It provides real-time monitoring and alerts, allowing fleet managers to take proactive measures to prevent accidents caused by drowsiness or distraction.
Q7. Can DriveSafe app be used in all driving conditions?
Ans- While the app is designed to work in various driving conditions, including day and night driving, it may be affected by factors such as poor lighting, extreme weather conditions, or obstructed camera views. Users should exercise caution and not solely rely on the app, especially in challenging driving environments where its effectiveness may be compromised.
Q8. What is Embitel’s level of expertise in developing solutions for automated and connected mobility?
Ans- Embitel is a CARIAD Group Company, part of the Volkswagen Group. We have been developing high-end automotive technology solutions for OEMs and Tier-1 suppliers for more than 17 years. Our client base is spread across Europe, USA, Australia, India, South Korea and China.
We are a reliable partner for automakers, supporting them in the end-to-end activities of product development, testing, series production, post-series supply, and market launch of innovative technologies.
Our customers always highlight the quality of our deliverables, as we internally pursue the goal of zero defects and superior quality.
Q9. Is DriveSafe app compatible with all smartphones and operating systems?
Ans- Currently, DriveSafe PoC is an Android-based driver drowsiness and distraction detection app that detects driver activities to a great degree of accuracy. Our goal is to make the app accessible to as many users as possible. While it’s compatible with most Android smartphones, compatibility may vary based on device specifications and operating system requirements.
We have designed the app in a way that it can be easily customised to ensure compatibility with a wide range of devices and operating systems.
