Overview
With a vision to infuse enhanced self-driving capabilities into its automobiles, our client wanted to prevent front-end collisions en route to its locations and bring efficiency to its manufacturing portfolio. Utilizing SYNERGYLABS’ designed computer-vision-based advanced driver assistance system or ADAS, the automobile manufacturer in India prevented service delays, reduced the number of collisions, for users while also improving customer satisfaction.
About the Automobile Manufacturer Company
Our client- a renowned automobile manufacturer company had a number of plants to manufacture the best-designed vehicles for their customers. They are responsible to bring out in the market the best model with high performance and efficiency to help run for the longest miles and deliver optimal services that aptly meet customer demands. Their long-industry reputation has been built around their efficiency in encouraging productivity in all sectors they serve without disrupting operational efficiency.
To match the customer expectations, they leverage speed and performance through digitization. And, now, they are looking to maintain long-term customer relationships to grow and scale beyond the known boundaries and territories.
The challenge
After the expansion of their customers, they started feeling growing pains. Their vehicles sweep through highways, roads, and lanes, increasing the rate of long-haul transit for their users occasionally or frequently. They felt a growing pressure to keep up with vehicle and asset maintenance and give the best value to their users.
This requires users to improve concentration on the highways or spaces where they drive to keep a safe distance from the vehicles ahead of them. Moving along the highways for a stretch of 4 or 6 hours- if not 8 hours is many a time usually a stressful journey for drivers. Simultaneously, they also need to keep pace with how safe their vehicles can move along the road. The approach is to determine that their vehicles are resulting in fewer risks associated with highway collisions due to drivers’ negligence or inadvertent driving faults.
With the safety and security of public commuters in mind, they are committed to encouraging safety, eliminating the chances of injury or accident-related losses, and building a secure driving experience for all.
“Over a few years, we’ve observed that our automobiles need more enhanced technology beyond GPS tracking systems not just to help us with tracking of vehicles and communications. We needed technologies that bring the convenience of managing our automobiles and also safety’, Vice President at the automobile manufacturing company.
For the owner, making their vehicles comply with road safety, efficiency, and growth strategy was challenging. They looked for support that could allow them to meet the immediate needs of customer satisfaction and scalability in the ever-evolving atmosphere.
The Solutions
Our team at SYNERGYLABS proposed a computer vision-based front-end collision avoidance system. This machine learning-programed system gives the best solution to transform the under-the-hood driving experience for every user.
We built dual-facing cameras programmed with computer vision (machine learning/natural language processing) technology to put them under the hood or driver cabin. Synced with a touchscreen dashboard, SYNERGYLABS-programmed predictive collision system provides real-time critical threat alerts on the screen to alert drivers and help take control of the vehicle before the incident could pose a huge risk to their assets and people.
To help them continuously monitor real-time driving situations and improve driving behavior, we gave our client the best solutions to help with identifying potential hazards and avoid them in real-time.
Avoiding unpredictable risks as the vehicles move along the road becomes possible by using AI algorithms that simplify the assessment of situational risks. With this, the system helps the owner determine the severity of the disruption or distraction on the road ahead- the nearly running traffic, stoppage, and the nearby locations.
By continuously fetching risk data that deliver real-time feed on the screen of the anti-collision system dashboard, some critical variables like driver behavior, vehicle movement, and level of collision are fast to grasp and comprehend. Thanks to the Convolution Neural Network or AI-based model that we built to infuse into the system and program to detect what threat the vehicle is likely to experience and alert the driver to handle the risk much before it could turn into a huge risk and impact their operations.
The predictive collision system we built for the client features critical components to enhance every step of the driving journey.
Headway collision monitoring - In critical weather conditions- heavy snowfall, cyclones, rains, or floods- taking control on speed control is tough for drivers. Our dashboard gives an alert when the vehicles come too close that may be a significant reason to cause rear-end or front-end collisions. The fleet drivers therefore can avoid collisions when the distance between two vehicles becomes unsafe.
Lane departure warning - The run-off-road crashes occur when unintended lane departure happens. Our predictive collision system can easily help drivers maintain lane marking with visual and audio signals as they deviate from the lane. Drivers now can maximize our computer-vision-based built AI model that helps them reduce serious injuries and also serious fatalities on road.
Obstacle detection - The front cameras use sensors to detect objects through the driveway. Usually, drivers can’t recognize obstacles and maintain the right distance while driving during low-visibility critical weather conditions like rain, snow, and fog.
The collision avoidance system also put together the best of components that include adaptive cruise control, emergency brake assist, and speed limit indicator.
“We evaluated a number of on-the-shelf predictive collision products before we zeroed in on SYNERGYLABS. They understood our needs better and offered us the most sophisticated AI-powered technology to maximize the power of automotive autonomy and support our commitment to safe driving”, the owner of the manufacturing company.
The results
There’s a visible increase in safety through enhanced monitoring of driver behavior. Front-end collisions are less likely to happen- they are building happy customers who are fond of autonomous driving technology. They were also satisfied by giving their clients the ability to reduce the number of visits to the repair shops.
Technology used
Computer Vision, AI, Ext JS, HTML, Java, Springboot, MySQL, Postgres, Socket programming with netty and Tensor Flow, python.
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