5 min
Road deaths are on the rise, with almost 1.5 million people killed in 2016 globally in road accidents, pressure has been mounting on carmakers and technology providers to tackle the fatalities caused by car crashes.
Safety systems to prevent cars from drifting into another lane or that warn drivers of vehicles in their blind spots are beginning to live up to their potential to significantly reduce crashes.
New technology around automobiles and vehicle safety have allowed us to move beyond passive safety and focus more on active safety. Cognitive IoT technologies are beginning to assist in preventing car crashes.
How automobile giants are using IoT for car safety:
Automobile companies have been working towards developing self-driving cars, which rely heavily on cognitive IoT for safety. Undoubtedly, the biggest concern for all companies and governments has been car crashes. However, with the latest technologies are helping big players make safer cars. We will talk about the technologies later, but let us first see how some leading companies are using IoT to make their cars safe. Volvo: It has become the first automaker to debut radar based safety systems in automobiles with the launch of XC90 hybrid in India. Volvo's radar based security systems include City Safety, a co-pilot system that detects obstructions in the way and brakes automatically if a collision is imminent. Another set of features that use radar based technology is Intellisafe. This is the system that works to actively avoid an accident and includes features like Adaptive Cruise Control. At speeds less than 50kmph Pilot Assist technology works alongside the Adaptive Cruise Control to keep the car in the lane with gentle steering inputs, should the driver deviate. Tesla: Tesla worked with its radar supplier, Bosch, to get upgraded drivers and access to raw input from the radar antenna on its Model S and X vehicles in order to build its own processing of the data. It enabled Tesla to push new safety features and owners are already reporting that the system has helped them avoid accidents. Tesla’s new suite with 360-degree camera coverage and ultrasonic sensors with a better range have the potential to be much more efficient. One of the most impressive features enabled by the new radar processing capacity is the ability for the system to see ahead of the car in front and basically track two cars ahead on the road. The radar is able to bounce underneath or around the vehicle in front of the Tesla Model S or X and see where the driver potentially can not because the leading vehicle is obstructing the view. Honda: By leveraging IBM Bluemix and the Watson IoT platform, Honda has been able to move further along its connected car initiative set for 2020. Honda has not only improved its products and services but also transformed the processes within the organisation. The Driving Coach System is able to capture data based on:- distance to other vehicles
- distance to other objects
- vehicle placement on the lane
- break distance and timing
- driver behaviour
The technologies taking over:
Vehicle-to-Vehicle communication: The new age sensor technology which will focus on the cars to communicate, will also detect pedestrians, bicycles within its proximity and adjusts the car’s speed accordingly. This will also help to create a network based traffic management system. Vehicle-to-Infrastructure (V2I) Communications: Vehicle infrastructure integration connects cars to physical surrounding and helps manage traffic and prevent accidents by alerting drivers to the traffic situation ahead and also to identify the most suitable route to the intended destination. Data Capture and Management: Connected cars operate as sources of IoT data generating information enabling critical transportation, logistics, and freight management decisions.Internet of Automobiles:
According to IBM, 100% of cars are expected to be connected by 2025, to transform automobiles into auto-mobility enabled by Cognitive IoT. Advanced safety features in the car have been designed to monitor driving patterns, or observe the driver directly to see they are driving safely and not nodding off while driving. A combination of local online control loops, aided by fleet-level or personalised learning in the cloud can provide this feature. Cars have emerged as the ultimate mobile machines in the prevalent era of the Internet of Things. It’s only a matter of time when the popular IoT car applications are embraced on a global scale as a necessity and not merely as innovation or luxury.- AMD’s Server CPU Business Faces a New AI Boom
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