Few automotive manufacturers like Tesla are already integrated certain level of automation into the cars, but not level 5 or full automation, as there are certain challenges of autonomous vehicles making difficult for the manufacturers to develop an AI-enabled fully automated car that can run without human intervention with complete safety.

Understanding the issues with self-driving cars is very important for machine learning engineers to develop such an AI-enabled vehicle for successful driving. So, right here we also discuss the most critical problems with self-driving cars.

Training AI Model with Machine Learning

As we know, to develop an autonomous vehicle, a machine learning-based technology used for integrating AI into the model. The data gathered through sensors can be understood by cars only through machine learning algorithms. 

These algorithms will help identify objects like a pedestrian, a street light detected by the sensors and classify them, as per the system’s training. And then, the car uses this information to help decide whether the car needs to take the right action to move, stop, accelerate, or turn aside to avoid a collision from objects detected by the sensors.  

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And with the more precise machine learning training process, in near future machines will be able to do this detection and classification more efficiently than a human driver can. But right now there is no widely accepted and agreed basis for ensuring the machine learning algorithms used in the cars. There are no such agreements across the automotive industry how far machine learning is reliable in developing such automated cars.

Open Road with Unlimited Objects

Autonomous cars run on the road, and once it starts driving, machine learning helps it learn while driving. And while moving on the road, it can detect various objects that have not come across while training and be subject to software updates.

As the road is open, and there could be unlimited or multiple types of new objects visible to cars, that have been not used to train the self-driving car model. And how to ensure that system continues to be just as safe its previous version. Hence, we need to be able to show that any new learning is safe and that the system doesn’t forget previously safe behaviors or something like this, the industry yet to reach agreement on.     

Lack of Regulations and Standards

Another hurdle for the self-driving car is there are no specific regulations or sufficient standards for the whole autonomous system. Actually, as per the current standards for the safety, for existing vehicles, the human driver has to take over the control in an emergency. 

For autonomous vehicles, there are few regulations for functions like automated lane-keeping system. And there are also international standards for autonomous vehicles that include self-driving cars, which sets related requirements but not useful in solving the various other problems like machine learning, operational learning, and sensors.

Social Acceptability Among the People 

Over the past year while testing or in real-life use, self-driving cars involved in the crash on autopilot mode. And such incidents discourage people to fully rely on autonomous cars due to safety reasons. Hence, social acceptability is not acceptable to such car owners but also among other people who are sharing the road while running on the road with them.     

So, people need to accept and adopt the self-driving vehicle’s systems with involvement in the introduction of such new-age technology. And unless the acceptability reached social levels, more people will not use to buy self-driving cars, making it difficult for the auto manufacturers to further improve the functions and performance of such cars.     

Use & Availability of Data for Sensors

To sense the surroundings of an environment, a self-driving car use a broad set of sensors like Camera, Radar, and LIDAR. These sensors help to detect varied objects like pedestrians, other vehicles, and road signs. The camera helps to view the object while on the other hand, Radar helps to detect objects and track their speed and direction. 

Similarly, there is another important sensor called LIDAR that uses lasers to measure the distance between objects and the vehicle. And a fully autonomous car needs such a set of sensors that accurately detect objects, distance, speed, and so on under all conditions and environments, without a human needing to intervene.