Building next gen chips for your next self driving car

In the past, the idea of a self driving car would be science fiction. But today, technological development has made it possible to integrate automation features into cars. According to Statista, in the year 2019, there were around 31 million cars globally, that had some level of automation in their operations. In the future self-driving cars may shape the future of personal as well as public transportation.

In the technology-driven era of the 21st century, the concept of self-driving cars has gained considerable momentum. Businesses have been investing large sums of money in recent years to develop autonomous vehicles (AVs) that can revolutionise driving by making it safer, enjoyable, and user-oriented. In contemporary vehicles, a majority of innovations are supported by semiconductors. Semiconductors are responsible for providing sensing capabilities as well as advanced actuation, thereby enhancing the performance, safety, and comfort aspects of vehicles. For advancing in the autonomous vehicle’s domain, it is imperative to continuously work on innovative technologies.

Classification of autonomous vehicles

The involvement of human beings in autonomous vehicles is limited to a significant extent. Due to this feature AVs are expected to be capable of seeing or sensing things around them so that they can drive smoothly. These modern vehicles rely on a broad range of sensors, in addition to hardware and software components which help in interpreting inputs from the sensors.

Without appropriate software applications, these vehicles cannot function independently. The integration of appropriate software is necessary to enable AVs to make appropriate driving-related decisions based on the existing road conditions. In order to develop a well-functional and robust autonomous vehicle, it is necessary to focus on each of the areas so that the vehicle can function efficiently and seamlessly.

Autonomous vehicles can be classified into six types, depending on the level of automation. The capabilities of each of the AVs may vary. Similarly, the semiconductor type that may be required in the AVs may also vary, based on the degree of automation. The different categories of AVs are presented below: 

Source: Society of Automotive Engineer (SAE) International

• Level 0 – In Level 0, there is no automation involved in automobiles. The driving is entirely managed by human control. The driver is responsible for carrying out all kinds of driving-related tasks like steering, braking, and acceleration. The vehicle cannot drive on its own unless the driver does the driving. 
• Level 1 – In the Level 1 category, an automation system is integrated into the vehicle. The system is there is provide assistance to the driver. The role of autonomous capabilities is restricted. For example, the system may help the driver by monitoring the vehicle’s speed via cruise control. 
• Level 2 – The Level 2 category is also known as partial automation. The AVs that belong to this category can perform a number of operations on their own such as acceleration as well as steering. In these AVs, the human driver can monitor the functions that are being conducted automatically and they can take control of the operations if they feel like it. 
• Level 3 – Level 3 is also known as conditional automation. The degree of automation that the vehicles possess is higher as they are capable of detecting the environment around them. The AVs belonging to Level 3 are capable of carrying out most of the driving operations. Nevertheless, human overriding may still be required, and it cannot be eliminated entirely.
• Level 4 – The autonomous vehicles that belong to Level 4 are high automation vehicles. By leveraging innovative and advanced technologies, these vehicles are capable of undertaking all the driving operations. However, it is essential to note that they can perform all driving operations when specific circumstances are met. At this level, human overrising can be considered to be an option. 
• Level 5 – The final classification of AV is Level 5 which is known as full automation. The autonomous vehicles are able to carry out entire driving activities under all kinds of circumstances. Due to the high degree of automation, there is no need for human interaction or attention at this level. 

Technical aspects of autonomous vehicles 

The autonomous vehicles that belong to Level 0, Level 1, and Level 2 categories can function by using standard chips. However, in the case of AVs that belong to higher levels such as Level 3 to Level 5, there is a need for more powerful chips. Typically, these AVs make use of specialty silicon. The demand for silicon chips in AVs has been gaining momentum since these chips have higher efficiency and hence support better performance of vehicle systems. Moreover, by integrating silicon chips into autonomous vehicles it is possible to make sure that the execution of complex software functions and analytics gets simplified. For instance, specialty silicon can support functions and operations that involve the sensor fusion of laser, camera, Light Detection and Ranging (LiDAR) sensor, and other devices. 

Currently, automobile manufacturers are collaborating with diverse stakeholders including vendors and software developers to work on AVs that belong to more advanced levels. For designing vehicles that possess higher automation capabilities, there is a need for more efficient chips, powerful sensors, and improved software applications. Without the fusion of the right kind of technologies, AVs cannot function to their full potential. The integration of technical features is a must to ensure that these vehicles can drive safely in a broad range of conditions, at varying speeds, without compromising convenience and performance for users. 

Technical path for autonomous vehicle 

In Autonomous Vehicles, the role of sensors is indispensable. In fact, most of the autonomous vehicles that exist in the market today utilise a number of sensors for the purpose of ‘seeing.’ These common types of sensors are cameras, radar, and LiDAR. These sensors may have a few overlapping characteristics; however, their contribution is immense to enable AVs to have a clear vision to operate the vehicle. The sensors fundamentally help AVs to function in varying weather conditions, travel lengths, or distances as well as lighting layouts.

Source: engineering.com

Camera as a sensory tool 

The AVs belonging to Level 1 or Level 2 categories may utilise the camera for purposes like the detection of lanes or carrying out other advanced driver assistance operations. However, in the case of AVs in the Level 3 category, cameras are used for the identification of traffic signs. When the weather conditions are clear, the camera may play a key role to provide an in-depth view of the surroundings of the vehicle. Hence the capabilities can help the AV to identify pedestrians, cyclists, and other vehicles and improve safety while driving. For AVs to function properly, several cameras facing diverse directions are essential so that a complete and detailed picture of the surrounding space can be obtained. 

Radar as a sensory tool

Apart from cameras, the role of radar is vital to strengthen the sensory capabilities of AVs. They serve as important sensory instruments that can be used in different Advanced Driver Assistance Systems (ADAS). Some of the common uses of radar in AVs are the detection of blind spots and adaptive cruise control. Auch uses of radar are common in AVs belonging to Level 0, 1, and 2 categories. However, their application in Level 3 AVs may drive their demand in the future. 

LiDAR as a sensory tool

Several manufacturers of AVs have been investing in LiDAR to improve the vision of these vehicles. Although the principles of radar are used in LiDAR detection systems, they rely on lights from a laser to sense things. In AVs, LiDAR is capable of shooting lasers in all directions. When these lasers bounce back, AVs are able to get an insight into the surrounding area. LiDAR systems help to measure the distance of objects and help AVs to maintain proper positioning on the road. 

Safety dimension in autonomous vehicles

In autonomous vehicles, semiconductors are used as a key part. As the quality and functionality of these elements may vary it is essential to integrate proper semiconductors that can add value to AVs by enhancing their operational capabilities. In the AV landscape, the careful selection of semiconductors is instrumental to ensure that all the specifications are carefully met and these elements can function efficiently for a long time without compromising the safety of users. 

Source: https://www.epdtonthenet.net/

Semiconductors are known to be highly fragile and delicate components. Their application in AVs, where the environmental conditions are complex increases their challenges. For example, these components need to have proper resistance against extreme climate conditions like humidity or vibrations so that they can function efficiently. Without proper robustness, semiconductors might not be able to support AVs with a high degree of automation capabilities. For AV manufacturers, it is essential to work on robust automotive chips that can withstand extreme conditions and continue to function perfectly. 

As the traffic landscape is evolving continuously, AV manufacturers need to integrate components that can ensure the safety of users, without diminishing vehicle performance. At present, the demand for chips is gradually expanding. In order to boost the safety aspects, AV manufacturers are expected to integrate systems such as Autonomous Emergency Braking (AEB) into their vehicles.

Currently, 'ADAS' is among the latest features that promotes safety in AVs. The AEB technology has the potential to enhance the safety feature of AVs by bringing the vehicles to a halt and preventing accidents. In the evolving technological landscape, the adoption of the latest technologies is a must to design a foolproof autonomous vehicle that combines safety, with performance and functionality. It has been estimated that in the future autonomous vehicles could prevent 1,442,000 accidents and approximately 12,000 fatalities.

Conclusion

Self-driving cars may be the future of transportation. However, the advancement of technology is essential so that next gen chips can be incorporated into these autonomous vehicles. For incorporating essential features in these vehicles, it is essential to look beyond semiconductors and focus on more versatile options. The advancement in the automobile arena can transform the concept of driving.