The growth of the automotive industry since the last century has been rapid owing to the high technological advancements and developments from original equipment manufacturers (OEMs), tier 1 manufacturers, and tier 2 manufacturers. In particular, the increasing number of passenger and commercial vehicles on road reflects the progress made by OEMs and other manufacturers. However, the increasing number of vehicles on road also creates immense opportunity for vision and navigation system providers to integrate advanced safety driver-assistance systems (ADAS) features in the vehicle to increase road safety and provide secure movement of goods via commercial vehicles.
Owing to the rapid integration of ADAS features in a vehicle, the automotive industry is on the crest of technological advancement, which is expected to further increase in the coming years, thereby providing improved and enhanced safety features in Level 3, 4, and 5 vehicles. The progressive evolution of automotive industry is attributed to the increasing focus of manufacturers toward the road safety, government regulations, and changing consumer preferences, which has led to the deployment of vehicles from Level 1 to Level 3.
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This evolution has resulted in the advancement of vehicles in terms of vehicle performance, communication capabilities, passenger safety, and driving comfort, among others. Consequently, the advancement and improvement in on-road vehicles performance has created a surge in the demand for vehicles, thereby raising the need for safer and advanced features in it.
The deployment of ADAS features in a vehicle makes the road safe for drivers as well as pedestrians. The increasing number of road accidents has compelled the government bodies and federal authorities such as “National Highway Traffic Safety Administration” (NHTSA), “Ministry of Land, Infrastructure, Transport and Tourism” (MLIT), and “European Commission” (EC) to work toward the deployment of autonomous vehicle by passing stringent regulations and laws for automakers. The consumers that are reaping the benefits of ADAS features in a vehicle are expecting more in the coming years with the deployment of Level 4 and Level 5 vehicles, which is going to improve automated features as compared to Level 1, 2, and 3 vehicles.
The improvement can be expected owing to the evolution of software with each level. Since the entire data gathered by the sensors is processed via software, it plays an important role in the deployment of advanced features in a vehicle. Moreover, with the expected commercialization of Level 4 and Level 5 vehicles in the coming years, software is going to play an essential role in making a vehicle partially or fully autonomous. The rise of deep learning, artificial intelligence, and machine learning is further going to help the evolution of software by making the self-driving cars more independent of human interaction.
However, legal issues pertaining to HD maps, high price of vision system components, and increasing threat from cyber-attacks are expected to limit the growth of the global vision and navigation system market for autonomous vehicles during the forecast period (2019-2024). In the automotive industry, the increasing volume of automobile sales for both passenger and commercial vehicles along with the rise in autonomy levels have increased the demand of automated features and advanced driver assistance system features.
The complexity of car’s electronic system is considerably increasing, thereby making the in-vehicle system/network architecture and software more multifaceted. This complexity which can be seen largely in autonomous cars, leads to more and more system updates, thus creating a huge risk of cyber-attacks. According to BIS Research analysis, the sales of autonomous cars is expected to reach 141.3 million units by 2030, in the vehicle-to-device category. The demand of autonomous vehicle is rapidly creating a large pool of data generated through connected ecosystem such as data generated from the electronic driver assistance systems (including speed regulation, pre-collision, parking, lane, and blind spot detection), and other infotainment systems (voice assistant, Bluetooth, navigation) and sensors (performance control). The large pool of data generated through different sensors in the vehicle, ranging from a user’s driving style to their personal credentials and preferences, are prone to cyber-attacks, leading to distrust in consumer inclination toward such vehicles.
Autonomous driving components of a vehicle include various sensors such as cameras, LiDARs, radars, and ultrasonic sensors. These sensors work together and give a detailed 3D analysis of the surrounding, revealing both dynamic and static objects such as cyclists, pedestrians, and traffic light. Since the past decade, a high surge in the demand for these sensors has been witnessed owing to the demand for more enhanced features in a vehicle. In addition to this, rising safety concern of the driver and the regulations imposed by government authorities are further fueling the growth of this market.
The market size of the vision and navigation system for autonomous vehicle has been valued by components (camera, LiDAR, radar, ultrasonic sensors, GPS, and IMU) and software in terms of value. Components play a significant role in the working of an autonomous vehicle. In order to meet the complex requirements of an autonomous vehicle, the components including camera and LiDAR allow the vehicle to see 360 degrees, working in both daytime and night. Cameras form an integral component of the vision system by providing a 360-degree field of view rather than the 120-degree view of human drivers. At present, cameras are being used for object detection, night vision, rear view enhancement, traffic sign recognition, and path detection, among other necessary applications for a safe movement of the highly automated vehicles.
The competitive landscape of the vision and navigation system market for autonomous vehicle consists of different strategies undertaken by major display manufacturers to gain market presence. Some of the strategies adopted by display manufacturers are a new range of product launches and developments, partnerships, collaborations and agreements, and mergers and acquisitions
Among all the strategies adopted, new partnership and collaborations dominated the competitive landscape during 2017-2019 and are the most widely adopted strategy amongst the vision and navigation system for autonomous vehicle manufacturers. Velodyne LiDAR Inc., Robert Bosch GmbH, ZF Friedrichshafen AG, and DENSO CORPORATION are the top four players forming partnership and collaboration in the global vision and navigation system market for autonomous vehicle.