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PARK ASSIST CAMERA MARKET SIZE AND SHARE ANALYSIS - GROWTH TRENDS AND FORECASTS (2023 - 2030)

Park Assist Camera Market, By Vehicle Type (Passenger Cars, Light Commercial Vehicles, Heavy Commercial Vehicles, Electric Vehicles, Others), By Technology (Rear view camera system, 360 degree camera system, Around view monitor system, Others), By Component (Camera, Display Unit, Sensors, ECU Module, Others), By Sales Channel (OEMs, Aftermarket), By Geography (North America, Latin America, Europe, Asia Pacific, Middle East & Africa)

Park Assist Camera Market Size and Trends

The park assist camera market size is estimated to be valued at US$ 2.20 Bn in 2023 and is expected to reach US$ 4.90 Bn by 2030, exhibiting a compound annual growth rate (CAGR) of 12.1% from 2023 to 2030.

Park assist cameras are advanced driver assistance systems that assist drivers while parking or reversing the vehicle. They use rear view, surround view, and 360-degree cameras along with ultrasonic sensors to provide visual aid and alerts to the driver. Park assist cameras enhance driver convenience, prevent collisions, and reduce accidents. The key factors driving the growth of this market are stringent safety regulations, adoption of advanced driver assistance systems (ADAS), and increasing vehicle production.

The park assist camera market is segmented into vehicle type, technology, component, sales channel, and region. By vehicle type, the market is segmented into passenger cars, light commercial vehicles, heavy commercial vehicles, electric vehicles, and others. Passenger cars is expected to be the largest and fastest growing segment during the forecast period due to safety regulations mandating park assist systems in passenger vehicles and increasing adoption of surround view and 360-degree park assist systems.

Park Assist Camera Market Trends:

  • Integration of park assist cameras with 360-degree surround view systems: A major technology trend is the integration of park assist cameras with 360-degree surround view systems that provide an immersive live view of the vehicle’s surroundings. Surround view systems stitch image feeds from multiple cameras to give drivers a virtual bird’s eye view of the vehicle, thus enabling easier and safer parking. Automakers such as Nissan, Hyundai, and Toyota already offer surround view technologies and their adoption is rising rapidly. More OEMs are expected to incorporate surround systems along with park assists.
  • Increasing adoption of user-friendly graphical interfaces: Park assist cameras are incorporating new user-friendly graphical interfaces and displays to enhance the parking experience. Companies are developing animated representations, customizable overlays, and predictive trajectory displays to provide visual aids to drivers. Interfaces are also integrating parking guidelines, hazards, and instructions. Voice alerts and touchscreen displays further simplify usage. As park assist technologies advance, intuitive, and expressive interfaces will play a key role in their adoption.
  • Cloud-based parking space sharing and mapping: Park assist technologies are progressively incorporating cloud connectivity for real-time parking space info. Automakers have demonstrated systems where vehicles share data on empty parking spots which is then available on the cloud for other users in the vicinity. Real-time parking maps reduce search time thereby enabling efficient space utilization. Companies are also exploring dedicating parking zones for vehicles equipped with advanced park/summon features. Seamless connectivity and data sharing will enhance automated parking capabilities.
  • Enhanced accuracy through sensor fusion and artificial intelligence (AI): Companies are leveraging sensor fusion and AI to develop smarter, more accurate park assist systems. Sensor fusion combines visual, ultrasonic, and radar data to achieve enhanced environmental perception and hazard detection. AI algorithms help process and make sense of this data deluge in real-time. Deep learning applied to fused sensor data can enable park assists to understand complex environments and self-improve over time through experience. Such advancements will lead to next-gen intelligent systems.

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