WILMINGTON, NEW CASTLE, DE, UNITED STATES, January 15, 2025 /EINPresswire.com/ -- Allied Market Research published a report, titled, "Automotive Intelligence Park Assist System Market by Vehicle Type (Passenger Car, Light Commercial Vehicles, and Heavy Commercial Vehicles), Application (Semi-Autonomous and Fully Autonomous), and Vehicle Class (Mid-priced and Luxury): Global Opportunity Analysis and Industry Forecast, 2021–2030." According to the report, the global automotive intelligence park assist system industry generated $4.33 billion in 2020, and is estimated to reach $38.93 billion by 2030, witnessing a CAGR of 24.9% from 2021 to 2030.

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Automotive intelligence park assist system is an advanced driver assistance system, which is installed in new vehicle models to provide safer & securer parking of the vehicle in tight parking space. Moreover, increased advancement in vehicle & related technology also supplements the automotive intelligence park assist system market during the forecast period. In addition, the installation of intelligence park assist system in a vehicle requires several components, such as sensors, camera, ICs, and other components, whose combination derives an exact image on the inbuilt display system of the vehicle, thus giving a clear view of the parking space.

The global automotive intelligence park assist system market has been segmented into vehicle type, application, vehicle class, and region. Based on vehicle type, it is divided into passenger car, light commercial vehicles, and heavy commercial vehicles. Based on application, it is bifurcated into semi-autonomous and fully autonomous. Based on vehicle class, it is classified into mid-priced and luxury. By region, the global market has been studied across North America, Europe, Asia-Pacific, and LAMEA.

Key Findings Of The Study

By vehicle type, the heavy commercial vehicles segment is expected to register a significant growth during the forecast period.
Depending on application, the fully autonomous segment is anticipated to exhibit significant growth in the future.
On the basis of vehicle class, the luxury segment is anticipated to exhibit significant growth in the future.
Asia-Pacific is anticipated to register the highest CAGR.

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The passenger car segment to continue its lead position throughout the forecast period

Based on vehicle type, the passenger car segment held the largest share in 2020, accounting for more than four-fifths of the global automotive intelligence park assist system market, and is projected to continue its lead position throughout the forecast period. This is due to its vital role in the transportation industry, introduction of safety & security features, and surge in penetration in different countries. However, the heavy commercial vehicles segment is expected to manifest the highest CAGR of 30.4% from 2021 to 2030. This is due to stringent regulations by government for safety features that enabled manufacturers use effective ADAS services such as height & pressure sensing system.

The semi-autonomous segment to continue its dominance throughout the forecast period

Based on application, the semi-autonomous segment contributed to the largest share in 2020, holding nearly 90% of the global automotive intelligence park assist system market, and is projected to continue its dominance throughout the forecast period. This is due to increased inclination of semi-autonomous vehicles worldwide. However, the fully autonomous segment is estimated to portray the largest CAGR of 29.2% from 2021 to 2030. This is attributed to introduction of features such as ADAS, connected cars, and others.

North America to maintain its leadership status by 2030

Based on region, North America contributed to the largest market share in 2020, accounting for nearly two-fifths of the global automotive intelligence park assist system market. This is due to increase in technology driven companies and surge in R&D activities. However, Asia-Pacific is expected to register the fastest CAGR of 29.4% during the forecast period, owing to rise in need for vehicles equipped with advanced features across the region.

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Leading market players

Aisin Seiki Co., Ltd.
Continental AG
Delphi Automotive
Hitachi Ltd.
Magna International
NXP Semiconductors
Robert Bosch GmbH
Siemens AG
Valeo SA
ZF Friedrichshafen

Factors, such as increased parking concern across the globe, surge in demand for Internet of Things (IoT)-based technology, and increase in number of vehicles, supplement the growth of the global automotive intelligence park assist system market. Moreover, high implementation cost & configuration complexity accompanied with low rate of internet penetration in developing regions hampers the growth of the market. However, rise in investment on building driverless vehicles and increase in government initiatives in building smart cities across the globe create ample opportunities for the growth of the global automotive intelligence park assist system market during the forecast period.

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Allied Market Research (AMR) is a full-service market research and business-consulting wing of Allied Analytics LLP based in Wilmington, Delaware. Allied Market Research provides global enterprises as well as medium and small businesses with unmatched quality of "Market Research Reports" and "Business Intelligence Solutions." AMR has a targeted view to provide business insights and consulting to assist its clients to make strategic business decisions and achieve sustainable growth in their respective market domain.

We are in professional corporate relations with various companies, and this helps us in digging out market data that helps us generate accurate research data tables and confirms utmost accuracy in our market forecasting. Each and every data presented in the reports published by us is extracted through primary interviews with top officials from leading companies of domain concerned. Our secondary data procurement methodology includes deep online and offline research and discussion with knowledgeable professionals and analysts in the industry.

David Correa
Allied Market Research
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