TRAFFIC SIGN RECOGNITION SYSTEM MARKET SIZE AND SHARE ANALYSIS - GROWTH TRENDS AND FORECASTS (2023 - 2030)

The global Traffic Sign Recognition System market size was valued at US$ 5.82 billion in 2023 and is expected to reach US$ 12.88 billion by 2030, grow at a compound annual growth rate (CAGR) of 12% from 2023 to 2030.

Traffic Sign Recognition (TSR) systems use image processing algorithms to detect traffic signs and provide information to drivers about speed limits, crossing, intersection, overtaking and warning signs. The key advantages of TSRs are increased road safety, driver assistance and compliance with traffic rules. The growth drivers include stringent road safety regulations, increasing adoption of ADAS features and growing demand for autonomous vehicles.

The Traffic Sign Recognition System Market is segmented by component, type, vehicle type, electric vehicle type, level of autonomous driving and region. By component, the market is segmented into hardware, software and services. The hardware segment accounted for the largest market share in 2022 and is expected to dominate the market during the forecast period due to the high installation rates of cameras and sensors used for traffic sign recognition.

Traffic Sign Recognition System Market Regional Insights

• North America is expected to be the largest market for Traffic Sign Recognition System Market during the forecast period, accounting for over 38% of the market share in 2022. The growth of the market in North America is attributed to stringent safety regulations, early adoption of ADAS technologies and presence of major automotive OEMs.
• The Europe market is expected to be the second-largest market for Traffic Sign Recognition System Market, accounting for over 32% of the market share in 2022. The growth of the market in Europe is attributed to high penetration of luxury vehicles equipped with ADAS and government initiatives for increasing adoption of active safety systems.
• The Asia Pacific market is expected to be the fastest-growing market for Traffic Sign Recognition System Market, with a CAGR of over 13% during the forecast period. The growth of the market in Asia Pacific is attributed to increasing disposable incomes, rising production of vehicles with ADAS features and growing awareness about active safety systems.

Figure 1. Global Traffic Sign Recognition System Market Share (%), by Region, 2023

Traffic Sign Recognition System Market Drivers:

• Stringent Road Safety Regulations: Government regulations regarding road safety have been a major driver for the traffic sign recognition system market. Regulatory authorities across regions have implemented mandates for equipping vehicles with active safety systems. For instance, the New Car Assessment Program tests vehicles based on crash avoidance technologies including traffic sign recognition. The European New Car Assessment Programme has made traffic sign recognition systems mandatory for achieving 5-star ratings. Such regulations have compelled automakers to accelerate the adoption of traffic sign recognition systems.
• Increasing Integration of ADAS Features: The integration of advanced driver assistance systems (ADAS) including traffic sign recognition in mass market vehicles has catalyzed market growth. ADAS features such as automatic emergency braking, lane departure warning and others are being integrated with traffic sign recognition to enhance their capabilities. According to estimates, the global ADAS market is expected to reach USD 183 billion by 2030. OEMs are offering ADAS bundled packages with traffic sign recognition and lane departure warning to tap into automotive safety demand.
• Technological Advancements in Computer Vision: Significant advances in computer vision, artificial intelligence and machine learning have enhanced the capabilities of traffic sign recognition systems. Computer vision algorithms such as YOLO, SSD and Faster R-CNN have enabled precise detection and recognition of road signage. Companies are using AI technologies such as deep learning and neural networks to improve detection accuracy under difficult conditions. The adoption of GPUs and dedicated AI accelerators in autonomous vehicles will further augment the precision of traffic sign recognition.
• Development of Connected Infrastructure: The development of smart city infrastructure and vehicle-to-everything (V2X) connectivity has created opportunities for traffic sign recognition systems. V2X allows real-time communication of traffic data from road infrastructure to vehicles which enhances dynamic signage detection. Moreover, HD mapping data generated from connected infrastructure aids real-time localization and mapping. Companies are partnering with cities to collect infrastructure data for traffic sign inventories and digital maps.

Traffic Sign Recognition System Market Opportunities:

• Growing Demand for Autonomous Vehicles: The increasing demand for autonomous vehicles across shared mobility and goods movement applications presents significant opportunities. Self-driving vehicles rely extensively on perception systems including cameras, LiDAR and radars for navigation, along with traffic sign recognition. Companies are developing high-resolution detection systems purpose-built for autonomous driving. According to projections, there could be around 8 million autonomous cars by 2030 globally, indicating strong long-term prospects.
• Partnerships with Mapping Companies: Strategic partnerships between automotive OEMs, autonomous technology companies and mapping service providers has unlocked new growth avenues. Collaborations aim to aggregate high definition map data for ADAS and autonomous driving applications. For instance, DeepMap partnered with NVIDIA to accelerate AV mapping capabilities. such partnerships help generate data for training algorithms and enable real-time localization and traffic sign mapping.
• Initiatives for Infrastructure Standardization: Initiatives for standardization and digitalization of road infrastructure will favorably impact the market outlook. For example, the US DOT is modernizing road signage with RFID tags and digital information to enable communication with autonomous vehicles. The European Commission has also proposed mandating traffic signs to include RFID tags. Standardization will allow aggregation of traffic sign inventories into databases for ADAS applications.
• Growing Usage in Commercial Vehicles: The adoption of ADAS and traffic sign recognition systems in commercial vehicles has risen owing to safety and efficiency benefits. Truck OEMs such as Volvo, Daimler are offering traffic sign recognition along with cruise control, brake assist for accident avoidance. Fleet operators are retrofitting ADAS capabilities in existing trucks to reduce risks and operating costs. Mandates regarding AEB fitment in new trucks will also drive installation of traffic sign recognition cameras.

Traffic Sign Recognition System Market Trends:

• Cloud-based Databases of Traffic Signs: The aggregation of traffic sign data into cloud-based databases for ADAS applications is a key trend. Companies are leveraging connected vehicles fleets and infrastructure mapping to build repositories covering road assets across cities. For instance, Rekor is aggregating data into a cloud platform by tapping thousands of commercial vehicles. Cloud databases enhance signage detection by allowing real-time data transfer to vehicles.
• Use of AI for Detection Accuracy: Artificial intelligence and deep learning integration for traffic sign recognition will gain traction owing to benefits such as near real-time object recognition, reduced processing time and accuracy across varying light conditions. Companies are utilizing neural networks, convolutional networks to accurately recognize obscured or partially visible signs. AI training using synthetic datasets is also driving algorithmic improvements for traffic sign recognition systems.
• Over the Air Updates: Automotive OEMs are leveraging over-the-air software updates to continuously train the algorithms and enhance the performance of ADAS systems including traffic sign recognition. OTA updates allow new capabilities to be added without hardware upgrades or dealership visits. Companies are performing data aggregation and running simulations to refine computer vision models to minimize false positives in traffic sign recognition systems.
• Sensor Fusion for Reliability: The adoption of sensor fusion techniques combining camera, radar and LiDAR will gain prominence to improve reliability and capabilities of traffic sign recognition systems. Sensor fusion provides redundancy in case of single sensor failure and enables functions such as distance estimation for dynamic speed limit adjustment. Companies are utilizing sensor fusion to accurately recognize signage in complex lighting conditions and occlusions.

Traffic Sign Recognition System Market Restraints:

• High System Costs: The high costs associated with procuring and integration of traffic sign recognition systems poses challenges for adoption. The cameras used are expensive due to high resolution requirements along with expensive GPUs for running AI algorithms. Moreover, microwave radars used for redundancy add to system costs. These factors lead to increased vehicle prices, limiting uptake in mid and low end mass market segments.
• Susceptibility to Adverse Weather: Traffic sign recognition systems exhibit performance limitations under certain weather conditions such as fog, snow and heavy rain which restricts adoption. Factors like snow obstructing camera visibility, lens wetting in rains and lens frosting in winters deteriorates signage detection accuracy. Although sensor fusion with radar and LiDAR improve robustness, susceptibilty in extreme weather remains a key restraint.
• Cybersecurity Threats: Potential cybersecurity vulnerabilities in connected systems including traffic sign recognition could inhibit integration in autonomous vehicles. Malicious actors could exploit cyber risks and send incorrect traffic sign data to vehicles, leading to wrong navigation and accidents. Complex system integration for ADAS and autonomous vehicles further escalates risks and necessitates comprehensive cybersecurity measures.

Recent Developments

New product launches

• In March 2022, Mobileye, an Intel company, unveiled its next-generation EyeQ system-on-chip that is purpose-built for Level 4 autonomous driving. The EyeQ5 promises to deliver more than a trillion operations per second.
• In January 2021, Continental unveiled its third-generation ARS540 traffic sign recognition system powered by a high-performance graphical processor for advanced object recognition capabilities.
• In September 2020, Bosch launched its latest long-range radar sensor which can detect and classify objects at up to 250 meters. The sensor is suited for automated driving applications.

Acquisition and partnerships

• In October 2022, Volvo Cars acquired an additional 15% stake in Zenseact to strengthen its position in autonomous driving software.
• In December 2021, Qualcomm acquired Veoneer’s Arriver business for $4.5 billion to scale its ADAS capabilities.
• In March 2021, Intel’s Mobileye partnered with Udelv to launch autonomous delivery vehicles by 2023.

Figure 2. Global Traffic Sign Recognition System Market Share (%), by Electric Vehicle Type, 2023

Top companies in Traffic Sign Recognition System Market

• Continental
• Daimler
• Delphi Automotive
• Bosch
• Denso
• Itseez
• Toshiba
• Mobileye
• ZF Friedrichshafen
• Magna International

Definition: The traffic sign recognition system market refers to the industry and technologies focused on developing systems that can recognize and interpret road signs and traffic signals using cameras, radar, LiDAR and artificial intelligence

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