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$ 33.62 billion in 2023 and is expected to reach US$ 46.27 billion by 2030, growing at a compound annual growth rate (CAGR) of 4.7% from 2023 to 2030.

Traffic sign recognition systems are advanced computer vision technologies used to automatically identify and classify different traffic signs. There are generally two main types of systems - commercial and research-based. Commercial systems available in the market use techniques like machine learning and deep neural networks to recognize signs printed on speed limit, stop, and hazard indication boards. They process images captured by a camera mounted inside the vehicle and compare visual features to identify the sign. These systems can reliably detect most common road signs and provide driver support features.

However, research-based traffic sign recognition systems tend to use more sophisticated algorithms and focus on challenging tasks like recognizing damaged, obscured, or low-quality signs. They employ complex deep learning models trained on huge publicly available sign databases. Such systems aim to achieve human-level perception for all traffic signs regardless of capturing conditions. While offering high detection accuracy, a key disadvantage is the heavy computational requirements for deep neural networks. Also, recognizing rare or unique signs designed for specific regions continue to pose difficulties. Nevertheless, ongoing research promises to make sign recognition more robust and help develop fully self-driving vehicles with contextual understanding of road environments.

The traffic sign recognition system market is segmented based on vehicle type, type, and region. By vehicle type, the market is segmented into passenger cars, light commercial vehicle, and heavy commercial vehicle. The passenger cars segment accounted for the largest market share in 2022 and is expected to dominate the market during the forecast period due to the rising demand for premium cars, government regulations regarding road safety, and increased road safety awareness.

Traffic Sign Recognition System Market Regional Insights

• North America is expected to be the largest market for traffic sign recognition systems during the forecast period, which accounted for over 34% of the market share in 2022. The growth of the market in North America is attributed to stringent safety regulations, early adoption of ADAS (Advanced driver-assistance systems) technologies, and the presence of major automotive OEMs (Original Equipment Manufacturer).
• The Europe market is expected to be the second-largest market for traffic sign recognition systems, which accounted for over 29% of the market share in 2022. The growth of the market in Europe is attributed to the high penetration of luxury vehicles equipped with ADAS and government initiatives for the increasing adoption of active safety systems.
• The Asia Pacific market is expected to be the fastest-growing market for traffic sign recognition systems, growing at a CAGR of over 22% 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

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Global Traffic Sign Recognition System Market: Analyst’s Viewpoint

The traffic sign recognition system market is witnessing strong growth driven by rising road safety concerns and the need for advanced driver assistance systems. Governments across regions are mandating the inclusion of TSR (Traffic Sign Recognition) systems in vehicles to reduce road accidents. This is creating significant opportunities for OEMs and vision technology providers in this space. However, data and computational limitations of current AI (Artificial Intelligence) and machine learning algorithms pose challenges to recognizing complex or ambiguous signs. This can restrain faster adoption until the technology matures to minimize error rates.

The European region is expected to remain dominant due to stringent regulations and an increase in supportive infrastructure. However, Asia Pacific is emerging as the fastest growing regional market, led by countries like China and India. Surging automobile production and sales coupled with government initiatives for connected and autonomous vehicles present a lucrative outlook. North America will also see healthy growth as technology giants increase investments in autonomous driving and advanced safety features gain wider acceptance.

Although aftermarket installations currently account for most sign recognition systems, original equipment production is likely to pick up steadily. Collaboration between automakers, vision technology developers, and road authorities to build sophisticated databases can help improve accuracy. Over-the-air updates provide opportunities for continuous upgrades to the algorithms. Successful commercialization of driverless vehicle technologies and growing demand for enhanced driver safety features are expected to further accelerate revenue streams for vision sensors and edge computing.

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. In January 2023, European car makers will be subject to a revised scoring system that incorporates Driver Monitoring System (DMS) features to enhance Safety Assist evaluations. These mandatory regulations have widespread implications for both automotive manufacturers and Original Equipment Manufacturers (OEMs) globally. Notably, China has made significant strides in implementing and advancing these regulations since 2020.
• 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 74.57 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 you only look once (YOLO), Single Shot Detector (SSD), and Faster Convolutional Neural Network (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, High-Definition (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 (Light Detection and Ranging), and radars for navigation, along with traffic sign recognition. Companies are developing high-resolution detection systems purpose-built for autonomous driving. According to McKinsey & Company, in 2030, 12% of newly purchased passenger cars will be equipped with Level 3 or higher autonomous technologies, and by 2035, 37% will feature Advanced Driver Assistance (AD) technologies.
• Partnerships with Mapping Companies: Strategic partnerships between automotive OEMs, autonomous technology companies and mapping service providers have 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 the standardization and digitalization of road infrastructure will favorably impact the market outlook. According to arxiv is an open-access repository of electronic preprints and postprints approved for posting after moderation, through enhanced encoding schemes for reader-tag communication and on-vehicle antennas, REI (Recreational Equipment, Inc.) can meet the criteria for traffic sign inventory management and environmental monitoring. However, it falls short in addressing the need for high-speed navigation.
• 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 and Daimler, are offering traffic sign recognition along with cruise control and brake assist for accident avoidance. Fleet operators are retrofitting ADAS capabilities in existing trucks to reduce risks and operating costs. Mandates regarding AEB (automated emergency braking) fitment in new trucks will also drive the 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 vehicle fleets and infrastructure mapping to build repositories covering road assets across cities. For instance, in March 2023, throughout the Navy Yard, Rekor's intelligent devices utilize artificial intelligence (AI), machine learning (ML), and enhanced edge processing to gather de-identified roadway data and conduct analysis. This data is then converted into essential traffic insights, which can be instantly viewed on Rekor's cloud-based platform. The analytics cover aspects such as visitor statistics, traffic volume, vehicle types, and the influence of both visitors and 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 (Over-the-Air Update) 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 (General Purpose Graphics Processing Unit) 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. On the flip side, it's crucial to acknowledge that ongoing advancements in technology and increased market demand could potentially drive economies of scale, leading to cost reductions over time. As these technologies mature and become more commonplace, manufacturers may find innovative ways to optimize production processes and reduce component costs. This, in turn, could pave the way for greater affordability and broader accessibility of traffic sign recognition systems, fostering increased adoption across diverse 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, susceptibility in extreme weather remains a key restraint. However, it is important to note that ongoing research and development efforts in the field of autonomous vehicle technology are dedicated to overcoming these weather-related challenges. Innovations such as improved sensor technologies and the integration of advanced weather-resistant materials in camera systems are actively being explored.
• Cybersecurity Threats: Potential cybersecurity vulnerabilities in connected systems including traffic sign recognition could inhibit integration in autonomous vehicles. Malicious 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. Nevertheless, ongoing advancements in cybersecurity technologies and protocols offer promising avenues for mitigating these vulnerabilities. Continuous research and development efforts are focused on bolstering the resilience of connected systems including robust encryption methods and intrusion detection systems. Collaboration between the automotive and cybersecurity industries is actively addressing emerging threats, fostering the development of more secure and reliable systems. As these cybersecurity measures advance, the industry can work towards building a safer and more resilient foundation for the integration of connected technologies in autonomous vehicles.

Recent Developments

New product launches

• In April 2022, Mercedes-Benz, a Germany-based luxury and commercial vehicle automotive brand, unveiled its new product, Data Traffic Signs. This product is designed to provide an efficient solution for its B2B and B2G customers to monitor the existing traffic sign network. It offers real-time notifications in the event of damage or loss of traffic signs. This not only enhances infrastructure-related applications but also contributes to the overall improvement of road safety for everyone.
• In January 2022, Mobileye, a company specializing in advanced driver assistance and autonomous driving and owned by Intel is one of the world's largest semiconductor chip manufacturers, unveiled the latest iteration of its EyeQ system-on-a-chip (SoC). This release was characterized as the most sophisticated system introduced by Mobileye to date and was officially announced at the 2022 Consumer Electronics Show held in Las Vegas in USA.
• In February 2021, Continental, a major automotive components manufacturer, has invested in Recogni, an AI chip startup based in Germany and the US. The increasing requirements for advanced processors are fueled by growing demands in connected vehicles, automation, and self-driving technologies

Acquisitions and Partnership

• As of December 31, 2022, Volvo Car AB, a company based in Sweden, declared that it had attained full ownership of Zenseact, its subsidiary focused on autonomous driving (AD) software development. Volvo Cars AB acquired the remaining 13.5% of Zenseact's shares from ECARX, making the AD software company a wholly-owned subsidiary of the Sweden-based automaker. Despite this acquisition, Zenseact will continue to function as an independent and standalone company, according to Volvo Cars AB.
• In April 2022, Qualcomm Incorporated, a company that creates semiconductors, software, and services related to wireless technology, finalized the acquisition of Arriver, a software company focused on sensor perception and drive policy, from SSW Partners (is the industry leader in engineered products for use in the refrigeration, cooking appliance, and HVAC markets). This acquisition strengthened Qualcomm Technologies' capacity to provide widespread, fully integrated, and competitive Advanced Driver Assistance System (ADAS) solutions to automakers and Tier-1 suppliers.
• In April 2021, Mobileye, and Udelv, a Silicon Valley venture-supported firm, revealed a collaboration where Mobileye's autonomous driving system, known as Mobileye Drive, will power the upcoming Udelv autonomous delivery vehicles named "Transporters." The partners aim to manufacture over 35,000 Mobileye-equipped Transporters by 2028, commencing commercial operations in 2023.

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

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Top Companies in the Traffic Sign Recognition System Market

• Continental AG
• Delphi (Phinia Inc.)
• Robert Bosch GmbH
• DENSO CORPORATION
• Toshiba
• Mobileye
• ZF Friedrichshafen AG
• Magna International Inc.
• Ford Motor Company
• Nissan Motor Co., Ltd
• The MathWorks, Inc.

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 (Light Detection and Ranging), and artificial intelligence.