Guosheng: ADAS + Siasun Robot&Automation jointly drive rising LiDAR demand and cost reduction in resonance

Guosheng released a research report stating that the LiDAR industry is moving toward solid-state, digital, and high-channel-count designs, with leading manufacturers accelerating the launch of "thousand-line era" high-channel-count digital LiDAR. The rapid increase in intelligent driving penetration is creating enormous market space, and combined with embodied intelligence, warehousing and logistics, and other fields, LiDAR demand is growing rapidly. Leading manufacturers are simultaneously expanding second growth curves such as spatial cameras. Guosheng's main viewpoints are as follows: LiDAR is the core component of the intelligent driving perception layer, with high industry barriers As an environmental perception sensor that uses laser beams for scanning and ranging, LiDAR is widely used in the intelligent driving field due to its advantages of high precision, long-distance detection, and stable all-weather operation. By scanning method, it is divided into three categories: mechanical, semi-solid-state, and fully solid-state. Semi-solid-state strikes a balance between cost and performance and is currently the most mainstream choice for mass-produced vehicles. Industry barriers are multidimensional: on the technology side, it covers the entire industry chain from core chips and complete machine integration to supply chain coordination; on the capital side, R&D investment is high (leading manufacturers' annual R&D expenses are about RMB 600-800 million, with an R&D expense ratio of about 30%, and investment in a single 10,000-unit production line exceeds RMB 10 million), making it difficult for new entrants to break through. In terms of technology trends, the industry is moving toward solid-state, digital, and high-channel-count designs, with leading manufacturers accelerating the launch of "thousand-line era" high-channel-count digital LiDAR. Falling prices boost adoption, and the LiDAR market has broad space LiDAR costs have dropped from USD 80,000 per unit in 2016 to about RMB 1,800/USD 200 for mainstream products in 2025, achieving a leap from "exclusive to million-yuan luxury cars" to economy vehicles. High-level autonomous driving is accelerating penetration. According to China Insights Consultancy, by 2030, shipments of L2+ and above intelligent vehicles will approach 50 million units, with penetration rising to 54%. LiDAR installation rate and per-vehicle installation volume are rising simultaneously, and the industry benefits from the dual dividends of "more vehicles equipped" and "more units per vehicle." The global automotive LiDAR market is expected to grow from USD 1.2 billion in 2024 to USD 32.1 billion in 2030, with a compound growth rate of 70.4% from 2025 to 2030; the 905nm and 1550nm technology routes are developing in parallel. In addition, non-automotive applications such as Siasun Robot&Automation, warehousing and logistics, and weeding Siasun Robot&Automation have considerable space, further driving demand higher. Industry concentration is highly concentrated, and leading manufacturers have significant advantages LiDAR industry giants occupy advantageous positions through technological breakthroughs, large-scale production, and resource integration, forming an efficient market consolidation effect. In 2025, industry concentration further increased, with CR3 at 92.3%, up 5.8 pct year-on-year. Among them, Huawei Technologies' market share increased significantly, reaching 41.5% in 2025, up 14.1 pct from 2024; Hesai Technology's share was 33.8%, up 8.2 pct year-on-year. ROBOSENSE and SEYOND saw their shares contract somewhat, with SEYOND's market share falling from 13.4% in 2024 to 7.7% in 2025, still ranking fourth in the industry. LiDAR prices continue to decline, and products are developing toward miniaturization and low cost, high performance, and technology integration, with high-channel-count and digital products accelerating from implementation to vehicle deployment. Risk warnings: industry demand falling short of expectations, risks of raw material price fluctuations, and risks of intense industry competition.