Shaping the Future of Autonomous Mobility: Innovation in Quantum Sensing Technologies

Figure 5: Legal Status

The dataset includes 1,108 patent families filed in the past 20 years. A large majority remain active (86%), highlighting a relatively steady and ongoing innovation trend, which is expected for a field characterized by long development cycles. A smaller portion are dead (14%), suggesting natural lifecycle attrition.

The landscape contains a diverse mix of industrial and academic contributors. Industrial applicants (68%) represent a slightly larger share of the portfolio, indicating strong commercial interest in translating quantum sensing advances into practical applications for autonomous navigation.

Academic and research institutions (32%) also play a substantial and influential role, underscoring the scientific depth and foundational research supporting this technology. Their contribution is essential for advancing core principles and enabling long-term innovation.

This balanced distribution between industrial and academic actors reflects a maturing technological domain in which both applied innovation and fundamental research progress in parallel, reinforcing each other and driving sustained development. 

Figure 6: Core Concept Clusters in Quantum Sensing for AVs

The concept-cluster map shows that quantum sensing patents for autonomous systems cluster strongly around LiDAR, optical detection, and sensor data processing. Additional clusters reveal significant activity in drone and UAV platforms, along with enabling technologies such as navigation algorithms, artificial intelligence, and on-board data storage. Overall, the map highlights a landscape dominated by optical quantum sensing but deeply interconnected with autonomous navigation and AI-driven perception.

Figure 8: Top 20 Applicants by Legal Status ©Questel

The chart above highlights the top 20 patent assignees in quantum sensing technologies for autonomous vehicles (AVs), offering a clear view of the organizations shaping this emerging field.

• Seyond stands out as the leading player, with an impressive portfolio of 44 families (36 pending and 8 granted). The high share of pending patents indicates very recent and aggressive innovation, likely in areas such as quantum LiDAR and quantum-enhanced ranging, showing Seyond’s intention to secure early leadership in a fast-evolving domain. This pattern typically reflects a fast-growing R&D pipeline and a desire to secure early leadership in a nascent but disruptive domain.
• HERE Global follows with 26 families (17 granted), reflecting mature, validated technologies that may enhance positioning, mapping, and localization, key pillars of autonomous navigation.
• Major electronics companies, including Samsung Electronics, LG Electronics, Sony Semiconductor Solutions, and LG Innotek, also rank highly, supported by portfolios largely composed of granted patents. Their activity points to advancements in quantum photonics, quantum dot sensors, and chip-level integration, aimed at improving sensitivity and signal quality in AV sensing modules.
• Automotive and mobility leaders, including Waymo, Baidu, and Robert Bosch, show meaningful activity as well. Their focus is probably directed toward integrating quantum sensors into LiDAR, inertial measurement units (IMUs), and GNSS enhancement systems, in order to overcome limitations of classical sensing, like performance in adverse weather, drift, and signal interference.
• Several academic institutions, such as Harbin Engineering University, Beihang University, and Xidian University, play a strong role, reflecting intense research efforts in Asia. Their work often targets foundational technologies like quantum magnetometers and cold-atom interferometers.
• Meanwhile, companies known for classical LiDAR, such as Innoviz Technologies, Ouster, and Sense Photonics, are increasingly exploring quantum-enhanced approaches to push the boundaries of long-range detection and resolution.

Overall, the mix of industrial leaders, sensor manufacturers, AV pioneers, and research institutions reveals a dynamic and competitive innovation landscape, with quantum sensing rapidly emerging as a key enabler of higher-accuracy and more robust autonomous perception.

Figure 9: Top 10 Applicants Filing Trends ©Questel

The heatmap shows that patenting activity in quantum sensing for autonomous vehicles (AVs) is highly recent, with activity accelerating from 2016 and peaking between 2020 and 2023. Seyond stands out with a sharp surge from 2020 and a peak in 2022, confirming its role as a fast-growing innovator. HERE Global, Samsung Electronics, and Waymo display more gradual or intermittent activity, reflecting steady but targeted investment in quantum-enhanced mapping, photonics, and sensing integration. Chinese players such as Baidu and Harbin Engineering University show consistent filings since 2017, indicating strong academic and industrial engagement. Companies traditionally focused on classical LiDAR, Innoviz Technologies, Sense Photonics, and Ouster appear with sporadic entries, suggesting exploratory steps toward quantum-enhanced architectures. Overall, the heatmap reveals a young and rapidly accelerating innovative landscape, driven by recent entrants racing to secure early leadership in quantum sensing for AVs.

However, when focusing specifically on 2025, the landscape becomes much more fragmented. Although 172 patent families were filed that year, none of the main applicants contributed more than two filings (Harbin Engineering University). The majority of the activity instead comes from academic institutions such as Chandigarh University, Harbin Engineering University, Jiangsu University, NRI Institute of Technology, the State Grid Hubei Electric Power Research Institute, and the Inner Mongolia University of Technology. These actors typically file single, highly specialized patents and therefore do not appear among the Top 10 applicants, which explains why the year shows strong overall volume but very little concentration among leading players.

Figure 12: Leading Industrial Applicants and their Geographic Origins in Quantum-Sensing Patent Filing ©Questel

The data shows that the United States is the dominant origin of industrial patent activity, with multiple top-ranking companies such as SEYOND, Waymo, Ouster, Sense Photonics, Boeing, and LAZR, appearing prominently. South Korea, China, and Europe (notably Germany, the Netherlands, the UK, and Belgium) also contribute significantly, though with fewer high-volume applicants.

Overall, the distribution indicates that U.S. industrial players lead the global landscape, followed by strong contributions from East Asian companies (South Korea, China, Japan) and select European innovators. This geographic concentration suggests that quantum sensing for autonomous vehicles is primarily driven by industrial ecosystems with advanced automotive, semiconductor, and sensing-technology sectors.

Figure 13: Patent Portfolio Dynamics and Value Indicators of Leading Industrial Assignees

SEYOND stands out with a remarkably high velocity value (8.6), far surpassing all other players, indicating an exceptionally active and fast-moving patenting strategy. This suggests SEYOND is aggressively expanding its portfolio and pushing innovation at a pace unmatched in the dataset.

By contrast, most other companies show moderate to low velocity levels. HERE Global, Samsung Electronics, and Waymo maintain steady activity, while others, such as BAIDU, GLAS TRUST, and LAZR, show minimal recent expansion.

The velocity indicators suggest that some players, particularly SEYOND, are accelerating their patenting activity, while others maintain more stable or slower filing rates. Such differences may illustrate how innovation strategies are shifting across the LiDAR and autonomous-vehicle sector.

Figure 15: Temporal Patent Trends: UAVs vs. Self-Driving Cars & ADAS ©Questel

The temporal evolution of patent filings reveals a decisive divergence between UAV innovation and the self-driving car and the ADAS segment. Until 2015, both domains advanced at a comparable pace. But from 2016 onward, we can see a turning point in commercial drone adoption with the curves separating sharply. UAV-related patents accelerate faster, peaking around 2022 and maintaining strong momentum through 2025. In contrast, self-driving and ADAS technologies experience sharper volatility and a pronounced decline after 2022.

This widening gap is not accidental; it reflects structural differences in market readiness. UAVs benefited from early regulatory frameworks, clearer deployment pathways, and rapid commercialization across high-impact sectors such as agriculture, energy inspection, delivery logistics, and emergency response. These industries enabled iterative testing in controlled or semi-controlled airspaces, allowing autonomous capabilities to mature quickly.

Self-driving cars, by comparison, remain tightly constrained. The graph’s post-2022 drop illustrates stalled progress caused by complex safety validation, fragmented road regulations, and the persistent challenge of mass deployment in unpredictable urban environments. Even with ADAS bundled in, terrestrial autonomy fails to match UAV momentum.

Ultimately, as the graph visualizes, UAVs dominate because the sky offers fewer regulatory, infrastructural, and operational obstacles than the road. This divergence doesn’t just reflect the present state of innovation; it signals the trajectory of future autonomous markets, where aerial systems are positioned to lead the next wave of commercial adoption.