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Ouster is pushing its BlueCity traffic platform deeper into connected-vehicle infrastructure, positioning 3D lidar as a roadside perception layer for advanced driver-assistance systems and vehicle-to-everything communication.
Ouster BlueCity can detect, classify, and track road users in three dimensions, then convert that information into standardized safety messages for connected vehicles and vulnerable road users. The goal is to give vehicles information they cannot reliably capture from onboard sensors alone, such as a pedestrian stepping out from behind a parked truck, a cyclist approaching from an occluded angle or a hazard forming beyond a driver’s line of sight.
The approach fits a broader shift in transportation infrastructure, from static traffic signals and isolated sensors toward intersections that observe road activity in real time and communicate directly with vehicles. Ouster outlined the V2X use case in a company post focused on how lidar-powered infrastructure can support safer roads as more vehicles adopt ADAS features.
How BlueCity Turns Intersections Into V2X Sensors
BlueCity combines Ouster’s digital lidar sensors with AI perception software and analytics to create what the company describes as a real-time 3D digital traffic twin of an intersection or corridor. Instead of relying only on 2D camera feeds, the system measures the position, speed, and trajectory of vehicles, pedestrians, and cyclists in 3D.
The spatial data matters for V2X because connected vehicles need reliable object-level information to act on a warning. A camera may identify a pedestrian in a frame, but Ouster argues that lidar’s 3D bounding boxes can more accurately locate a person, cyclist, or vehicle in physical space, which can reduce false positives and improve the quality of alerts sent to drivers or automated systems.
Once BlueCity detects and tracks road users, the data can be translated into established transportation safety messages. The platform supports SAE J2735 Basic Safety Messages for vehicles and Personal Safety Messages for pedestrians and cyclists, as well as the newer SAE J3224 sensor data sharing message, which can package information about multiple road users into a broader view of the scene.
A roadside unit can then broadcast those messages to connected vehicles or other road users equipped with compatible onboard units. In practice, that means a vehicle could receive a warning about a pedestrian entering a crosswalk, a cyclist approaching quickly, or another hazard before the object is visible to the driver or the vehicle’s own sensors.
Why Roadside Perception Matters for ADAS
ADAS features are increasingly common in new vehicles, but their performance is still constrained by what a car can sense from its own position. Onboard cameras, radar, and lidar can be blocked by large vehicles, corners, buildings, poor visibility, or complex intersection geometry. Roadside sensors offer a different vantage point, especially for vulnerable road users.
U.S. safety data shows pedestrian and cyclist deaths remain elevated compared with pre-pandemic levels. The Governors Highway Safety Association estimated 7,318 pedestrian fatalities in 2023, down from the prior year but still above 2019 levels, while cyclist deaths also rose in 2023.
Cities pursuing Vision Zero policies find that the same sensing layer can serve several functions at once. It can support signal actuation, safety analytics, near-miss detection, and long-term traffic planning while also feeding V2X warnings to connected vehicles. That makes the infrastructure case broader than a single driver-assistance use case.
The regulatory environment is also becoming more defined. In November 2024, the Federal Communications Commission adopted final rules for cellular vehicle-to-everything communication, giving transportation agencies and technology providers a clearer framework for C-V2X deployment in the 5.9 GHz band. That policy clarity could make roadside communication infrastructure easier for cities and vendors to plan around.
Chattanooga Shows the Deployment Model
Ouster’s clearest real-world example is in Chattanooga, Tennessee, where the city, the University of Tennessee at Chattanooga’s Center for Urban Informatics and Progress, Southern Lighting & Traffic Systems, and Ouster have worked on a lidar-enabled smart traffic network.
After an initial pilot, Chattanooga expanded BlueCity toward more than 120 intersections, covering a downtown smart corridor and using the system for traffic management, safety analysis and V2X applications. BlueCity is also deployed or contracted across hundreds of intersections globally, with deployments involving transportation agencies and municipalities.
Those deployments are important because infrastructure technology is often judged less by a lab demonstration than by whether agencies can install, maintain, and use it across ordinary intersections. BlueCity is designed for non-invasive installation, low maintenance, and integration with multiple roadside-unit vendors without custom API development.
The privacy model is also part of the pitch. Since lidar captures 3D spatial data rather than conventional video imagery, the system can provide traffic intelligence without collecting personally identifiable visual information in the same way camera-based systems can.
Smart Roads Become Part of the AI Infrastructure Stack
The BlueCity V2X push shows how physical AI is moving beyond robots and vehicles into the built environment. Instead of treating each car as a self-contained intelligence system, the model adds perception to the intersection itself and lets infrastructure share that information with connected vehicles.
It does not remove the need for onboard safety systems, but it gives them another source of context. Drivers get earlier warnings, and cities get a sensing layer that can improve signal timing, identify risky patterns, and support future connected-vehicle deployments from the same installation.
Ouster’s argument is that lidar-equipped intersections can become active safety nodes rather than passive traffic-control points. If cities continue to adopt V2X infrastructure, systems like BlueCity could help define how roadside AI perception is used to make connected mobility more aware of what individual vehicles cannot see on their own.
