Making Roads Safer for Everyone
Safety is hard to ensure both on the roads and for pedestrians. One step towards improving safety is by building safer infrastructure based on data. Data collection can be limited because of a lack of adequate equipment. Once sensors (e.g., LiDARs, cameras, radars) are installed, the city becomes “smarter and safer”. LiDAR can accelerate this digitization by providing a sensor that is resilient to weather and environmental conditions. It provides the high KPI that is necessary for planning, implementation, and navigation decisions that have lives at stake. Moreover, the data collected needs to be abide by privacy standards.
Corridor to the Future
In the case of US-based Sensagrate, the first generation of Innoviz's LiDARs was deployed in a “smart intersection corridor”. LiDARs were installed on existing infrastructure, and the InnovizOne’s point cloud, when combined with Sensagrate’s perception software and analytics, is used to gather data on traffic volume, near-miss collisions, counts of mobility objects, and other roadside safety metrics. The first generation of Innoviz LiDAR's high resolution and range specifications enable it to scan and analyze in a detailed way while abiding by privacy considerations (e.g., GDPR). The smart intersection corridor is a demonstration site for multiple concepts including smart sensing for intersections, V2X (vehicle-to-everything communication) between vehicles and infrastructure all empowered by edge computing.
LiDAR vs Other Sensors
LiDAR can provide accurate 3D detection and data during adverse weather and lighting conditions, whereas Innoviz’s robust build provides durability and relatively easy installation. In addition, while detecting objects with a fine resolution, LiDAR does not impinge on privacy concerns, making it a more compliant solution as compared to other sensors, which may have difficulty abiding by GDPR and other privacy laws. The LiDAR, point cloud, and analytics gather data, while promoting pedestrian, automobile, and other vulnerable road user safety by optimizing traffic design and flow. This is done by collecting data for root cause analysis of pedestrian-related incidents (or near-miss collisions) through intelligent data collection and predictive analytics.