Compare Helm.ai vs. MOVA

We provide licensing for AI software that spans the entire L2-L4 autonomous driving framework, which includes components like perception, intent modeling, path planning, and vehicle control. Our solutions achieve exceptional accuracy in perception and intent prediction, significantly enhancing the safety of autonomous driving systems. By leveraging unsupervised learning alongside mathematical modeling, we can harness vast datasets for improved performance, bypassing the limitations of supervised learning. These advancements lead to technologies that are remarkably more capital-efficient, resulting in a reduced development cost for our clients. Our offerings include Helm.ai's comprehensive scene vision-based semantic segmentation, integrated with Lidar SLAM outputs from Ouster. We facilitate L2+ autonomous driving capabilities with Helm.ai on highways 280, 92, and 101, which encompasses features such as lane-keeping and adaptive cruise control (ACC) lane changes. Additionally, Helm.ai excels in pedestrian segmentation, utilizing key-point prediction to enhance safety. This includes sophisticated pedestrian segmentation and accurate keypoint detection, even in challenging conditions like rain, where we address corner cases and integrate Lidar-vision fusion for optimal performance. Our full scene semantic segmentation also accounts for various road features, including botts dots and faded lane markings, ensuring reliability across diverse driving environments. Through continuous innovation, we aim to redefine the boundaries of what autonomous driving technology can achieve.

MOVA is engineered to address various traffic scenarios, spanning from minimal vehicle flows to heavily congested junctions. Primarily, it functions in a mode that minimizes delays prior to the onset of congestion; however, when any approach becomes excessively crowded, the system transitions to a mode focused on maximizing capacity. Furthermore, MOVA is versatile enough to manage a diverse array of junction types, ranging from straightforward ‘shuttle-working’ configurations to complex, multi-phase, multi-lane intersections. It is particularly beneficial at locations facing capacity challenges under Vehicle Actuated (VA) control, especially where congestion affects one or more approaches. Additionally, it facilitates the incorporation of pedestrian amenities or safer staging structures by providing the required additional capacity. Nearly all traffic signal authorities utilize MOVA, making it a standard requirement for new signal installations and significant upgrades on trunk roads. As a result, its adoption has become crucial in improving traffic management across various urban environments.