Low-speed autonomy is the concept of low-speed autonomous vehicles (LSAV) that travel at slow speeds, designated as less than 35 miles per hour. The concept revolves around introducing autonomous vehicles to the public at low speeds in order to ease them into society, gain traffic and pedestrian data insight and improve safety in the meantime. Micromobility services, which consist of small, lightweight vehicles that operate at low speeds such as scooters, skateboards and bicycles, have also begun incorporating low-speed autonomy.
Low-speed shuttles have been a popular way to introduce autonomous vehicle technology into the public, with companies currently utilizing the slower moving robots to shuttle passengers and deliver packages. Lyft's self-driving vehicles have already carried over 100,000 customers (with an attendant) in Las Vegas, showing the public is receptive to utilizing the technology. Most of these services currently require an attendant to oversee the vehicle and act as a technology ambassador to passengers, although some services have managed to remove safety drivers from cars. Most LSAVs do not operate in weather like snow or rain, and seldom operate in mixed traffic.
Sidewalk Autonomous Delivery Robots (SADR) and low-speed shuttles utilize numerous sensors and systems to enable robot detection of humans and other obstacles. While the majority of these sensors are present in all current autonomous vehicles, lidar is the preferred method for computer vision in LSAVs because of its high effectiveness at detecting non-metal objects.
Safety is a key factor in low-speed autonomous vehicles, not only for passengers in the vehicles but more importantly pedestrians. Speed reduction allows more reaction time, for people and computer alike, and drastically reduces damage in case of incident. Due to delivery robots moving on sidewalks and walking paths, it is crucial to reduce the chance for a crashes and accident.
Lidar technology companies research, develop and offer technology used to measure distance ranging via laser light emission and reflection detection in order to enable computer vision. This technology's ability to detect objects and create 3D maps for computers to read makes it a practical solution for autonomous robots. While lidar is used in most current autonomous vehicles regardless of speed, it is heavily favored in LSAVs because of its ability to detect objects regardless of composition. This is compared to radar, which is better at detecting metal objects (cars), but not effective for vehicles which share spaces with humans such as sidewalks or walkways.
Lidar is only one of the technologies which are heavily implemented in the autonomous vehicle industry, which include radar and sonar sensors, GPS, computer vision, environmental imaging, and telematic and communication systems. These technologies are all present in the majority of autonomous vehicle technology systems, including them incurrent LSAVs as well.
