Self-Driving Shuttle navigates 100% without human input.
It can detect surroundings by using a variety of techniques such as radar, Lidar, GPS, odometry, and computer vision. Sensory system as "eyes", provide driverless bus ability to identify appropriate navigation paths, as well as obstacles and relevant signage. Computer, which so-called "brain", allows connection of diverse subsystems involving sensor, positioning, navigation, locomotion, motion control, energy and communication. The system allows vehicle to recognize, analyze, and operate automatically, enabling shuttles to execute obstacle avoidance, passing, overtaking and giving way, which is believed to enhance the transporting efficiency and safety.
Nowadays, the applications of Driverless Shuttle Bus is often at closed-circuits areas, private or public sites, such as airports, industrial sites, theme parks, hospitals, convention centers, university campuses etc. Following the evolution of public transportation, another potential application of Self-Driving Shuttle is for GRT (Group Rapid Transit), an automated transit system with an exclusive right-of-way, providing a shared ride for 6 to 30 passengers per vehicle.
Above multiple applications, Self-Driving Shuttle's utilization in city center is highly recognized and emphasized. During rush hour, the shuttles run according to fixed route every three minutes at all stations; while in off-peak hours, shuttles support on demand service through APP ordering. This kind of fleet management system provide convenient, green, low-cost, even flexible traffic network.
The utilization of Self-Driving Shuttle is expected to create a shared transportation for the first and last mile, ameliorate traffic condition in remote areas, and provide another transport method for the elder, inconvenience, and women with children, framing a safe and intelligent traffic setting.
Current: Door-to-Door Challenge
Future: First Mile & Last Mile Transportation