Cooperative side-by-side driving lets two mobility vehicles chat
Learning Side-by-Side Navigation for Personal Mobility Vehicles from Human Drivers
Robotics
Summary
Driving two personal mobility vehicles side by side is tricky because they need to stay close to chat but also avoid crashing. The authors created a method where each vehicle plans its path by thinking about the other’s movements, sharing only simple position info. They taught the system by watching people drive in pairs to mimic natural, safe behavior. Tests in computer simulations showed the vehicles can keep a comfortable conversation distance longer than humans do, while staying safe.
What this means in practice
- •For robotics system developers: Build two personal mobility robots that can move side-by-side for social interaction while avoiding obstacles safely.
- •For indoor transport operators: Improve paired automated transport vehicles to carry passengers through corridors maintaining safe, smooth rides and conversational distance.
Authors
Luis Yoichi Morales, Florent Ferreri
Abstract
This paper presents an approach to achieve side-by-side autonomous motion with a pair of personal mobility vehicles (PMVs). Given a global path, two PMVs plan cooperatively so as to hold a social formation that lets the passengers hold a conversation, while keeping the ride safe and smooth. Each vehicle runs its own sampling-based model-predictive planner; the planners exchange nothing but the odometry each vehicle could observe of the other, and the joint decision is expressed as a pair of utility matrices over pairs of candidate trajectories, resolved by a common rule. The behavioural parameters are fitted by inverse reinforcement learning from 409 minutes of driving by ten pairs of people in human-driven PMVs in an indoor environment, and the lanes the pair can use are derived offline from the corridor itself rather than fixed by hand. A safety layer the cost cannot override executes a move only if the vehicle can still brake clear, measured from its whole body, and a vehicle that is stuck reverses along its own path and continues. In closed-loop simulation over 24 runs in the conditions the drivers were recorded in and 24 in four generated obstacle layouts, no vehicle entered a wall or a cone. The pair holds conversational formation for 60.5 and 68.9 percent of the time among obstacles (anticlockwise and clockwise) and 81.2 and 91.5 percent in a clear aisle, against the drivers' 34.0 and 36.0 percent, and 52.9 and 56.0 percent, and it matches their speed. It keeps one lateral formation where the drivers alternated between a close diagonal and a wide abreast one, and it varies far less. Experimental results are based on a differential drive kinematic simulator running on ROS 2.