Path Planning for Autonomous Bus Driving in Urban Environments
This addresses the challenging problem of autonomous driving for large vehicles like buses in urban settings, which is incremental by building on existing path planning methods with domain-specific adaptations.
The paper tackles path planning for autonomous buses in urban environments by developing an optimization framework that uses a road-aligned vehicle model and novel approximations for collision avoidance, enabling buses to exploit curbs and overhangs for maneuvers, with simulations demonstrating applicability and benefits.
Driving in urban environments often presents difficult situations that require expert maneuvering of a vehicle. These situations become even more challenging when considering large vehicles, such as buses. We present a path planning framework that addresses the demanding driving task of buses in urban areas. The approach is formulated as an optimization problem using the road-aligned vehicle model. The road-aligned frame introduces a distortion on the vehicle body and obstacles, motivating the development of novel approximations that capture this distortion. These approximations allow for the formulation of safe and non-conservative collision avoidance constraints. Unlike other path planning approaches, our method exploits curbs and other sweepable regions, which a bus must often sweep over in order to manage certain maneuvers. Furthermore, it takes full advantage of the particular characteristics of buses, namely the overhangs, an elevated part of the vehicle chassis, that can sweep over curbs. Simulations are presented, showing the applicability and benefits of the proposed method.