A Driving Behavior Planning and Trajectory Generation Method for Autonomous Electric Bus

• Published in: Future internet Vol. 10; no. 6; p. 51
• Main Authors: Yu, Lingli, Kong, Decheng, Yan, Xiaoxin
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 01-06-2018
• Subjects: Algorithms; Automation; autonomous electric bus; Autonomous vehicles; Behavior; Decision making; Decision trees; Finite state machines; high-precision map building; International conferences; Internet; Lane changing; Methods; Network analysis; path planning; Planning; Polynomials; Researchers; Robotics; Robots; trajectory generation; Trajectory planning; United States > US; China
• ISSN: 1999-5903; 1999-5903
• DOI: 10.3390/fi10060051

A framework of path planning for autonomous electric bus is presented. ArcGIS platform is utilized for map-building and global path planning. Firstly, a high-precision map is built based on GPS in ArcGIS for global planning. Then the global optimal path is obtained by network analysis tool in ArcGIS. To facilitate local planning, WGS-84 coordinates in the map are converted to local coordinates. Secondly, a double-layer finite state machine (FSM) is devised to plan driving behavior under different driving scenarios, such as structured driving, lane changing, turning, and so on. Besides, local optimal trajectory is generated by cubic polynomial, which takes full account of the safety and kinetics of the electric bus. Finally, the simulation results show that the framework is reliable and feasible for driving behavior planning and trajectory generation. Furthermore, its validity is proven with an autonomous bus platform 12 m in length.