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On-Road Trajectory Planning for General Autonomous Driving with Enhanced Tunability

Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 302)

Abstract

In order to achieve smooth autonomous driving in real-life urban and highway environments, a motion planner must generate trajectories that are locally smooth and responsive (reactive), and at the same time, far-sighted and intelligent (deliberative). Prior approaches achieved both planning qualities for full-speed-range operations at a high computational cost. Moreover, the planning formulations were mostly a trajectory search problem based on a single weighted cost, which became hard to tune and highly scenario-constrained due to overfitting. In this paper, a pipelined (phased) framework with tunable planning modules is proposed for general on-road motion planning to reduce the computational overhead and improve the tunability of the planner.

Keywords

On-road motion planning Autonomous passenger vehicle 

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Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  1. 1.Electrical and Computer Engineering (ECE)Carnegie Mellon UniversityPittsburghUSA
  2. 2.ECE and Robotics Institute (CS)Carnegie Mellon UniversityPittsburghUSA
  3. 3.Research and DevelopmentGeneral MotorsWarrenUSA

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