Longitudinal Behavior Planning with Maneuver Prediction for Urban Driving

Master thesis (2018)

Authors

R.P. Willems Mechanical Engineering

Contributors

J. Alonso-Mora (supervisor 1)
R. Happee (supervisor 2)
P.P. Jonker (supervisor 2)
Faculty
Mechanical Engineering
Copyright: © 2018 Rick Willems
Autonomous driving Decision Making Model Predictive Control Intelligent Vehicles Behavior Planning
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Published Date

05-07-2018

Language

English

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Faculty

Mechanical Engineering

Abstract

One of the remaining challenges in the development of intelligent vehicles is the topic of behavior planning in urban scenarios. Based on perception of the environment around the intelligent vehicle, driving behavior has to be optimized to achieve a comfortable driving experience without sacrificing safety. This work covers the development of a novel longitudinal behavior planning method for an intelligent passenger vehicle in urban scenarios. A multi-layer situation analysis architecture consisting of localization, maneuver prediction and trajectory prediction is used to predict traffic object trajectories on urban intersections and roundabouts. A universal model predictive controller is developed to determine the optimal longitudinal acceleration behavior of the intelligent vehicle online in a variety of urban scenarios, based on the predicted trajectories. Real-time simulations show that the behavior planning method is able to maintain safe driving conditions with reasonable comfort during scenarios with varying traffic maneuvers.