Longitudinal Behavior Planning with Maneuver Prediction for Urban Driving

Longitudinal Behavior Planning with Maneuver Prediction for Urban Driving

Willems, Rick (TU Delft Mechanical, Maritime and Materials Engineering; TU Delft Biomechanical Engineering)

Alonso Mora, Javier (mentor)
Happee, Riender (graduation committee)
Jonker, Pieter (graduation committee)

Delft University of Technology

2018-07-05

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.

Behavior Planning
Decision Making
Model Predictive Control
Intelligent Vehicles
Autonomous driving

http://resolver.tudelft.nl/uuid:57f9a5f4-0608-42ca-b956-346afe5e4b7d

Student theses

master thesis

© 2018 Rick Willems