/Interactive Ramp Merging Planning in Autonomous Driving: Multi-Merging Leading PGM

Interactive Ramp Merging Planning in Autonomous Driving: Multi-Merging Leading PGM

Chiyu Dong, John M. Dolan and Bakhtiar Litkouhi
Conference Paper, IEEE International Conference on Intelligent Transportation, pp. 2186-2191, October, 2017

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Cooperative driving behavior is essential for driving in traffic, especially for ramp merging, lane changing or navigating intersections. Autonomous vehicles should also manage these situations by behaving cooperatively and naturally. The challenge of cooperative driving is estimating other vehicles’ intentions. In this paper, we present a novel method to estimate other human-driven vehicles’ intentions with the aim of achieving a natural and amenable cooperative driving behavior, without using wireless communication. The new approach allows the autonomous vehicle to cooperate with multiple observable merging vehicles on the ramp with a leading vehicle ahead of the autonomous vehicle in the same
lane. To avoid calculating trajectories, simplify computation, and take advantage of mature Level-3 components, the new
method reacts to merging cars by determining a following target for an off-the-shelf distance keeping module (ACC)
which governs speed control of the autonomous vehicle. We train and evaluate the proposed model using real traffic data.
Results show that the new approach has a lower collision rate than previous methods and generates more human driver-like behaviors in terms of trajectory similarity and time-to-collision to leading vehicles.

Associated Lab - General Motors-Carnegie Mellon Autonomous Driving Collaborative Research Lab

BibTeX Reference
author = {Chiyu Dong and John M. Dolan and Bakhtiar Litkouhi},
title = {Interactive Ramp Merging Planning in Autonomous Driving: Multi-Merging Leading PGM},
booktitle = {IEEE International Conference on Intelligent Transportation},
year = {2017},
month = {October},
pages = {2186-2191},
keywords = {autonomous driving, behaviors, merging, probabilistic graphical model},