Authors:
Lamia Iftekhar
and
Reza Olfati-Saber
Affiliation:
Dartmouth College, United States
Keyword(s):
Cyber-physical Systems, Autonomous Driving, Flocking Algorithms, Intelligent Transportation Systems.
Related
Ontology
Subjects/Areas/Topics:
Distributed Control Systems
;
Informatics in Control, Automation and Robotics
;
Intelligent Control Systems and Optimization
;
Intelligent Transportation Technologies and Systems
;
Mobile Robots and Autonomous Systems
;
Modeling, Simulation and Architectures
;
Network Robotics
;
Robotics and Automation
Abstract:
In this paper, we introduce cooperative autonomous driving algorithms for vehicular networks in urban environments
that take human safety into account and are capable of performing vehicle-to-vehicle (V2V) and
vehicle-to-pedestrian (V2P) collision avoidance. We argue that “flocks” are multi-agent models of vehicular
traffic on roads and propose novel autonomous driving architectures for cyber-physical vehicles capable of
performing autonomous driving tasks such as lane-driving, lane-changing, braking, passing, and making turns.
These autonomous driving algorithms are inspired by the flocking theory of Olfati-Saber (Olfati-Saber, 2006),
though, there are notable differences between autonomous driving on urban roads and flocking behavior—
flocks have a single desired destination whereas most drivers on road do not share the same destination. We
demonstrate that lane-driving for a vehicular network with n > 3 vehicles cannot necessarily be performed
using pairwise vehicular interactions
and might require triangular interactions among triplets of vehicles. The
self-driving vehicles in our framework turn out to be nonlinear switching systems with discrete states that are
related to the driving modes of the vehicles. Complex driving maneuvers can be performed using a sequence
of mode switchings. We present several examples of driving tasks that can be effectively performed using our
proposed driving algorithms.
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