Motion Planning for Multiple Autonomous Vehicles

Into an automated, cooperative, diverse and integrated futuristic transportation system

10th October, 2014Best PhD Award Presentation at ITSC, 2014

IIIT Allahabad

ROBOTICS AND ARTIFICIAL INTELLIGENCE LABORATORY

INDIAN INSTITUTE OF INFORMATION TECHNOLOGY, ALLAHABAD

Rahul Kala

Problem Solving in Mobile Robotics

rkala.inMotion Planning for Multiple Autonomous Vehicles

IIIT Allahabad

Organized

Image Courtesy: railway-technical.com, blogs.abc.net.au

Unorganized

Trajectory Generation

A

 

Static Obstacles

B

C

Select the best plan: (a) A overtakes B from right, B drifts left, A crosses the obstacles, C waits, (b) A follows B and both cross the obstacles while C waits, (c) B crosses the obstacles followed by C and A, (d) C crosses the obstacle a from its left, while A follows B to cross the others

a

rkala.inMotion Planning for Multiple Autonomous Vehicles

IIIT Allahabad

Trajectory Generation

rkala.inMotion Planning for Multiple Autonomous Vehicles

IIIT Allahabad

Algorithms

Sampling Based

Genetic Algorithms

RRT

RRT-Connect

Graph Search Based

Multi-Level Planning

Dynamic Distributed Lanes

ReactiveFuzzy Logic

Lateral Potential

Near-ReactiveElastic Strip

Logic Based Planning

Intelligent Management of the Transportation System

rkala.inMotion Planning for Multiple Autonomous Vehicles

IIIT Allahabad

Routing objective/

considerations

Routing frequency

Recurrent or non-recurrent

Traffic LightsLane change

Entirely semi-autonomous,

mixed, manual

Reservations

Intelligent Management of the Transportation System

rkala.inMotion Planning for Multiple Autonomous Vehicles

IIIT Allahabad

• Experiment new traffic behaviours • Traffic light, Dynamic Speed Lanes• Lane Booking, Road Booking• Density Regularization, Blockages, Re-routing

Dynamic Traffic

Management

• Non-recurrent traffic• City based scenario• Short frequent re-planning• Single lane overtakes• Density and Traffic Light avoidance

Congestion Avoidance

• Recurrent Traffic• Route and Start Time Determination• Maximize probability of reaching on time and

minimize wait time• Cooperative traffic lights and lane changes

Reaching Destination

before Deadline

The Thesis

rkala.inMotion Planning for Multiple Autonomous Vehicles

IIIT Allahabad

Videos

Presentations

Graphical Abstract

Key Contributio

ns

Website

Acknowledgements

Prof. Kevin Warwick

Indian Institute of Information Technology,

Allahabad

rkala.inMotion Planning for Multiple Autonomous Vehicles

IIIT Allahabad

Thank You

rkala.inMotion Planning for Multiple Autonomous Vehicles

IIIT Allahabad