Dynamic distributed lanes: motion planning for multiple autonomous vehicles

Rahul Kala, Kevin warwick

Research output: Contribution to journalArticle

6 Citations (Scopus)
45 Downloads (Pure)


Unorganized traffic is a generalized form of travel wherein vehicles do not adhere to any predefined lanes and can travel in-between lanes. Such travel is visible in a number of countries e.g. India, wherein it enables a higher traffic bandwidth, more overtaking and more efficient travel. These advantages are visible when the vehicles vary considerably in size and speed, in the absence of which the predefined lanes are near-optimal. Motion planning for multiple autonomous vehicles in unorganized traffic deals with deciding on the manner in which every vehicle travels, ensuring no collision either with each other or with static obstacles. In this paper the notion of predefined lanes is generalized to model unorganized travel for the purpose of planning vehicles travel. A uniform cost search is used for finding the optimal motion strategy of a vehicle, amidst the known travel plans of the other vehicles. The aim is to maximize the separation between the vehicles and static obstacles. The search is responsible for defining an optimal lane distribution among vehicles in the planning scenario. Clothoid curves are used for maintaining a lane or changing lanes. Experiments are performed by simulation over a set of challenging scenarios with a complex grid of obstacles. Additionally behaviours of overtaking, waiting for a vehicle to cross and following another vehicle are exhibited.
Original languageEnglish
Pages (from-to)260-281
JournalApplied Intelligence
Issue number1
Publication statusPublished - Jul 2014

Bibliographical note

The final publication is available at Springer via http://dx.doi.org/10.1007/s10489-014-0517-1


  • Autonomous vehicles · Robotics · Graph
  • search · Planning · Multi-robot path planning ·
  • Multi-robotic systems


Dive into the research topics of 'Dynamic distributed lanes: motion planning for multiple autonomous vehicles'. Together they form a unique fingerprint.

Cite this