1 / 15

A Stochastic Model of Platoon Formation in Traffic Flow

A Stochastic Model of Platoon Formation in Traffic Flow. USC/Information Sciences Institute K. Lerman and A. Galstyan USC M. Mataric and D. Goldberg TASK PI Meeting, Santa Fe, NM April 17-19 2001. Traffic on Automated Highways. Ordinary highway. Benefits increased safety

Download Presentation

A Stochastic Model of Platoon Formation in Traffic Flow

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. A Stochastic Model of Platoon Formation in Traffic Flow USC/Information Sciences Institute K. Lerman and A. Galstyan USC M. Mataric and D. Goldberg TASK PI Meeting, Santa Fe, NM April 17-19 2001

  2. Traffic on Automated Highways Ordinary highway • Benefits • increased safety • increased highway capacity Platoon formation on an automated highway

  3. Our Approach • Traffic as a MAS • each car is an agent with its own velocity • simple passing rules based on agent preference • distributed mechanism for platoon formation • MAS is a stochastic system • stochastic Master Equation describes the dynamics of platoons • study the solutions

  4. Traffic as a MAS • Car = agent • velocity vi drawn from a velocity distribution P0(v) • risk factorRi : agent’s aversion to passing • desire for safety (no passing) • desire to minimize travel time (passing) • Traffic = MAS • heterogeneous system (velocity distribution) • on- and off-ramps • distributed control – platoons arise from local interactions among cars

  5. Passing Rules • When a fast car (velocity vi) approaches a platoon (velocity vc), it • maintains its speed and passes the platoon with probability W • slows down and joins platoon with probability 1-W • Passing probability W • Q(x) is a step function • R is the same for all agents

  6. v1 vC vC v2 v2 vC vC Platoon Formation

  7. MAS as a Stochastic System Behavior of an individual agent in a MAS is very complex and has many influences: • external forces – may not be anticipated • noise – fluctuations and random events • other agents – with complex trajectories • probabilistic behavior – e.g. passing probability While the behavior of each agent is very complex, the collective behavior of a MAS is described very simply as a stochastic system.

  8. Physics-Based Models of Traffic Flow • Gas kinetics models • similarities between behavior of cars in traffic and molecules in dilute gases • state of the system given by distribution funct P(v,x,t) • Hydrodynamic models • can be derived from the gas kinetic approach • computationally more efficient • reproduce many of the observed traffic phenomena free flow, synchronous flow, stop & go traffic • valid at higher traffic densities

  9. Some Definitions Density of platoons of size m, velocity v Initial conditions: where P0(v) is the initial distribution of car velocities Car joins platoon at rate for v>v’ Individual cars enter and leave highway at rate g

  10. loss due to collisions merging of smaller platoons inflow of cars outflow of cars Master Equation for Platoon Formation Inflow and outflow drive the system into a steady state

  11. Average Platoon Size

  12. Platoon Size Distribution

  13. Steady State Car Velocity Distribution

  14. Conclusion • Platoons form through simple local interactions • Stochastic Master Equation describes the time evolution of the platoon distribution function • Study platoon formation mathematically But, • Does not take into account spatial inhomogeneities • Need a more realistic passing mechanism • effect of the passing lane

  15. Future work • Multi-lane model • for each lane i, Pmi(v,t) • Passing probability depends on density of cars in the other lane, and on platoon size • Microscopic simulations of the system • Particle hopping (stochastic cellular automata) • What are the parameters that optimize • average travel time • total flow

More Related