A Traffic Chaos Reduction Approach for Emergency Scenarios

A Traffic Chaos Reduction Approach for Emergency Scenarios Syed R. Rizvi † , Stephan Olariu † , Mona E. Rizvi ‡ , and Michele C. Weigle † † Department of Computer Science, Old Dominion University, Norfolk, VA ‡ Department of Computer Science, Norfolk State University, Norfolk, VA NetCri’07 The First International Workshop on Research Challenges in Next Generation Networks for First Responders and Critical Infrastructures April 13th, 2007

Problems Addressed
Traffic chaos caused by presence of emergency vehicles
sirens
increased accidents for emergency personnel
Traffic chaos caused by large-scale evacuations
resource availability
contraflow

Our Approach
Efficient chaos-reducing information dissemination approach
targeted towards first responders and evacuations
using a vehicular ad-hoc network (VANET)
Provide emergency vehicle path-clearing technique
Provide real-time resource availability information

Assumptions
All vehicles act as information servers relaying information for the VANET.
No location servers or access points on the roadside.
Every vehicle has a navigation system, which plans its route and knows its current location.

Building Blocks
Resources : emergency service vehicles (ESVs), gas stations, hospitals, shelters, etc.
Reports : information sent by resources
Dissemination: wireless broadcast
Selection strategies: based on spatial relevance

ESV Route Traffic Chaos Reduction Approach
The ESV periodically broadcasts a report containing:
unique ID of ESV
type of ESV
start and end points
route code
tentative average speed of ESV along route
current ESV location and time
timestamp of report sent by the ESV

Clearing Time Computation
Each vehicle in the path computes the time to intersection with the ESV based on the average ESV speed, ESV location, and current time
Driver should give way to ESV between 30-60 seconds before intersection time

Report Selection Strategy
The relevance of a resource report is calculated through a relevance function
time report was sent
distance from the ESV
speed of the ESV
Periodically, reports in a vehicle’s database are sorted according to relevance
Most relevant report is used for computing clearing time and is broadcast to neighbors

ESV Route Code Connecticut Ave, Point P {px,py} Point R {rx,ry} Street Code: 13 Street Code: 14 Street Code: 15 Street Code: 12 Street Code: M Street Code: N Street Code: O Street Code: P Street Code: cnt Start {sx,sy} End {dx,dy} {(sx,sy)/cnt, (px,py)/O, (rx,ry)/15, (dx,dy)}

Evacuation Traffic Chaos Reduction Approach
Resources (gas stations, shelters, hospitals) periodically broadcast reports
type of resource
availability of resource
location
timestamp of report
Reports updated as availability changes
Information filtered for relevance according to vehicle’s location

ESV Simulation Model
Written in
use of multiple threads for traffic generation, automobiles and ESVs.
Mobility model
nodes move in piecewise linear fashion, following city streets.

Simulation Parameters

Simulation Results
Data success rate
ratio of number of vehicles on ESV route that receive the message in time to clear the path to the total number of vehicles on the ESV route
As expected, increasing the density of vehicles, improves the success rate
Vehicular Density (vehicles/km 2 ) Data Success Rate

Conclusion
Traffic Chaos Reduction Approach for Emergency Scenarios
emergency service vehicle path-clearing
evacuation resource availability
Future Work
improve simulation/mobility model
investigate bandwidth usage
investigate security issues

Department of Computer Science
Old Dominion University
Norfolk, Virginia
VANET Research Group
http://www.cs.odu.edu/~vanet
Department of Computer Science
Norfolk State University
Norfolk, Virginia

A Traffic Chaos Reduction Approach for Emergency Scenarios

by Michele Weigle on Aug 19, 2010

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