OKI Project Phase 2

1
OKI Project Phase 2 Project Progress
Summary Department of Electrical and
Computer Engineering The Ohio State
University May 2004
2
Key Accomplishments

• Physical Layer Channel Modeling
• Investigated a modified two-ray model for
  line-of-sight condition, comparing vehicle
  rooftop vs. ground reflections 1
• Investigated a model for no line-of-sight
  condition 2
• Determined appropriate reflection coefficients
  15
• Wireless Simulators
• Improving original simulator to better represent
  wireless transmission behavior, including
  additional packet updates, packet retransmission,
  and a repeater at the intersection
• Enhanced data update logic
• Transmission every 10 meters, within 50 meters
  from intersection
• Packet retransmission for configurable number of
  attempts
• Given real-time limitations on simulator
  performance, developing a statistical wireless
  simulator for packet behavior under a variety of
  vehicle conditions
• Vehicle Traffic Simulator
• Improving simulator to allow user to select
  different simulation input parameters, such as
  vehicle density and throughput
• Developed graphical user interface to perform
  and monitor simulation

3
Physical Layer Channel Modeling Line-Of-Sight
Path 1
Considering a 2-path model, the received power is
mainly contributed by the direct path and single
reflection from a surface.
4
Physical Layer Channel Modeling Line-Of-Sight
Path 1
Simulation Results

• At short distances, the direct path and road
  reflection path have rapid phase shift, yielding
  the oscillations noted in the right-hand chart.
  The rooftop reflection, for the antenna height
  selected, yields a phase shift that smooths out
  the path loss. Further investigation is
  necessary to determine appropriate parameters
  (i.e., antenna height, reflection coefficient,
  etc.)
• There is a significant difference (40 dB)
  between the traditional model and the modified
  two-ray model further investigation is in
  progress to determine if the vehicle density can
  be leveraged to provide a more accurate
  approximation

5
Physical Layer Channel Modeling No
Line-Of-Sight Path 2
We use a Virtual Source (VS) to model
diffraction. (RX1 only)
Path loss (between RX1 and VS)
6
Non Real-Time Wireless Simulator
Input Parameters - Vehicle density - Vehicle
throughput
Wireless Simulator
Vehicle Traffic Simulator

• Trace files
• Vehicle information
• Vehicle position
• - Vehicle velocity

Physical layer model
Multiple scenarios with different input parameters

• Information collected from the multiple scenario
  executions will be the basis for Statistical
  Wireless Simulator

7
Statistical Wireless Simulator
Statistical Wireless Simulator
Vehicle density Vehicle positions Communication
protocol Protocol parameters
Vehicle Traffic Simulator
Packet Generator
Driver Behavior
Nodes that received packet Packet reception time
(request time packet length)

• The statistical wireless network simulator will
  allow real-time feedback to the vehicle traffic
  simulator. This, in turn, enables driver
  behavior to be modified by information from the
  wireless simulator.

8
Vehicle Traffic Simulator - Overview

• Warning System and Driver Behavior Model
• Human factors must be taken into consideration
  for developing an intelligent collision warning
  system (6,7,8,9).
• A viable collision warning system should satisfy
  the following
• 1. Reduce the collisions
• 2. Minimize the drivers attention load
• 3. Not to give out excessive warning signal
• 4. Not to distract the driver

9
Vehicle Traffic Simulator Warning System
Algorithm
Three Level Warning System Get Communication
Data Compute Route Contention If no Route
Contention No Warning Else Compute TTC and
TTA If TTC gt TTA Drivers Response Time (1.93 s
-2.53 s) If DecelerationgtTTA Deceleration No
Warning Else If Deceleration lt TTA
Deceleration Warning Level 1 Else If no
acceleration Warning Level 2 Else (acceleration)
Warning Level 3 Else No Warning

• Notes
• Drivers Response Time Initial Driver action
  was defined as the first action the subject
  performed after the incurring vehicle initiated
  movement. (Either begin to release the
  accelerator pedal or begin to steer as part of
  this measure) Data comes from actual experiments.
  10
• TTC In research on Traffic Conflicts
  Techniques, Time-To-Collision (TTC) has proven to
  be an effective measure for rating the severity
  of conflicts. 11 TTC is defined as "The time
  required for two vehicles to collide if they
  continue at their present speed and on the same
  path". In principle, the lower the TTC, the
  higher the risk of a collision has been
  (12,13).

10
Vehicle Traffic Simulator Driver Behavior Model
6, 10, 14

• Aggressive Driver
• Only response to Warning Level 3
• Initial accelerator release only
• Normal Driver
• Response to Both Warning Level 3 and Level 2
• Braking to Warning Level 3
• Decelerate slowly to Warning Level 2
• Conservative Driver
• Response to all the Warnings
• Braking to Warning Level 3 and Warning Level 2
• Decelerate quickly to Warning Level 1

11
Vehicle Traffic Simulator

• Simulation snapshot for left-turn signal scenario
• Indicates signal status
• Indicates last collision event

Parameter specification during simulation startup
12
Next Steps

• Physical Layer Modeling
• Develop received path loss simulation module for
  multiple input conditions (i.e. vehicle density
  and velocity)
• Wireless Network Simulator
• Integrate improved physical layer simulation
  module
• Generate statistical wireless simulator for
  multiple input conditions (i.e. vehicle density
  and velocity)
• Vehicle Traffic Simulator
• Develop Warning System using statistical data to
  interact with received packet information
• Develop driver behavior module to react warnings
  
• Determine impact of received information on
  driver behavior and collision avoidance
• Integrate statistical wireless network simulator
  for real-time feedback

13
References
1 Y. Oda, K. Tsunekawa and M. Hata, Advanced
LOS path-loss model in microcellular mobile
communications, IEEE Trans. Vehicular Techn.,
vol. 49, (6), Nov. 2000, pp. 2121 2125. 2
H.M. El-Sallabi, Fast path loss prediction by
using virtual source technique for urban
microcell, IEEE VTC 2000-Spring Tokyo, pp. 2183
2187. 3 T.C.W. Schenk, R.J.C. Bultitude, L.M.
Augustin, R.H. van Poppel and G. Brussaard,
Analysis of propagation loss in urban microcells
at 1.9GHz and 5.8GHz 4 V. Erceg, A.J. Rustako
Jr. and R.S. Roman, Diffraction around corners
and its effects on the microcell coverage area in
urban and suburban environments at 900MHz, 2GHz,
and 6GHz, IEEE Transactions on Vehicular
Technology, vol. 43, no. 3 pp. 762 766, Aug
1994. 5 H.L. Bertoni, W. Honcharenko, L.R.
Maciel, and H.H. Xia, UHF propagation prediction
for wireless personal communications, Proc.
IEEE, vol. 82, pp. 1333 1359, Sept. 1994. 6
Ronald Miller and Qingfeng Huang, An Adaptive
Peer-to-Peer Collision Warning System IEEE
VTC2002 7 John D. Lee, Michelle L. Ries,
Dannile V.McGehee, and Timothy L. Brown, Can
Collision Warning Systems Mitigate Distraction
Due to In-Vehicle Devices?, May 2000, NHTSA
http//www-nrd.nhtsa.dot.gov/departments/nrd-13/dr
iver-distraction/PDF/31.PDF 8 Mark Vollrath and
Ingo Totzke, In-Vehicle Communication and
Driving An attempt to Overcome their
Interference, June 2000 NHTSA http//www.psycholo
gie.uni-wuerzburg.de/methoden/forschung/vortraege/
vollrathtotzke_NHTSA_artikel.pdf 9 Louis
Tijerina, Issues in the Evaluation of Drive
Distraction Associated with In-vehicle
Information and Telecommunication Systems, May
2000,NHTSA http//www-nrd.nhtsa.dot.gov/department
s/nrd-13/driver-distraction/PDF/3.PDF 10 Daniel
V. McGehee, Timothy L. Brown Effect of Warning
Timing on Collision Avoidance Behavior in a
Stationary Lead Vehicle Scenario Transportation
Research Record 1803 paper No. 02-3746 11
Richard van der Horst Jeroen Hogema
TIME-TO-COLLISION AND COLLISION AVOIDANCE
SYSTEMS http//www.ictct.org/workshops/93-Salzbur
g/Horst.pdf 12 Delphi-Delco Electronic Systems
Automotive Collision Avoidance Systems (ACAS)
Program Final Report DOT HS 809 080 August 2000
http//www.nhtsa.dot.gov/people/injury/research/pu
b/ACAS/TOC.htm 13 Hayward, J.Ch. (1972). Near
miss determination through use of a scale of
danger. Report no.TTSC 7115, The Pennsylvania
State University, Pennsylvania. 14 Dariush,
B.   Fujimura, K.   A framework for driver
specific inference of danger at signalized
intersections Intelligent Transportation
Systems, 1999. Proceedings. 1999 IEEE/IEEJ/JSAI
International Conference 5-8 Oct. 1999 Tokyo
Japan On page(s) 195 200 15 W.C. Jakes Jr.,
Microwave Mobile Communication. New York Wiley,
1974