www.gtri.gatech.edu

Wayne Daley, Principal Research Engineer, 404-407-8828, wayne.daley@gtri,gatech.edu

Colin Usher, Research Engineer II, 404-407-8833, colin.usher@gtri,gatech.edu

GTRI Aerospace, Transportation, & Advanced Systems Lab

Detection of Vehicle Occupants for HOV Lane Monitoring; Georgia Department of Transportation (GDOT) Research Project RP 11-06

Approach Sensing

Short integration time (200 micro seconds)

Near IR illumination

Optical filtering to reduce solar influence

Geometry chosen to view all seats

Optical trigger for vehicle detection

Installation

Site chosen with same geometry as HOT lanes

Access for testing and evaluation

Operation

System operated for 6 months

Varying weather conditions

For Further Information Contact

Project Objective

Development and evaluation of a system to monitor HOV/HOT lane

usage

Problem

Need to monitor HOV usage to optimize operational performance

Modifications in optical transmission properties of windshields

Developments on sensing technologies

Developments in software tools

Integration to provide a system with desired functionality

Algorithmic Approach Results

Test Site Vehicle in Rain

• Operated system for 2.5 months at test site • Demonstrates potential for performing screening monitoring

functions • False positives are the more significant source of error • Performance improves with training • Potential improvement by reducing the field of view • Multi-cameras enhances ability to see in cabin • Properties of glass changed/changing from earlier generation • Reduced optical penetration in some vehicles • Possibility to suggest standards for optical properties

0

10

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60

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400 600 800

Pe

rce

nt

Tran

smis

sio

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Wavelength (nanometers)

Windshield Transmission 3/5/2010 at Glass Doctor in Norcross)

DW01255_GBYLOF

DW01231 GGNPPG

FW02009 GBNPPG

FW02012 ZTNPPG

FW02734 GBNPLK

FW02371 GGN

DW01582GBNPPG

DW01224 GBNPPG

FW2158

Vechicle Detection Window Detection Occupant Detection Vechicle Detection Window Detection Occupant Detection 3D Occupant Detection

DATE TIME RANGE

# Faces

# Detected # FP

FN (# MISSED)

Face Detection Accuracy (%)

Total Accuracy (FP+FN)

10/19 12AM – 7:30AM 180 208 49 21 87.77778 61.11

10/19 3:47PM – 5:11PM 167 167 17 17 89.8204 79.64

10/26 12AM – 7:50AM 197 203 33 27 86.2944 69.54

10/26 5:36PM – 7PM 199 185 21 35 82.41 71.86

11/02 8:02PM – 12AM 211 200 24 41 83.4 69.19

11/09 4:15PM – 5:37PM 193 214 52 29 83.94 58.03

Average: 85.6067 68.22

One Occupant

DATE # Faces # Detected # FP # Missed Face

Detection

Accuracy

Total

Accuracy

(FP + FN)

10/19 160 163 8 5 96.88 91.875

10/26 172 167 5 10 94.19 91.28

Two Occupants

10/19 118 170 57 5 95.76 47.46

11/2 184 244 75 15 91.85 51.1

Three Plus

Occupants

10/19 – 11/16 295 369 96 22 92.54 60.0

10/20 – 11/17 435 435 41 41 90.57 81.15

10/18 – 11/15 153 162 28 19 87.58 69.28