Post on 04-Jan-2016
description
Test Intersection: Status, Results, Preparation for State Data Collection
Lee AlexanderPi-Ming Cheng Alec GorjestaniArvind Menon
Craig ShankwitzIntelligent Vehicles LabUniversity of Minnesota
Presentation
System Overview Test Intersection Status
Construction Sensing Data collection Analysis
Examples of Data Collected Animations Video
Database status Installation in partner states
Design Documents Cost
System Overview
Mainline surveillance Radar based sensing Provides position, speed, lane assignment, and time to
intersection of each sensed vehicle Minor Road Surveillance
Laser based system provides “profile” of stopped vehicle Used for data analysis, timing of warnings (when DII deployed)
Crossroads Surveillance Used to capture driver behavior (one step or two) NOT part of deployed IDS system
Computation Acquires driver behavior data now Compute warning timing when IDS deployed
Central Processor
Wired/WirelessCommunication
Wired/WirelessCommunication
Wired/WirelessCommunication
DII
Vehicle waiting toenter traffic stream
Vehicle/DriverClassification
System
Weather/RoadCondition Sensor
DII
Vehicle waiting toenter traffic stream
Wired/WirelessCommunication
Transceiver
Wired/WirelessCommunication
Wired/WirelessCommunication
Wired/WirelessCommunication
Wired/WirelessCommunication
Radar SensorsBoth Directions of Major Road
(400 ft. range per sensor5 sensors per leg typical
Construction - Mainline
Construction - Mainline
Construction- Vehicle Classification
Construction – Crossroads Surveillance
Construction- Control Cabinet
Test Intersection Status
Mainline surveillance Construction Complete All sensors operational Series of Validation Experiments Complete
Mainline System Performance Results
Detection Rate: 99.990% (5 “misses” out of 51,942) Miss defined as vehicle not
within 40 meters of test zone Results for a single sensor;
multiple sensors decrease likelihood of a “miss”
Camera
Radar
Retro-reflectiveLaser
Mainline System Performance Results
Lane Data Accuracy Longitudinal Accuracy 8 meters Lane assignment accuracy 90%
• Ambiguity during lane changes, hanging near center line
• Limitations of angular resolution of radar Speed accurate to 1 MPH
ID 144 ID 225
DGPS-ProbeVehicle
ID 169
Mainline System Performance Results
Vehicle Shadowing
X
Performance: Range accuracy will be no worse than 75 feet if lateral shadowing occurs
Performance: Can resolve 2 vehicles if separated by 50 or more feet
Vehicle Classification Validation Configuration
DGPS
HorizontalLaser
Vertical Laser
VehicleClassifying
RadarLaserPresenceDetector
Camera
Vehicle Classification Performance
Accuracy approximately 85% based on vehicle height One sensor reduces cost substantially
Grouping conservative….classify as larger than actual
Vehicle Classification: Height Only
CarsLt. Truck
SUV
Med.Truck
Semi.Truck
Crossroads Surveillance
Positions based on locating front of vehicle Working definition of gap Accuracy 1-2 meters Larger concern 1 step or 2, time in crossroads
Performance Left turns sensed, captured correctly 95% of time Right turns sensed, captured correctly 95% of time
Open Issue Straight through captured only 60% right now Camera issues
• Absolute vs. Relative thresholds (being tested today/tonight)• IR Illuminators
Cheaper ($2k system vs. $26K system) We control illumination
Crossroads Trajectory Tracker Validation: Day with Visible Light
Camera
Crossroads Trajectory Tracker Validation: Night with IR Camera
Crossroads Trajectory Tracker Validation: Night with IR Camera
Intersection Surveillance System:Visualization of all Data
Data Collection: Visualization
iDAQ
TrackerSensor
Collector
Removable Hard Drive
TrackedTargets
DataGap Data
RawSensorData
SensorStatusData
Database"friendly" ASCII
files
Collects datafrom all
intersectionsensors
Kalman filterbased trackingof all vehiclesin intersection
Intersection DataAcquisition
System
Hard driveremoved everytwo weeks andtake by courrierto the Intelligent
Vehicles Lab
Data Acquisition – Control Cabinet
Removable Hard Drive
Tracked
Targets
Table
Gap
Data
Table
Raw
Sensor
Table
Sensor
Status
Table
Hwy 52Database
ARWIS
Weather
Table
Batch program copies datafrom removable hard driveand inserts into database
stored on Terrabyte server
Data Acquisition – IV Lab Data Flow/Archival
Batch program finds vehicles enteringintersection from minor road (Vehicles ofInterest (VOI) ) and consolidates tracking
information to new table
120 Gbyte IDE Drive requires replacement once every 2 weeks. DOT will have to dispatch someone to swap out to mail to U of MN.
Data Acquisition – IV Lab Analysis Processes
Tracked
Targets
Table
Gap
Data
Table
Raw
Sensor
Table
Sensor
Status
Table
Hwy 52Database
ARWIS
Weather
Table
VOI
Intermetiary
Results
Table
Selected
Gaps
Table
Results File
GUI program takes user input of desireddata, queries the database and creates
table of gaps selected by drivers on minorroad. Produces file with compiled results.
QueryProgram
Batch program finds vehicles entering intersection from minor road (Vehicles of Interest (VOI) ) and consolidates tracking information to new table
User specified queries
User specified results
Data Acquisition and Analysis
Database system has been design Initial automated queries have been completed. Will be validating results next two weeks Automated and specialized queries supported
Automated queries (can be run as frequently as desired).
Gaps as a function of vehicle classification Gaps as a function of time of day Gaps for Right, Straight, Left turns Percentages of one step vs. two step
maneuver Identification of near misses/accidents Other queries supported as well.
Add license plate reader, further refine data set.
Data Analysis – cont’d
Weird Observational Data For every 100 Right turns,
• 100 Straight-throughs• 5 left turns
2 drivers have missed intersection approaching from west, none have missed from right
• Both crashes, damages could have been much worse.• Last crash, no sensor damage, just mount damage
Can we build one for you?
FLASHBACK!Intersection Build Details from AP 2004
•Radar Stations •Vehicle Classification Stations•Vision Systems•Central Cabinet•Ethernet and Video Cable
$191,837
Cost Data
Electrical Contractor: $101K Bought guys lunch last week in Cannon Falls, must be happy Rethinking Laser for Vehicle Classification Two Crash repairs:
• #1, $2500
• #2, $800
MN vs. Partner States Cost
Minnesota Radar Subsystem: $50K Video (Xroads): $70K Minor Roads: $48K Cabling (Power and Data):
$10k
Grand total (Contractor + HW): $314K
Partner States Radar Subsystem: $50K Video (Xroads): $35K
• 2 masts, not 4• SDRC with IR Illumination,
not IR Cam. Minor Roads: $35K (2 lasers,
not 4) Cabling (Power and Data):
$10k Computer Assy, parts
procurement: $20K Estimated total
(Contractor+HW): $275K
Build one for you?
Final Reports due 28 Feb 2005 Master Design Document will be appendix Can make available to states who wish to
review/help them make decision to install equipment.