Date post: | 14-Jan-2015 |
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Evaluation of NDOR’s Active Advance Warning System
Laurence R. Rilett Ph.D., P.E.University of Nebraska-Lincoln
Presentation Outline
• Background• Analyses
– Safety– Operation– Simulation– Sensitivity
• Conclusions• Recommendations
Background• Dilemma Zone
– At the legal speed limit, the driver can neither clear the intersection before the end of the intergreen period nor stop without entering the intersection.
Background• Dilemma Zone: NDOR 2002 Report
– “Length of roadway in advance of the intersection wherein drivers may be indecisive or respond differently to the onset of the yellow indication.”
– Also known as “option zone” or “zone of indecision”
Background
• If an intersection is designed correctly (e.g. NDOR) a dilemma zone will not exist– Assuming deterministic system
• Vehicles same characteristics (accelerate, decelerate, weather, etc.)– Trucks/braking
• Drivers make the correct decisions– Stop, proceed
• Assuming: legal maneuvers (not running red light)
Potential Problems
• A major safety concern at high speed signalized intersections
Common Treatments
• Advance Warning (AW) Flashers– Flashing signal heads and warning signs
• Activated at predetermined time before end of green
• “Mixed” results regarding effectiveness
Common Treatments• Advance Detection (AD)
– Series of detectors in advance of intersection• Extend green on detection
– Effective in reducing crashes and conflicts– Increases likelihood of extending green to maximum
(max-out)• Dilemma zone protection is lost
NDOR’s Actuated Advance Warning (AAW) System • Combines advance detection and advance warning
– Single detector– Shorter maximum allowable headway– Lower frequency of max-out
Issues
• Results positive but mostly anecdotal• Guidelines for installation
– When do they need to be removed (if ever)?• Motivation for study
Part 1
Crash Data Analyses
Safety Effectiveness
• Test Sites– 26 treated intersections– 29 reference intersections
• “Similar” characteristics as treated intersections
• Provided by NDOR– 13 year of crash counts and AADT
• 1996-2008
Treated Intersections: Table 2.2
Simple example ignores regression to mean, changes in AADT…Need to compare to untreated intersections…
Safety Effectiveness
• Method– Full Bayes– Accounts for uncertainty in data– Generates a distribution of likely expected number of
crashes– Combines this distribution with site-specific crash
data to obtain expected crash frequency– Approach is complex but requires less data
Safety Effectiveness
• Crash Reduction Rate
Safety Effectiveness
• Model
Safety Effectiveness Results
Safety Effectiveness Results
Safety Effectiveness Results
Safety Effectiveness Results
Safety Effectiveness Results
Safety Effectiveness Results
Safety Effectiveness Results
Safety Effectiveness Results
Part 2
Operational Analyses
Operational Analyses
• Main Characteristics– Approach speeds– Acceleration/deceleration characteristics
• Following onset of yellow• During lead flash
– Frequency of max-outs– Rate of dilemma zone “entrapment”– Waiting time on conflicting phases
Study Site: Lincoln
• Highway 77 and Saltillo Road
Study Site: Omaha
• Highway 370 and N 132nd Street
Operational Analyses
• Data
Operational Analyses
• Max-out probabilities
Operational Analyses
• Waiting time on minor road
Operational Analyses
• Waiting time on minor road
Lincoln (Figure 3.13)
• Acceleration/deceleration- lead flash
Omaha
• Acceleration/deceleration- lead flash
Operational Analyses
• (Average) speed profile- lead flash
Operational Analyses
• Acceleration/deceleration- yellow
Operational Analyses • Acceleration/deceleration- yellow
Operational Analyses
• (Average) speed profile- yellow
Operational Analyses
• Vehicles in dilemma zone- yellow
Part 3
Microsimulation Analyses
Microsimulation Model
• VISSIM– Inputs: geometry, traffic counts, timing, speeds, etc.
• Calibration– Adjust model parameters such that field data
“matches” simulated data– Measures of performance
• Average waiting time• Speed profile
Microsimulation Model • GA Calibration Procedure
Microsimulation Model
• Calibration Results
Microsimulation Model
• Measures of performance– Average waiting time
Microsimulation Model
• Measures of performance– Speed profile
Sensitivity Analysis • Experimental Design
Sensitivity Analysis
• Simulation runs– 480 total factor combinations– 1-hour simulation run for each– 10 replications each
• Output– Waiting times– Number of conflicts
Sensitivity Analysis
• Effect of turn percentage– On average waiting times
Conclusions
• Safety effects– Greater than 90% probability that installation of
system is beneficial• Operational effects
– Lower than expected number of vehicles in dilemma zone
– Low max-out probabilities– System seems to work well
Conclusions
• Simulation model– Developed framework for modeling system– Successfully applied to two sites
• Sensitivity analysis – Site specific– Can be used to perform sensitivity analyses
Recommendations
• System worth considering at other high-speed signalized intersections– From a safety perspective
• Guidelines regarding installation– McCoy and Pesti (2002)
• Guidelines regarding removal– Simulation study
• Max out, delay, etc.
Slide design © 2009, Mid-America Transportation Center. All rights reserved.
Dr. Laurence Rilett, Ph.D., P.E. University of Nebraska-Lincoln
CREDITS