EVALUATING THE SAFETY ASPECTS OF ADAPTIVE SIGNAL CONTROL SYSTEMS SPC Transportation Operations & Safety Forum October 27, 2016 Dr. Mark Magalotti and Zulqarnain H. Khattak MSCE Department of civil & Environmental engineering University of Pittsburgh
OUTLINE Background Literature Review Hypothesis Methodology Field Study Test Locations Statistical Evaluation (Empirical Bayes Method) Conclusion
Background Traffic demand Stops & delays Road Crashes
Background Adaptive Signals Review Advanced detectors Communicates on traffic conditions Algorithms optimize signal timings Considers opposing flows, approaches with high traffic volumes given priority
Literature Review Rhythm Engineering report on Safety No statistical evaluation but indicated safety benefits Illinois Department of Transportation No statistical evaluation on safety benefits ( found cost/benefit ratio and percent changes) Proposed to find CMF University of Virginia report on safety benefits of ASCT Calculated CMF but with limited after deployment period data (1 year only) Used only 1 type of system but didn t mention which one
Hypothesis Adaptive traffic signals have safety benefits Reduces the number of stops and travel time leading less aggressive driving Reduce road crashes thus saving precious human lives THESIS DEFENCE
Methodology Two type of approaches Field study of before and after deployment of an adaptive system GPS App to conduct travel runs Data analyzed for Stops, Travel time & Speed Empirical Bayes Method (Using Approach From Highway Safety Manual) to evaluate before and after crash data ( minimum 3 years of data) Safety Performance Functions (SPF) used to calculate expected crash frequency Expected crash frequency incorporated into observed crash frequency to find Crash modification factor (CMF)
Field Study Figure 1 Baum/Centre Avenue Surtrac Intersections for Travel time Runs
Field Study Baum and Centre Ave corridor with 23 intersections evaluated 9 travel runs conducted on each route with corridor and crossings Both in Eastbound and Westbound direction For both with and without Surtrac in Operation, AM: 8:00-9:00 Mid-day: 11:00-12:00 PM: 4:00-5:00
Field Study Figure-2 Corridor and Crossings GPS Tracks for and Travel Runs in both Eastbound & Westbound Direction
SPEED (MPH) Field Study Results Baum Travel Speed 20 18 16 14 12 10 8 6 4 2 0 AM MID-DAY PM
SPEED (MPH) Field Study Results Centre Ave Travel Speed 16 14 12 10 8 6 4 2 0 AM MID-DAY PM
NUMBER OF STOPS Field Study Results Baum Boulevard Number of Stops 9 8 7 6 5 4 3 2 1 0 AM MID-DAY PM
NUMBER OD STOPS Field Study Results Center Avenue Number of Stops 16 14 12 10 8 6 4 2 0 AM MID-DAY PM
TRAVEL TIME (SEC) Field Study Results Baum Travel Time 500 450 400 350 300 250 200 150 100 50 0 AM MID-DAY PM
TRAVEL TIME (SEC) Field Study Results Center Ave Travel Time 1000 900 800 700 600 500 400 300 200 100 0 AM MID-DAY PM
Field Study Results (Summary) Considerable decrease in number of stops with ASCT operation Travel time also reduced but in a few cases a little increase observed Speed also increased with ASCT operation
Empirical Bayes Safety Evaluation A rigorous and reliable method used to estimate CMFs recommended by HSM Used to estimate the expected long-term crash experience Replaces current method of ranking by crash rates No CMFs currently available for coordination of traffic signals Weighted average of the observed crashes (from crash reports) at the intersection of interest and the predicted crashes from an SPF.
Empirical Bayes Safety Evaluation
Site Selection and Data Collection List of intersections with ASCT Deployments from PennDOT ( on 2/4/15-204 intersections operating in Pennsylvania with 9 systems operational and 12 in planning) Date of Deployment & Types of System ( In-Sync, Centrac Adaptive, Surtrac and ACS Lite) Crash Data from PennDOT (7 years) (3 systems/ 42 intersections with 3 years minimum of before and after data) AADT from itms Website for particular years Used PennDOT growth rates to transform AADT from one period in time to another ( before & after periods)
Sites Selection for ASCT Crash Evaluation Allegheny County East Liberty Intersections, City of Pittsburgh Pennsylvania Montgomery County Intersections, Montgomery Township Pennsylvania
Site Selection for ASCT Crash Evaluation Montgomery County Upper Merion Intersections, Upper Marion Township Pennsylvania
Safety Performance Functions SPF s are regression equation used to predict the average number of crashes per year at a location as a function of exposure and, in some cases, roadway or intersection characteristics (e.g., number of lanes, traffic control, or median type). SPFs are developed using data from specific locations at a specific period in time and represent the average conditions for a given facility type. As such, it may be necessary to adjust the SPF through calibration to better reflect your local conditions or a different study period. The Highway Safety Manual identifies the base conditions for each SPF and provides applicable adjustment factors. National SPFs were used, no SPFs available currently for Pennsylvania
Safety Performance Functions Safety Performance Functions for Urban/Suburban Intersections Type Crash Safety Performance Functions Over-dispersion parameter (k) Signalized Signalized Signalized Signalized FI= Fatal +Injury Crashes K= Indicating statistical reliability of a particular SPF, Closer the value to zero, more reliable is the estimate
Deployment Period Calculations Number of Approaches with Left turn lanes Intersection type Traffic Control One Two Three Four 3 leg Minor road stop control 0.67 0.45 Traffic signal 0.93 0.86 0.80 4 leg Minor road stop control 0.73 0.53 Traffic signal 0.90 0.81 0.73 0.63
Deployment Period Calculations
Deployment Period Calculations r i = N predicted,a N predic ted,b
Crash Modification Factor
CMF Results Overall Crash Modification Factor Results for all Intersections Crash Severity Safety Measure (CMF) Std. Error Safety Effectiveness Total 0.66 0.043 34% FI 0.50 0.037 50%
CMF Results Crash Modification Factor Results for Surtrac and In-Sync Systems Separately Type Crash Severity Safety Measure (CMF) Std. Error Safety Effectiveness Surtrac Total 0.43 0.06 57% Surtrac FI 0.53 0.11 47% Insync Total 0.58 0.04 42% Insync FI 0.43 0.03 57%
CMF Results Crash Modification Factor Results for four & three legged Intersections (Insync & Surtrac Combined) Type Crash Severity Safety Measure (CMF) Std. Error Safety Effectiveness 4 legged Total 0.61 0.045 39% 4 legged FI 0.45 0.038 55% 3 legged Total 0.42 0.107 58% 3legged FI 0.27 0.035 73%
Safety Effectiveness/Standard Error Confidence Level from HSM Plot Showing 95% Confidence level for CMF 20 18 16 14 12 10 8 6 4 2 0 Combined Surtrac Insync 4 legged 3 legged Type Used for Developing CMF Total FI Plot Showing Confidence Level of CMF All values for safety effectiveness/ standard error>2 ; 95% confidence level
CMF 95% Confidence Interval 0.8 CMF for total Crashes with 95% Confidence Interval 0.7 0.6 0.5 0.4 0.3 0.2 0.1 0 Combined Surtrac Insync 4 legged 3 legged
CMF 95% Confidence Interval 0.8 CMF for Fatal & Injury Crashes with 95% Confidence Interval 0.7 0.6 0.5 0.4 0.3 0.2 0.1 0 Combined Surtrac Insync 4 legged 3 legged
Conclusion Adaptive traffic signals have safety benefits CMF lower than 1, indicates reduction in crashes Both total and fatal & injury crashes are reduced Both Surtrac & InSync systems reduce crashes
Future Research Local Safety Performance Functions Include Other types of ASCT Systems Study Human behavior in terms of human factors