DETERMINING THE ENVIRONMENTAL BENEFITS OF ADAPTIVE SIGNAL CONTROL SYSTEMS USING SIMULATION MODELS

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Swanson School of Engineering Civil and Environmental Engineering Civil and Environmental Engineering DETERMINING THE ENVIRONMENTAL BENEFITS OF ADAPTIVE SIGNAL CONTROL SYSTEMS USING SIMULATION MODELS Xin Wei October 5 th 2015 2015 MASITE Annual Meeting King of Prussia, PA 20 Mar 2015

Outline Background Methodology Testing Linking Conclusion 2 1/13/2016

Background Traffic demand Traffic stops and delay Traffic emissions Climate change and health damage 3 1/13/2016

Reduce Traffic Emissions Matters Civil and Environmental Engineering The situation allows of no delay 4 1/13/2016

Adaptive Traffic Control Systems 5 1/13/2016

How ATCSs work 6 1/13/2016

Hypothesis and Objectives Microsimulation develop a methodology to estimate emission reduction benefits by the installation of ATCS tested this methodology to use microsimulation models results of an operating ATCS system to estimate emission levels in a corridor Linking with other models established guidelines for linking emission and dispersion models to estimate emission levels at specific receptors in a corridor. 7 1/13/2016

Methodology Select a simulation model Build a Model Synchro Optimized Timing Data Optimizing for TOD Plan Input counting data from ATCS Inputting Data InSync Actual Timing Data Inputting ATCS Timing Calibration and validation based on ATCS s model Calibration Model Calibration and validation in field studies Running Simulation Compare & Evaluate Emission Results Running Simulation Future links to Emission & Dispersion Models 8 1/13/2016

Testing Test bed Microsimulation models Time of Day (TOD) Plans InSync Plans Simulation results 9 1/13/2016

Test bed: Route 19 corridor (Perry Highway), Wexford, PA 10 1/13/2016

Adaptive Traffic Control Systems InSync Adaptive Traffic Control System by Rhythm Engineering Wexford, PA 11 1/13/2016

12 1/13/2016

Microsimulation Models 13 1/13/2016

Time of Day (TOD) Plans Time of day Optimized plan 7:00-8:00 Plan 1 (AM) 8:00-9:00 9:00-10:00 10:00-11:00 11:00-12:00 12:00-13:00 13:00-14:00 14:00-15:00 15:00-16:00 16:00-17:00 17:00-18:00 18:00-19:00 Plan 2 (Mid-Day) Plan 3 (PM) The optimized Plans 1,2 and 3 can be developed in Synchro in such a way that these three traffic performance periods were optimized separately while setting the signal timing for the rest of the hourly network unaltered. 14 1/13/2016

InSync Plans http://rhythmtraffic.com/how-insync-works/the-insync-model/ 15 1/13/2016

Aggregation method for ATCS timings The mean green time of each phase was calculated and combined into a timing cycle with all-red and yellow period timing, which was used to define the timing profile required for the representative timing data. 16 1/13/2016

Aggregation method results Phase 1 2 4 5 6 8 Cycle Length (s) SBL NBT EBT NBL SBT WBT 1 SR19_NASH 7:00-8:00 0 135 5 5 131 5 152 2 SR19_Richard_Reichold 7:00-8:00 2 76 23 5 73 23 111 3 SR19_N_Meadows_Wexford_Plaza 7:00-8:00 4 91 13 0 95 13 111 4 SR19_Brooktree_Brooker 7:00-8:00 1 107 8 3 105 4 122 5 SR19_Wright_Pontiac 7:00-8:00 0 437 8 0 437 8 452 6 SR19_Brown_Rd 7:00-8:00 1 95 22 1 95 22 119 7 SR19_Bonnieview 7:00-8:00 0 411 7 2 409 7 425 8 SR19_NChapel_Manor 7:00-8:00 8 55 21 7 56 22 106 17 1/13/2016

Synchro/SimTraffic 18 1/13/2016

Time Space Diagram of TOD for 7-8 am 19 1/13/2016

Time Space Diagram of InSync for 7-8 am 20 1/13/2016

Emission results TOD Plans Total Emissions for 12-hour simulation 18:00-19:00 17:00-18:00 16:00-17:00 15:00-16:00 14:00-15:00 13:00-14:00 12:00-13:00 11:00-12:00 10:00-11:00 9:00-10:00 8:00-9:00 7:00-8:00-10000 10000 30000 50000 70000 90000 110000 TOD HC Emissions TOD CO Emissions TOD NOx Emissions 21 1/13/2016

Emission results InSync Plans Total Emissions for 12-hour simulation 18:00-19:00 17:00-18:00 16:00-17:00 15:00-16:00 14:00-15:00 13:00-14:00 12:00-13:00 11:00-12:00 10:00-11:00 9:00-10:00 8:00-9:00 7:00-8:00-10000 10000 30000 50000 70000 90000 110000 InSync HC Emissions InSync CO Emissions InSync NOx Emissions 22 1/13/2016

Comparison of Hydrocarbons (HC) emissions COMPARISON OF HC EMISSIONS 4000 12.00% 3500 10.00% 3000 2500 8.00% 2000 6.00% 1500 4.00% 1000 500 2.00% 0 7:00-8:00 8:00-9:00 9:00-10:00 10:00-11:00 11:00-12:00 12:00-13:00 13:00-14:00 14:00-15:00 15:00-16:00 16:00-17:00 17:00-18:00 18:00-19:00 TOD HC Emissions InSync HC Emissions Reduction percentage 0.00% 23 1/13/2016

Comparison of Carbon Monoxide (CO) emissions COMPARISON OF CO EMISSIONS 100000 90000 80000 70000 60000 50000 40000 30000 20000 10000 0 7:00-8:00 8:00-9:00 9:00-10:00 10:00-11:00 11:00-12:00 12:00-13:00 13:00-14:00 14:00-15:00 15:00-16:00 16:00-17:00 17:00-18:00 18:00-19:00 TOD CO Emissions InSync CO Emissions Reduction percentage 7.00% 6.00% 5.00% 4.00% 3.00% 2.00% 1.00% 0.00% 24 1/13/2016

Comparison of Nitrogen Oxide (Nox) emissions COMPARISON OF NOx EMISSIONS 12000 25.00% 10000 20.00% 8000 15.00% 6000 4000 10.00% 2000 5.00% 0 7:00-8:00 8:00-9:00 9:00-10:00 10:00-11:00 11:00-12:00 12:00-13:00 13:00-14:00 14:00-15:00 15:00-16:00 16:00-17:00 17:00-18:00 18:00-19:00 TOD NOx Emissions InSync NOx Emissions Reduction percentage 0.00% 25 1/13/2016

SPSS T-Test 26 1/13/2016

Paired t-test results For HC emissions, average t = 6.40, and p = 0.037; For CO emissions, average t = 13.12, and p = 0.017; For NOx emissions, average t = 10.11, and p = 0.019. Although moderate, these improvements, especially NOx emissions, are statistically significant from the SPSS paired t-test analysis. 27 1/13/2016

Linking models Microsimulation Models Pollutant level at specific receptor Vehicle trajectory Specific receptors Emission Models Emission Factors Dispersion Models 28 1/13/2016

Microsimulation Emissions Modeling Pairings Microsimulation Model AIMSUM INTEGRATION Paramics VISSIM TRANSIMS CORSIM Synchro/SimTraffic Emissions Model Versit+micro VT-Micro CMEM Versit PHEM MOVES TREMOVE COPERT (EEA) ModEM 29 1/13/2016

Microsimulation Emissions Dispersion Models traffic parameters meteorological parameters emission factor site position Dispersion Models 30 1/13/2016

Conclusion InSync Plans outperforms TOD Plans in environmental performance measures during a twelve hour test period by saving: 5.98% in HC emissions; 4.09% in CO emissions; 9.28% in NOx emissions. 31 1/13/2016

FUTURE RESEARCH Modelling Accuracy the calibration and validation of the Synchro model in this research was not determined, there were many assumptions and limitations. Representative Data Accuracy There needs to be other methods that can be applied by modeling the operations for individual cycles and inputting them to microsimulation models. Linking between Microsimulation Models and other Models this research was not sufficient to complete all the integration methods between microsimulation and other emission and dispersion models. 32 1/13/2016

Thanks for all you patience! Doubts, Queries & Suggestions 33 1/13/2016