Smart Information for a Sustainable World True Adaptive Signal Control A Comparison of Alternatives Technical Paper # Presentation to the 18 th World Congress on Intelligent Transport Systems Technical Session 95 (TS95) Wednesday 19 October Oct. 2011

Authors Cary Vick, PE – Telvent Transportation (presenting) Farhad Pooran, PE, PhD - Telvent Transportation José Carlos Riveira Martinez - Telvent Trafico y Transporte 2

Purpose / Agenda Clarify definitions and capabilities of true adaptive signal control Urge selection of some type of advanced signal control We can do better with what we have It’s not just for research any more Summarize approach of available technologies / products Not a comprehensive review and comparison of results 3

Deployment of Adaptive Signal Control Technologies SCATS SCOOT ACSLite InSync RHODES OPAC LA ATCS State with Active ASCT State with Pending ASCT 4

Categories of Signal Control Definitions (USDOT / FHWA Traffic Signal Control Handbook (Gordon and Tighe)): Isolated Time Based Coordination Interconnected Control Traffic Adjusted Control Traffic Responsive Control Traffic Adaptive Control The primary differentiator for Traffic Adaptive Control is the use of a traffic flow model to predict demand and adapt timings to meet expected traffic flows 5

What is NOT Adaptive Control Traffic Responsive: Trigger plan or timing changes Volume Density: Modify parameters based on demand Off-line Optimization: Real time measurements trigger re-optimization of timing plans Central + Local Optimization: Real time measurements trigger re-optimization of selected timing parameters (off set) then local control applies and adjusts All approaches have value, but they are NOT adaptive signal control 6

Summary of ASCT Alternatives Function Control System ACS LiteInSyncLA ATCSOPACRHODE S SCATSSCOOTUTOPIAITACANAZTECQuicNet ActionP + R P (only) R ( only ) P + RPro-activeP + RR ( only ) R ( only ) ArchitectureDist. CentralDist.Central Simulation Model? Yes NoYes No Time Frame5–10 minPhase/ Cycle / 15 min. CyclePhase/ Cycle / 5 min. Sec by sec CycleCycle/ 5 min. 3 sec & Cycle 5 sec & Cycle 5–10 min OptimizationS / OS / C / O / PS S / C / O S S / C / O / PS S / PSS / C / O / PS S / C / O 7

8 Adaptive Traffic Signal Control Processes Offset Optimizer Split Optimizer Cycle Optimizer Offset weights Split weights Cycle weights Intersection control Platoon modeling VolumeOccupancy Traffic Engineer B A A + B A or B Expert Rules

Control Center Traffic Flow / Queue Model    Street Observer for Calibration Operator / Traffic Engineer Traffic data at detection ponts Intersection structure Mean travel time Queue lengths Exit flows Queue capacity Operations of Adaptive Signal Control Real Time Data Pro Active Timing Changes 9

Weighting Factors Apply Expert Rules to Adaptive Control Strategies ITACA Expert Rules System Usable range is -10 to +10 Positive weights apply importance to affected links Negative weights reduce importance of associated links 2 weighting parameters for each link (split and offset) 1 weighting parameter for each intersection (cycle) Can be adjusted in real time manually or by expert rules Each final weight may reflect adjustments by different sources If Then Until Route A is highly congested Reduce weight for Transversal Route B Intersection B20 has maximum queue 10

Cabinet OPAC Hardware Configuration Advanced Traffic Controllers OPAC Single Board Computer (local) Upstream Advance Detectors Single Board Computer (Linux OS) running OPAC software Traffic Signal Controller: Type 2070 or NEMA (TS1 / TS2) Force offs & Holds Detector Data 11

ACS-Lite Architecture 12 ACS-Lite Computer Communications Interface and/or NTCIP Translators NTCIP controllers or Proprietary protocol controllers Minimum 9600 baud Communications (serial or IP) NTCIP On-street Master (optional)

Advantages of Predictive Modeling Continuous adjustment to changing demand Pro-active timing changes Optimal use of available capacity Adjusts to incident conditions The primary differentiator for Traffic Adaptive Control is the use of a traffic flow model to predict demand and adapt timings to meet expected traffic flows 13

Cycle Length Adaptability 14 Incident Occurs

References: Stevanovic, Aleksandar, “Adaptive Traffic Control Systems: Domestic and Foreign State of Practice” NCHRP Synthesis 403, Transportation Research Board, Washington, DC, 2010 Gordon, Robert L, and Tighe, Warren “Traffic Control Systems Handbook.” Federal Highway Administration Report FHWA-HOP , Washington, DC, Gartner, N.H., F.J. Poorhan, and C.M. Andrews. “Implementations and Field Testing of the OPAC Adaptive Control Strategy in RT-TRACS.” TRB Paper No Presented at the 81st Annual Meeting of the Transportation Research Board, Washington, DC, Riveira Martínez, José Carlos. “The Road to ITACA”, internal white paper, Telvent, MacGowan, J., and I. J. Fullerton Development and testing of advanced control strategies in the urban traffic control system. Public Roads 43, no. 2, 3, and 4. 15

Smart Information for a Sustainable World Thank You Smart Information for a Sustainable World 19 Oct. 2011