Yellowhead Trail ITS Simulation Laboratory and Edmonton ShowcasePresented at the 2011 TAC meeting Craig Walbaum, M. Sc., P. EngDirector Traffic Engineering City of Edmonton

Thomas Bauer, MS, PE, PTOECOO Mygistics, Inc.

Presentation Agenda Background Project Overview System Architecture System Overview Live Demonstration Results Discussion

Background

City of Edmonton Capital City of the province of Alberta 780,000 city population; 1,155,000 metropolitan population 53 degrees latitude City area 684.37 sq. km Population density 1067/sq. km West Edmonton Mall is the largest mall in North America (Worlds largest until 2004, currently 4th)

Current Situation City of Edmonton Transportation Master Plan focused on mode shift to modes other than auto Infrastructure funding predominantly allocated to transit projects such as LRT extensions and new LRT lines No funding for building additional roadway capacity in the form of roadway widening or interchanges Goods and services movement is highest priority but limited to increased efficiency of existing roadways ITS is the only effective way of dealing with these conditions

City ITS Programs ~$10M spent on ITS infrastructure Traffic signal systems Vehicle detection Cameras Dynamic Message Signs (DMS)

Provides information to the Traffic Management Centre and the driver about what has happened or is happening. Response to current conditions is not quick enough to effectively deal with current and upcoming conditions.

Overall ITS VisionCooperative System with Circular Data FlowIntelligent Infrastructure

Smart Vehicle and Travelers

Model-based Decision Support optimizing traffic control (signals, dynamic lane control, DMS, etc.) to best support current and predicted traffic Personalized Route Advisories providing individual paths to motorists to optimally distribute current traffic over the available roadway infrastructure Operational Awareness where Traffic Management and Traveler Information share same knowledge and are consistent in their reaction (i.e., detour advice is coupled with signals optimized for detour traffic)

The Future Becoming Now

Artist Impression of Future ITS System (Source: Museum of American History, Washington, DC)

ITS Roadmap Traffic Count Management VISUM Operational Traffic Model OPTIMA + Adaptive Signal Control Laboratory OPTIMA + Adaptive Signal Control Model-Based Decision Support Other Peripheral Subsystems MyTIS Traveler Information System Cooperative Services

Project Overview

Project Description Model-based incident response system Real-time traffic simulation model (OPTIMA) Based on offline DTA model (VISUM) Fused with real-time data feeds (simulated by VISSIM) Volume/speed (detectors), signal timing (signal controllers), DMS advisory text

Models current traffic conditions and short-term forecast (30 min horizon)

Project Description Real-time adaptive traffic signal control Optimizes cycle/split/offsets based on 5 min traffic forecasts (BALANCE) Continuous local optimization fine-tuning in 1 sec increments (EPICS) Implemented in VISSIM simulation (D4) Incident alerts DMS advisory text selection Adaptive signal control settings

User interaction

How Does It Fit into the ITS Roadmap? Traffic Count Management VISUM Operational Traffic Model OPTIMA + Adaptive Signal Control Laboratory OPTIMA + Adaptive Signal Control Model-Based Decision Support Other Peripheral Subsystems MyTIS Traveler Information System Cooperative Services

Project Objectives Develop an ITS Simulation Laboratory Test and demonstrate data flow From the new detection equipment Processing into information broadcasted to the motorists using the new DMS signs Including any expected traffic diversion Develop into short-term (30 min) traffic prediction Integrate with real-time adaptive signal control

Test laboratory to demonstrate potential of ITS Lead into full field corridor implementation Lead into city-wide implementation

Project Team PTV America Overall project management Macroscopic travel demand modeling (VISUM) ITS project management DTA and microscopic modeling (VISSIM) System set up and integration Real-time modeling (OPTIMA) Real-time adaptive signal control (BALANCE, EPICS) Type 2070 local traffic control and VISSIM integration (D4)

Mygistics (PTV subsidiary)

SISTeMA (PTV subsidiary) GEVAS (longterm PTV partner)

Fourth Dimension (longterm PTV partner)

System Architecture

System Architecture Edmonton Laboratory ComponentsVISUM Demand Model VISSIM Traffic Count Management

Optima

ModelModel-based Incident Response Adaptive Signal Control (BALANCE)

DMS In-vehicle InNavigation1in cooperation with BMW

1 Demonstration

System Architecture Edmonton ComponentsVISUM Demand Model Live Detectors, Traffic Count Management

Optima

ModelModel-based Decision Support Event / Strategy Management Adaptive Signal Control (BALANCE)

DMS, MyTIS, In-vehicle Navigation In-

Edmonton ITS Lab: System Architecture and Data FlowOPTIMA

System Overview

Project Area

10 km, 127 signals (31 adaptively controlled)

Preset IncidentAccident on EB YHT Two lanes blocked east of 97th S. Expected clear time: 45 min

Accident on eastbound Yellowhead Trail east of 97th S. Two out of three lanes blocked Clear time 45 minutes

Dynamic Message SignsDMS @ EB YHT @170th COLLISION YHT E OF 97TH 2 LANES CLOSED USE 127TH OR 132ND AVE NW

Six DMS signs within project area Four text options per DMS Level 1: Off Level 2: COLLISION YHT E OF 97TH Level 3: COLLISION YHT E OF 97TH, USE 127TH OR 132ND AVE NW Level 4: COLLISION YHT E OF 97TH, 2 LANES CLOSED, USE 127TH OR 132ND

Adaptive Signal Control

31 adaptively controlled traffic signals within project area System-wide cycle/split/offset optimization based on 5 min forecast volume (BALANCE) Real-time local green time fine-tuning based on detector input (EPICS) VISSIM software-in-the-loop implementation via Type 2070 controller firmware (D4)

Live Demonstration

Interface Overview

Incident Visible

Traffic Forecast

Incident Response / DMS Settings

Signals

VISSIM

Results

Do Nothing Base Case1-3 0 1-1 1-2 1-4 6-1 6-2

DMS + Adaptive Signal Control1-1 0 1-2 1-4 6-1 6-2

1-3

Local Impacts of DMSDMS advising left-turn at 127th St.

Without DMS

Local Impacts of DMSDMS advising left-turn at 127th St.

With DMS

Local Impacts of DMSDMS advising left-turn at 127th St.

Time 1800 3600 5400 7200 9000

DMS Advisory Without With #Veh #Veh 203 208 235 395 253 447 127 430 288 419

Difference Absolute % 5 2 160 68 194 77 303 239 131 45

Benefits of Integrated Adaptive Signal ControlDMS advising left-turn at 127th St.

Without Adaptive Control

Left-turn queue spillback

Benefits of Integrated Adaptive Signal ControlDMS advising left-turn at 127th St.

YHT @ 127th St EBL Interval DMS Active DMS Inactive 1-1800 Avg. Delay [sec/veh] Avg. Number of Stops 1801-3600 Avg. Delay [sec/veh] Avg. Number of Stops

Adaptive Control Without With Difference Absolute 38.2 1.9 33.4 1.4 -4.8 -0.5 Absolut 74.2 5.7 44.2 2.2 -30.0 -3.4 % 12 24 % 40 60

Conclusion

From Laboratory to Real World Lab is preparation for field implementation Way to test various strategies (detector placement, VMS messages and placement, etc.) under different traffic conditions or events Build a library of robust strategies Develop action plans for traveler information and traffic management Once live, real-world traffic replaces simulation via field detectors Showcase benefits of the ITS investment (detectors, VMS, etc.)

Thank you!