Farhad Pooran, Ph.D., P.E. Rockville, Maryland Annual Meeting of ITS Midwest

Transcription

1 Managing Traffic Congestion Using Air Quality Data Farhad Pooran, Ph.D., P.E. Telvent Transportation ti North America Rockville, Maryland 2009 Annual Meeting of ITS Midwest

2 Introduction World-wide activities TRACE Project Outline Operational Strategies Case Study: Adaptive Signal Control 2

3 The Issue Ever increasing congestion Air quality becoming a serious problem in urban areas Transportation is a big part of the climate change debate Road vehicles are the major contributors to the air pollution 3

4 The Context t Americans drive 5 billion miles a day We consume 40% of US petroleum products On road vehicles are responsible for: 22% of US Greenhouse gases 50% of GHG emissions in Bay Area Nearly 50% of smog-forming g volatile organic compounds (VOCs) More than 50% of the nitrogen oxide emissions About 50% of the toxic air pollutant emissions 75% of carbon monoxide emissions 4

5 Addressing the Air Quality Initiatives Kyoto Protocol to reduce Carbon Dioxide Clean Air Act on National Ambient AQ standards CMAQ & SAFETE-LU initiatives to reduce criteria pollution 5

6 On-going Activities iti Earlier work focused on monitoring air quality and/or restricting access to downtown areas Addressing impact of transportation t ti on climate change and GHG Emissions European pilot projects to develop ITS strategies to improve the quality of the air 6

7 Quantifying the benefits: Challenges If you can t measure it, you can t manage it. Current activities t in Europe estimate benefits e of deployed strategies through modeling Direct measurement of air quality parameters requires advanced d roadway sensors GHG Emissions - There is no sensors or technologies readily available to measure and/or monitor GHG emissions. 7

8 TRACE Project Integration of Air Quality with Traffic Management Measure & monitor air quality and traffic congestion Model & forecast GHG and air quality parameters Provide Operational Strategies Adapt to the Network 8

9 System Architecture t 9

10 Model and Forecast Integrated solution with Traffic Management System Use of real-time vehicular and meteorological data Currently using European atmospheric dispersion s modeling system Integration with the US EPA s MOVES2009 final version when becomes available 10

11 Real-Time Data: Monitoring & Forecasting Meteorological Data (hourly update) Temperature, Relative Humidity, Wind Speed, Wind Direction, Cloud Cover Traffic Data (from traffic management system) Hourly count, Average link speed, Vehicle type AQ data from AQ monitoring sensors CO, NO, NOx, NO2, PM 11

12 Operational Solutions Arterial Traffic Control: Adaptive Signal Control Optimum Driving Speed Rerouting traffic to parallel streets Active Traffic Management: Adaptive Ramp Metering Dynamic lane management Speed Harmonization Load Balancing between freeways and parallel arterials Traffic Demand Forecasting (ATIS) 12

13 Access control Operational Solutions Gating Congestion/Low emission zone pricing Integrated solution with Tolling Adjust Fares Coordination with transit system Adjust fare structures (free bus rides, reduced fare) Signal priority 13

14 Case Study: Adaptive Signal Control Minimize Stops & Delays Minimizing stops has a significant impact on limiting fuel inefficient accelerations Manage prevailing traffic conditions including traffic surges and special events Maintain a consistent pace throughout the corridor using signal coordination Enforce access control through gating 14

15 Case Study: Adaptive Signal Control Measuring AQ Parameters Measuring several pollutants in a modular platform with ambient air analyzers Currently measuring CO, NOx, PM2.5 15

16 Case Study: Adaptive Signal Control Real-time Traffic Data 16

17 Case Study: Adaptive Signal Control Before/After Studies Traditional approach: travel time & stops/delays Environmental evaluation: Air quality parameters Evaluation Period: March 3-8, 2009 OPAC adaptive control March 9-15, 2009Time Of Day (TOD) plans 17

18 Case Study: OPAC Adaptive vs. TOD Particulate Matter (PM) PM Weekly ms/m3) PM (micro gra OPAC 3/2-3/8 TOD 3/9-3/15 Day & Time 18

19 Case Study: OPAC Adaptive vs. TOD Carbon Monoxide (CO) CO Emission i - Weekly OPAC 3/2-3/8 TOD 3/9-3/15 10 CO (pp pm) Day & Time 19

20 Conclusions Congestion and environment control and management are key challenges for policies that deliver sustainability. Integration of ITS technologies and traffic management system with air quality is required to provide some measurable benefits. Different operational solutions may be evaluated to identify applicable strategies to specific networks. 20

21 Thank you! 21