Variable Speed Limits. M-30 Ring Motorway - Polis network

1 Madrid Case Study Variable Speed limits . M-30 ring Motorway Madrid, 26/11/2014. Alvaro Garcia-Castro, TRANSyT-UPM. Contents 1. ICT-Emission measures 2. Variable Speed Limit. Section description 3. Data collection campaign 4. Data analysis. Results 5. Traffic modelling. Calibration process and preliminary results 6. Next Steps Madrid Case Study ICT-Emissions EU 7th Framework Programme ITS Main focus on: Models Eco driving Traffic management and control Demand and access management Advanced driver assistance system Energy Navigation and travel information consumption and CO2. ICT measures Variable Speed limits Data Collection Data analysis Results real data Modelling Micro Macro Emissions Emissions Case Study Structure Variable Speed limits .

2 Concept Variable Speed limits (VSL). From real traffic-flow and weather information, this system adapt dynamically the posted Speed limit by means of Variable Message Signs. It can display recommended or mandatory limits . Effects on traffic flow, emissions and safety. Variable Speed limits Variable Speed limits . Case Study of Madrid West section- Southbound 3 lanes Motorway . Length of km Traffic intensity in the afternoon peak hours rounding 6,000 veh/h Limited to 90 km/h, except last 100 m. limited to 70 km/h (tunnel entrance). Recommended Variable Speed 80, 70, 60, 50 or 40 km/h depending on the control algorithm (average Speed differences downstream). Variable Speed limits Variable Speed limits Data Collection Data analysis Results real data Modelling Micro Macro Emissions Emissions Case Study Structure Preliminary tests (June 2012): Measurements Based on floating car data (no fuel consumption).

3 Variable Speed limits (recommended): West section of the ring road M-30. Surveys (March-April 2013): Based on floating car data and traffic data (measuring points). Section Speed control: East section of the ring Motorway M-30. Variable Speed limits (recommended): West section of the ring road M-30. Eco-driving techniques: Urban and M30 sections Cruise control: East and West section of the ring road M-30 (including By-pass). ICT Measures deactivated ICT Measures activated 7000 M-30: West section 6000. Intensity (veh/h). 5000. 4000. 3000. 2000. 1000. 0. 1:00 3:00 5:00 7:00 9:00 11:00 13:00 15:00 17:00 19:00 21:00 23:00. M-30: Intensity in West Section Floating car data More than 2,000 trips recorded (1Hz).

4 - GPS position - Speed - Rpm and consumption 9 drivers and 3 vehicles: - Punto - Punto - Bravo Other info: - Traffic incidents - Driver - Day time - Temperature - Weather - ITS measure activation DATA AVAILABILITY. Traffic data From induction loops: - Intensity - Average Speed - Occupancy Every 5 minutes!! Detailed Geometrical data DATA AVAILABILITY. Variable Speed limits Data Collection Data analysis Results real data Modelling Micro Macro Emissions Emissions Case Study Structure Traffic data. Effects on Average Speed -Intensity curves Section 5: congestion in peak hours VSL OFF. VSL ON. Results. Traffic data Floating car data: Consumption and time saving results Results. Floating Vehicles Variable Speed limits Data Collection Data analysis Results real data Modelling Micro Macro Emissions Emissions Case Study Structure Traffic data models in Madrid: ptv vissim and VISUM.

5 Traffic models MICRO TRAFFIC MODEL ( vissim ). - Field trials: instant Speed and travel times - Traffic loops (8): traffic intensity every 5 minutes - Simulation period: from 4 to 10 pm CALIBRATION PROCESS. - Step 1: TRAFFIC volume convergence (loops). - Step 2: TIME convergence (floating cars). Variable Speed Limit Control Algorithm. Software implementation - Implemented in vissim using Visual Basic and the COM Interface - Based on Speed differences in 2 measuring points - Recommended Speed displayed on a Variable Message Sign (80, 70, 60, 50 or 40 km/h). Variable Speed Limit Implementation Variable Speed Limit Control Algorithm. Calibration of desired Speed decision. Analysis of the Speed profiles from floating cars Definition of new desired Speed distributions for each recommended Speed Programming of Visual Basic code to control vissim and simulate the Variable Speed limits .

6 Adjustment of desired Speed distribution to fit travel times data recorded by floating vehicles. Variable Speed Limit Implementation Variable Speed Limit. Sensitivity tests on simulation randomness - 10 replications of simulations done for VSL OFF, 10 replications of simulations done for VSL ON. - Congested traffic selected from time data (19:30 19:45), only for one vehicle class Statistics of 10 runs comparing same random seeds (CO2 in g/km): Mean value: + Min/max value: / + Standard deviation: Variable Speed Limit Implementation Variable Speed Limit Control Algorithm. Next Steps Conclusions on sensitivity tests Calibration refinement Emission calculation at micro level with ICT-Emissions Integration Tool (CRUISE.)

7 Model). Interface micro-macro traffic models ( vissim -VISUM): BPR curves calibration at macro level using traffic data extracted from micro traffic model. Calibration of Macro model Variable Speed Limit Implementation Thank you very much for your attention Variable Speed Limit