Presentation is loading. Please wait.

Presentation is loading. Please wait.

Utilizing ITS to Reduce Truck Overturn Crashes Due to High Winds at Bordeaux, Wyoming Edward Offei Rhonda Young, PhD, PE.

Similar presentations


Presentation on theme: "Utilizing ITS to Reduce Truck Overturn Crashes Due to High Winds at Bordeaux, Wyoming Edward Offei Rhonda Young, PhD, PE."— Presentation transcript:

1 Utilizing ITS to Reduce Truck Overturn Crashes Due to High Winds at Bordeaux, Wyoming Edward Offei Rhonda Young, PhD, PE

2 Outline Background Project Location Data Sources Data Analysis High Wind Warning System

3 Background Wyoming is noted for frequent severe wind conditions especially at the southeastern part of the state. Many wind farms established due to the high wind conditions. Wind speeds reach 30 to 40 mph and wind gust speeds of 50 to 60 mph during the winter.

4 Background Wind direction effect is greatest if it is perpendicular to the road. High profile vehicles (empty or lightly loaded) are vulnerable to the high wind. Previous research have investigated how wind speeds correlated with truck safety.

5 Research Objectives Conduct field studies to provide an overview of the study location and chose the suitable locations for the installation of the monitoring equipment. Confirm the relation between high wind conditions and high risk of truck crashes. Determine appropriate threshold values for the high wind warning system. Analyze crash data to create baseline conditions to monitor the future effectiveness of the system. Develop final recommendations for the High Wind Warning System.

6 Locating the Study Area

7 Project Location

8 Data Sources Road Weather Information System (RWIS) Tower Two Wavetronix Speed Sensors 2 Pan-Tilt-Zoom (PTZ) Cameras attached to a 2 channel Pelco 4000 Digital Video Recorder

9 ITS Equipment RWIS TOWER

10 ITS Equipment Speed Sensor Cabinet

11 ITS Equipment HOBO Weather Station

12 CRASH VIDEO SNAPSHOTS

13 TRUCK CRASH FREQUENCY

14 TRUCK CRASHES THAT OCCURRED DURING 2008 – 2010 WINTER SEASONS IndexCrash KeyMilepostDateWind SpeedWind Gust SpeedWind Direction 120082043570.5012/5/20085373W 220082043670.2512/5/20084970SW 320082044170.0012/17/20083547W 420082090170.0012/27/20085066SW 520082090870.7512/31/20084062SW 620082090970.5012/31/20084567SW 720082284570.0012/31/20084771SW 820090035370.621/5/20095876W 920090035470.601/5/20095374W 1020090177370.001/21/20094057SW 1120090257070.622/6/20094562SW 1220090257170.002/6/20095568SW

15 TRUCK CRASHES THAT OCCURRED DURING 2008 – 2010 WINTER SEASONS IndexCrash KeyMilepostDateWind SpeedWind Gust SpeedWind Direction 1320090257270.632/6/20094772SW 1420090355069.983/8/20094868W 1520090355270.503/8/20094573W 1620090456269.883/8/20095171W 1720090356671.503/9/2009911NE 1820091568670.6210/31/20095063SW 1920091819165.0012/07/2010611E 2020091873170.2512/10/20093555SW 2120091819770.5012/12/20095170W 2220100087370.6001/12/20104051SW 2320100087970.5001/18/20102938SW 2420100272969.1002/03/20102030SW 2520100228366.0002/18/20101620N

16 Data Analysis  Multiple Logistic Regression Model Response Variable: Overturning Truck Crash, 1 is assigned for overturning and 0 otherwise Predictor Variables: All weather condition parameters  Modeling Methodology 95% confidence intervals All parameters included in initial model Parameters with p-value larger than 0.05 removed from model one at a time starting with largest p-value variable Filtering loop continue until all parameters have p-value < 0.05 Hosmer and Lemeshow goodness-of-fit test to determine how well the model fit the data

17 Data Analysis Multiple Logistic Regression Model Equation

18 Model Output Initial ModelFinal Model Predictor VariableEstimateP-valueEstimateP-value Intercept(β 0 )-1.74830.0782-1.75220.0426 Lighting Condition (β 1 )0.19520.8049-- Road Condition (β 2 )-2.68570.0061-2.56280.0048 Wind Speed(β 3 )0.12520.08010.0893<0.0001 Wind Gust(β 4 )-0.0350.5257-- Wind Direction Binary(β 5 )0.33870.7799--

19 Wind Speed and Truck Overturning Relationship

20 Vehicle Speeds at Different Wind Conditions Vehicle TypeCategory Average Vehicle Speed (mph) Standard Deviation Cars Wind Speed <=10mph76.654.86 Wind Speed >=30mph77.097.03 Trucks Wind Speed <= 10mph69.758.42 Wind Speed >=30mph67.728.63

21 RWIS vs. HOBO RWIS located near the top of an adjacent hillside. HOBO located 40 feet near the roadside. Positive difference indicate RWIS Data > HOBO Data. RWIS wind speeds higher than HOBO wind speeds. Difference increases as the wind speed increases.

22 Truck Weight Analysis Result

23 Crash Frequency vs. Wind Speed

24 Operational Levels Level 1: 30mph wind speed threshold was recommended for advisory warning messages on the DMS’s. Level 2: 40 mph wind speed threshold was determined for road closure to all high-profile, light-weight vehicles. Level 3: 45mph wind speed threshold was determined for road closure to all trucks.

25 High Wind Warning System  DMS signs (2 were installed adjacent to the corridor)  CB Wizard  Highway Advisory Radio (HAR)  511 Phone Service  Website (WYDOT)  Weigh-In-Motion (WIM)  Over Height Vehicle Detector (OHVD)

26 Edward Offei eoffei@uwyo.edu QUESTIONS


Download ppt "Utilizing ITS to Reduce Truck Overturn Crashes Due to High Winds at Bordeaux, Wyoming Edward Offei Rhonda Young, PhD, PE."

Similar presentations


Ads by Google