Responsive Traffic Management Through Short-Term Weather and Collision Prediction

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Responsive Traffic Management Through Short-Term Weather and Collision Prediction Presenter: Stevanus A. Tjandra, Ph.D. City of Edmonton Office of Traffic Safety (OTS) Co-authors: Yongsheng Chen, Ph.D., P.Eng., Frank Feng, Ph.D. OTS Tony Qiu, Ph.D., Gerhard Reuter, Ph.D., Lawrence Lan, M.Sc., Clark Pennely, M.Sc. University of Alberta

Weather-Responsive Traffic Management (WRTM) City of Edmonton Weather and Collision Prediction

City of Edmonton Office of Traffic Safety (OTS) http://www.edmonton.ca/transportation/traffic-safety.aspx Established in 2006 as a result of Mayor Traffic Safety Task Force Focus on urban traffic safety through evidence-based approaches Shifting Rural to Urban World Population (UN Report 2009): Year Urban Population Rural Population 2009 3.4 billion 3.4 billion 2050 6.3 billion 2.9 billion The OTS will reduce the prevalence of fatal, injury, and property damage collisions through the 4 E s of traffic safety (Engineering, Education, Enforcement, and Evaluation) by improving urban traffic safety engineering road user behaviour speed management and data, business intelligence and analytics

Weather Impacts on Safety and Mobility US DOT Road Weather Management Program: 1 In US, over 5,870,000 vehicle collisions each year - 23% (nearly 1,312,000) are weatherrelated. On average, 6,250 fatalities and over 480,000 injuries in weather-related collisions each year. 23 percent of the non-recurrent delay on highways across the US is due to snow, ice, and fog 544 million vehicle-hours of delay per year. Weather-related collision costs in Canada are estimated to be approximately $1 billion per year. 2 Survey indicated the importance of information on weather conditions for travelers. 3 51% 1 http://www.ops.fhwa.dot.gov/weather/q1_roadimpact.htm; accessed on May 15, 2014. 2 Andrey, J., B. Mills, and J. Vandermolen. Weather Information and Road Safety: Final Report. Final Report Presented to the Institute for Catastrophic Loss Reduction, 2001. Downloadable from http://www.iclr.org/images/weather_information_and_road_safety.pdf. 3 Federal Highway Administration. US Department of Transportation. Weather-Responsive Traffic Management: New Approaches to Improve Safety and Mobility. (Spring 2011). FHWA-JPO-11-093.

Daily temperature (ºC) Snowfall (cm) Weather in Edmonton Throughout the year, temperatures can range from below -40 C during the winter, to above 30 C in the summer. 25 20 15 10 5 0-5 Average 1981-2010 1 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 30 25 20 15 10-10 -15 5-20 0 35 30 25 20 15 10 5 0 Average # days with snow depth of at least 1, 5, 10 or 20 cm on the ground (1981-2010) 1 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec >= 1 cm >= 5 cm >= 10 cm >= 20 cm In the City of Edmonton, around 57% of collisions occurred in the fall and winter months (January - March and October - December). 2 1 1981-2010 Climate Normals & Averages http://climate.weather.gc.ca/climate_normals/index_e.html 2 City of Edmonton annual motor vehicle collision reports. Downloadable from http://www.edmonton.ca/transportation/traffic_reports/collisionspeed-reports.aspx.

Weather Impacts on Traffic Safety: Trends and Patterns

Weather Impacts on Traffic Safety Weather impact on collision 1 : Min Temp<-10, Total Snow>0 and Speed of Max Gust >20 increased FTC (Followed Too Closely) collisions between 17.9% and 33.0%. 1 El-Basyouny, K., Barua, S., Islam, Md.T., Li, R. 2014. Assessing the Effect of Weather States on Crash Severity and Type using Full Bayesian Multivariate Safety Models. TRB 93rd Annual Meeting Compendium.

Weather-Responsive Traffic Management (WRTM) Goal 1 : to minimize the delay and risk experienced by motorists while driving in bad weather. Strategies 1 : Advisory strategies provide warning and other information to travelers; Control strategies to regulate or optimize traffic flow; and Treatment strategies to ensure the roads are clear of obstructions Implementation: Integrated Transportation Management Centre WRTM Congestion management Advanced Traveler Information System (ATIS) Situational awareness and planning functionality Emergency operations centre capability 1 Federal Highway Administration. US Department of Transportation. Weather-Responsive Traffic Management: Real Solutions for Serious Traffic Problems. FHWA-JPO-09-035. Increase access, mobility and safety

WRTM - City of Edmonton s Initiative Building 6 new weather stations collecting/calculating: Wind speed and direction Barometer pressure Snow and rain fall Air temperature and humidity Dew point Weather, collision and traffic flow (volume & speed) prediction: Current state: 7 days ahead prediction of citywide daily weather and collision Collision prediction: public roadway collisions and police-call (CAD) collisions Collaborators: Weather prediction: Department of Earth and Atmospheric Sciences, University of Alberta Collision and traffic flow prediction: City of Edmonton Office of Traffic Safety Web-base application: Department of Civil and Environmental Engineering, University of Alberta Current users: the Edmonton Police Service and City of Edmonton Office of Traffic Safety

1-Apr 2-Apr 3-Apr 4-Apr 5-Apr 6-Apr 7-Apr 8-Apr 9-Apr 12-Feb 13-Feb 14-Feb 15-Feb 16-Feb 17-Feb 18-Feb 19-Feb 20-Feb 21-Feb 22-Feb 23-Feb 24-Feb 25-Feb 26-Feb 27-Feb 28-Feb 1-Mar 2-Mar 3-Mar 4-Mar 5-Mar 6-Mar 7-Mar 8-Mar 9-Mar 10-Mar Predicted Total & FTC Collisions Amount of Precipitation (MM) Snow Fall Amount (cm) 11/20/2012 11/22/2012 11/24/2012 11/26/2012 11/28/2012 11/30/2012 12/02/2012 12/04/2012 12/06/2012 12/08/2012 12/10/2012 12/12/2012 12/14/2012 12/16/2012 12/18/2012 12/20/2012 12/22/2012 12/24/2012 12/26/2012 12/28/2012 12/30/2012 01/01/2013 01/03/2013 01/05/2013 01/07/2013 01/09/2013 City of Edmonton Weather, Collision and Traffic Flow Prediction Weather Data Set-up for Edmonton Calendar Data Month, Day of Week, Holiday Traffic Flow Data VDS Sites: Speed, Volume 90 85 80 75 70 65 60 Traffic Speed (km/h, Location: SW VDS Site - WMD & 156 St) High Speed Alert Warranted Future Work 16 14 12 10 8 6 4 1-day-earlier Forecast Snow (cm) Actual Amount Snow (cm) 7-day-earlier Forecast Snow (cm) Past Future Volume & Speed Prediction Day 2 140 PredictedTotal PredictedFTC AmountPrecipitation 8 0 120 7 Weather 100 80 60 40 6 5 4 3 2 Prediction 0 0 20 1 Collision Prediction

Equitable Threat (skill) RSME Predicted variables by four quadrants (NE, SE, NW, SW): Wind speed and direction Barometer pressure Snow and rain fall Weather Prediction Air temperature (low, high, mean) and humidity Visibility Weather data source: National Oceanic and Atmospheric Administration (NOAA) Use Weather Research and Forecasting model (WRF) for prediction Prediction accuracy: RSME: Root Mean Squared Error 25.0 20.0 15.0 10.0 5.0 0.0 0.40 0.35 0.30 0.25 0.20 0.15 0.10 0.05 0.00 Weather Prediction Error 1st Day 2nd Day 3rd Day 4th Day 5th Day 6th Day 7th Day Day in Prediction Weather Prediction Error: Precipitation 1st Day 2nd Day 3rd Day 4th Day 5th Day 6th Day 7th Day Day in Prediction Max T (ºC) Min T (ºC) Wind Speed (km/h) 0.2 mm 1.0 mm 5.0 mm

Public Roadway Collision Prediction MAE: Mean Absolute Error MAPE: Mean Absolute Percent Error

Police call (CAD)-Collision Prediction MAPE 13%

Weather and Collision Prediction: Web-Base Application http://www.its.ualberta.ca/default

Benefits Icy Curves Ahead Icy Curve Warning System (ICWS) 1 Deployment of the ICWS reduced the number of annual collisions by 18% (CMF = 0.82), PDO collision rate was reduced from 5.51 to 4.00 collisions per winter season Fatal and Injury collision rate decreased from 2.86 to 2.67 collisions per season ICWS has potentially provided safety benefits of $1.7 million dollars per winter season 1 Zhirui, Y., Veneziano, D., Turnbull, I., Safety Effects of Icy Curve Warning Systems. Presented at the 91st Annual Meeting of the Transportation Research Board, Paper No. 12-0985, Washington, D.C., (2012)

Next Steps Hourly predictions for the next 7 days; models updated every 6 hours Alarm threshold development Collision prediction by specific area and corridors Traffic volume and speed prediction CMF and C/B-ratio estimation Integration with the Traffic Management Centre Utilize media (radio, TV) and social media (Twitter, Facebook) to increase driver awareness

Thank You Contact: Stevanus.Tjandra@edmonton.ca