Road Weather Information Network Systems INSE 6400 Final Project Presentation Fall 2013 Hassan Algarni Abdulaziz Alqahtani Alaa Eddine Sohaili Ali Aghanaya

Outline Introduction The Road Weather Information System for Canada (RWISC) Weather data and Camera images A Telephone-Based Conversational Interface for Weather Information Wireless Traffic Service Platform Conclusion

Introduction Accurate and Real-Time road conditions information can enhance road users’ safety. More efficient transportation system and highway maintenance in an extremes and seasonal contrasts weather in very wide country like Canada. The Road Weather Information System for Canada (RWISC) Road images and road condition data can improves road condition classification. Real time telephone based weather information system Vehicle wireless communication platforms

The Road Weather Information System for Canada (RWISC) The Road Weather Information System for Canada (RWISC) implemented since fall 2004 in Ontario. Collaboration between multiple levels of Government and the private sector. Integrating a Canada-wide network of environment system sensors (ESS) and instrumented vehicles. The RWIN high-level architecture integrated environment for data collection, validation, transformation, storage and delivery

RWISC System Environmental System Sensors (ESS)integrated to provide a continuous stream of observation data. Developed using object oriented methodology, J2EE and the Java2 programming language. Provincial Computer Centres (PC2) obtain data from fixed and mobile ESS stations in real-time.

Cont. RWISC Using the Canadian Meteorological Mark-up Language (CMML), RWISC will acquire data from PC2 Meteorological Service of Canada (MSC) established RWIN for integrating data from PC2 protecting data, making raw and QA/QC real-time data available to provinces in CMML format and archiving this data. Provinces are responsible to develop PC2 and making ESS data available to RWIN.

Road condition using weather data and camera images: Main goal: provide accurate information about road condition. Knowing the road condition in advance, road maintenance and high traffic safety can be increased. These types of information can be obtained from existing meteorological sensors and camera images from Road Weather information Systems (RWIS). Aims to find a relation between road data including road images and road condition, which in the end improves road condition classification.

the Road condition using weather data and camera images:- Traditional method: Information obtained from roadside sensor value air temperature and road temperature Data provided by the roadside sensors is not sufficient to determine critical road condition. Due to rapid changes in weather and human intervention…(de-icing chemicals). By add road cameras, the analysis and forecast become more accurate… how?

the Road condition using weather data and camera images:- Advanced methods Classifying road conditions into different classes RWIS variables, road weather and road surface temperature, together with camera images Multi-class classifiers, which are neural networks, support vector machines and multi-variate analysis, has been done for the purpose of classifying the road condition.

the Road condition using weather data and camera images:- Methodology Collect and analyse all of the available variables from RWIS and camera images at specific instants of time. The images converted to image properties in order to be amenable to analysis by computer software. At each observation, the road condition is assessed and then placed into the road classes, dry, wet, snowy, icy or tracks; that means snowy with wheel tracks. To find the relation between variables, the Principal Component Analysis (PCA) is preformed. PCA shows the variation between road conditions Preform fitness evaluation For better fitness, the outcome of the fitness evaluation should be close to value 1.0 Test and visualize the relations and differences between road classes

JUPITER: Telephone-Based Conversational Interface for Weather Information A real time telephone based weather information system used to enable users to interact with a SQL database using natural speech. Provides weather information forecast for approximately 500 cities and 166 countries. Can forecast and answer questions for 3 to 5 days ahead (i-e: precipitation, temperature, humidity,…).

Cont. JUPITER Different challenges need to be addressed on the system: Poor signal condition The absence of a high quality verbal answer. High system performance, High availability and quick response time. Knowledge/information acquisition: - Linguistic. - Overlapping/redundant and/or complementary. - Data collection/selection and content processing and understanding.

Cont. JUPITER System Architecture: Client server architecture. Different human language technologies. Interactions mediated by a hub and controlled via a scripting language. Tokens exchange communication protocol.

Conclusion Road weather information network supported by real-time intelligent sensors such as road cameras will increase road users’ safety and road maintenance efficiency. Three concepts of gathering, exchanging and providing real-time road and weather information. The integration of such systems using standardized protocols and a coherent information exchange architecture will ensure that the whole platform ecosystem is open and will permit adding new modular applications and technologies.

References Sukuvaara, T.; Nurmi, P., "Wireless traffic service platform for combined vehicle-to-vehicle and vehicle-to-infrastructure communications," Wireless Communications, IEEE , vol.16, no.6, pp.54,61, December 2009 doi: 10.1109/MWC.2009.5361179  Koonar, A.; Eng, P.; Delannoy, P.; Denault, D., "Building a road weather information network for integrating data from heterogeneous sources" Information Technology and Applications, 2005. ICITA 2005. Third International Conference on , vol.1, no., pp.501,507 vol.1, 4-7 July 2005 doi: 10.1109/ICITA.2005.87 Patrik Jonsson, Member, IEEE. “Road Condition Discrimination using Weather Data and Camera Images”. 2011 14th International IEEE Conference on Intelligent Transportation Systems Washington, DC, USA. October 5-7, 2011. Victor Zue, Member, IEEE, Stephanie Seneff, James R. Glass, Member, IEEE, Joseph Polifroni, Christine Pao, Timothy J. Hazen, and Lee Hetherington. “JUPITER: A Telephone-Based Conversational Interface for Weather Information”. IEEE TRANSACTIONS ON SPEECH AND AUDIO PROCESSING. VOL. 8, NO. 1, JANUARY 2000.