Leveraging Big Data to Improve Traffic Incident Management (2019)

Below is the uncorrected machine-read text of this chapter, intended to provide our own search engines and external engines with highly rich, chapter-representative searchable text of each book. Because it is UNCORRECTED material, please consider the following text as a useful but insufficient proxy for the authoritative book pages.

125 Alvarez, P. 2015. “Big Data Helps Pedestrian Planning Take a Big Step Forward.” Transportation Professional. Barrett, Byrd Associates, Tunbridge Wells, Kent, UK. Amazon. 2017. “Amazon Rekognition.” AWS. Webpage: https://aws.amazon.com/rekognition/ (accessed June 2017). Amazon Web Services. n.d. “C-SPAN Case Study.” AWS Website: https://aws.amazon.com/solutions/case-studies/ cspan/ (accessed July 24, 2018). American Automobile Association. 2017. AAA Digest of Motor Laws. Webpage: http://drivinglaws.aaa.com/tag/ move-over-law/ (accessed May 15, 2017). Anderson, J. M., N. Kalra, K. D. Stanley, P. Sorensen, C. Samaras, and O. A. Oluwatola. 2016. Autonomous Vehicle Technology. Santa Monica, CA: RAND Corporation. Available online: http://www.rand.org/content/dam/ rand/pubs/research_reports/RR400/RR443-2/RAND_RR443-2.pdf. APCO International. 2010. High Priority Information Sharing Needs for Emergency Communications and First Responders. Association of Public Safety Communications Officials, Daytona Beach, FL. Available online: https://www.apcointl.org/doc/911-resources/375-high-priority-info-sharing-needs-for-emerg-comm- and-first-responders-final-pdf/file.html. Applied Engineering Management Corp. and toXcel, LLC. 2018. NCHRP Research Report 865: Guidance for Development and Management of Sustainable Enterprise Information Portals. Transportation Research Board, Washington, D.C. Automotive Supply Chain. 2016. Automotive Supply Chain. Webpage: http://automotivesupplychain.org/supply- chain/crown-commercial-service-appoints-ald-automotive-to-vehicle-telematics-framework-agreement/ (accessed July 2018). Baltimore Metropolitan Council. 2017. “Traffic Incident Management Committee” webpage: https://baltometro. org/community/committees/traffic-incident-management-committee (accessed June 2017; url updated May 2019). Barichello, K., and S. Knickerbocker. 2017. “Using INRIX Data in Iowa.” www.mtmug.org.Webpage: http:// www.mtmug.org/Presentations/rev_INRIX%20presentation%20MTMUG.pdf (accessed May 15, 2017). Barrachina, J., P. Garrido, M. Fogue, and F. J. Martinez. 2012. “VEACON: a Vehicular Accident Ontology Designed to Improve Safety on the Roads.” Journal of Network and Computer Applications. Available online: https://www.researchgate.net/publication/236842047_Efficient_Regression_Testing_of_Ontology-Driven_ Systems. BDE n.d. “Big Data Europe Empowering Communities with Data Technologies—Integrating Big Data, Software, and Communities for Addressing Europe’s Societal Needs.” Big Data Europe. Webpage: https://drive.google. com/file/d/0By9UYHuCedbmcjJKZF9YQkROcG8/view (accessed June 10, 2017). BDE and ERTICO-ITS Europe. 2015. Big Data Europe for Smart, Green and Integrated Transport. First Workshop Report, ITS Conference (Bordeaux, Oct. 7, 2015). Beach, J. 2014. “Big Data & Trucking.” Trucking Info. Webpage: http://www.truckinginfo.com/article/ story/2014/12/big-data-tracking.aspx (accessed November 2016). Birenbaum, I., C. Creel, and S. Wegmann. 2009. Traffic Control Concepts for Incident Clearance. FHWA- HOP-08-057. Office of Transportation Operations, Federal Highway Administration, U.S. Department of Transportation, Washington, D.C. Available online: https://ops.fhwa.dot.gov/publications/fhwahop08057/ fhwahop08057.pdf. Bonetti, P. 2013. “How to Really Outsmart Traffic.” HERE 360. Webpage: http://360.here.com/2013/07/09/ how-to-really-outsmart-traffic/ (accessed June 2017). Bostock, M. 2015. “Bivariate Hexbin Map—Released Under the GNU General Public License, Version 3.” Mike Bostock’s Blocks. Webpage: https://bl.ocks.org/mbostock/4330486 (accessed October 19, 2018). References

126 Leveraging Big Data to Improve Traffic Incident Management Branch, A. 2016. “Victims ID’d in Fatal Quassy Amusement Park Crash: Report.” Patch. Webpage: https:// patch.com/connecticut/woodbury-middlebury/victims-idd-fatal-quassy-amusement-park-crash-report (accessed July 2018). Brickley, D. n.d. “W3C Semantic Web Interest Group.” W3C. Webpage: https://www.w3.org/2003/01/geo/. Broad, E. (2015) “Closed, Shared, Open Data: What’s in a Name?” Blog (September 17, 2015): http://oldsite. theodi.org/blog/closed-shared-open-data-whats-in-a-name. Brooke, K., K. Dopart, T. Smith, A. Flannery. 2004. NCHRP Report 520: Sharing Information Between Public Safety and Transportation Agencies for Traffic Incident Management. Transportation Research Board of the National Academies, Washington, D.C. BTS. 2011. “Clarus.” Bureau of Transportation Statistics. Webpage: https://ntl.bts.gov/lib/44000/44300/44374/ FHWA-JP0-11-154_Clarus_Overview_final.pdf (accessed February 2017). Burt, M., M. Cuddy, and M. Razo. 2014. Big Data’s Implications for Transportation Operations: An Exploration. FHWA-JPO-14-157. Federal Highway Administration, U.S. Department of Transportation, Washington, D.C. Carrick, G., S. Srinivasan, and I. Bejleri. 2015. “Analysis and Characterization of Secondary Traffic Crashes in Florida.” Presented at 94th Annual Meeting of the Transportation Research Board. Transportation Research Board, Washington, D.C. Carrick, G., K. Jermprapai, S. Srinivasan, and Y. Yin. 2017. “Development of Guidance for Safety Service Patrol Deployment Decisions in Florida.” Transportation Research Record: Journal of the Transportation Research Board, 2660(1), Transportation Research Board of the National Academies, Washington, D.C., pp. 48-57. https://doi.org/10.3141/2660-07. Carrick, G., and S. Washburn. 2012. “The Move Over Law: Effect of Emergency Vehicle Lighting in Driver Compliance on Florida Freeways.” Transportation Research Record: Journal of the Transportation Research Board, 2281. Transportation Research Board of the National Academies, Washington, D.C., pp. 1–7. https:// doi.org/10.3141/2281-01. Carson, J. L. 2008. Traffic Incident Management Quick Clearance Laws: A National Review of Best Practices. FHWA- HOP-09-005. Office of Transportation Operations, Federal Highway Administration, U.S. Department of Transportation, Washington, D.C. Carson, J. L. 2010. Best Practices in Traffic Incident Management. FHWA-HOP-10-050. Office of Operations, Federal Highway Administration, U.S. Department of Transportation, Washington, D.C. CATT Lab. 2015. “RITIS Platform, Features & Applications Overview.” Webpage: http://www.cattlab.umd.edu/ files/RITIS%20Overview%20Book-2-2-15%20FINAL.pdf. Center for Advanced Automotive Technology. n.d. “Connected and Automated Vehicles.” Center for Advanced Automotive Technology. Webpage: http://autocaat.org/Technologies/Automated_and_Connected_Vehicles/ (accessed February 2017). Chire. 2011. “Single-linkage cluster analysis.” Image, used under a Creative Commons Attribution-Share Alike 3.0 (CC BY-SA 3.0) Unported License.” Wikipedia. Available online: https://en.wikipedia.org/wiki/Cluster_ analysis#/media/File:SLINK-Gaussian-data.svg (accessed July 24, 2018). Clark, M., I. Turnbull, T.A. Lasky, and S. Donecker. 2016. “Responder System Allows Caltrans First Responders to Collect and Share At-Scene Information Quickly and Efficiently.” California Department of Transporta- tion. Webpage: http://www.dot.ca.gov/research/rural/docs/responder_phase_III_summary-2016-07-12.pdf (accessed March 2017). Colak, S., L. P. Alexander, B. G. Alvim, S. R. Mehndiretta, and M. Gonzalaz. 2014. “Analyzing Cell Phone Location Data for Urban Travel: Current Methods, Limitations and Opportunities.” Presented at 94th Annual Meeting of the Transportation Research Board, Washington, D.C. Connected Citizens Program. 2016. Connected Citizens Program. Webpage: https://wiki.waze.com/wiki/ Connected_Citizens_Program (accessed June 2017). Corbin, J. 2008. “A National Unified Goal for Traffic Incident Management (TIM): What Is it, and Why Is it Needed.” Presentation for ITS PCB T3 Webinar, September 11, 2008. National Traffic Incident Management Coalition, American Association of State Highway and Transportation Officials, Washington, D.C. Available online: https://www.pcb.its.dot.gov/t3/s080911/corbin.pdf (accessed June 2017). Cox, S., and C. Little. 2017. “Time Ontology in OWL.” W3C. Webpage: https://www.w3.org/TR/owl-time/ (accessed July 2017). Daniell, J. N. 2009. Traffic Incident Management in Hazardous Materials Spills in Incident Clearance. FHWA- HOP-08-058. Office of Transportation Operations, Federal Highway Administration, U.S. Department of Transportation, Washington, D.C. Dardailler, D. 2012. “Draft Road Accident Ontology.” World Wide Web Consortium (W3C). Webpage: http:// www.w3.org/2012/06/rao.html#graph (accessed May 2017). Delgado, R. 2017. “Big Data’s Impact on Public Transportation. How Can Data Help Cities Build Transport Infrastructure?” The Innovation Enterprise, Inc. Webpage: https://channels.theinnovationenterprise.com/ articles/big-data-s-impact-on-public-transportation (accessed May 2017).

References 127 Dong, H., M. Wu, L. Jia, and X. Zhou. 2015. “Traffic Zone Division Based on Big Data from Mobile Phone Base Stations.” Transportation Research, Part C: Emerging Technologies, Vol. 58, Part B. Elsevier, Ltd., London, UK, pp. 278-291. Drow, M., P. Lange, and B. Laufer. 2015. “Big Progress in Big Data.” International Parking Institute. Webpage: http://www.parking.org/2016/01/26/tpp-2015-02-big-progress-in-big-data (accessed February 2016). Dunn Engineering Associates. 2006. Alternate Route Handbook. FHWA-HOP-06-092. HOTO-1, Federal Highway Administration, U.S. Department of Transportation, Washington, D.C. Durkin, E. 2015. “NYC Explores Drone Use for Everything from Disaster Response to Traffic Surveillance.” New York Daily News (November 23). Available online: http://www.nydailynews.com/new-york/nyc- explores-drone-disaster-response-traffic-jams-article-1.2444023 (accessed June 2017). Einstein, N., and J. Luna. 2018. SHRP2 Traffic Incident Management Responder Training Program: Final Report. FHWA-HRT-18-038. Federal Highway Administration, U.S. Department of Transportation, Washington, D.C. FEMA. 2011. National Fire Incident Reporting System, Version 5.0: Fire Data Analysis Guidelines and Issues. U.S. Department of Homeland Security, Washington, D.C. Webpage: https://www.usfa.fema.gov/downloads/ pdf/nfirs/nfirs_data_analysis_guidelines_issues.pdf. FHWA. n.d.-a. “National Traffic Incident Management Responder Training—Web Based.” National Highway Institute. Webpage: https://www.nhi.fhwa.dot.gov/course-search?tab=0&key=133126&sf=0&course_ no=133126A (accessed June 2017; url updated July 2019). FHWA. n.d.-b. Roadway Safety Data Program. Webpage: https://safety.fhwa.dot.gov/rsdp/mire.aspx (accessed June 2017). FHWA. 2012. National TIM Responder Training Program. Webpage: https://www.fhwa.dot.gov/goshrp2/Solutions/ Reliability/L12_L32A_L32B/National_Traffic_Incident_Management_Responder_Training_Program (accessed June 2017). FHWA. 2013a. “National Performance Management Research Data Set (NPMRDS) Technical Frequently Asked Questions.” Freight Management and Operations. Webpage: https://ops.fhwa.dot.gov/freight/freight_ analysis/perform_meas/vpds/npmrdsfaqs.htm (accessed June 2017). FHWA. 2013b. National Traffic Incident Management Responder Training Program: Train-the-Trainer Guide. Federal Highway Administration, U.S. Department of Transportation, Washington, D.C. FHWA. 2017a. “Surveillance, Monitoring, and Prediction” Road Weather Management Program. Webpage: https://ops.fhwa.dot.gov/weather/mitigating_impacts/surveillance.htm#esrw (accessed February 2017). FHWA. 2017b. “Traffic Incident Management Benefit-Cost (TIM-BC) Tool.” Federal Highway Administration/ Software. Webpage: https://www.fhwa.dot.gov/software/research/operations/timbc/ (accessed July 24, 2018). FHWA. 2017c. Traffic Incident Management Knowledgebase. Webpage:https://ops.fhwa.dot.gov/eto_tim_pse/ Preparedness/tim/knowledgebase/index.htm (accessed August 2018). Florida Department of Transportation. 1996. “TIM Teams.” Traffic Incident Management. Webpage: http:// www.floridatim.com/Teams.htm (accessed June 2017). Florida Department of Transportation. 2011. “Sunguide Disseminator.” Florida Department of Transportation. Webpage: http://www.fdot.gov/traffic/Newsletters/2011/2011-001-Jan.pdf (accessed June 2017). Florida Department of Transportation. 2016. “NPMRDS.” Florida Department of Transportation. Webpage: http://www.fdot.gov/planning/statistics/multimodaldata/multimodal/National%20Performance%20 Management%20Research%20Data%20Set%20(NPMRDS).pdf (accessed April 2017). Freeze, B. 2017. “Predictive Analytics for TDOT HELP.” Presentation at AASHTO STSMO Meeting (September 14, 2017, Rapid City, SD). Gantz, J.F. 2007. The Expanding Digital Universe: A Forecast of Worldwide Information Growth Through 2010. International Data Corporation, Framingham, MA. Available online: https://www.tobb.org.tr/BilgiHizmetleri/ Documents/Raporlar/Expanding_Digital_Universe_IDC_WhitePaper_022507.pdf. GenCore Candeo, Ltd. 2017. Genesis PULSE in Partnership with Waze. Webpage: https://genesispulse.com/ features/waze/ (accessed June 2017). Gettman D., A. Toppen, K. Hales, A. Voss, S. Engel, and D. El Azhari. 2017. Integrating Emerging Data Sources into Operational Practice—Opportunities for Integration of Emerging Data for Traffic Management and TMCs. FHWA-JPO-18-625 (Final Report). Federal Highway Administration, U.S. Department of Transportation, Washington, D.C. Goodin, D. 2014. “Poorly Anonymized Logs Reveal NYC Cab Drivers’ Detailed Whereabouts.” Ars Technica. Webpage: https://arstechnica.com/tech-policy/2014/06/poorly-anonymized-logs-reveal-nyc-cab-drivers- detailed-whereabouts/ (accessed March 1, 2018). Haynes, L. 2015. Introducing the Data Maturity Framework. Webpage: https://dssg.uchicago.edu/2016/04/28/ introducing-the-data-maturity-framework/ (accessed May 2017). Horridge, M. 2011. A Practical Guide To Building OWL Ontologies, Using Protégé 4 and CO-ODE Tools, Edition 1.3. technical, Manchester: The University of Manchester. Available online: http://mowl-power. cs.man.ac.uk/protegeowltutorial/resources/ProtegeOWLTutorialP4_v1_3.pdf.

128 Leveraging Big Data to Improve Traffic Incident Management Houston, N., C. Baldwin, A. Vann Easton, S. Cyra, M. Hustad, and K. Belmore. 2008. Federal Highway Admin- istration Service Patrol Handbook. FHWA-HOP-08-031. HOTO-1, Federal Highway Administration, U.S. Department of Transportation, Washington, D.C. Huddleston, G. 2016. “Cognitive Analytics Is Helping To Reduce Roadway Fatalities In Tennessee.” Forbes (April 28, 2016). Available online: https://www.forbes.com/sites/ibm/2016/04/28/cognitive-analytics-is- helping-to-reduce-roadway-fatalities-in-tennessee/#46d47fd07825 (accessed February 8, 2018). Ian. 2016. “What Is a Column Store Database?” Database.guide (June 23, 2016). Webpage: http://database.guide/ what-is-a-column-store-database (accessed February 12, 2018). IBM. 2013. What Will We Make of This Moment? 2013 IBM Annual Report. IBM: Armonk, NY. Available online: https://www.ibm.com/annualreport/2013/bin/assets/2013_ibm_annual.pdf. ICIJ. 2016. “Giant Leak of Offshore Financial Records Exposes Global Array of Crime and Corruption.” ICIJ Investigations: The Panama Papers. Webpage: https://panamapapers.icij.org/20160403-panama-papers- global-overview.html (accessed June 2017). International Transport Forum. 2015. Big Data and Transport: Understanding and Assessing Options. Corporate Partnership Board Report. International Transport Forum at the OECD, Paris, France. internetlivestats.com 2016. Internet Live Stats. Webpage: http://www.internetlivestats.com/internet-users/ (accessed June 2017). Iowa State University. 2017. “Iowa State Engineers Dive Into Big Data to Develop Better System to Manage Traf- fic Incidents.” Iowa State University News Service (March 22, 2017). Webpage: http://www.news.iastate.edu/ news/2017/03/22/timeli (accessed June 2017). Issenberg, S. 2012. “How Obama Used Big Data to Rally Voters, Part 1: How President Obama’s Campaign Used Big Data to Rally Individual Voters.” MIT Technology Review (December 16, 2012). Webpage: https://www.technologyreview.com/s/508836/how-obama-used-big-data-to-rally-voters-part-1/ (accessed July 24, 2018). Jin, X., M. S. Hossan, A. Gan, and D. Chen. 2014. “Comprehensive Framework for Planning and Assessment of Traffic Incident Management Programs.” Transportation Research Record, Vol. 2470. Transportation Research Board of the National Academies, Washington, D.C., pp. 1–12. Kanniyappan, R., and B. McQueen. 2014. “What’s the Big Deal about Big Data in Transportation?” Florida Department of Transportation, Data Symposium (Orlando, FL, October 23–24, 2014). Available Online: http://www.fdot.gov/statistics/symposium/2014/bigdatatransport.pdf (accessed November 2016). Kim, M., J. Cobb, M. J. Harrold, K. Malhotra, A. Orso, J. Saltz, S. B. Navathe, A. Post, and T. Kurc. 2012. Efficient Regression Testing of Ontology-Driven Systems. Minneapolis: International Symposium on Software Testing and Analysis. Available online: https://www.researchgate.net/publication/236842047_Efficient_Regression_ Testing_of_Ontology-Driven_Systems. Klieman & Lyons. 2014. “Vehicle Telematics: A Useful Litigation Tool For Attorneys, A Boon To Insurers And The Privacy Concerns Big Data Raises For Us All.” Klieman & Lyons. Webpage: http://www.kliemanlyons.com/ 2014/09/vehicle-telematics-a-useful-litigation-tool-for-attorneys-a-boon-to-insurers-and-the-privacy- concerns-big-data-raises-for-us-all/ (accessed February 12, 2018). Krechmer, D., A. Samano III, P. Beer, and N. Boyd. 2012. Role of Transportation Management Centers in Emergency Operations: Guidebook. FHWA-HOP-12-050. Office of Operations, Federal Highway Administration, U.S. Department of Transportation, Washington, D.C. Available online: https://ops.fhwa.dot.gov/publications/ fhwahop12050/fhwahop12050.pdf. Laroca, R., E. Severo, L. A. Zanlorensi, L. S. Oliveira, G. Resende Goncalves, W. R. Schwartz, and D. Menotti. 2018. “A Robust Real-Time Automatic License Plate Recognition Based on the YOLO Detector.” arXiv. Webpage: https://arxiv.org/pdf/1802.09567.pdf (accessed July 24, 2018). Latonski, J., and J. Ang-Olson. 2006. Simplified Guide to the Incident Command System for Transportation Profes- sionals. FHWA-HOP-06-004. Office of Operations, Federal Highway Administration, U.S. Department of Transportation, Washington, D.C. Lima, J. 2015. “Top 10 Biggest Data Centers from Around the World.” Computer Business Review. Webpage: http://www.cbronline.com/news/data-centre/top-10-biggest-data-centres-from-around-the-world-4545356/ (accessed June 2017). Lohmann, S., V. Link, E. Marbach, and S. Negru. 2014. “WebVOWL: Web-based Visualization of Ontologies.” Presented at 19th International Conference on Knowledge Engineering and Knowledge Management (November 24–28, 2014, Linköping, Sweden). Available online: https://link.springer.com/chapter/ 10.1007%2F978-3-319-17966-7_21. Lokanathan, S., G. E. Kreindler, N. H. Nisansa de Silva, Y. Miyauchi, D. Dhananjaya, and R. Samarajiva. 2016. “The Potential of Mobile Network Big Data as a Tool in Colombo’s Transportation and Urban Planning.” Information Technologies & International Development [Special Issue], 12 (2), 63–73. Ma, J., and T. Lochrane. 2015. User’s Manual for the Traffic Incident Management Benefit-Cost (TIM-BC) Tool Version 1.0.0. Federal Highway Administration, U.S. Department of Transportation, Washington, D.C.

References 129 Available online: https://www.fhwa.dot.gov/publications/research/operations/15059/15059.pdf (accessed August 2018). Ma, J., E. Miller-Hooks, M. Tariverdi, T. Lochrane, F. Zhou, D. Prentiss, K. Hudgins, P. Jodoin, Z. Huang, and M. Hailemariam. 2016. User-Friendly Traffic Incident Management (TIM) Program Benefit-Cost Estimation Tool Version 1.2. Federal Highway Administration, U.S. Department of Transportation, Washington, D.C. Available online: https://www.fhwa.dot.gov/publications/research/operations/16055/16055.pdf. Mailvaganam, H. 2007. “Introduction to OLAP.” Data Warehousing Review. Online: http://www.dwreview.com/ OLAP/Introduction_OLAP.html (accessed June 2017). Marr, B. 2015. “How Big Data and The Internet of Things Improve Public Transport in London.” Forbes (May 27, 2015). Available online: http://www.forbes.com/sites/bernardmarr/2015/05/27/how-big-data-and- the-internet-of-things-improve-public-transport-in-london/#1b0ed2453ab3 (accessed November 2016). Marr, B. 2017. “Really Big Data At Walmart: Real-Time Insights From Their 40+ Petabyte Data Cloud.” Forbes (January 23, 2017). Available online: https://www.forbes.com/sites/bernardmarr/2017/01/23/really- big-data-at-walmart-real-time-insights-from-their-40-petabyte-data-cloud/#7531c7e06c10 (accessed February 13, 2018). Martinelli, J. 2017. “Tennessee Sheriffs Will Receive Technology That Can Help Predict Fatal Crashes.” Nashville Public Radio (October 11, 2017). Available online: http://nashvillepublicradio.org/post/tennessee-sheriffs- will-receive-technology-can-help-predict-fatal-crashes#stream/0 (accessed February 8, 2018). Matrix. 2014. “Police Patrol Beat Evaluation Study.” City of Berkeley. Webpage: https://www.cityofberkeley.info/ uploadedFiles/Police/Level_3_-_General/Berkeley%20Beat%20Structure%20Final%20Report%208-20- 14(1).pdf (accessed May 2017). Nelson, P. 2016. “Just One Autonomous Car Will Use 4,000 GB of Data/Day.” Network World (December 7, 2016). Webpage: http://www.networkworld.com/article/3147892/internet/one-autonomous-car-will-use- 4000-gb-of-dataday.html (accessed July 2017). Nemschoff, M. 2014. “Why the Transportation Industry Is Getting on Board with Big Data & Hadoop.” Map R Technologies, Inc. (August 2014). Webpage: https://www.mapr.com/blog/why-transportation-industry- getting-board-big-data-hadoop. Neumann, C-S. 2015. Big Data Versus Big Congestion: Using Information to Improve Transport. Available online: http://www.mckinsey.com/industries/capital-projects-and-infrastructure/our-insights/big-data-versus- big-congestion-using-information-to-improve-transpo (accessed June 2017). Ng, L. 2014. “Engage Users with Crowdsourced Translation.” OneSky. Blog (September 22, 2014): http://www. oneskyapp.com/blog/how-to-engage-users-with-crowdsourced-translation/ (accessed July 2018). NHTSA. 2012. Traffic Records Program Assessment Advisory. Technical Advisory. U.S. Department of Transpor- tation, Washington, D.C. Available online: https://crashstats.nhtsa.dot.gov/Api/Public/ViewPublication/ 811644. NJ TIM. n.d. “New Jersey TIM Working Groups, TMC CAD [Computer Aided Dispatch] Integration.” Webpage: http://www.njtim.org/NJTIM/Group/GroupLogin. NOAA. 2016. “MADIS.” National Oceanic and Atmospheric Administration. Webpage: https://madis.ncep.noaa. gov/ (accessed February 2017). ODPA. 2010. “Ontology:DOLCE+DnS Ultralite.” Ontology Design Patterns (March 10). Association for Ontology Design & Patterns (ODPA). Webpage: http://ontologydesignpatterns.org/wiki/Ontology: DOLCE+DnS_Ultralite (accessed July 2017). Oerter, J. A. 2010. North Carolina’s Application of the INRIX Data. North Carolina Department of Transportation. Available online: http://www.i95coalition.org/wp-content/uploads/2015/03/TRB_2010_Session_531- JoAnnOeter.pdf?5a9c76 (accessed May 15, 2017). Open Data Institute. n.d. “The Data Spectrum.” Open Data Institute. Webpage: https://theodi.org/data-spectrum (accessed July 2017). Open Knowledge Foundation n.d.-a. “What Is Open Data?” Open Data Handbook. Webpage: http://opendata handbook.org/guide/en/what-is-open-data/ (accessed May 2017). Open Knowledge Foundation. n.d.-b. Open Definition. Online: http://opendefinition.org/ (accessed May 2017). Oracle. 1999. “Oracle8i Designing and Tuning for Performance.” Oracle. Webpage: http://docs.oracle.com/cd/ A87860_01/doc/server.817/a76992/ch3_eval.htm#2680 (accessed June 2017). Oregon DOT. 2018. “Assigned Over 90 Minute Crash Causes.” Workshop graphic (July 2018). Owens, N. D., A. H. Armstrong, C. Mitchell, and R. Brewster. 2009. Federal Highway Administration Focus States Initiative: Traffic Incident Management Performance Measures: Final Report. FHWA-HOP-10-010. Federal Highway Administration, U.S. Department of Transportation, Washington, D.C. Owens, N. D., A. H. Armstrong, P. Sullivan, C. Mitchell, D. Newton, R. Brewster, and T. Trego. 2010. Traffic Inci- dent Management Handbook. FHWA-HOP-10-013. Office of Operations, Federal Highway Administration, U.S. Department of Transportation, Washington, D.C.

130 Leveraging Big Data to Improve Traffic Incident Management Paul, R. 2008. “Gartner: 80% of Commercial Apps to Use Open Source by 2012.” arstechnica.com (February 5, 2008). Webpage: https://arstechnica.com/information-technology/2008/02/gartner-80-percent-of-commercial- software-programs-will-include-open-source-by-2012/. Pecheux, K. K. 2016. Process for Establishing, Implementing, and Institutionalizing a Traffic Incident Management Performance Measurement Program. FHWA-HOP-15-028. Federal Highway Administration, U.S. Depart- ment of Transportation, Washington, D.C. Pecheux, K. K., R. E. Brydia, and J. Holzbach. 2014. “Guidance for Implementation of Traffic Incident Management Performance Measurement.” TIMPM [NCHRP Project 07-20, “Guidance for Implementation of Traffic Incident Management Performance Measurement” website]. Webpage: http://nchrptimpm.timnetwork.org/. Pecheux, K. K., V. Shah, and C. O’Donnell. 2016. Making the Business Case for Traffic Incident Management. FHWA-HOP-16-084. Federal Highway Administration. U.S. Department of Transportation, Washington, D.C. Petricek, T. 2010. “Parallel Programming in F# (III.): Aggregating data.” Thomas Petricek. Blog (September 6, 2010): http://tomasp.net/blog/fsharp-parallel-aggregate.aspx/ (accessed July 2018). Protégé. 2016. Protégé. Webpage: http://protege.stanford.edu/ (accessed July 2017). Rensel, E., D. Lebo, B. Graves, K. Malarich, and C. Yorks. 2012. “Traffic Incident Management Cost Manage- ment and Cost Recovery: Executive-Level Briefing.” Presentation. Federal Highway Administration, U.S. Department of Transportation, Washington, D.C. Avaliable online: https://ops.fhwa.dot.gov/eto_tim_pse/ ppt/tim_cm_cr_exec_brief/tim_cm_cr_exec_brief.pdf (accessed June 2017). Rice, D. 2013. “3 Video Analytics Any Retailer Can Use to Boost Their Bottom Line.” SDM (July 18, 2013). Webpage: http://www.sdmmag.com/articles/89461-video-analytics-any-retailer-can-use-to-boost-their- bottom-line (accessed June 2017). Rocchini, C. 2007. “Graph Betweenness—Creative Commons Attribution-Share Alike 3.0 Unported License.” Wikipedia (April 23, 2007). Webpage: https://commons.wikimedia.org/wiki/File:Graph_betweenness.svg (accessed July 24, 2018). SB. 2016. “Average Cost of Hard Drive Storage.” Statistic Brain Research Institute. Webpage: http://www.statistic brain.com/average-cost-of-hard-drive-storage/ (accessed June 2017). Shaw, R. 2010. “LODE: An Ontology for Linking Open Descriptions of Events.” Linked Events. Webpage: http:// linkedevents.org/ontology/ (accessed June 2017). Shi, Q. and M. Abdel-Aty. 2015. “Big Data Applications in Real-Time Traffic Operation and Safety Monitoring and Improvement on Urban Expressways.” Transportation Research Part C, Vol. 58. Elsevier, Ltd., London, UK, pp. 380–394. Smith, A. 2016. “Wazing 511: How We Integrated Waze Connected Citizens Partnership Data (CCP) into Four State 511 Systems.” Presented at 2016 National Rural ITS Conference (October 3, 2016, Chattanooga, TN). Available online: http://www.national ruralitsconference.org/wp-content/uploads/2016/10/G2_Smith.pdf (accessed June 2017). Socrata, Inc. 2014. “Open Data Maturity Level.” www.socrata.com. Webpage: https://www.slideshare.net/ epsiplatform/big-data-session/6-Open_Data_Maturity_Model_6 (accessed May 2017). Sparks, J., J. Schuh, and A. Smith. 2009. Field Operations Guide for Safety/Service Patrols. FHWA-HOP-10-014. Office of Operations, Federal Highway Administration, U.S. Department of Transportation, Washing- ton, D.C. Stonebreaker, M., and S. Jarr. 2013. “Navigating the Database Universe.” Presentation at GOTOCon: AARHUS International Software Development Conference (January 29, 2013). Available online: https://www.slideshare. net/BigDataCloud/big-data-cloud-meetup-jan-29-2013-mike-stonebraker-of-voltdb (accessed February 2018). Tay, L. 2013. “Inside eBay’s 90PB data warehouse.” IT News (May 10, 2013). Webpage: https://www.itnews.com. au/news/inside-ebays-90pb-data-warehouse-342615 (accessed February 12, 2018). Tennessee Department of Safety and Homeland Security. 2017. “Tennessee Highway Patrol Provides Predictive Analytics Software to All Tennessee Sheriffs’ Offices.” Tennessee Department of Safety and Homeland Secu- rity. Webpage: https://www.tn.gov/safety/news/2017/10/10/tennessee-highway-patrol-provides-predictive- analytics-software-to-all-tennessee-sheriffs—offices.html (accessed October 16, 2018). Thomson, D. and T. Glocer. n.d. “Annual Report 2010.” Thomson Reuters. Available online: http://archive.annual- report.thomsonreuters.com/2010/ (accessed June 2017). University of Chicago. n.d. “Data Maturity Framework Questionnaire.” Center for Data Science and Public Policy. Webpage: http://dsapp.uchicago.edu/wp-content/uploads/2016/04/Data_Maturity_Framework_4.28.16.pdf (accessed May 2017). University of Chicago. 2017. “Data Maturity Framework.” Center for Data Science and Public Policy. Webpage: https://dsapp.uchicago.edu/home/resources/datamaturity/ (accessed May 2017). University of Manchester. 2009. CO-ODE Project. Webpage: http://owl.cs.manchester.ac.uk/research/co-ode/ (accessed October 18, 2018).

References 131 U.S. DOT. 2017a. “DOT|TRCC Data Systems and Attribute Icons.” U.S. Department of Transportation (December 11, 2017). Webpage: https://www.transportation.gov/government/traffic-records/dottrcc- data-systems-and-attribute-icons (accessed July 2018). U.S. DOT. 2017b. MMUCC. Webpage: https://www.transportation.gov/government/traffic-records/ model-minimum-uniform-crash-criteria-mmucc-0 (accessed June 2017). USFA. 2017. U.S. Fire Administration (May). Webpage: https://www.usfa.fema.gov/data/statistics/order_download_ data.html (accessed February 2017). VA Exec. Order No. 58. (February 4, 2013). Commonwealth of Virginia, Office of the Governor. Webpage: http://digitool1.lva.lib.va.us:8881/R/PRTKTK7BT14QPSA7A2524MRX85KUNDVUFPD3LLU5ELGY BANSJV-02299?func=results-jump-full&set_entry=000065&set_number=818011&base=GEN01” http:// digitool1.lva.lib.va.us:8881/R/PRTKTK7BT14QPSA7A2524MRX85KUNDVUFPD3LLU5ELGYBANSJV- 02299?func=results-jump-full&set_entry=000065&set_number=818011&base=GEN01 (accessed May 2019). VA Exec. Order No. 15. (April 24, 2015). Commonwealth of Virginia, Office of the Governor. Webpage: https:// governor.virginia.gov/media/3345/eo-15-updated-4222015ada.pdf (accessed June 2017). Washington State Department of Transportation. 2016a. “Joint Operations Policy Statement.” Washington State Department of Transportation. Webpage: https://www.wsdot.wa.gov/NR/rdonlyres/F7F858A5-4246-4D34- 8C24-5C91A0EB13CC/0/WSDOTWSPWFCJOPS.pdf (accessed June 2017). Washington State Department of Transportation. 2016b. “Washington State.” TIMPM [NCHRP Project 07-20, “Guidance for Implementation of Traffic Incident Management Performance Measurement” website]. Webpage: http://nchrptimpm.timnetwork.org/?page_id=1394 (accessed June 2017). Wiener, G., and A. Braeckel. 2016. Integrating Big Data into Transportation Services. White Paper. Colorado Department of Transportation, Denver, CO. Younas, M. 2013. “How to Really Outsmart Traffic.” Ibuymobile.co.uk (July 9, 2013). Webpage: http://ibuymobile. co.uk/reviews/2013/07/09/how-to-really-outsmart-traffic. Zeng, Q., A. Reddy, A. Lu, and B. Levine. 2015. “Develop New York City Surface Transit Boarding and Alighting Ridership Daily Production Application Using Big Data.” Presented at 94th Annual Meeting of the Trans- portation Research Board, Washington, D.C.