Extraction of Vehicle CAN Bus Data for Roadway Condition Monitoring
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JOINT TRANSPORTATION RESEARCH PROGRAM INDIANA DEPARTMENT OF TRANSPORTATION AND PURDUE UNIVERSITY Extraction of Vehicle CAN Bus Data for Roadway Condition Monitoring Howell Li, Enrique Saldivar-Carranza, Jijo K. Mathew, Woosung Kim, Jairaj Desai, Timothy Wells, Darcy M. Bullock SPR-4323 • Report Number: FHWA/IN/JTRP-2020/20 • DOI: 10.5703/1288284317212 RECOMMENDED CITATION Li, H., Saldivar-Carranza, E., Mathew, J. K., Kim, W., Desai, J., Wells, T., & Bullock, D. M. (2020). Extraction of vehicle CAN bus data for roadway condition monitoring (Joint Transportation Research Program Publication No. FHWA/IN/JTRP- 2020/20). West Lafayette, IN: Purdue University. https://doi.org/10.5703/1288284317212 AUTHORS Howell Li JTRP Senior Software Engineer Lyles School of Civil Engineering Purdue University (765) 494-9601 [email protected] Corresponding Author Enrique Saldivar-Carranza, Graduate Research Assistant Jijo K. Mathew, PhD, Woosung Kim, Jairaj Desai, GraduateTransportation Research Assistant Research Engineer Lyles School of CivilSoftware Engineering Engineer Purdue University Timothy Wells, Highway Engineer Supervisor 4 Indiana Department of Transportation Darcy M. Bullock, PhD, PE Lyles Family Professor of Civil Engineering Lyles School of Civil Engineering Purdue University Principal Investigator JOINT TRANSPORTATION RESEARCH PROGRAM The Joint Transportation Research Program serves as a vehicle for INDOT collaboration with higher education in- stitutions and industry in Indiana to facilitate innovation that results in continuous improvement in the planning, https://engineering.purdue.edu/JTRP/index_html design, construction, operation, management and economic efficiency of the Indiana transportation infrastructure. Published reports of the Joint Transportation Research Program are available at http://docs.lib.purdue.edu/jtrp/. NOTICE - The contents of this report reflect the views of the authors, who are responsible for the facts and the accuracy of the- tiondata orpresented regulation. herein. The contents do not necessarily reflect the official views and policies of the Indiana Depart ment of Transportation or the Federal Highway Administration. The report does not constitute a standard, specifica TECHNICAL REPORT DOCUMENTATION PAGE 1. Report No. 2. Government Accession No. 3. Recipient’s Catalog No. FHWA/IN/JTRP-2020/20 4. Title and Subtitle 5. Report Date Extraction of Vehicle CAN Bus Data for Roadway Condition Monitoring August 2020 6. Performing Organization Code 7. Author(s) 8. Performing Organization Report No. Howell Li, Enrique Saldivar-Carranza, Jijo K. Mathew, Woosung Kim, Jairaj Desai, FHWA/IN/JTRP-2020/20 Timothy Wells, and Darcy M. Bullock 9. Performing Organization Name and Address 10. Work Unit No. Joint Transportation Research Program (SPR) Hall for Discovery and Learning Research (DLR), Suite 204 11. Contract or Grant No. 207 S. Martin Jischke Drive SPR-4323 West Lafayette, IN 47907 12. Sponsoring Agency Name and Address 13. Type of Report and Period Covered Indiana Department of Transportation Final Report State Office Building 14. Sponsoring Agency Code 100 North Senate Avenue Indianapolis, IN 46204 15. Supplementary Notes Conducted in cooperation with the U.S. Department of Transportation, Federal Highway Administration. 16. Abstract Obtaining timely information across the state roadway network is important for monitoring the condition of the roads and operating characteristics of traffic. One of the most significant challenges in winter roadway maintenance is identifying emerging or deteriorating conditions before significant crashes occur. For instance, almost all modern vehicles have accelerometers, anti- lock brake (ABS) and traction control systems. This data can be read from the Controller Area Network (CAN) of the vehicle, and combined with GPS coordinates and cellular connectivity, can provide valuable on-the-ground sampling of vehicle dynamics at the onset of a storm. We are rapidly entering an era where this vehicle data can provide an agency with opportunities to more effectively manage their systems than traditional procedures that rely on fixed infrastructure sensors and telephone reports. This data could also reduce the density of roadway weather information systems (RWIS), similar to how probe vehicle data has reduced the need for micro loop or side fire sensors for collecting traffic speeds. 17. Key Words 18. Distribution Statement controller area network, CAN bus, on board diagnostics, enhanced No restrictions. This document is available through the probe data, winter roadway condition monitoring, inclement National Technical Information Service, Springfield, VA weather conditions, wheel slip, traction control, anti-lock brake 22161. (ABS) systems 19. Security Classif. (of this report) 20. Security Classif. (of this page) 21. No. of Pages 22. Price Unclassified Unclassified 44 including appendices Form DOT F 1700.7 (8-72) Reproduction of completed page authorized EXECUTIVE SUMMARY systems, drivetrain, accelerometer, steering, climate, lighting, and emergency systems) into existing dashboard interfaces for identifying winter road and hazardous conditions. Introduction 3. The team found braking and wheel counter data to be the most useful for early indication of winter conditions. Obtaining timely information across the state roadway network 4. The volume and velocity of the CAN Bus data will be the is important for monitoring the condition of the roads and the most challenging to implement over a large fleet as many operating characteristics of traffic. One of the most significant signals are generated at millisecond fidelity. To help with the challenges in winter roadway maintenance is identifying emerging scaling process, only relevant signals from the vehicle should or deteriorating conditions before significant crashes occur. For be transmitted to the agency using efficient protocols to a instance, almost all modern vehicles have accelerometers, anti- scaled-out, high-performance back-office system, or cloud lock brake (ABS), and traction control systems. This data can be data center. read from the Controller Area Network (CAN) of the vehicle and, 5. A few emerging off-the-shelf products from automotive combined with GPS coordinates and cellular connectivity, can manufacturers and equipment suppliers are starting to provide valuable on-the-ground sampling of vehicle dynamics at provide roadway metrics from CAN Bus data. Continued the onset of a storm. We are rapidly entering an era where this engagement and collaboration with these industry partners vehicle data can provide an agency with opportunities to more will enable INDOT to make use of and transition to scalable, effectively manage their systems than traditional procedures that commercially-supported, state-of-the-art platforms. rely on fixed infrastructure sensors and telephone reports. This data could also reduce the density of roadway weather informa- tion systems (RWIS), similar to how probe vehicle data has Implementation reduced the need for micro loop or side fire sensors for collecting traffic speeds. Near- and medium-term recommendations are as follows, with action items for each term: Methods 1. Near-term (6–18 months) Over the course of the project, the research team engaged a a. Develop relationships with CV data providers to number of industry partners to collaborate, consult experts, test integrate hard braking events into Traffic Management equipment, and share findings of the research with stakeholders. Center (TMC) operations. Vehicles from three different manufacturers were used for testing b. Develop relationships with CV data providers to CAN data elements in nine categories. A system for receiving, integrate loss of friction data (ABS or traction control) transmitting, and processing the CAN data was piloted using a into TMC operations and coordinate with winter weather vehicle interface (VI) with an embedded computer, cellular maintenance colleagues. networks, and back-office data system at Purdue University. c. Develop relationships with CV data providers to identify A series of dashboards for transforming and displaying the data locations of pavement distress or work zone irregularities were developed as part of the user interface deliverables. using vehicle pitch, roll, and steering. Findings 2. Medium-term (18 months or longer) The findings of this research were as follows: a. Evaluate the feasibility of capturing weather-related data such as windshield wipers, defroster settings, and 1. The team successfully piloted an integrated CAN Bus road temperature readings to enhance TMC and winter monitoring system to identify roadway hazards in real-time weather management activities. during winter events. This enables data-driven decision- b. Develop plans to integrate this data into business making for practitioners. processes used by central office, districts, sub-districts, 2. The team successfully identified, tested, and integrated CAN and units. The winter weather data is particularly Bus data elements from nine categories (speed, GPS, braking valuable to sub-districts and units. CONTENTS 1. PROJECT OVERVIEW . ......................................................... 1 1.1Introduction................................................................ 1 1.2DisseminationofResearchResults................................................. 2 2. CAN BUS DATA ELEMENTS..................................................... 2 2.1Speed..................................................................... 2 2.2GPS.....................................................................