Project: #77 SmartShuttle: Model Based Design and Evaluation of Automated On-Demand Shuttles for Solving the First-Mile and Last-Mile Problem in a Smart City Progress Report - Reporting Period Ending: March 30, 2018 Principal Investigator: Umit Ozguner Status: Active Start Date: June 19, 2017 End Date: Sept. 30, 2018 Research Type: Applied Grant Type: Research Grant Program: FAST Act Grant Cycle: 2017 Mobility21 UTC Progress Report (Last Updated: March 29, 2018, 4:18 p.m.) % Project Completed to Date: 75 % Grant Award Expended: 53 % Match Expended & Document: 88 USDOT Requirements Accomplishments Year 1 Accomplishments (100% complete): - The unified, scalable and replicable architecture that is being used was prepared. - The hardware-in-the-loop automated driving simulator was prepared/updated for use in this project. - Extensive model-in-the-loop and hardware-in-the-loop (HiL) simulations were conducted. - Two Denso DSRC modems were added to the HiL simulator and used to test communication with other vehicles and instrumented traffic lights. Year 2 Accomplishments (50% complete): - Results (architecture) from first year was applied to our newly donated Dash EV neighborhood electric vehicle, converting it to a research vehicle for automated driving. - Our path following and collision avoidance algorithms were scaled and replicated from our Ford Fusion Hybrid research automated driving vehicle to our Dash EV vehicle. - We used our Ford Fusion Hybrid automated vehicle to collect perception sensor data from the OSU campus and are preparing a labeled dataset. We will collect similar data from the Easton Town Center outdoor shopping area in the next 6 month period. - We identified a relatively large and mostly empty parking lot for our proof-of-concept demo. We have also used our parking lot and the lawn area behind our garage for some of the scalability and replicability tests. We did some proof-of-concept demos in our parking lot. We will do one more proof-of-concept demo in the last 6 month period of this project. - We re-created the OSU AV test pilot route in our HiL simulator with other vehicles and created a soft version of our automated driving vehicle that shuttles from our lab to our main center along that pilot AV route. This has demonstrated the effectiveness of our HiL simulator environment for testing automated driving. Impacts The SmartShuttle project impact is on demonstrating a scalable and replicable low speed autonomous shuttle solution for smart cities, especially for the smaller companies that dominate that area. The resulting impact will be more widespread use of autonomous shuttles in smart cities and more mobility choices especially for the first-mile and last-mile problem. The project work until now has already had an impact. Prof. Levent Guvenc and Prof. Bilin Aksun Guvenc were members of the Autonomous Electric Vehicles working group of Smart Columbus and informed group members in Columbus and in OSU of the potential benefits and the accompanying problems of autonomous shuttles used in geo-fenced areas as first and last mile solutions. The project results were helpful in making Smart Columbus and OSU leaders understand more about the capabilities of existing autonomous shuttles and make more informed decisions. We shared project results and the resulting expertise with the OSMI (Ohio State Mobility Initiatives) group where Prof. Levent Guvenc was a member. This, among other developments, led recently to Ohio Department of Transportation's DriveOhio smart mobility program which is one of the results of the continuation of the OSMI group effort. A conference presentation in IEEE Systems, Man and Cybernetics 2017 and a keynote speech in the 2017 SAE ADAS to Automated Driving Symposium were used to inform the public about project results. Other Accepted Conference Publications Acknowledging Project Support (not yet presented, paper will be shared in final report): Cantas, M.R., Guvenc, L., “Camera and GPS Fusion for Automated Lane Keeping Application,” WCX18: SAE World Congress Experience, April 10-12, Detroit, Michigan, Active Safety: Systems and Sub Systems, SAE Paper Number 2018-01-0608. https://www.sae.org/publications/technical-papers/content/2018-01-0608/ Wang, H., Guvenc, L., 2018, “Use of Robust DOB/CDOB Compensation to Improve Autonomous Vehicle Path Following Performance in the Presence of Model Uncertainty, CAN Bus Delays and External Disturbances,” WCX18: SAE World Congress Experience, April 10-12, Detroit, Michigan, Intelligent Vehicle Initiative, SAE Paper Number 2018-01-1086. Bowen, W., Gelbal, S.Y., Aksun-Guvenc, L., Guvenc, L., 2018, “Localization and Perception for Control and Decision Making of a Low Speed Autonomous Shuttle in a Campus Pilot Deployment,” WCX18: SAE World Congress Experience, April 10-12, Detroit, Michigan, Driver Assistance Systems: Algorithms, Applications and Electronic Sensing, SAE Paper Number 2018-01-1182. https://www.sae.org/publications/technical-papers/content/2018-01-1182/ Submitted Conference Papers Acknowledging Project Support : Sheng, Zhu, Gelbal, S.Y., Li, X., Cantas, M.R., Aksun- Guvenc, B., Guvenc, L., 2018, “Parameter Space and Model Regulation based Robust, Scalable and Replicable Lateral Control Design for Autonomous Vehicles,” 57th IEEE Conference on Decision and Control, Miami Beach, Florida, under review. Website pages with stories related to SmartShuttle: Road to smart mobility means merging minds, Chronicle of Higher Education https://www.chronicle.com/paid-article/Road-to-smart-mobility-means/93 Columbus: Driverless Destination https://mae.osu.edu/news/2017/10/columbus-driverless-destination Driving Toward an Automated Future, Together https://car.osu.edu/news/2017/09/driving-toward-automated-future-together Avoiding pedestrian collisions in a future of automated cars https://car.osu.edu/news/2017/09/avoiding-pedestrian-collisions-future-automated-cars YouTube Videos: DASH Low Speed Autonomous Shuttle https://youtu.be/K9dCd4ofYxA Realistic Simulation of Autonomous Shuttle on OSU AV Pilot Test Route https://youtu.be/_yWiZWP0Rag Automatically Labeled Camera Data on OSU AV Pilot Test Route https://youtu.be/E63lKSIFmQI New Partners There were no new partners. Innova donated a new Dash EV neighborhood electric vehicle which we are using in the second year of the project. Issues There are no technical issues related to this project. We will be finishing the project at the planned time. There were coordination issues between OSU and CMU due to late signing of sub-contracts that resulted in late approval and delayed transfer of OSU funding. First year project funding was available as year 2 of the project was starting. There were similar delays in the transfer of year 2 funding. We worked hard to make sure that this issue did not affect the technical performance of the project. The reporting of USDOT and cost share used funds is therefore for the two year budget of the project. The full two year completion rate of the project is 75% and will increase to 100% by the end of year 2 (next 6 months) and the full budget including cost share will be used by that time.