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Use of Hardware in the Loop (HIL) Simulation for Developing Connected Autonomous Vehicle (CAV) Applications
Technical Paper
2019-01-1063
ISSN: 0148-7191, e-ISSN: 2688-3627
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English
Abstract
Many smart cities and car manufacturers have been investing in Vehicle to Infrastructure (V2I) applications by integrating the Dedicated Short-Range Communication (DSRC) technology to improve the fuel economy, safety, and ride comfort for the end users. For example, Columbus, OH, USA is placing DSRC Road Side Units (RSU) to the traffic lights which will publish traffic light Signal Phase and Timing (SPaT) information. With DSRC On Board Unit (OBU) equipped vehicles, people will start benefiting from this technology. In this paper, to accelerate the V2I application development for Connected and Autonomous Vehicles (CAV), a Hardware in the Loop (HIL) simulator with DSRC RSU and OBU is presented. The developed HIL simulator environment is employed to implement, develop and evaluate V2I connected vehicle applications in a fast, safe and cost-effective manner. The prepared simulator allows realistic, real-time evaluation of mobility and fuel economy benefits over simulated actual routes in a safe lab setting before actual deployment in an experimental vehicle. To show the capabilities of the designed HIL simulator, Green-Wave algorithm, which lowers the idling time at the signalized intersections and improves fuel economy, is simulated.
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Cantas, M., Kavas, O., Tamilarasan, S., Gelbal, S. et al., "Use of Hardware in the Loop (HIL) Simulation for Developing Connected Autonomous Vehicle (CAV) Applications," SAE Technical Paper 2019-01-1063, 2019, https://doi.org/10.4271/2019-01-1063.Data Sets - Support Documents
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References
- U.S. Environmental Protection Agency https://www3.epa.gov/climatechange/ghgemissions/sources/transportation.html 2016
- Hoed , R.V.D. , Harmelink , M. , and Joosen , S 2006 https://www.ecofys.com/files/files/aid-ee-2006-evaluation-ecodrive-netherlands.pdf
- IEA http://www.iea.org/textbase/nppdf/free/2008/japan2008.pdf 2012
- National Transportation Library http://ntl.bts.gov/lib/44000/44600/44661/FHWA-JPO-11-139_AERIS_Applications_SOP_Report-FINAL_081211-REV_9-13-11.pdf
- Wada , T. , Yoshimura , K. , and Doi , S.I. Proposal of an Eco-Driving Assist System Adaptive to Driver’s Skill Proceedings of the International IEEE Conference on Intelligent Transportation Systems Washington, DC Oct. 5-7 2011 1880 1885
- Durbin , T.D. , Miller , J.W. , Johnson , K. , Hajbabaei , M. et al. 2011
- Hu , J. , Shao , Y. , Sun , Z. , Wang , M. et al. Integrated Optimal Eco-Driving on Rolling Terrain for Hybrid Electric Vehicle with Vehicle-Infrastructure Communication Transp. Res. Part C 68 228 244 2016
- Zegeye , S.K. , De Schutter , B. , Hellendoorn , J. , and Breunesse , E.A Variable Speed Limits for Green Mobility Proceedings of the 2011 14th International IEEE Conference on Intelligent Transportation Systems (ITSC) Washington, DC 2011 2174 2179
- Ghassan , A. Integrated Adaptive-Signal Dynamic-Speed Control of Signalized Arterials J. Transp. Eng. 128 447 451 2002
- Barth , M. and Boriboonsomsin , K. Energy and Emissions Impacts of a Freeway-Based Dynamic Eco-Driving System Transp. Res. Part D 14 400 410 2009
- Saboohi , Y. and Farzaneh , H. Model for Developing an Eco-Driving Strategy of a Passenger Vehicle Based on the Least Fuel Consumption Appl. Energy 86 1925 1932 2009
- Mandava , S. , Boriboonsomsin , K. , and Barth , M Arterial Velocity Planning Based on Traffic Signal Information under Light Traffic Conditions Proceedings of the 2009 12th International IEEE Conference on Intelligent Transportation Systems St. Louis, MO Oct. 4-7 2009 1 6
- Kamal , M. , Mukai , M. , and Murata , J. On Board Eco-Driving System for Varying Road-Traffic Environments Using Model Predictive Control IEEE Int. Conf. Control Appl. 58 1636 1641 2010
- Rakha , H. and Kamalanathsharma , R.K. Eco-Driving at Signalized Intersections Using V2I Communication Proceedings of the International IEEE Conference on Intelligent Transportation Systems Washington, DC Oct. 5-7 2011 341 346
- Mensing , F. , Trigui , R. , and Bideaux , E Vehicle Trajectory Optimization for Application in ECO-Driving Proceedings of the IEEE Vehicle Power and Propulsion Conference Chicago, IL Sept. 6-9 2011 1 6
- Gelbal , Ş.Y. , Cantaş , M.R. , Tamilarasan , S. , Güvenç , L. et al. A Connected and Autonomous Vehicle Hardware-in-the-Loop Simulator for Developing Automated Driving Algorithms 2017 IEEE International Conference on Systems, Man, and Cybernetics (SMC) Banff Center, Banff, Canada 2017
- Altan , O.D. , Wu , G. , Barth , M.J. , Kanok , B. et al. GlidePath: Eco-Friendly Automated Approach and Departure at Signalized Intersections IEEE Transactions on Intelligent Vehicles 2 4 Dec 2017
- Treiber , M. , Hennecke , A. , and Helbing , D. Congested Traffic States in Empirical Observations and Microscopic Simulations Physical Review E 62 2 1805 1823 2000
- Tubaishat , M. , Shang , Y. , and Hongchi , S. Adaptive Traffic Light Control with Wireless Sensor Networks 4th IEEE Consumer Communications and Networking Conference, 2007 (CCNC 2007) IEEE 2007 187 191
- Eric , N. and Bullock , D. Impact of Emergency Vehicle Preemption on Signalized Corridor Operation: An Evaluation Transportation Research Record: Journal of the Transportation Research Board 1727 1 11 2000