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Bench-marking Computational Performance of Dynamic Programming For Speed Profiling and Fuel Efficiency of Autonomous-capable HEV

Ohio State University-Wilson Perez, Amit Ruhela, Punit Tulpule
  • Technical Paper
  • 2020-01-0968
To be published on 2020-04-14 by SAE International in United States
Dynamic programming has been used for optimal control of hybrid powertrain and vehicle speed optimization particularly in design phase for over a couple of decades. With the advent of autonomous and connected vehicle technologies, automotive industry is getting closer to implementing predictive optimal control strategies in real time applications. The biggest challenge in implementation of optimal controls is the limitation on hardware which includes processor speed, IO speed, and random access memory. Due to the use of autonomous features, modern vehicles are equipped with better onboard computational resources. In this paper we present a comparison between multiple hardware options for dynamic programming. The optimal control problem considered, is the optimization of travel time and fuel economy by tuning the torque split ratio and vehicle speed while maintaining charge sustaining operation. The system has two states - battery state of charge and vehicle speed, and two inputs namely, total torque and torque split ratio. First, we develop a Matlab® based program to solve the optimal control problem. The Matlab® code is optimized for performance and memory…
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Model-Based Design of a Hybrid Powertrain Architecture with Connected and Automated Technologies for Fuel Economy Improvements

Ohio State University-Shawn Midlam-Mohler
Center For Automotive Research-Kristina Kuwabara, Jacqueline Karl-DeFrain
  • Technical Paper
  • 2020-01-1438
To be published on 2020-04-14 by SAE International in United States
Simulation-based design of connected and automated hybrid-electric vehicles is a challenging problem. The design space is large, the systems are complex, and the influence of connected and autonomous technology on the process is a new area of research. The Ohio State University EcoCAR Mobility Challenge team developed a comprehensive design and simulation approach as a solution. This paper covers the detailed simulation work conducted after initial design space reduction was performed to arrive at a P0-P4 hybrid vehicle with a gasoline engine. Two simulation environments were deployed in this strategy, each with unique advantages. The first was Autonomie, which is a commercial software tool that is wellvalidated through peer-reviewed studies. This allowed the team to evaluate a wide range of components in a robust simulation framework. To ensure consistent evaluation between potential architectures, the team paired Autonomie with a particle swarm optimizer to automatically calibrate the hybrid supervisory control and achieve near optimal control calibrations. The team also utilized a dynamic programming model environment to evaluate the fuel economy impact of connected and autonomous systems…
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Hardware-in-the-Loop and Public Road Testing of RLVW and GLOSA Connected Vehicle Applications

Ohio State University-Sukru Yaren Gelbal, Mustafa Ridvan Cantas, Bilin Aksun Guvenc, Levent Guvenc
Camp LLC-Jayendra Parikh
  • Technical Paper
  • 2020-01-1379
To be published on 2020-04-14 by SAE International in United States
Each year, large number of traffic accidents with a large number of injuries and fatalities occur. To reduce these accidents, automotive companies have been developing newer and better active and passive safety measures to increase the safety of passengers. With the developments in connected vehicle infrastructure on the roads and on-board-units for Vehicle to Everything (V2X) connectivity in newer vehicles, V2X communication offers possibilities for preventing accidents as V2X equipped vehicles have situational awareness of other vehicles and road users around them through Vehicle to Vehicle (V2V) and Vehicle to Pedestrian (V2P) communication, and signal phase and timing and map information on signalized intersections through Vehicle to Infrastructure (V2I) communication. Therefore, vehicle on-board computers can calculate an optimal speed profile for fuel economy purposes or prevent crashes related to red light violations. This paper addresses these two main advantages, firstly by developing and using Hardware-in-the-Loop (HIL) simulator testing and experimental vehicle testing environments of an algorithm for preventing red light violation, called Red Light Violation Warning (RLVW). The HIL simulator used in the testing is…
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Engine-in-the-loop study of a hierarchical predictive online controller for connected and automated heavy-duty vehicles

Ohio State University-Stephen Boyle, Stephanie Stockar
Clemson University-Mohammad Naghnaeian
  • Technical Paper
  • 2020-01-0592
To be published on 2020-04-14 by SAE International in United States
This paper presents a cohesive set of engine-in-the-loop (EIL) studies examining the use of hierarchical model-predictive control for fuel consumption minimization in a class-8 heavy-duty truck intended to be equipped with Level-1 connectivity/automation. This work is motivated by the potential of connected/automated vehicle technologies to reduce fuel consumption in both urban/suburban and highway scenarios. We begin by presenting a hierarchical model-predictive control scheme that optimizes multiple chassis and powertrain functionalities for fuel consumption. These functionalities include: vehicle routing, arrival/departure at signalized intersections, speed trajectory optimization, platooning, predictive optimal gear shifting, and engine demand torque shaping. The primary optimization goal is to minimize fuel consumption, but the hierarchical controller explicitly accounts for other key objectives/constraints, including operator comfort and safe inter-vehicle spacing. The main focus of this work is on a sequence of EIL studies intended for evaluating the computational costs and fuel savings associated with these algorithms. These EIL studies involve both the open-loop playback of simulation-based evaluation studies as well as the closed-loop validation of the proposed control strategies, both individually and combined. These…
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A cybersecurity testbed for connected and autonomous vehicles

Ohio State University-Matthew Appel, Pradeep Sharma Oruganti, Qadeer Ahmed, Jaxon Wilkerson, Rubanraj Sekar
  • Technical Paper
  • 2020-01-1291
To be published on 2020-04-14 by SAE International in United States
Connectivity and autonomy in vehicles promise improved efficiency, safety and comfort. The increasing use of embedded systems and the cyber element bring with them many challenges regarding cyberattacks which can seriously compromise driver and passenger safety. Beyond penetration testing, assessment of the security vulnerabilities of a component must be done through the design phase of its life cycle. This paper describes the development of a benchtop testbed which allows for the safety and security evaluations of components with all capabilities from Model-in-loop to Software-in-loop to Hardware-in-loop testing. Environment simulation is obtained using the AV simulator, CARLA which provides realistic scenarios and sensor information such as Radar, Lidar etc. MATLAB runs the vehicle, powertrain and control models of the vehicle allowing for the implementation and testing of realistic models. Real-time simulation and connectivity with external components is obtained through the use of a Speedgoat real-time machine. A fluid integration between the multiple software parts are realized using Robotic-Operating-System (ROS). Communication with external hardware can be achieved through different network protocols such as CAN, LIN, SAE J1939…
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Hardware-in-the-Loop, Traffic-in-the-Loop and Software-in-the-Loop Autonomous Vehicle Simulation for Mobility Studies

Ohio State University-Karina Meneses Cime, Mustafa Ridvan Cantas, Garrett Dowd, Levent Guvenc, Bilin Aksun Guvenc
Ford Motor Company-Archak Mittal, Adit Joshi, James Fishelson
  • Technical Paper
  • 2020-01-0704
To be published on 2020-04-14 by SAE International in United States
We are interested in finding and analyzing the relevant parameters affecting traffic flow when introducing Autonomous Vehicles for ride hailing applications and Autonomous Shuttles for circulator applications in geo-fenced urban areas. Different scenarios have been created in traffic simulation software that model the different levels of autonomy, traffic density, routes, and other traffic elements. Similarly, software that specializes in vehicle dynamics, physical limitations, and vehicle control has been used to closely simulate such scenarios. On the other hand, software for autonomous entities is also continuously improved. However, benchmarks for such software usually run in isolation from other factors such as the ones mentioned above. Yet, in order to effectively study the effects of the introduction of autonomous agents into city streets, all these factors must be considered. For these reasons, different simulation tools are needed to converge into a single simulation environment. We create a realistic simulator with Hardware-in-the-Loop (HiL), Traffic-in-the-Loop (TiL), and Software in-the-Loop (SiL) simulation capabilities. Our work merges the traffic simulation software Vissim to create realistic traffic, the vehicle dynamic simulation software…
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Development of a MiL/HiL/AViL Approach to Pre-Deployment Testing of Low Speed Urban Road Autonomous Driving in the Context of the Smart Columbus Autonomous Shuttle Deployment Sites

Ohio State University-Xinchen Li, Aravind Chandradoss Arul Doss, Bilin Aksun Guvenc, Levent Guvenc
  • Technical Paper
  • 2020-01-0706
To be published on 2020-04-14 by SAE International in United States
Low speed autonomous shuttles emulating SAE Level L4 automated driving using human driver assisted autonomy have been operating in geo-fenced areas in several cities in the US and the rest of the world. These autonomous vehicles (AV) are operated by small to mid-sized technology companies that do not have the resources of automotive OEMs for carrying out exhaustive, comprehensive testing of their AV technology solutions before public road deployment. Yet, we have a large number of public road deployments of these AV shuttles including two deployment sites in Columbus through the Department of Transportation funded Smart City Challenge project named Smart Columbus. Due to the low speed of operation and hence not operating on roads containing highways, the base vehicles of these AV shuttles are not required to go through rigorous certification tests. The way these vehicles driver assisted AV technology is tested and allowed for public road deployment is continuously evolving but is not standardized and shows differences between different states where these vehicles operate. Safety of operation is achieved by first limiting the…
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The roles of vehicle seat cushion stiffness and length in child restraint system (CRS) performance

Ohio State University-Julie Mansfield, Yun-Seok Kang
Transportation Research Center Inc.-HyunJung Kwon
  • Technical Paper
  • 2020-01-0977
To be published on 2020-04-14 by SAE International in United States
The objective is to determine whether responses and injury risks for pediatric occupants in child restraint systems (CRS) are affected by vehicle seat cushion stiffness and fore/aft length. Eighteen sled tests were conducted using the FMVSS 213 frontal pulse (48 km/h). Seats from a recent model year vehicle were customized by the manufacturer with three different levels of cushion stiffness: compliant, mid-range, and stiff. Each stiffness level was quantified using ASTM D 3574-08 and all were within the realistic range of modern production seats. The usable length of each seat cushion was manipulated using foam spacers provided by the manufacturer. Two different seat lengths were examined: short (34.0 cm) and long (43.5 cm). Three different types of CRS were tested with size-appropriate anthropomorphic test devices (ATDs): rear-facing (RF) CRS with 12-month-old CRABI, forward-facing (FF) CRS with Hybrid III 3-year-old, and high-back booster with Hybrid III 6-year-old. Each CRS, vehicle seat (including cushion and frame), seat belt webbing and buckle were replaced after every test. ATD kinematic and kinetic data were compared across seat cushion lengths…
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The Effects of Varying Penetration Rates of L4-L5 Autonomous Vehicles on Fuel Efficiency and Mobility of Traffic Networks

Ohio State University-Ozgenur Kavas-Torris, Mustafa Ridvan Cantas, Karina Meneses Cime, Bilin Aksun Guvenc, Levent Guvenc
  • Technical Paper
  • 2020-01-0137
To be published on 2020-04-14 by SAE International in United States
With the current drive of automotive and technology companies towards producing vehicles with higher levels of autonomy, it is inevitable that there will be an increasing number of SAE level L4-L5 autonomous vehicles (AVs) on roadways in the near future. The effect of this gradually increasing penetration of AVs on mobility, viewed as traffic congestion or traffic flow efficiency in this paper, and fuel efficiency improvement for the individual AV and for the whole road network with a mixed traffic of AVs and non-AVs is currently not well known. Microscopic traffic simulators that simulate realistic traffic flow are crucial in studying, understanding and evaluating the possible effects of having a higher number of autonomous vehicles (AVs) in traffic under realistic mixed traffic conditions including both autonomous and non-autonomous vehicles. In this paper, L4-L5 AVs with varying penetration rates in total traffic flow were simulated using the microscopic traffic simulator Vissim on urban, mixed and freeway roadways to study the effect of penetration rate on fuel consumption and efficiency of traffic flow. The roadways used in…
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Performance Evaluation of the Pass at Green Connected Vehicle V2I Application Using Simulation, Dynamometer and Track Testing

Ohio State University-Ozgenur Kavas-Torris, Mustafa Ridvan Cantas, Sukru Yaren Gelbal, Levent Guvenc
  • Technical Paper
  • 2020-01-1380
To be published on 2020-04-14 by SAE International in United States
In recent years, the trend in the automotive industry has been favoring the reduction of fuel consumption in vehicles with the help of new and emerging technologies, such as Vehicle to Infrastructure (V2I), Vehicle to Vehicle (V2V) and Vehicle to Everything (V2X) communication. As the world of transportation gets more and more connected through these technologies, the need to implement algorithms with V2I capability is amplified. In this paper, an algorithm called Pass at Green (PaG), utilizing V2I to modify the speed profile of a vehicle to decrease fuel consumption has been studied. PaG uses Signal Phase and Timing (SPaT) information acquired from upcoming traffic lights, which are the current phase of the upcoming traffic light and the remaining time that the phase stays active. Then, PaG modifies the speed of the vehicle by accelerating, keeping its speed constant or decelerating to decrease fuel consumption, minimize idling time and reduce the likelihood of catching a red light in an intersection. As presented in this paper, the fuel economy benefit achieved by the PaG algorithm was…