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The current approach for new Advanced Driver Assistance System (ADAS) and Connected and Automated Driving (CAD) function development involves a significant amount of public road testing which is inefficient due to the number miles that need to be driven for rare and extreme events to take place, thereby being very costly also, and unsafe as the rest of the road users become involuntary test subjects. A new development, evaluation and demonstration method for safe, efficient, and repeatable development, demonstration and evaluation of ADAS and CAD functions called Vehicle-in-Virtual –Environment (VVE) was recently introduced as a solution to this problem. The vehicle is operated in a large, empty, and flat area during VVE while its localization and perception sensor data is fed from the virtual environment with other traffic and rare and extreme events being generated as needed.

Autonomous vehicle technology has been developing rapidly in recent years. Vehicle parametric uncertainty in the vehicle model, variable time delays in the CAN bus based sensor and actuator command interfaces, changes in vehicle sped, sensitivity to external disturbances like side wind and changes in road friction coefficient are factors that affect autonomous driving systems like they have affected ADAS and active safety systems in the past. This paper presents a robust control architecture for automated driving systems for handling the abovementioned problems. A path tracking control system is chosen as the proof-of-concept demonstration application in this paper. A disturbance observer (DOB) is embedded within the steering to path error automated driving loop to handle uncertain parameters such as vehicle mass, vehicle velocities and road friction coefficient and to reject yaw moment disturbances.

Typically, the combustion analysis for S.I. engines is limited to the determination of the apparent heat release from in-cylinder pressure measurements, effectively using a single zone approach with constant properties determined at some average temperature. In this paper, we follow an approach consistent with the engine modeling approach (i.e., reverse modeling) to extract heat release rate from combustion pressure data. The experimental data used here solely consists of quantities measured in a typical engine dynamometer tests, namely the crank-angle resolved cylinder pressure, as well as global measurements of the A/F ratio, engine speed, load, EGR, air mass flow rate and temperature and exhaust emissions. We then perform a two-zone, crank-angle resolved analysis of the pressure data using variable composition and properties.

In this study, an adaptive control mechanism is proposed to design a silencer applying variable volume resonator concept. Transfer matrix method is used to calculate the transmission loss and evaluate acoustic performance of the proposed mechanism. Effects of damping factor, area ratio of expansion chambers are examined first for a fixed double chamber resonator. Then a two-dimensional search scheme is developed to find optimal piston position that achieves maximum transmission loss with minimal effort. This study shows that the proposed adaptive silencer can efficiently attenuate noise when comparing with a conventional fixed resonator.

The Ohio State University Center for Intelligent Transportation Research (CITR) has developed three automated vehicles demonstrating advanced cruise control, automated steering control for lane keeping, and autonomous behavior including automated stopping and lane changes in reaction to other vehicles. Various sensors were used, including a radar reflective stripe system and a vision based system for lane position sensing, a radar system and a scanning laser rangefinding system for the detection of objects ahead of the vehicle, and various supporting sensors including side looking radars and an angular rate gyroscope. These vehicles were demonstrated at the National Automated Highway System Consortium (NAHSC) 1997 Technical Feasibility Demonstration in a scenario involving mixed autonomous and manually driven vehicles. This paper describes the demonstration, the vehicle sensing, control, and computational hardware, and the vehicle control software.

This paper describes the mechanical design of a Suspension Parameter Identification Device and Evaluation Rig (SPIDER) for wheeled military vehicles. This is a facility used to measure quasi-static suspension and steering system properties as well as tire vertical static stiffness. The machine operates by holding the vehicle body nominally fixed while hydraulic cylinders move an “axle frame” in bounce or roll under each axle being tested. The axle frame holds wheel pads (representing the ground plane) for each wheel. Specific design considerations are presented on the wheel pads and the measurement system used to measure wheel center motion. The constraints on the axle frames are in the form of a simple mechanism that allows roll and bounce motion while constraining all other motions. An overview of the design is presented along with typical results.

With increasing demands to reduce emissions from internal combustion engines, engine manufacturers are forced to seek out new technology. One such technology employed primarily in the diesel and two-stroke engine community is direct-injection (DI). Direct injection has shown promising results in reduction of CO and NOx for both two- and four-stroke engines. While having been used for several years in the diesel industry, direct injection has been scrutinized for an inability to meet future requirements to reduce particulate matter emissions. Direct injection has also came under fire for complicating fuel delivery systems, thus making it cost prohibitive for small utility engine manufacturers. Recent research shows that the application of piezo-driven actuators has a positive effect on soot formation reduction for diesel engines and as this paper will distinguish, has the ability to simplify direct injection fuel delivery systems in general.

The evolution of the flow field inside an IC engine during the intake stroke was studied using 2 different experimental techniques, namely the 2–D Particle Image Velocimetry (2–D PIV) and 3–D Particle Tracking Velocimetry (3–D PTV) techniques. Both studies were conducted using a water analog engine simulation rig. The head tested was a typical pent–roof head geometry with two intake valves and one exhaust valve, and the simulated engine operating point corresponded to an idle condition. For both the 2–D PIV and 3–D PTV experiments, high–speed CCD cameras were used to record the motion of the flow tracer particles. The camera frame rate was adjusted to correspond to 1/4° of crank angle (CA), hence ensuring excellent temporal resolution for velocity calculations. For the 2–D PIV experiment, the flow field was illuminated by an Argon–ion laser with laser–sheet forming optics and this laser sheet was introduced through a transparent piston crown to illuminate the center tumble plane.

This paper describes a systematic approach to identify the best sensor combination by performing sensor placement analysis to detect and isolate clutch stuck-off faults in Automatic Transmissions (AT) based on structural analysis. When an engaged clutch in the AT loses pressure during operation, it is classified as a clutch stuck-off fault. AT can enter in neutral state because of these faults; causing loss of power at wheels. Identifying the sensors to detect and isolate these faults is important in the early stage of the AT development. A universal approach to develop a structural model of an AT is presented based on the kinematic relationships of the planetary gear set elements. Sensor placement analysis is then performed to determine the sensor locations to detect and isolate the clutch stuck-off faults using speed sensors and clutch pressure sensors. The proposed approach is then applied to a 10-Speed AT to demonstrate its effectiveness.

This study is focused on exploring the possibilities of using camera and route planner images for autonomous driving in an end-to-mid learning fashion. The overall idea is to clone the humans’ driving behavior, in particular, their use of vision for ‘driving’ and map for ‘navigating’. The notion is that we humans use our vision to ‘drive’ and sometimes, we also use a map such as Google/Apple maps to find direction in order to ‘navigate’. We replicated this notion by using end-to-mid imitation learning. In particular, we imitated human driving behavior by using camera and route planner images for predicting the desired waypoints and by using a dedicated control to follow those predicted waypoints. Besides, this work also places emphasis on using minimal and cheaper sensors such as camera and basic map for autonomous driving rather than expensive sensors such Lidar or HD Maps as we humans do not use such sophisticated sensors for driving.

The Ohio State University has fielded teams at all three of the DARPA Grand Challenge and DARPA Urban Challenge autonomous vehicle competitions, using three very different vehicle platforms. In this paper we present our experiences in these competitions, comparing and contrasting the different requirements, strategies, tasks, and vehicles developed for each challenge. We will discuss vehicle control and actuation, sensors, sensor interpretation, planning, behavior, and control generation. We will also discuss lessons learned from the engineering and implementation process for these three vehicles.

This paper presents the modeling of an Electromagnetic Valve Actuator (EMV). A nonlinear model is formulated and presented that takes into account secondary nonlinearities like hysteresis, saturation, bounce and mutual inductance. The uniqueness of the model is contained in the method used in modeling hysteresis, saturation and mutual inductance. Theoretical and experimental methods for identifying parameters of the model are presented. The nonlinear model is experimentally validated. Simulation and experimental results are presented for an EMV designed and built in our laboratory. The experimental results show that sensorless estimation could be a possible solution for position control.

This paper presents an empirical dynamic model of a single spring electromagnetic solenoid actuator system, including bounce, temperature effects and coil leakage inductance. The model neglects hysteresis and saturation, the aim being to compensate for these uncertainties through estimator robustness. The model is validated for all regions of operation and there is a good agreement between model and experimental data. A nonlinear (sliding mode) estimator is developed to estimate position and speed from current measurements. Since the estimator makes use of only current measurement it is given the name sensorless. The estimator is validated in simulation and experimentally. The novelty in this paper lies in the fact that accurate state estimation can be realized on a simple linear model using a robust observer theory. Also, the formulations for leakage inductance and coil temperature are unique.

The acoustic and performance characteristics of an automotive centrifugal compressor are studied on a steady-flow turbocharger test bench, with the goal of advancing the current understanding of compression system instabilities at the low-flow range. Two different ducting configurations were utilized downstream of the compressor, one with a well-defined plenum (large volume) and the other with minimized (small) volume of compressed air. The present study measured time-resolved oscillations of in-duct and external pressure, along with rotational speed. An orifice flow meter was incorporated to obtain time-averaged mass flow rate. In addition, fast-response thermocouples captured temperature fluctuations in the compressor inlet and exit ducts along with a location near the inducer tips.

Roundabout is a unique approach of managing traffic at intersections because it relies on driver’s instincts of safety. Roundabouts are considered safer than other ways of intersection traffic management due to low speed limits, smoother merging, and reduced fatal accidents. Despite their benefits and increasing usage, there is lack of clear understanding of the roundabouts, particularly due to scarcity of data and simulation models and the complexity of the structure. Real-time and offline traffic data recorded at a roundabout provides a basis for 1) identification of the safety issues, 2) understanding unexpected and risky driver behavior, 3) proposing potential mobility solutions, and 4) developing simulation models. The processed data may be used in controlling metered roundabouts, communicating with connected and automated vehicles (CAVs) etc. In this paper an approach to obtain useful traffic information from video feed data at a roundabout is presented.

The introduction of tumble into the combustion chamber is an effective method of enhancing turbulence intensity prior to ignition, thereby accelerating the burn rates, stabilizing the combustion, and extending the dilution limit. In this study, the primary intake runners are partially blocked to produce different levels of tumble motion in the cylinder during the air induction process. Experiments have been performed with a Chrysler 2.4L 4-valve I4 engine at maximum brake torque timing under two operating conditions: 2.41 bar brake mean effective pressure (BMEP) at 1600 rpm, and 0.78 bar BMEP at 1200 rpm. A method has been developed to quantify the tumble characteristics of blockages under steady flow conditions in a flow laboratory, by using the same cylinder head, intake manifold, and tumble blockages from the engine experiments.

Electronic Throttle Control systems substitute the driver in commanding throttle position, with the driver acting on a potentiometer connected to the accelerator pedal. Such strategies allow precise control of air-fuel ratio and of other parameters, e.g. engine efficiency or vehicle driveability, but require detailed information about the engine operating conditions, in order to be implemented inside the Electronic Control Unit (ECU). In order to determine throttle position, an interpretation of the driver desire (revealed by the accelerator pedal position) is performed by the ECU. In our approach, such interpretation is carried out in terms of a torque request that can be appropriately addressed knowing the actual engine-vehicle operating conditions, which depend on the acting torques. Estimates of the torque due to in-cylinder pressure (indicated torque), as well as the torque required by the vehicle (load torque), must then be available to the control module.

Highway safety remains a significant concern, especially in mixed traffic scenarios involving heavy-duty vehicles (HDV) and smaller passenger cars. The vulnerability of HDVs following closely behind smaller cars is evident in incidents involving the lead vehicle, potentially leading to catastrophic rear-end collisions. This paper explores how automatic speed enforcement systems, using speed cameras, can mitigate risks for HDVs in such critical situations. While historical crash data consistently demonstrates the reduction of accidents near speed cameras, this paper goes beyond the conventional notion of crash occurrence reduction. Instead, it investigates the profound impact of driver behavior changes within desired travel speed distribution, especially around speed cameras, and their contribution to the safety of trailing vehicles, with a specific focus on heavy-duty trucks in accident-prone scenarios.

Measurements of the temporal evolution of the 3-D velocity field were performed in an IC engine during the latter part of the intake stroke using a Water Analog Engine Simulation Rig and the 3-D Particle Tracking Velocimetry technique (3-D PTV). The engine head tested was a typical 4 valve, pent-roof type combustion chamber shape with slightly asymmetric intake passages to favor a preferred swirl with one intake valve almost deactivated to reinforce the swirling flow pattern. This study was aimed at characterizing the dynamic development of the flow field resulting from this head geometry and asymmetric valve event during the latter part of the intake stroke. The most salient feature of this flow field is that this final, highly organized and energetic vortex does not emerge until relatively late in the intake stroke. Even as late at 60° BBDC, the flow field is still characterized by smaller (of the order of 1/4 or 1/3 of the bore size) structures, particularly in the tumble plane.

An important part of automotive driving assistance systems and autonomous vehicles is speed optimization and traffic flow adaptation. Vehicle sensors and wireless communication with surrounding vehicles and road infrastructure allow for predictive control strategies taking near-future road and traffic information into consideration to improve fuel economy. For the development of autonomous vehicle speed control algorithms, it is imperative that the controller can be evaluated under different realistic driving and traffic conditions. Evaluation in real-life traffic situations is difficult and experimental methods are necessary where similar driving conditions can be reproduced to compare different control strategies. A traditional approach for evaluating vehicle performance, for example fuel consumption, is to use predefined driving cycles including a speed profile the vehicle should follow.