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Challenges that persons with disabilities face with current modes of transportation have led to difficulties in carrying out everyday tasks, such as grocery shopping and going to doctors’ appointments. Autonomous vehicles have been proposed as a solution to overcome these challenges and make these everyday tasks more accessible. For these vehicles to be fully accessible, the infrastructure surrounding them need to be safe, easy to use, and intuitive for people with disabilities. Thus, the goal of this work was to analyze interview data from persons with disabilities, and their caregivers, to identify barriers to accessibility for current modes of transportation and ways to ameliorate them in pick up/drop off zones for autonomous vehicles. To do this, interview subjects were recruited from adaptive sports clubs, assistive living facilities, and other disability networks to discuss challenges with current public transit stops/stations.

LiDAR sensors are common in automated driving due to their high accuracy. However, LiDAR processing algorithm development suffers from lack of diverse training data, partly due to sensors’ high cost and rapid development cycles. Public datasets (e.g. KITTI) offer poor coverage of edge cases, whereas these samples are essential for safer self-driving. We address the unmet need for abundant, high-quality LiDAR data with the development of a synthetic LiDAR point cloud generation tool and validate this tool’s performance using the KITTI-trained PIXOR object detection model. The tool uses a single camera raycasting process and filtering techniques to generate segmented and annotated class specific datasets.

Mixture formation and combustion dynamics are the primary contributors to the performance and emission characteristics of direct-injected spark ignition (SI) engines. This requires assessing the benefits and tradeoffs of the design and control factors that influence mixing and the subsequent combustion event. In this study, Taguchi's L18 orthogonal array design of experiment (DoE) methodology has been applied to assess contributions and tradeoffs of varied compression ratio, piston bowl design, intake port tumble design, injector spray pattern, injection timing, injection pressure, exhaust gas recirculation (EGR) rate, and intake valve closing timing in a single-cylinder boosted gasoline direct injection (GDI) SI engine. This multiparameter study has been carried out across three speed-load conditions representative of typical automotive application operating ranges.

Continuous efforts to improve thermal efficiency and reduce exhaust emissions of internal combustion engines have resulted in development of various solutions towards improved lean burn ignition systems in spark ignition engines. The Dual Mode, Turbulent Jet Ignition (DM-TJI) system is one of the leading technologies in that regard which offers higher thermal efficiency and reduced NOx emissions due to its ability to operate with very lean or highly dilute mixtures. Compared to other pre-chamber ignition technologies, the DM-TJI system has the distinct capability to work with a very high level of EGR dilution (up to ~40%). Thus, this system enables the use of a three-way catalyst (TWC). Auxiliary air supply for pre-chamber purge allows this system to work with such high EGR dilution rate. This work presents the results of experimental investigation carried out with a Dual Mode, Turbulent Jet Ignition (DM-TJI) optical engine equipped with a cooled EGR system.

Deep learning based approaches for object detection are heavily dependent on the nature of data used for training, especially for vehicles driving in cluttered urban environments. Consequently, the performance of Convolutional Neural Network (CNN) architectures designed and trained using data captured under clear weather and favorable conditions, could degrade rather significantly when tested under cloudy and rainy conditions. This naturally becomes a major safety issue for emerging autonomous vehicle platforms relying on CNN based object detection methods. Furthermore, despite a noticeable progress in the development of advanced visual deraining algorithms, they still have inherent limitations for improving the performance of state-of-the-art object detection. In this paper, we address this problem area by make the following contributions.

The automotive industry is subject to stringent regulations in emissions and growing customer demands for better fuel consumption and vehicle performance. Engine calibration, a process that optimizes engine performance by tuning engine controls (actuators), becomes challenging nowadays due to significant increase of complexity of modern engines. The traditional sweep-based engine calibration method is no longer sustainable. To tackle the challenge, this work considers two powerful global optimization methods: genetic algorithm (GA) and Bayesian optimization for steady-state engine calibration for single speed-load point. GA is a branch of meta-heuristic methods that has shown a great potential on solving difficult problems in automotive engineering. Bayesian optimization is an efficient global optimization method that solves problems with computationally expensive testing such as hyperparameter tuning in deep neural network (DNN), engine testing, etc.

The development of connected-vehicle technology, which includes vehicle-vehicle and vehicle-infrastructure communications, opens the door for unprecedented active safety and driver-enhanced systems. In addition to exchanging basic traffic messages among vehicles for safety applications, a significantly higher level of safety can be achieved when vehicles and designated infrastructure-locations share their sensor data. In this paper, we propose a new system where cameras installed on multiple vehicles and infrastructure-locations share and fuse their visual data and detected objects in real-time. The transmission of camera data and/or detected objects (e.g., pedestrians, vehicles, cyclists, etc.) can be accomplished by many communication methods. In particular, such communications can be accomplished using the emerging Dedicated Short-Range Communications (DSRC) technology.

Piston temperature plays a major role in determining details of fuel spray vaporization, fuel film deposition and the resulting combustion in direct-injection engines. Due to different heat transfer properties that occur in optical and all-metal engines, it becomes an inevitable requirement to verify the piston temperatures in both engine configurations before carrying out optical engine studies. A novel Spot Infrared-based Temperature (SIR-T) technique was developed to measure the piston window temperature in an optical engine. Chromium spots of 200 nm thickness were vacuum-arc deposited at different locations on a sapphire window. An infrared (IR) camera was used to record the intensity of radiation emitted by the deposited spots. From a set of calibration experiments, a relation was established between the IR camera measurements of these spots and the surface temperature measured by a thermocouple.

Three dimensional numerical simulation of the transient turbulent jet and ignition processes of a premixed methane-air mixture of a turbulent jet ignition (TJI) system is performed using Converge computational software. The prechamber initiated combustion enhancement technique that is utilized in a TJI system enables low temperature combustion by increasing the flame propagation rate and therefore decreasing the burn duration. Two important components of the TJI system are the prechamber where the spark plug and injectors are located and the nozzle which connects the prechamber to the main chamber. In order to model the turbulent jet of the TJI system, RANS k-ε and LES turbulent models and the SAGE chemistry solver with a reduced mechanism for methane are used.

High frequency variations in crankcase pressure have been observed in Inline-four cylinder (I4) engines and an understanding of the causes, frequency and magnitude of these variations is helpful in the design and effective operation of various engine systems. This paper shows through a review and explanation of the physics related to engine operation followed by comparison to measured vehicle data, the relationship between crankcase volume throughout the engine cycle and the observed pressure fluctuations. It is demonstrated that for a known or proposed engine design, through knowledge of the key engine design parameters, the frequency and amplitude of the cyclic variation in crankcase pressure can be predicted and thus utilized in the design of other engine systems.

Turbulent jet ignition is a pre-chamber ignition enhancement method that produces a distributed ignition source through the use of a chemically active turbulent jet which can replace the spark plug in a conventional spark ignition engine. In this paper combustion visualization and characterization was performed for the combustion of a premixed propane/air mixture initiated by a pre-chamber turbulent jet ignition system with no auxiliary fuel injection, in a rapid compression machine. Three different single orifice nozzles with orifice diameters of 1.5 mm, 2 mm, and 3 mm were tested for the turbulent jet igniter pre-chamber over a range of air to fuel ratios. The performance of the turbulent jet ignition system based on nozzle orifice diameter was characterized by considering both the 0-10 % and the 10-90 % burn durations of the pressure rise due to combustion.

Camless Variable Valve Actuation (VVA) technologies have been known for improving fuel economy, reducing emissions, and enhancing engine performance. VVA can be divided into electro-magnetic, electro-hydraulic, and electro-pneumatic actuation. This paper presents an electro-hydraulic VVA design (called GD-VVA-2) that offers continuously variable timing and two discrete lifts (low lift S1 and high lift S2). The lift control is achieved through a lift control sleeve, which is hydraulically switched between two mechanically defined positions to provide accurate lifts. The low lift S1 has a wide design range, anywhere between zero and the high lift S2, i.e., 0 < S1 < S2. If S1 ≥ 0.5*S2, engine valves may operate at the low lift during most of a typical drive cycle. Operation at the low lift reduces energy consumption significantly. The GD-VVA-2 design offers compact package size and reasonable energy consumption.

Fully three-dimensional computational fluid dynamic simulations with detailed chemistry of a single-orifice turbulent jet ignition device installed in a rapid compression machine are presented. The simulations were performed using the computational fluid dynamics software CONVERGE and its RANS turbulence models. Simulations of propane fueled combustion are compared to data collected in the optically accessible rapid compression machine that the model's geometry is based on to establish the validity and limitations of the simulations and to compare the behavior of the different air-fuel ratios that are used in the simulations.

Camless Variable Valve Actuation (VVA) technologies have been known for improving fuel economy, reducing emissions, and enhancing engine performance. VVA can be divided into electro-magnetic, electro-hydraulic, and electro-pneumatic actuation. A family of camless VVA designs (called LGD-VVA or Gongda-VVA) has been presented in an earlier SAE publication (SAE 2007-01-1295) that consists of a two-spring actuation, a bypass passage, and an electrohydraulic latch-release mechanism. The two-spring pendulum system is used to provide efficient conversion between the moving mass kinetic energy and the spring potential energy for reduced energy consumption and to be more robust to the operational temperature than the conventional electrohydraulic actuation; and the electrohydraulic mechanism is intended for latch-release function, energy compensation and seating velocity control.

Large Eddy Simulations of atomization and evaporation of liquid fuel sprays in diesel engine conditions are performed with stochastic breakup and non-equilibrium droplet heat and mass transfer models. The size and number density of the droplets generated by the breakup model are assumed to be governed by a Fokker-Planck equation, describing the evolution of the PDF of droplet radii. The fragmentation intensity spectrum is considered to be Gaussian and the scale of Lagrangian relative velocity fluctuations is included in the breakup frequency calculations. The aerodynamic interactions of droplets in the dense part of the spray are modeled by correcting the relative velocity of droplets in the wake of other droplets. The stochastic breakup model is employed together with the wake interaction model for simulations of non-evaporating and evaporating sprays in various gas temperature and pressure conditions.

A direct-injection and spark-ignition single-cylinder engine with optical access to the cylinder was used for the combustion visualization study. Gasoline and ethanol-gasoline blended fuels were used in this investigation. Experiments were conducted to investigate the effects of fuel injection pressure, injection timing and the number of injections on the in-cylinder combustion process. Two types of direct fuel injectors were used; (i) high-pressure production injector with fuel pressures of 5 and 10 MPa, and (ii) low-pressure production-intent injector with fuel pressure of 3 MPa. Experiments were performed at 1500 rpm engine speed with partial load. In-cylinder pressure signals were recorded for the combustion analyses and synchronized with the high-speed combustion imaging recording. Visualization results show that the flame growth is faster with the increment of fuel injection pressure.

Combustion studies were completed using an International VT275-based, optical DI Diesel engine fueled with Diesel fuel, a Canola-derived FAMES biodiesel, as well as with a blend of the Canola-derived biodiesel and a cetane-reducing, oxygenated fuel, Di-Butyl Succinate. Three engine operating conditions were tested to examine the combustion of the fuels across a range of loads and combustion schemes. Pressure data and instantaneous images were recorded using a high-speed visible imaging, infrared imaging, and high-speed OH imaging techniques. The recorded images were post processed to analyze different metrics, such as projected areas of in-cylinder soot, OH, and combustion volumes. A substantially reduced in-cylinder area of soot formation is observed for the Canola-DBS blended fuel with a slight reduction from the pure FAMES biodiesel compared to pump Diesel fuel.

EGR coolers are used in combustion engines to reduce NOx emissions. However, heat transfer in these coolers also results in thermophoresis-temperature-gradient driven motion of suspended particles towards cooler regions-which leads to significant soot deposition. A simple one-dimensional model is proposed to predict the deposition velocity and soot layer thickness that compares reasonably well with experimental data. The behavior of soot deposits on cooled surfaces is complex, with the thickness of the soot layer stabilizes after around 100 hours, reaching a uniform, thickness over the entire heat-exchanger surface. An analysis of this trend and a tentative mechanism to explain this type of behavior is given, based on experimental observations.

To increase robustness of the crush mode and to decrease repair costs after a crash, it is desirable for front and rear rails in an automotive vehicle to crush progressively. Here, progressive crush refers to a mode of axial crush that initiates near the tip of the rail and then progresses rearward in a controlled fashion. In this study, a new strategy is investigated to achieve progressively crushing designs during an automated design optimization study. This strategy employs the definition of crush zones along the length of a rail, and a design optimization problem statement that encourages maximum energy absorption in any particular crush zone to occur prior to any energy absorption in rearward zones. It is demonstrated that high performing designs with progressive crush can be obtained using the proposed approach.

To obtain the maximum output power and fuel economy from an internal combustion engine, it is often necessary to detect engine knock and operate the engine at its knock limit. This paper presents the ability to detect knock using in-cylinder ionization signals on a large displacement, air-cooled, “V” twin motorcycle engine over the engine operational map. The knock detection ability of three different sensors is compared: production knock (accelerometer) sensor, in-cylinder pressure sensor, and ionization sensor. The test data shows that the ionization sensor is able to detect knock better than the production knock sensor when there is high mechanical noise present in the engine.