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Driving inattention caused by drowsiness has been a significant reason for vehicle crash accidents, and there is a critical need to augment driving safety by monitoring driver drowsiness behaviors. For real-time drowsy driving awareness, we propose a vision-based driver drowsiness monitoring system (DDMS) for driver drowsiness behavior recognition and analysis. First, an infrared camera is deployed in-vehicle to capture the driver’s facial and head information in naturalistic driving scenarios, in which the driver may or may not wear glasses or sunglasses. Second, we propose and design a multi-modal features representation approach based on facial landmarks, and head pose which is retrieved in a convolutional neural network (CNN) regression model. Finally, an extreme learning machine (ELM) model is proposed to fuse the facial landmark, recognition model and pose orientation for drowsiness detection. The DDMS gives promptly warning to the driver once a drowsiness event is detected.

The pursuit of greater fuel economy in internal combustion engines requires the optimization of all subsystems including thermal management. The reduction of cooling power required by the electromechanical coolant pump, radiator fan(s), and thermal valve demands real time control strategies. To maintain the engine temperature within prescribed limits for different operating conditions, the continual estimation of the heat removal needs and the synergistic operation of the cooling system components must be accomplished. The reductions in thermal management power consumption can be achieved by avoiding unnecessary overcooling efforts which are often accommodated by extreme thermostat valve positions. In this paper, an optimal nonlinear controller for a military M-ATV engine cooling system will be presented. The prescribed engine coolant temperature will be tracked while minimizing the pump, fan(s), and valve power usage.

This paper outlines a real-time hierarchical control allocation algorithm for multi-axle land vehicles with independent hub motor wheel drives. At the top level, the driver’s input such as pedal position or steering wheel position are interpreted into desired global state responses based on a reference model. Then, a locally linearized rigid body model is used to design a linear quadratic regulator that generates the desired global control efforts, i.e., the total tire forces and moments required track the desired state responses. At the lower level, an optimal control allocation algorithm coordinates the motor torques in such a manner that the forces generated at tire-road contacts produce the desired global control efforts under some physical constraints of the actuation and the tire/wheel dynamics. The performance of the proposed control system design is verified via simulation analysis of a 3-axle heavy vehicle with independent hub-motor drives.

Combustion phasing of Spark Ignition (SI) engines is traditionally regulated with map-based spark timing (SPKT) control. The calibration time and effort of this feed forward SPKT control strategy becomes less favorable as the number of engine control actuators increases. This paper proposes a model based combustion phasing control frame work. The feed forward control law is obtained by real time numerical optimization utilizing a high-fidelity combustion model that is based on flame entrainment theory. An optimization routine identifies the SPKT which phases the combustion close to the target without violating combustion constraints of knock and excessive cycle-by-cycle covariance of indicated mean effective pressure (COV of IMEP). Cylinder pressure sensors are utilized to enable feedback control of combustion phasing. An Extended Kalman Filter (EKF) is applied to reject sensor noise and combustion variation from the cylinder pressure signal.

The automotive cooling system configuration has remained fixed for many decades with a large radiator plus fan, coolant pump, and bypass valve. To reduce cooling system power consumption, the introduction of multiple computer-controlled heat exchangers may offer some benefits. A paradigm shift from a single large radiator, sized for maximum load, to n-small radiators with individual flow control valves should allow fine tuning of the heat rejection needs to minimize power. In this project, a series of experimental scenarios featuring two identical parallel radiators have been studied for low thermal load engine cooling (e.g., idling) in ground transportation applications. For high thermal load scenarios using two radiators, the fans required between 1120 - 3600 W to maintain the system about the coolant reference temperature of 85oC.

Traditional Electronic Stability Control (ESC) for automobiles is usually accomplished through the use of estimated vehicle dynamics from simplified models that rely on parameters such as cornering stiffness that can change with the vehicle state and time. This paper proposes a different method for electronic stability control of oversteer by predicting the degree of instability in a vehicle. The algorithm is solely based on measurable response characteristics including lateral acceleration, yaw rate, speed, and driver steering input. These signals are appropriately conditioned and evaluated with fuzzy logic to determine the degree of instability present. When the “degree of instability” passes a certain threshold, the appropriate control action is applied to the vehicle in the form of differential yaw braking. Using only the measured response of the vehicle alleviates the problem of degraded performance when vehicle parameters change.

Vehicle safety remains a significant concern for consumers, government agencies, and automotive manufacturers. One critical type of vehicle accident results from the right or left side tires leaving the road surface and then returning abruptly due to large steering wheel inputs (road runoff and return). A subset of runoff road crashes that involve a steep hard shoulder has been labeled shoulder induced accidents. In this paper, a limited authority real time steering controller has been developed to mitigate shoulder induced accidents. A Kalman Filter based tire cornering stiffness estimation technique has been coupled with a feedback controller and driver intention module to create a safer driving solution without excessive intervention. In numerical studies, lateral vehicle motion improvements of 30% were realized for steering intervention. Specifically, the vehicle crossed the centerline after 1.0 second in the baseline case versus 1.3 seconds with steering assistance at 60 kph.

Novice drivers are often ill-equipped to safely operate a motor vehicle due to their limited repertoire of skills and experiences. However, automotive simulation tools can be applied to better educate young drivers for a number of common driving scenarios. In this paper, the Clemson Automotive Training System (CATS) will be presented to educate and train novice drivers to safely operate four wheel passenger vehicles on paved roadways. A portable automotive simulator can be programmed to emulate a variety of high-crash rate scenarios and roadway geometries. Drivers receive instructions regarding proper driving techniques and behaviors with an opportunity to practice the given vehicle maneuver. An on-line evaluation methodology has been designed to analyze the drivers' capabilities at handling these roadway events. First, a pre-simulation questionnaire evaluates their basic understanding of everyday driving situations.

In this work, a novel opposed piston architecture is proposed where one crankshaft rotates at twice the speed of the other. This results in one piston creating a 2-stroke profile and another with a 4-stroke profile. In this configuration, the slower piston operates in the 2-stroke CAD domain, while the faster piston completes 2 reciprocating cycles in the same amount of time (4-stroke). The key benefit of this cycle is that the 4-stroke piston increases the rate of compression and expansion (dV/dθ), which lowers the combustion-induced pressure rise rate after top dead center (crank angle location of minimum volume). Additionally, it lowers in-cylinder temperatures and pressures more rapidly, resulting in a lower residence time at high temperatures, which reduces residence time for thermal NOx formation and reduces the temperature differential between the gas and the wall, thereby reducing heat transfer.

In this work, two blends of isopropanol, n-butanol, and ethanol (IBE) that can be produced by metabolically engineered clostridium acetobutylicum are studied experimentally in advanced compression ignition (ACI). This is done to determine whether these fuel blends have the right fuel properties to enable thermally stratified compression ignition, a stratified ACI strategy that using the cooling potential of single stage ignition fuels to control the heat release process. The first microorganism, ATCC824, produces a blend of 34.5% isopropanol, 60.1% n-butanol, and 5.4% ethanol, by mass. The second microorganism, BKM19, produces a blend of 12.3% isopropanol, 54.0% n-butanol, and 33.7% ethanol, by mass. The sensitivity of both IBE blends to intake pressure, intake temperature, and cylinder energy content (fueling rate) is characterized and compared to that of its neat constituents. Both IBE blends behaved similarly with a reactivity level between that of ethanol and n-butanol.

This paper presents a methodology for designing a simple open-loop steering robot profile to simulate a double lane change maneuver for track testing of a heavy tractor/trailer combination vehicle. For track testing of vehicles in a lane change type of maneuver, a human driver is typically used with a desired path defined with visual cues such as traffic cones. Such tests have been shown to result in poor test repeatability due to natural variation in driver steering behavior. While a steering robot may be used to overcome this repeatability issue, such a robot typically implements open-loop maneuvers and cannot be guaranteed to cause the vehicle to accurately follow a pre-determined trajectory. This paper presents a method using offline simulation to design an open-loop steering maneuver resulting in a realistic approximation of a double lane change maneuver.

The functionality and performance of an internal combustion (spark or compression ignition) engine's thermal management system can be significantly enhanced through the application of mechatronics technology. The replacement of the conventional thermostat valve and mechanical coolant pump in the heating/cooling system by a servo-motor driven smart valve and variable flow pump permits powertrain control module regulated coolant flow through the engine block and radiator. In this paper, a dynamic mathematical model will be created for a 4.6L spark ignition engine to analyze various thermal management system architectures. The designs to be studied include the factory configuration, a smart valve upgrade, and the smart valve combined with a variable flow pump and radiator fan. Representative results are presented and discussed to demonstrate improvements in the engine warm-up time, temperature tracking, and component power consumption.

The operation of internal combustion engines depend on the successful management of the fuel, spark, and cooling processes to ensure acceptable performance, emission levels, and fuel economy. Two different thermal management systems exist for engines - air and liquid cooling. Smaller displacement utility and spark ignition aircraft engines typically feature air cooled systems which rely on forced convection over the exterior engine surfaces. In contrast, passenger/light-duty engines use a water-ethylene glycol mixture which circulates through the radiator, water pump, and heater core. The regulation of the overall engine temperature, based on the coolant's temperature, has been achieved with the thermostat valve and (electric) radiator fan. To provide insight into the thermal behavior of the cylinder-head assembly for enhanced cooling system operation, a dynamic model must exist.

Understanding the effects of tire and vehicle properties on the rollover propensity of tractor semi-trailer trucks is essential. The major objective of the project described by this paper was to develop a simplified computational tool that can be used to understand and predict the effects of various tire characteristics and truck design parameters on rollover under steady cornering and non-tripped conditions. In particular, this tool may be used to help understand the basic mechanisms governing rollover propensity of trucks equipped with New Generation Wide Single tires as contrasted with conventional tires. Effects of tire flexibility, roll-compliant suspensions, fifth - wheel lash and nonlinear suspension characteristics are included in the model and are presented below. Design parameter data used as input to the model were obtained from Michelin Americas Research and Development Corporation.

Race teams compete at a level where fractions of a second separate the finishers. Consequently, teams devote significant resources to gain a competitive edge. Limitations on track time and high track rental prices dictate efficiency in testing. Thus, proper use of data acquisition and computer aided engineering tools is essential. These tools can be used to quickly analyze test data and serve as the basis for recommendations for changes in chassis setup and driver technique. This project describes the further development of such a tool that can be used to analyze and diagnose the control inputs of a driver as well as diagnose the overall balance of the chassis (i.e., understeer and oversteer). This tool is an “expert system” (implemented in MATLAB) that provides an understanding of the effects of both chassis setup changes and driver steering, braking, and throttle control inputs on overall lap times.

The automotive thermal management system is responsible for maintaining engine and passenger compartment temperatures, which promote normal combustion events and passenger comfort. This system traditionally circulates a water ethylene glycol mixture through the engine block using a belt-driven water pump, wax pellet thermostat valve, radiator with electric fan, and heater core. Although vehicle cooling system performance has been reliable and acceptable for many decades, advances in mechatronics have permitted upgrades to powertrain and chassis components. In a similar spirit, the introduction of a variable speed electric water pump and servo-motor thermostat valve allows ECU-based thermal control. This paper examines the integration of an electric water pump and intelligent thermostat valve to satisfy the engine's basic cooling requirements, minimize combustion chamber fluctuations due to engine speed changes, and permit quick heating of a cold block.

Heat rejection in ground vehicle propulsion systems remains a challenge given variations in powertrain configurations, driving cycles, and ambient conditions as well as space constraints and available power budgets. An optimization strategy is proposed for engine radiator geometry size scaling to minimize the cooling system power consumption while satisfying both the heat removal rate requirement and the radiator dimension size limitation. A finite difference method (FDM) based on a heat exchanger model is introduced and utilized in the optimization design. The optimization technique searches for the best radiator core dimension solution over the design space, subject to different constraints. To validate the proposed heat exchanger model and optimization algorithm, a heavy duty military truck engine cooling system is investigated.

In the next 20 years fully autonomous vehicles are expected to be in the market. The advance on their development is creating paradigm shifts on different automotive related research areas. Vehicle interiors design and human vehicle interaction are evolving to enable interaction flexibility inside the cars. However, most of today’s vehicle manufacturers’ autonomous car concepts maintain the steering wheel as a control element. While this approach allows the driver to take over the vehicle route if needed, it causes a constraint in the previously mentioned interaction flexibility. Other approaches, such as the one proposed by Google, enable interaction flexibility by removing the steering wheel and accelerator and brake pedals. However, this prevents the users to take control over the vehicle route if needed, not allowing them to make on-route spontaneous decisions, such as stopping at a specific point of interest.

Emerging autonomous driving technologies, with emergency navigating capabilities, necessitates innovative vehicle steering methods for operators during unanticipated scenarios. A reconfigurable “plug and play” steering system paradigm enables lateral control from any seating position in the vehicle’s interior. When required, drivers may access a stowed steering input device, establish communications with the vehicle steering subsystem, and provide direct wheel commands. Accordingly, the provision of haptic steering cues and lane keeping assistance to navigate roadways will be helpful. In this study, various steering devices have been investigated which offer reconfigurability and haptic feedback to create a flexible driving environment. A joystick and a robotic arm that offer multiple degrees of freedom were compared to a conventional steering wheel.

This study was driven by the prevalence of older drivers’ overrepresentation in crashes caused by pedal application errors. Previous research has shown tasks prone to pedal errors, which include emergency braking, parking lot maneuvers and reaching out of the driver’s window. However, pedal usage characteristics of older drivers while performing on-road driving tasks are unknown. The objective of this research was to understand pedal usage characteristics of older drivers during on-road driving tasks in an instrumented vehicle. Twenty-six drivers over the age of 60 completed 10 stopping tasks as the baseline for stopping performance, a startle-braking task, two forward parking tasks and two reaching out of the vehicle tasks. Results for this instrumented vehicle study showed significantly positive correlations between stature and the percent of foot pivoting, and between shoe length and percent of foot pivoting in the baseline stopping tasks.