Development of a Driving Behavior-Based Collision Warning System Using a Neural Network

An advanced driver assistance system (ADAS) uses radar, visual information, and laser sensors to calculate variables representing driving conditions, such as time-to-collision (TTC) and time headway (THW), and to determine collision risk using empirically set thresholds. However, the empirically set threshold can generate differences in performance that are detected by the driver. It is appropriate to quickly relay collision risk to drivers whose response speed to dangerous situations is relatively slow and who drive defensively. However, for drivers whose response speed is relatively fast and who drive actively, it may be better not to provide a warning if they are aware of the collision risk in advance, because giving collision warnings too frequently can lower the reliability of the warnings and cause dissatisfaction in the driver, or promote disregard. To solve this problem, this study proposes a collision warning system (CWS) based on an individual driver’s driving behavior. In particular, a driver behavior model was created using an artificial neural network learning algorithm so that the collision risk could be determined according to the driving characteristics of the driver. Finally, the driver behavior model was learned using actual vehicle driving data and the applicability of the proposed CWS was verified through simulation.     

Optimal Design for the Rear-Glass Joint of an Automobile for Squeak and Rattle Noise Reduction

Ever since vehicle noise, vibration, and harshness (NVH) reduction technology made dramatic improvements, vehicle interior noises represented by Squeak and Rattle (S/R) becomes an ever more important factor to improve the emotional quality of vehicles. Generally, people detect S/R noises on automotive interior parts, brake system, suspension, Body in White (BIW), etc. Among them, the rear-glass joint is a major source for vehicle interior noise, and can cause S/R noises under a variety of environmental and driving conditions. This study uses, two approaches, experimental and numerical approaches, to define the cause of S/R noise at the rear-glass section. Based on these two approaches, this study confirms that S/R noises generate through the contact between bottom side of molding and BIW. The sealant penetration length, panelmolding distance, and sealant width are the parameters affecting noise generation. In addition, this study created an optimal design with Design of Experiments (DOE) of the rear-glass joint. The design maximized the sealant penetration length, which is a parameter that majorly affects noise. The optimal design comprises of two steps: sealant injections shape optimization and rear-glass joint parameter optimization. Each step is carried out with FEA and validated by sealant penetration experiments. Through these optimizations, this study obtained an optimum combination of design parameters and fignificantly reduced the noise generated by rear-glass section.     

OH-radical behavior of unsteady lifted flame based on instantaneous change of the equivalence ratio

In an earlier study, the current authors showed that an unsteady-state lifted flame generated by an equivalence ratio conversion system for a given fuel, was similar to a steady-state lifted flame in terms of the change characteristics from a premixed flame to a critical flame and then to a triple flame with a diffusion flame positioned in the middle according to the concentration difference. Therefore, this study used an OH-PLIF method to investigate the characteristics of a steady-state lifted flame and an unsteady-state lifted flame created under conditions identical to the flames in the preceding study. PLIF (Planar laser induced fluorescence) is practically effective for visualizing the concentration fields within a flame. The resulting OH-radical measurements showed that an unsteady-state lifted flame created under the specific conditions used in this study showed similar tendencies in terms of OH-radical distribution, fluorescence intensity, and liftoff height, to a steady-state lifted flame, thereby confirming that the behavior of an unsteady-state lifted flame can be effectively predicted based on the behavior of a steady-state lifted flame.     

Study of RCM-based maintenance planning for complex structures using soft computing technique

To guarantee the efficiency of maintenance strategies for a complex structure, safety and cost limitations must be considered. This research introduces RCM-based (Reliability Centered Maintenance) life cycle optimization for reasonable maintenance. The design variable is the reliability of each part, which consists of a complex structure, while the objective is to minimize the total cost function in order to maintain the system within the desired system reliability. This research constructs the cost function that can reflect the current operating condition and maintenance characteristics of individual parts by generating essential cost factors. To identify the optimal reliability of each component in a system, this paper uses a Neuro-Evolutionary technique. Additionally, this research analyzes the reliability growth of a system by using the AMSAA (Army Material Systems Analysis Activity) model to estimate the failure rate of each part. The MTBF (Mean Time Between Failure) and the failure rate of the whole system, which is responding to the individual parts, are estimated based on the history data by using neural networks. Finally, this paper presents the optimal life cycle of a complex structure by applying the optimal reliability and the estimated MTBF to the RAMS (Reliability, Availability, Maintainability, and Safety) algorithm.     

Investigation of the shear flows over a sunroof opening based on a linear inviscid instability analysis

The large-scale shear flows over the sunroof opening of a mid-sized SUV measured using a PIV system were investigated. The shear flows were measured for five different cases of deflector protrusion (one case was the baseline test without deflector) at two different free stream flow velocities below the critical velocity where the buffeting noise level reached a maximum. The structures of the shear flows were observed to differ, apparently depending on whether the radiated buffeting noise is relatively strong or not. For strongly buffeting experimental cases, the momentum thicknesses of the shear layers were observed to grow rapidly and saturated at a station near the downstream edge of the sunroof opening, where the saturation of the transverse velocity fluctuations was also observed, and where the vortex coalescence process was presumably completed. On the other hand, no discrete large-scale vortex structures were observed for none-buffeting or weakly buffeting cases. Streamwise growth of the velocity fluctuations was found to be well predicted by a linear hydrodynamic instability analysis for the strongly buffeting cases. Numerical results obtained from a linear inviscid instability analysis using a hyperbolic tangent mean velocity profile were used to calculate the amplification factors with the initial momentum thickness and the streamwise fluctuation wavenumber. The shear flows were found to form large-scale discrete vortices when the linear inviscid amplification factors exceeded a threshold amplification factor.     

Speed estimation and length based vehicle classification from freeway single-loop detectors

Roadway usage, particularly by large vehicles, is one of the fundamental factors determining the lifespan of highway infrastructure. Operating agencies typically employ expensive classification stations to monitor large vehicle usage. Meanwhile, single-loop detectors are the most common vehicle detector and many new, out-of-pavement detectors seek to replace loop detectors by emulating the operation of single-loop detectors. In either case, collecting reliable length data from these detectors has been considered impossible due to the noisy speed estimates provided by conventional data aggregation at single-loop detectors. This research refines non-conventional techniques for estimating speed at single-loop detectors, yielding estimates that approach the accuracy of a dual-loop detector’s measurements. Employing these speed estimation advances, this research brings length based vehicle classification to single-loop detectors (and by extension, many of the emerging out-of-pavement detectors). The classification methodology is evaluated against concurrent measurements from video and dual-loop detectors. To capture higher truck volumes than empirically observed, a process of generating synthetic detector actuations is developed. By extending vehicle classification to single-loop detectors, this work leverages the existing investment deployed in single-loop detector count stations and real-time traffic management stations. The work also offers a viable treatment in the event that one of the loops in a dual-loop detector classification station fails and thus, also promises to improve the reliability of existing classification stations.     

A suggestion of gap flow control devices for the suppression of rudder cavitation

This paper presents the numerical analysis of rudder cavitation in propeller slipstream and the development of a new rudder system aimed for lift augmentation and cavitation suppression. The new rudder system is equipped with cam devices which effectively close the gap between the horn/pintle and movable wing parts. A computational fluid dynamics code that solves the Reynolds-averaged Navier–Stokes equations is used to analyze the flow field of various rudder systems in propeller slipstream. The body force momentum source terms that mimic flow field behind a rotating propeller are added in the momentum equations to represent the influence of the propeller and its slipstream. For detailed explication of the new rudder system’s lift augmentation and cavitation suppression mechanism, three-dimensional flow analysis is carried out. Simulations clearly display the mechanism of the lift augmentation and cavitation suppression. The computational results suggest that the Reynolds-averaged Navier–Stokes-based computational fluid dynamics reproduces the flow field around a rudder in propeller slipstream and that the present concept for a cavitation suppressing rudder system is highly feasible and warrant further study for inclusion of the interaction with hull and mechanical design for manufacturing and operations.     

Component Sizing of Parallel Hybrid Electric Vehicle Using Optimal Search Algorithm

In designing a parallel hybrid electric vehicle, it is essential to select the optimal capacity of power sources and the optimal gear ratio of the torque coupler. The capacity of the power sources and the gear ratio of the torque coupler should be optimized simultaneously. However, since this process is excessively time-consuming, previous studies have selected the gear ratio of the torque coupler and then selected the capacity of power source. However, this approach cannot guarantee global optimization. In this paper, a feasible region is defined to satisfy the required performance of vehicle such as maximum speed, hill-climbing. and feasible points are selected inside the feasible region. In the conventional technique, the global optimal solution is obtained by simulating all feasible points. In the optimization technique, optimal points are simulated within the feasible region using several optimal search algorithms, such as the golden section search algorithm and the hillclimbing search algorithm. And using these algorithms, the number of simulations is reduced and the capacity of the power source and the gear ratio of the torque coupler are optimized simultaneously. Finally, the validity of the component sizing results is verified by comparing the global optimal solution obtained by applying the conventional technique with the solution obtained by applying the proposed optimization technique.     

An integrated measure of accessibility and reliability of mass transit systems

The growth of a city or a metropolis requires well-functioning transit systems to accommodate the ensuing increase in travel demand. As a result, mass transit networks have to develop and expand from simple to complex topological systems over time to meet this demand. Such an evolution in the networks’ structure entails not only a change in network accessibility, but also a change in the level of network reliability on the part of stations and the entire system as well. Network accessibility and reliability are popular measures that have been widely applied to evaluate the resilience and vulnerability of a spatially networked system. However, the use of a single measure, either accessibility or reliability, provides different results, which demand an integrated measure to evaluate the network’s performance comprehensively. In this paper, we propose a set of integrated measures, named ACCREL (Integrated Accessibility and Reliability indicators) that considers both metrics in combination to evaluate a network’s performance and vulnerability. We apply the new measures for hypothetical mass transit system topologies, and a case study of the metro transit system in Seoul follows, highlighting the dynamics of network performance with four evolutionary stages. The main contribution of this study lies in the results from the experiments, which can be used to inform how transport network planning can be prepared to enhance the network functionality, thereby achieving a well-balanced, accessible, and reliable system. Insights on network vulnerability are also drawn for public transportation planners and spatial decision makers.     

Quantifying individuals’ trade-offs between privacy,liberty and security: The case of rail travel in UK

Public transport systems have been targets in several terrorist attacks, notably in recent years, resulting in tight security measures worldwide. However, individuals’ privacy and liberty often conflict with efforts towards safety and security, making it difficult to assess the implications of security measures balanced against the costs (e.g., citizens may be stopped, searched and asked to provide personal identification data to authorities without any particular reason). Henceforth, our research question asks, “to what extent would people sacrifice their right to privacy and liberty in exchange for potentially safer and more secure travel?” This paper uses a stated choice experiment to quantify individuals’ trade-offs between privacy and security within a real-life context, namely rail travel in the UK. Using a nationwide sample, the empirical analysis yields the importance of improvements in the security infrastructure and identifies areas of concern with regard to privacy and liberty controlling for travel related factors. Further, trade-offs across different security measures for rail travel are quantified in terms of individuals’ willingness-to-pay extra on top of the average ticket price.