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This paper deals with a blind spot assistance system that assists the driver by generating yaw-moment when a driver's lane change maneuver is detected and when there is an object present in the blind spot area of the adjacent lane. The system combines lane information and driver's maneuver information for estimating the driver's lane change. If the millimeter wave sensor detects an object in the rear blind spot area in the event of a lane change, direct yaw-moment in the opposite direction of the lane change maneuver is generated. The unique method of detecting driver's lane change, control method of assisting the driver to recover back in lane, and the system design to maintain driver compatibility is mentioned, together with the effectiveness of the system.

The National Highway Traffic Safety Administration (NHTSA) and the Insurance Institute for Highway Safety (IIHS) have both developed crash test methodologies to address frontal collisions in which the vehicle's primary front structure is either partially engaged or not engaged at all. IIHS addresses Small Overlap crashes, cases in which the vehicle's primary front energy absorbing structure is not engaged, using a rigid static barrier with an overlap of 25% of the vehicle's width at an impact angle of 0°. The Institute's Moderate Overlap partially engages the vehicle's primary front energy absorbing structure using a deformable static barrier with 40% overlap at a 0° impact angle. The NHTSA has developed two research test methods which use a common moving deformable barrier impacting the vehicle with 20% overlap at a 7° impact angle and 35% overlap at a 15° impact angle respectively.

A method for detecting drivers' intentions is essential to facilitate operating mode transitions between driver and driver assistance systems. We propose a driver behavior recognition method using Hidden Markov Models (HMMs) to characterize and detect driving maneuvers and place it in the framework of a cognitive model of human behavior. HMM-based steering behavior models for emergency and normal lane changes as well as for lane keeping were developed using a moving base driving simulator. Analysis of these models after training and recognition tests showed that driver behavior modeling and recognition of different types of lane changes is possible using HMMs.

Rollover crashes have continued to be a source of extensive research into determining both vehicle performance, and occupant restraint capabilities. Prior research has utilized various test procedures, including the FMVSS 208 dolly fixture, as a basis for evaluating vehicle and restraint performance. This research, using 2001 Nissan Pathfinder sport utility vehicles (SUVs), was conducted to update the status of passenger vehicle rollover testing, and evaluate dynamic test repeatability with a new test procedure. A series of eight rollover tests was conducted using these SUV vehicles, mounted on a modified FMVSS 208 rollover dolly fixture, with instrumented dummies in both front seat positions. This test protocol involved launching the vehicles horizontally, after snubbing the dolly fixture, and having the leading-side tires contact curbing for a trip mechanism.

With the increasing emphasis on Systems Engineering, there is a need to ensure that Electrical/Electronic (E/E) Systems Endurance Testing of vehicles, in a real world environment, prior to Production Launch, is performed in a manner and at a technological level that is commensurate with the high level of electronics and computers in contemporary vehicles. Additionally, validating the design and performance of individual standalone electronic systems and modules “on the bench” does not guarantee that all the permutations and combinations of real-world hardware, software, and driving conditions are taken into account. Traditional Proving Ground (PG) vehicle testing focuses mainly on powertrain durability testing, with only a simple checklist being used by the PG drivers as a reminder to cycle some of the electrical components such as the power window switches, turn signals, etc.

A robotic driver has been designed on the basis of an analysis of a human driver's action in following a given driving schedule. The self-learning algorithm enables the robot to learn the vehicle characteristics without human intervention. Based on learned relationships, the robotic driver can determine an appropriate accelerator position and execute other operations through sophisticated calculations using the future scheduled vehicle speed and vehicle characteristics data. Compensation is also provided to minimize vehicle speed error. The robotic driver can reproduce the same types of exhaust emission and fuel economy data obtained with human drivers with good repeatability. It doesn't require long preparation time. Thereby making it possible to reduce experimentation work in the vehicle development process while providing good accuracy and reliability.

This paper describes a study of drag reduction devices for production pick-up trucks with a body-on-frame structure using full-scale wind tunnel testing and Computational Fluid Dynamics (CFD) simulations. First, the flow structure around a pick-up truck was investigated and studied, focusing in particular on the flow structure between the cabin and tailgate. It was found that the flow structure around the tailgate was closely related to aerodynamic drag. A low drag flow structure was found by flow analysis, and the separation angle at the roof end was identified as being important to achieve the flow structure. While proceeding with the development of a new production model, a technical issue of the flow structure involving sensitivity to the vehicle velocity was identified in connection with optimization of the roof end shape. (1)A tailgate spoiler was examined for solving this issue.

Driving tests were conducted using an experimental vehicle equipped with an adaptive cruise control system incorporating low-speed following capability in order to evaluate drivers' trust in a driver support system. The results revealed that the drivers' trust in the system declined in cases where the control algorithm produced vehicle behavior that was inconsistent with their expectations. However, that decline in trust ceased to be observed as the drivers' understanding of the system improved. This result suggests a correlation between their understanding of the system and trust in it.

A study was made on a control method for an adaptive cruise control (ACC) system that uses vehicle-to-vehicle communication to achieve a substantial improvement in string stability and natural headway distance response characteristics at lower levels of longitudinal G. A control system using model predictive control was constructed to achieve this desired ACC vehicle behavior. Control simulations were performed using experimental data obtained in vehicle-following driving tests conducted on a proving ground course using a platoon of three manually driven vehicles. The results showed that the proposed ACC system satisfactorily achieved higher levels of required ACC performance.

The probability or risk of traffic accidents must be estimated quantitatively in order to implement effective traffic safety measures. In this study, various statistical data and probability theory were used to examine a method for predicting the risk of crossing-collisions, representing a typical type of accident at intersections in Japan. Crossing-collisions are caused by a variety of factors, including the road geometry and traffic environment at intersections and the awareness and intentions of the drivers of the striking and struck vehicles. Bayes' theorem was applied to find the accident probability of each factor separately. Specifically, the probability of various factors being present at the time of a crossing-collision was estimated on the basis of traffic accident data and observation survey data.

A safety support system that uses information received from the road infrastructure is being developed in a project sponsored by the Ministry of Land, Infrastructure and Transport. The purpose of this system is to reduce the number of accidents at intersections and on highways. The system is now being tested in an experimental vehicle. This paper describes what kind of information is helpful to drivers based on the experimental results.

Wheels play an important role in determining the aerodynamic drag of passenger vehicles. This is because the contribution of wheels to aerodynamic drag comes from not only the wheels themselves, but also from the interference effect between wheel wakes and the base wake. As far as the authors are aware, there have been no reports about aerodynamic drag sensitivity to wheel shape factors for different vehicle types and different exterior body shapes. The purpose of this study was to clarify CD sensitivity to wheel shape factors for a sedan and an SUV, including different rear fender shapes. Many different wheel configurations were investigated in terms of the CD, base pressure and flow fields in wind tunnel tests. Multiple regression analyses were conducted to clarify CD sensitivity to each wheel shape factor based on the test data. This study revealed high CD sensitivity factors for both the sedan and SUV.

An electric vehicle (EV) has less powertrain energy loss than an internal combustion engine vehicle (ICE), so its aerodynamic accounts have a larger portion of drag contribution of the total energy loss. This means that EV aerodynamic performance has a larger impact on the all-electric range (AER). Therefore, the target set for the aerodynamics development for a new EV hatchback was to improving AER for the customer’s benefit. To achieve lower aerodynamic drag than the previous model’s good aerodynamic performance, an ideal airflow wake structure was initially defined for the new EV hatchback that has a flat underbody with no exhaust system. Several important parameters were specified and proper numerical values for the ideal airflow were defined for them. As a result, the new EV hatchback achieves a 4% reduction in drag coefficient (CD) from the previous model.

The Hybrid III family of dummies is used to estimate the response of an occupant during a crash. One recent area of interest is the response of the neck during air bag loading. The biomechanical response of the Hybrid III dummy's neck was based on inertial loading during crash events, when the dummy is restrained by a seat belt and/or seat back. Contact loading resulting from an air bag was not considered when the Hybrid III dummy was designed. This paper considers the effect of air bag loading on the 5th percentile female Hybrid III dummies. The response of the neck is presented in comparison to currently accepted biomechanical corridors. The Hybrid III dummy neck was designed with primary emphasis on appropriate flexion and extension responses using the corridors proposed by Mertz and Patrick. They formulated the mechanical performance requirements of the neck as the relationship between the moment at the occipital condyles and the rotation of the head relative to the torso.

A two-channel LDV system is used to obtain accurate airflow measurements around scale models of passenger cars in wind tunnel tests at the Nissan Research Center. A 2-watt argon-ion laser is employed as the light source. The main optical unit and probe head are connected by optical fibers. The probe head consists of a compact LDV probe with a beam expander and focusing lens with a long focal length can be easily traversed. A new type of signal processor, performing a digital autocorrelation function, is employed to process the Doppler signals. Mean airflow velocities and turbulence intensities are calculated by a micro computer to evaluate the flow fields. The results of preliminary experiments conducted with this system indicate that the system is not only capable of measuring the mean velocity components, including reverse flow, it can also provide accurate estimation of turbulence components.

In making driver workload assessments, it is important to evaluate the driver's level of brain activity because the operation of a motor vehicle presumably involves higher-order brain functions. Driving on narrow roads in particular probably imposes a load on the driver's brain functions because of the need to be cognizant of the tight space and to pay close attention to the surroundings. Test vehicles were fitted with a functional near-infrared spectroscopy (fNIRS) system for measuring bloodstream concentrations at 32 locations in the frontal lobe of the participating drivers in order to evaluate their levels of mental activity while driving on narrow roads. The results revealed significant increases in cerebral blood flow corresponding to the perceived workload. This suggests that increases in cerebral blood flow can be used as an effective index for estimating mental workloads.

For the purpose of protecting the driver from injury in a crash, a safety standard has been established that specifies the allowable impact force when the driver hits the steering wheel as a result of an impact. In this work, an investigation was lade of steering column collapse behavior in which the steering column was constructed such that the crash energy was absorbed by the bending and tearing of a thin steel plate. As a result, a finite element analysis method has been developed for conducting an impact analysis using a ductile fracture model of the thin plate. This method makes it possible to predict the collapse behavior of the steering column and the deceleration that develops on the body block of the safety standard test model.

Eight rollover research tests were conducted using the 2001 Nissan Pathfinder with a modified FMVSS 208 dolly rollover test method where the driver and right front dummy restraint performance was analyzed. The rollover tests were initiated with the vehicle horizontal, not at a roll angle. After the vehicle translated laterally for a short distance, a trip mechanism was introduced to overturn the vehicle. Retractor, buckle, and latch plate performance in addition to the overall seat belt performance was analyzed and evaluated in the rollover test series. Retractor pretensioners were activated near the rollover trip in three of the tests to provide research data on its effects. Various dummy sizes were utilized. The test series experienced incomplete data collection and a portion of the analog data was not obtained. National Automotive Sampling System (NASS) data was also analyzed to quantify the characteristics of real world rollovers and demonstrated the benefits of restraint use.

The thermal fatigue resistance of engine exhaust system parts has conventionally been evaluated in thermal fatigue tests conducted with a restrained specimen. However, the test results have not always been consistent with data obtained in engine endurance tests. Two new evaluation methods have been developed to overcome this problem. One is a method of predicting thermal fatigue life on the basis of nonlinear elastic and plastic thermal analyses performed with a finite element model and the ABAQUS program. The other is a method of evaluating exhaust system parts using an exhaust system simulator. This paper describes the concepts underlying the two methods and their relative advantages.

In recent years, the slip lock-up mechanism has been adopted widely, because of its fuel efficiency and its ability to improve NVH. This necessitates that the automatic transmission fluid (ATF) used in automatic transmissions with slip lock-up clutches requires anti-shudder performance characteristics. The test methods used to evaluate the anti-shudder performance of an ATF can be classified roughly into two types. One is specified to measure whether a μ-V slope of the ATF is positive or negative, the other is the evaluation of the shudder occurrence in the practical vehicle. The former are μ-V property tests from MERCON® V, ATF+4®, and JASO M349-98, the latter is the vehicle test from DEXRON®-III. Additionally, in the evaluation of the μ-V property, there are two tests using the modified SAE No.2 friction machine and the modified low velocity friction apparatus (LVFA).