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Wireless Power Transfer (WPT) promises automated and highly efficient charging of electric and plug-in-hybrid vehicles. As commercial development proceeds forward, the technical challenges of efficiency, interoperability, interference and safety are a primary focus for this industry. The SAE Vehicle Wireless Power and Alignment Taskforce published the Recommended Practice J2954 to help harmonize the first phase of high-power WPT technology development. SAE J2954 uses a performance-based approach to standardizing WPT by specifying ground and vehicle assembly coils to be used in a test stand (per Z-class) to validate performance, interoperability and safety. The main goal of this SAE J2954 bench testing campaign was to prove interoperability between WPT systems utilizing different coil magnetic topologies. This type of testing had not been done before on such a scale with real automaker and supplier systems.

Road Noise is generated by the change of random displacement input inside the tire contact patch. Since the existing 3 or 6 directional electromagnetic shakers have a flat surface at the tire contact patch, these shakers cannot excite the vehicle in a manner representative of actual on-road road noise input. Therefore, this paper proposes a new experimental method to measure the road noise vehicle transfer function. This method is based on the reciprocity between the tire contact patch and the driver's ear location. The reaction force sensor of the tire contact patch is newly developed for the reciprocal loud speaker excitation at the passenger ear location. In addition, with this equipment, it is possible to extract the dominant structural mode shapes creating high sound pressure in the automotive interior acoustic field. This method is referred to as experimental structure mode participation to the noise of the acoustic field in the vibro-acoustic coupling analysis.

This paper deals with a vehicle detection method for realizing a blind spot warning function, under various environmental conditions. We introduced a method that is capable of discriminating the target object vehicles, under poor lighting conditions and in cases where the lens may be exposed to splashes in wet, snow and dirt roads. The image sensing of the vehicle detection consists of four functional components: obstacle detection, velocity estimation, vertical edge detection, and final classification. Such componets allow robust performances resembling geometry based approaches, with low calculation power as an apperance based approach. This paper describes the functional components, and furthermore methods to enhance the performances under low contrast conditions and also suppress false detections caused by residue on the lens, which becomes essential for installation on vehicles driven in actual road conditions.

An active vision system equipped with a high-speed pulsed light-emitting projector and a high-speed image sensor is proposed and applied to lane marker detection in this paper. The proposed system has the capability to suppress image information obtained from the background light and provides only the image information from the signal light emitted by the projector. This is accomplished by synchronizing image capture with the time of signal light emission. To reduce the power consumption and cost of the system, a relatively low intensity projector is used as the light source. The background illuminance on a bright day can be much higher than that of the signal. To improve the signal-to-background ratio, the signal light is modulated using a pulse width modulation technique. Then, the image is captured using a high-speed camera operating in synchronization with the time the signal light is emitted.

In 2006, Nissan began limited leasing of the X-TRAIL FCV equipped with their in-house developed Fuel Cell (FC) stack. Since then, the FC stack has been improved in durability, cold start-up capability, cost and size with the aim of promoting full-scale commercialization of FCVs. However, reduction of cost and size has remained a significant challenge because limited mass transport through the membrane electrode assembly (MEA) has made it difficult to increase the rated current density of the FC. Furthermore, it has been difficult to reduce the variety of FC stack components due to the complex stack configuration. In this study, improvements have been achieved mainly by adopting an advanced MEA to overcome these difficulties. First, the adoption of a new MEA and separators has improved mass transport through the MEA for increased rated current density. Second, an integrated molded frame (IMF) has been adopted as the MEA support.

In 2006, Nissan began limited leasing of the X-TRAIL FCV equipped with their in-house developed Fuel Cell (FC) stack. Since then, the FC stack has been improved in cost, size, durability and cold start-up capability with the aim of promoting full-scale commercialization of FCVs. However, reduction of cost and size has remained a significant challenge because limited mass transport through the membrane electrode assembly (MEA) has made it difficult to increase the rated current density of the FC. Furthermore, it has been difficult to reduce the variety of FC stack components due to the complex stack configuration. In this study, improvements have been achieved mainly by adopting an advanced MEA to overcome these difficulties. First, the adoption of a new MEA and separators has improved mass transport through the MEA for increased rated current density. Second, an integrated molded frame (IMF) has been adopted as the MEA support.

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.

After the turn of the century, growing social attention has been paid to environmental concerns, especially the reduction of greenhouse gas emissions and it comes down to a personal daily life concern which will affect the purchasing decision of vehicles in the future. Among all the sources of greenhouse gas emissions, the transportation industry is the primary target of reduction and almost every automotive company pours unprecedented amounts of money to reengineer the vehicle technologies for better fuel efficiency and reduced CO2 emission. Besides those efforts paid for sheer improvements of genuine vehicle technologies, NISSAN testified that “connectivity” with outside servers contributed a lot to reduce fuel consumption, thus the less emission of GHG, with two major factors; 1. detouring the traffic congestions with the support of probe-based real-time traffic information and 2. providing Eco-driving advices for the better driving behavior to prompt the better usage of energy.

Curbing emissions of carbon dioxide (CO₂), which is believed by many scientists to be a major contributor to global warming, is one of the top priority issues that must be addressed by automobile manufacturers. Automakers have set their own strategies to improve fuel economy and to reduce CO₂ emissions. Some of them include integrated approaches, focusing on not only improvement of vehicle technology, but also human factors (eco-driving support for drivers) and social and transportation factors (traffic management by intelligent transportation systems [ITS]). Among them, electric vehicles (EVs) will be a key contributor to attaining the challenging goal of CO₂ reduction. Mass deployment of EVs is required to achieve a zero-emission society. To accomplish that, new advanced technologies, new business schemes, and new partnerships are required.

To promote widespread use of fuel cell vehicles (FCVs), further improvement of cold start capability is required for operation in various extreme temperature regions all over the world. Sub-freezing, cold start issues of fuel cells must be resolved through gaining a better understanding of the physical phenomena taking place in a cell during cold start and by elucidating the mechanisms hindering cold startup. Nissan has improved its understanding of the physical phenomena occurring in a fuel cell (FC) during cold startup by a laboratory-scale FC experiment at subfreezing temperatures and a numerical calculation that expresses various transport processes in a fuel cell, including those of the reactant gases, water, electrons and heat. The results have identified several necessary conditions for mass transport in a cell during cold startup and the factors that limit and govern the phenomena involved.

The SKY Project (Start ITS from Kanagawa, Yokohama) was launched in October 2004 in Yokohama, Japan in order to contribute to the local community by reducing traffic accidents and congestion. SKY is a private sector collaboration between Nissan Motor Co., Ltd., NTT DoCoMo, Inc., Panasonic Corporation, and Xanavi Informatics Corporation (now Clarion Ltd.). Support has also been provided from the public sector, namely the National Police Agency of Japan (NPA) and the Kanagawa Prefectural Police. Through the use of in-vehicle technology and an Intelligent Transportation Systems (ITS) that communicates with the infrastructure, information on nearby vehicles and the surrounding traffic environment can be utilized to reduce traffic accidents, shorten travel times, and increase fuel savings. These are the goals of the SKY project. This paper shows the results of early stage testing and the introduction of newly started trials.

In order to reduce traffic accidents and ease traffic congestion utilizing ITS (Intelligent Transportation System), a large-scale FOT (Field Operational Test) involving 2,000 ordinary drivers was launched in October 2006 in the city of Yokohama in Kanagawa, Japan. The test is slated to continue through March 2009. Target applications include Intersection Collision Avoidance using V-I (Vehicle-to-Infrastructure) communication, ISA (Intelligent Speed Advisory) using digital maps in the vehicle navigation system, and the probe system, which provides detailed traffic information. In this paper, the progress of this FOT will be introduced.

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.

This paper describes a new 5.6-liter DOHC V8 engine, VK56DE, which was developed for use on a new full-size sport utility vehicle and a full-size pickup truck. To meet the demands for acceleration performance when merging into freeway traffic, passing or re-acceleration performance from low speed in city driving and hill-climbing or passing performance when towing, the VK56DE engine produces high output power at top speed and also generates ample torque at low and middle engine speeds (90% of its maximum torque is available at speeds as low as 2500 rpm). Furthermore, this engine achieves top-level driving comfort in its class as a result of being derived from the VK45DE engine that was developed for use on a sporty luxury sedan. Development efforts were focused on how to balance the required performance with the need for quietness and smoothness.

Traffic accidents in Japan claim some 10,000 precious lives every year, and there is seemingly no end to the problem. In an effort to overcome this situation, vehicle manufacturers have been pushing ahead with the development of a variety of advanced safety technologies. Joint public- private sector projects related to Intelligent Transport Systems (ITS) are also proceeding vigorously. Most accidents can be attributed to driver error in recognition, judgment or vehicle operation. This paper presents an analysis of driver behavior characteristics in emergency situations that lead to an accident, focusing in particular on operation of the brake pedal. Based on the insights gained so far, we have developed a Brake Assist System with a Preview Function (BAP) designed to prevent accidents by helping drivers with braking actions. Experimental results have confirmed that BAP is effective in reducing the impact speed and the frequency of accidents in emergency situations.

Traffic accidents in Japan claim some 10,000 precious lives every year, and there is seemingly no end to the problem. In an effort to overcome this situation, vehicle manufacturers have been pushing ahead with the development of a variety of advanced safety technologies. Joint public-private sector projects related to Intelligent Transport Systems (ITS) are also proceeding vigorously. Most accidents can be attributed to driver error in recognition, judgment or vehicle operation. This paper presents an analysis of driver behavior characteristics in emergency situations that lead to an accident, focusing in particular on operation of the brake pedal. Based on the insights gained so far, we have developed a Brake Assist System with a Preview Function (BAP) designed to prevent accidents by helping drivers with braking actions. Experimental results have confirmed that BAP is effective in reducing the impact speed and the frequency of accidents in emergency situations.

An Adaptive Cruise Control system with stop-and-go capability has been developed to reduce the driver's workload in traffic jams on expressways. Based on an analysis of driving behavior characteristics in expressway traffic jams, a control system capable of modeling those characteristics accurately has been constructed to provide natural vehicle behavior in low-speed driving. The effectiveness of the system was evaluated with an experimental vehicle, and the results confirmed that it reduces the driver's workload. This paper presents an outline of the system and its effectiveness along with the experimental results.

This paper describes an image processing system for tracking a traffic lane by recognizing white lines on the road ahead. The system utilizes the features of the white lines and the Hough transformation to detect white line candidate points in images taken with a CCD camera. The parameters of the road configuration and vehicle attitude are estimated with an extended Kalman filter. This system has been applied to achieve a lane-keeping assistance system that provides steering control based on the host vehicle’s lateral position in its lane.

Two working groups in the JSAE Committee of Fatigue–Reliability Section1 are currently researching the issue of fatigue life by both experimental and the CAE approach. Information regarding frequent critical problems on arc–welded structures were sought from auto–manufacturers, vehicle component suppliers, and material suppliers. The method for anti–fatigue design on arc–welded structures was established not only by a database created by physical test results in accordance with the collected information but also with design procedure taking Fracture–Mechanics into consideration. This method will be applied to vehicle development as one of the virtual laboratories in the digital prototype phase. In this paper, both the database from bench–test results on arc welded structures and FEA algorithm unique to JSAE are proposed some of the analysis results associated with the latter proposal are also reported.

This paper describes an image processing method for recognizing white lines on the road ahead to accomplish automatic lane tracking. The behavior of detected points on the white lines can be regarded as multi-channel time-series data. The stochastic behavior of each point correlates with not only its own past behavior but also the behavior of other points around it. Behavior is identified by using a multi-variable auto-regressive (AR) model. This method can estimate the road configuration ahead logically even if the points cannot be detected clearly because a line is discontinuous or is hidden by a forward vehicle.