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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.

Vehicle to Vehicle Communication use case performance heavily relies on market penetration rate. The more vehicles support a use case, the better the customer experience. Enabling these use cases with acceptable quality on vehicles without built-in navigation systems, elaborate map matching and highly accurate sensors is challenging. This paper introduces a simulation framework to assess system performance in dependency of vehicle positioning accuracy for matching approach path traces in Decentralized Environmental Notification Messages (DENMs) in absence of navigation systems supporting map matching. DENMs are used for distributing information about hazards on the road network. A vehicle without navigation system and street map can only match its position trajectory with the trajectory carried in the DENM.

Lean NOx Traps (LNTs) are one type of lean NOx reduction technology typically used in smaller diesel passenger cars where urea-based Selective Catalytic Reduction (SCR) systems may be difficult to package . However, the performance of lean NOx traps (LNT) at temperatures above 400 C needs to be improved. The use of Rapidly Pulsed Reductants (RPR) is a process in which hydrocarbons are injected in rapid pulses ahead of a LNT in order to expand its operating window to higher temperatures and space velocities. This approach has also been called Di-Air (diesel NOx aftertreatment by adsorbed intermediate reductants) by Toyota. There is a vast parameter space which could be explored to maximize RPR performance and reduce the fuel penalty associated with injecting hydrocarbons. In this study, the mixing uniformity of the injected pulses, the type of reductant, and the concentration of pulsed reductant in the main flow were investigated.

This paper focuses on finding and analyzing the relevant parameters affecting traffic flow when autonomous vehicles are introduced for ride hailing applications and autonomous shuttles are introduced for circulator applications in geo-fenced urban areas. For this purpose, different scenarios have been created in traffic simulation software that model the different levels of autonomy, traffic density, routes, and other traffic elements. Similarly, software that specializes in vehicle dynamics, physical limitations, and vehicle control has been used to closely simulate realistic autonomous vehicle behavior under such scenarios. Different simulation tools for realistic autonomous vehicle simulation and traffic simulation have been merged together in this paper, creating a realistic simulator with Hardware-in-the-Loop (HiL), Traffic-in-the-Loop (TiL), and Software in-the-Loop (SiL) simulation capabilities.

The transportation sector is facing three revolutions: shared mobility, electrification, and autonomous driving. To inform decision making and guide smart transportation system development at the city-level, it is critical to model and evaluate how travelers will behave in these systems. Two key components in such models are (1) individual travel demands with high spatial and temporal resolutions, and (2) travelers’ sociodemographic information and trip purposes. These components impact one’s acceptance of autonomous vehicles, adoption of electric vehicles, and participation in shared mobility. Existing methods of travel demand generation either lack travelers’ demographics and trip purposes, or only generate trips at a zonal level. Higher resolution demand and sociodemographic data can enable analysis of trips’ shareability for car sharing and ride pooling and evaluation of electric vehicles’ charging needs.

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.

The USDOT and the Crash Avoidance Metrics Partnership-Vehicle Safety Communications 2 (CAMP-VSC2) Consortium (Ford, GM, Honda, Mercedes, and Toyota) initiated, in December 2006, a three-year collaborative effort in the area of wireless-based safety applications under the Vehicle Safety Communications-Applications (VSC-A) Project. The VSC-A Project developed and tested communications-based vehicle safety systems to determine if Dedicated Short Range Communications (DSRC) at 5.9 GHz, in combination with vehicle positioning, would improve upon autonomous vehicle-based safety systems and/or enable new communications-based safety applications.

The United States Department of Transportation (USDOT) and the Crash Avoidance Metrics Partnership-Vehicle Safety Communications 2 (CAMP-VSC2) Consortium (Ford, General Motors, Honda, Mercedes-Benz, and Toyota) initiated, in December 2006, a three-year collaborative effort in the area of wireless-based safety applications under the Vehicle Safety Communications-Applications (VSC-A) Project. The VSC-A Project developed and tested Vehicle-to-Vehicle (V2V) communications-based safety systems to determine if Dedicated Short Range Communications (DSRC) at 5.9 GHz, in combination with vehicle positioning, would improve upon autonomous vehicle-based safety systems and/or enable new communications-based safety applications.

The ways in which vehicles are used in the field are continually becoming more diverse. In order to provide the optimum solution with respect to performance and weight, it is necessary to be able to assure vehicle endurance reliability with a high degree of accuracy in relation to the manner of use in each market. This situation has increased the importance of accurately quantifying the ways in which vehicles are used in the field and of designing vehicles with sufficient endurance reliability to match the usage requirements. This report presents a “market model” by which the manner of usage in the field can be treated quantitatively using combinations of environmental factors that influence the road load, drive load and corrosion load, representing typical loads vehicles must withstand.

Detergent additives in automotive gasoline fuel are mainly designed to reduce deposit formation on intake valves and fuel injectors, but it has been reported that some additives may contribute to CCD formation. Therefore, a standardized bench engine test method for CCDs needs to be developed in response to industry demands. Cooperative research between the Petroleum Association of Japan (PAJ) and the Japan Automobile Manufacturers Association, Inc. (JAMA), has led to the development of a 2.2L Honda engine dynamometer-based CCD test procedure to evaluate CCDs from fuel additives. Ten automobile manufacturers, nine petroleum companies and the Petroleum Energy Center joined the project, which underwent PAJ-JAMA round robin testing. This paper describes the CCD test development activities, which include the selection of an engine and the determination of the optimum test conditions and other test criteria.

This paper describes a headway distance control system for platoon driving on an automated highway system (AHS). The system implemented on a test vehicle is described first, followed by a description of a vehicle control method based on the use of throttle and brake actuators. This method makes it possible to obtain the target acceleration and deceleration regardless of the vehicle speed range and the rate of acceleration or deceleration. Experimental and simulation results obtained with this method are presented. A control method is then described that uses inter-vehicle communication and laser radar to maintain a constant headway between vehicles. The results of simulations and driving tests conducted with three vehicles are presented to illustrate that the use of inter-vehicle communication is highly effective in improving headway control performance.

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.

In the past few years, car navigation and cellular phone system are rapidly increased in Japan and vehicle information and communication system (VICS), the public traffic information service started in 1996, accelerates realization of ITS world. This rapid movement causes drivers to want more information on not only traffic jam but also other versatile items like parking availability, weather report and the latest news, etc. via cellular phone network. This paper describes the on-demand information service with the interactive human interface by operators and the development of the information center and the in-vehicle system to realize it.

Trail-Braking (TB) is a common cornering technique used in rally racing to negotiate tight corners at (moderately) high speeds. In a previous paper by the authors it has been shown that TB can be generated as the solution to the minimum-time cornering problem, subject to fixed final positioning of the vehicle after the corner. A TB maneuver can then be computed by solving a non-linear programming (NLP). In this work we formulate an optimization problem by relaxing the final positioning of the vehicle with respect to the width of the road in order to study the optimality of late-apex trajectories typically followed by rally drivers. We test the results on a variety of corners. The optimal control inputs are approximated by simple piecewise linear input profiles defined by a small number of parameters. It is shown that the proposed input parameterization can generate close to optimal TB along the various corner geometries.

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.

Wavelets are a powerful mathematical tool used to multi-resolution time-frequency decomposition of signals, in order to analyze them in different scales and obtain different aspects of the information. Despite being a relatively new tool, wavelets have being applied in several areas of human knowledge, especially in signal processing, with emphasis in encoding and compression of image, video and audio. Based on a previous successful applications (FRAZIER, 1999) together a commitment to quality results, this paper evaluates the use of the Discrete Wavelet Transform (DWT) as an compression algorithm to reduce the amount of data collected in road load signals (load history) which are used by the durability engineering teams in the automotive industry.

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.

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.

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.

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.