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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.

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.

The challenge of developing a robust, real-time driver gaze classification system is that it has to handle difficult edge cases that arise in real-world driving conditions: extreme lighting variations, eyeglass reflections, sunglasses and other occlusions. We propose a single-camera end-toend framework for classifying driver gaze into a discrete set of regions. This framework includes data collection, semi-automated annotation, offline classifier training, and an online real-time image processing pipeline that classifies the gaze region of the driver. We evaluate an implementation of each component on various subsets of a large onroad dataset. The key insight of our work is that robust driver gaze classification in real-world conditions is best approached by leveraging the power of supervised learning to generalize over the edge cases present in large annotated on-road datasets.

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.

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.

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.

Accurately predicting real-world vehicle energy consumption is essential for optimizing vehicle designs, enhancing energy efficiency, and developing effective energy management strategies. This paper presents a data-driven approach that utilizes machine learning techniques and a comprehensive dataset of vehicle parameters and environmental factors to create precise energy consumption prediction models. The methodology involves recording real-world vehicle data using data loggers to extract information from the CAN bus systems for ICE and hybrid electric, as well as hydrogen and battery fuel cell vehicles. Data cleaning and cycle-based analysis are employed to process the dataset for accurate energy consumption prediction. This includes cycle detection and analysis using methods from statistics and signal processing, and then pattern recognition based on these metrics.

This paper presents the results of a study of how people interacted with a production voice-command based interface while driving on public roadways. Tasks included phone contact calling, full address destination entry, and point-of-interest (POI) selection. Baseline driving and driving while engaging in multiple-levels of an auditory-vocal cognitive reference task and manual radio tuning were used as comparison points. Measures included self-reported workload, task performance, physiological arousal, glance behavior, and vehicle control for an analysis sample of 48 participants (gender balanced across ages 21-68). Task analysis and glance measures confirm earlier findings that voice-command interfaces do not always allow the driver to keep their hands on the wheel and eyes on the road, as some assume.

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.

An automatic, falling, occupant-protecting net is being developed for spreading in front of automobile occupants in the time interval between vehicle impact and occupant collision. The device is designed to counteract forward body acceleration and minimize head, neck, and chest injuries. This device was investigated by sled and barrier tests using anthropomorphic dummies. Significant improvements in occupant kinematics and remarkable reduction in head and chest impact force has been observed. Some problems such as whiplash injury await solution but continuing investigation of proposed measures of correction show that they are not insurmountable.

The use of automatic transmissions is continually increasing because of their ease of operation. Transmission performance requirements that have become more important in recent years include smooth shift quality and a shift schedule that matches the driver's intentions. An electronically controlled automatic gearbox, which sets the shift schedule according to the vehicle speed and throttle valve opening, provides a dramatic improvement in shift quality over its hydraulically controlled counterpart. However, even with an electronically controlled automatic transmission, shift hunting occurs when driving uphill or towing an object Based on the use of fuzzy logic, a technique has been developed for estimating running resistance, represented by the road gradient. This technique has been incorporated in a new shift schedule control method that eliminates shin hunting Research is now under way on a fuzzy logic technique for inferring the driver's intention to accelerate

Because of rising demands to improve aerodynamic performance owing to its impact on vehicle dynamics, efforts were previously made to reduce aerodynamic lift and yawing moment based on steady-state measurements of aerodynamic forces. In recent years, increased research on dynamic aerodynamics has partially explained the impact of aerodynamic forces on vehicle dynamics. However, it is difficult to measure aerodynamic forces while a vehicle is in motion, and also analyzing the effect on vehicle dynamics requires measurement of vehicle behavior, amount of steering and other quantities noiselessly, as well as an explanation of the mutual influence with aerodynamic forces. Consequently, the related phenomena occurring in the real world are still not fully understood.

At Nissan we have developed a new parallel hybrid system for rear-wheel-drive hybrid vehicles. As the main components of the hybrid system, both the motor and the inverter have been developed and are manufactured in house to attain high power density for providing responsive acceleration, a quiet EV drive mode and improved fuel economy. Because the motor is located between the engine and the transmission, it had to be shortened to be within the length allowed for the powertrain. Therefore, new technologies have been developed such as high-density, square-shaped windings and an optimized magnetic circuit specially designed for concentrated winding motors. The inverter is sized to a 12V battery, which it replaces in the engine compartment. Despite its compact size, the inverter must have rather large current capacity to drive a high-power motor. Heat management is critical to the design of a small but high-power inverter.

The fuel energy consumption of subsonic air transportation is examined. The focus is on identification and quantification of fundamental engineering design tradeoffs which drive the design of subsonic tube and wing transport aircraft. The sensitivities of energy efficiency to recent and forecast technology developments are also examined.

This paper describes the method used to design the basic control algorithm of a lane-keeping support system that is intended to assist the driver's steering action. Lane-keeping control has been designed with steering torque as the control input without providing a minor loop for the steering angle. This approach was taken in order to achieve an optimum balance of lane-keeping control, ease of steering intervention by the driver and robustness. The servo control system was designed on the basis of H2 control theory. Robustness against disturbances, vehicle nonlinearity and parameter variation was confirmed by μ - analysis. The results of computer simulations and driving tests have confirmed that the control system designed with this method provides the intended performance.

A new map display technique has been developed for car navigation systems that presents a bird's-eye view of three-dimensional map images. This view allows both detailed and wide-area information to be presented simultaneously in a single screen display. It provides drivers with a reassuring feeling while driving along their route because the two types of information can guide them accurately to their destination. The results of evaluation tests have confirmed the effectiveness of this technique. On the other hand, some aspects requiring further improvement were also identified. This paper discusses how the technique was developed and describes the tests conducted to evaluate its effectiveness along with the results obtained.

This paper presents a newly developed adaptive cruise control system with low-speed following capability that is designed to reduce the driver's workload in low-speed driving such as in congested traffic. This system incorporates a forward-looking sensor with a wider range of view for improved detection of a preceding vehicle in the same lane. It also has a control algorithm that achieves natural vehicle behavior without any disconcerting feeling, as a result of being constructed on the basis of analyses of driving behavior characteristics at low speed like that of congested traffic. Evaluations conducted on a driving simulator have confirmed that the system is effective in reducing the driver's workload.