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The goal of this interview analysis was to explore and document the perceptions of two unique lane centering systems (S90’s Pilot Assist and CT6’s Super Cruise). Both systems offer a similar type of functionality (adaptive cruise control and lane centering), but have significantly different design philosophies and HMI (Human-Machine Interface) implementations. Twenty-four drivers drove one of the two vehicle models for a month as part of a field operational test (FOT) study. Upon vehicle return, drivers took part in a 60-minute semi-structured interview covering their perceptions of the vehicle’s various advanced driver-assistance systems (ADAS). Transcripts of the interviews were coded by two researchers, who tagged each statement with relevant system and perception code labels. For analysis, the perception codes were grouped into larger thematic bins of safety, comfort, driver attention, and system performance.

To make informed decisions about travel and vehicle purchase, consumers need unbiased and accurate information of the fuel economy they will actually obtain. In the past, the EPA fuel economy estimates based on its 1984 rules have been widely criticized for overestimating on-road fuel economy. In 2008, EPA adopted a new estimation rule. This study compares the usefulness of the EPA's 1984 and 2008 estimates based on their prediction bias and accuracy and attempts to improve the prediction of on-road fuel economies based on consumer and vehicle attributes. We examine the usefulness of the EPA fuel economy estimates using a large sample of self-reported on-road fuel economy data and develop an Individualized Model for more accurately predicting an individual driver's on-road fuel economy based on easily determined vehicle and driver attributes. Accuracy rather than bias appears to have limited the usefulness of the EPA 1984 estimates in predicting on-road MPG.

To provide useful information for automakers to design successful plug-in hybrid electric vehicle (PHEV) products and for energy and environmental analysts to understand the social impact of PHEVs, this paper addresses the question of how many of the U.S. consumers, if buying a PHEV, would prefer what electric ranges. The Market-oriented Optimal Range for PHEV (MOR-PHEV) model is developed to optimize the PHEV electric range for each of 36,664 sampled individuals representing U.S. new vehicle drivers. The optimization objective is the minimization of the sum of costs on battery, gasoline, electricity and refueling hassle.

It is rare for an attempt towards optimization at the fleet-level when consideration is given to the sheer number of seemingly unpredictable interactions among vehicles and infrastructure in congested urban areas. To close the gap, we introduce a simulation based framework to explore the impact of speed synchronization on fuel economy improvement for fleets in traffic. The framework consists of traffic and vehicle modules. The traffic module is used to simulate driver behavior in urban traffic; and the vehicle module is employed to estimate fuel economy. Driving schedule is the linkage between these two modules. To explore the impact, a connected vehicle technology sharing vehicle speed information is used for better fuel economy of a fleet including six vehicles. In all scenarios analyzed, the leading vehicle operates under the EPA Urban Dynamometer Driving Schedule (UDDS), while the other five vehicles follow the leader consecutively.

Current artificial intelligence techniques for end to end driving of autonomous vehicles typically rely on a single form of learning or training processes along with a corresponding dataset or simulation environment. Relatively speaking, success has been shown for a variety of learning modalities in which it can be shown that the machine can successfully “drive” a vehicle. However, the realm of real-world driving extends significantly beyond the realm of limited test environments for machine training. This creates an enormous gap in capability between these two realms. With their superior neural network structures and learning capabilities, humans can be easily trained within a short period of time to proceed from limited test environments to real world driving.

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.

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.

Flat panel displays for automobiles are facing a new era with the development of navigation systems. As navigation systems become more important as driver's assistance devices, development of birds-eye-view and 3D displays continues, as well as improvements for larger display screens and higher mounting positions. In response to the progress of mobile multimedia technologies, demands for larger display screens and larger aspect ratios have been increasing. Significance for improvements to anti-glare features or view angles has increased as they provide better visibility and the increase layout options. The use of human machine information interaction, which interfaces visual, audio and tactile senses, makes it possible to realize safer, more convenient and comfortable multimedia era 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.

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.

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.

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 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.

On-board voice-interaction systems such as a voice-activated system or a text -to-speech (TTS) system enable drivers to operate devices or to obtain desired information without relying on visual processes. These systems are aimed to reduce the driver's workload, but there is a concern about their possible effect on mental distraction. This paper describes driving simulator tests that were conducted to examine the potential influence of such systems on driver's mental distraction. The results obtained for all of the indices show that the mental distraction level when operating a voice-activated system is significantly lower than that of a traditional manually operated system.

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.

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.

In this study, an attempt was made to apply the steering entropy method, proposed by Boer and Nakayama as a workload measurement technique, to a comparative evaluation of the workload of older and younger drivers. As the first step, driving simulator tests were conducted to examine a method of making comparisons between subjects whose driving performance differed. The same method was then used in making evaluations during driving tests conducted with an actual vehicle. Under the conditions used in this study, the results indicate that it should be possible to compare driving workloads among different subjects through the combined used of Hp and α. Hp is a quantified value of steering perturbation as an information entropy value that is calculated from a time history of steering angle data. It changes between 0 (no steering perturbation) and 1 (absolute randomness) in a theoretical sense.

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.

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.

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.