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The adoption of the electronic controlled steering systems with new technologies has been extended in recent years. They have interactions with other complex vehicle subsystems and it is a hard task for the vehicle developer to find the best solution from huge number of the combination of parameter settings with track tests. In order to improve the efficiency of the steering system development, the authors had developed a steering bench test method for steering system using a Hardware-In-the-Loop Simulation (HILS). In the steering HILS system, vehicle dynamics simulation and the tie rod axial force calculation are required at the same time in the real-time simulation environment. The accuracy of the tie rod axial force calculation is one of the key factors to reproduce the vehicle driving condition. But the calculation cannot be realized by a commercial software for the vehicle dynamics simulation.

Transport vehicles consume a large amount of fuel with low efficiency, which is significantly affected by drivers' behaviors. An assessment system of eco-driving pattern for buses could identify the deficiencies of driver operation as well as assist transportation enterprises in driver management. This paper proposes an assessment method regarding drivers' economic efficiency, considering driving conditions. To this end, assessment indexes are extracted from driving economy theories and ranked according to their effect on fuel consumption, derived from a database of 135 buses using multiple regression. A layered structure of assessment indexes is developed with application of AHP, and the weight of each index is estimated. The driving pattern score could be calculated with these weights.

The interactions between automatic controls, physics, and driver is an important step towards highly automated driving. This study investigates the dynamical interactions between human-selected driving modes, vehicle controller and physical plant parameters, to determine how to optimally adapt powertrain control to different human-like driving requirements. A cyber-physical system (CPS) based framework is proposed for co-design optimization of the physical plant parameters and controller variables for an electric powertrain, in view of vehicle’s dynamic performance, ride comfort, and energy efficiency under different driving modes. System structure, performance requirements and constraints, optimization goals and methodology are investigated. Intelligent powertrain control algorithms are synthesized for three driving modes, namely sport, eco, and normal modes, with appropriate protocol selections. The performance exploration methodology is presented.

Threat assessment (TA) method is vital in the decision-making process of intelligent vehicles (IVs), especially for ADAS systems. In the research of TA, the probabilistic threat assessment (PTA) method is acting an increasing role, which can reduce the uncertainties of driver’s maneuvers. However, the driver behavior model (DBM) used in present PTA methods was mainly constructed by limited data or simple functions, which is not entirely reasonable and may affect the performance of the TA process. This work aims to utilize crash data extracted from Event Data Recorder (EDR) to establish more accurate DBM and improve the current PTA method in rear-end situations. EDR data with responsive maneuvers were firstly collected, which were then employed to construct the initial DBM (I-DBM) model by using the multivariate Gaussian distribution (MGD) framework. Besides, the model was further subdivided into six parts by two important risk indicators, Time-to-collision (TTC) and velocity.

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.

In order to build a useful and comfortable in-car human machine interface systems, the information presentation method should be easy to understand (low mental workload) and one should be able to respond with ease to the information presented (low response workload). We are making efforts to establish an evaluation method that would differentiate between mental workload and response workload. Here, we present the results of our trial using brain waves measurements (Eye Fixation Related Potentials). We focus on the relation between P3 latencies and drivers response workload compared to mental workload in a task involving eye movements. Previous experiments showed that P3 latency correlates strongly with the amount of information presented. The current experiment shows that P3 latencies seem to be independent to the type of response the subject is requested to perform.

Pedestrian upper leg impact protection is a challenging requirement in the Euro NCAP assessment. In upper legform to bonnet leading edge tests, the legform impact force, the legform intrusion and the injury parameters (impact force and bending moment measured on the upper legform) are highly related to design of vehicle front-end styling and structure, as well as clearance underneath bonnet leading edge. In the course of impact, the contact area variation has significant influence on the stress distribution and consequently the force and the bending moment on the upper legform. Using finite element simulations of upper legform impact with a typical sedan, the deformation of the legform and the vehicle structure, and the variation of the contact force distribution are characterized and analyzed.

Automotive safety is always the focus of consumers, the selling point of products, the focus of technology. In order to achieve automatic driving, interconnection with the outside world, human-automatic system interaction, the security connotation of intelligent and connected vehicles (ICV) changes: information security is the basis of its security. Functional safety ensures that the system is operating properly. Behavioral safety guarantees a secure interaction between people and vehicles. Passive security should not be weakened, but should be strengthened based on new constraints. In terms of information safety, the threshold for attacking cloud, pipe, and vehicle information should be raised to ensure that ICV system does not fail due to malicious attacks. The cloud is divided into three cloud platforms according to functions: ICVs private cloud, TSP cloud, public cloud.

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.

A set of devices for measurement of human balance orientation and eye movements in weightlessness was developed for neurovestibular experiments on Spacelab. The experiments involve astronaut motion, limb position changes, and moving visual fields, measurements are made of eye movements, muscular activity and orientation perception. This joint US/Canadian research program represent a group of closely related experiments designed to investigate space motion sickness, any associated changes in otolith-mediated responses occurring during weightlessness, and the continuation of changes to postflight conditions. The otoliths are a component of the vestibular apparatus which is located in the middle ear. It is responsible for maintaining the body's balance. Gravitational pull on the otoliths causes them to constantly appraise the nervous system of the position of the head with respect to the direction of gravity.

This study focused on European NCAP activities of introducing a new head protection evaluation procedure, as proposed by BASt (Federal Highway Research Institute - GERMANY). Various kinds of E-bikes are available in the market, ranging from E-bikes that have a small motor to assist the rider’s pedal-power i.e., pedelecs to somewhat more powerful E-bikes which is similar to a moped-style scooter. This paper focused on identifying the factors influencing bicyclist head kinematics during bicycle vs. passenger vehicle (PV) collisions at the intersection. Two AM50 bicyclist FE models are developed using i) GHBMC Human Body Model (HBM) and ii) WorldSID (WS) side impact dummy. Head kinematics of bicyclists of pedal-assist E-bike and normal bike were compared using CAE simulation. It is found that the vehicle’s impact velocity, type of bicycle, the mass of E-bike and bicycle traveling speed will influence the head kinematics.

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.

An energy management strategy is needed to optimally allocate the driver's power demands to different power sources in the fuel cell hybrid vehicles. The driver's power demand is modelled as a Markov process in which the transition probabilities are estimated on the basis of the observed sample paths. The Markov Decision Process (MDP) theory is applied to design a stochastic energy management strategy for fuel cell hybrid vehicles. This obtained control strategy was then tested on a real time simulation platform of the fuel cell hybrid vehicles. In comparison to the other 3 strategies, the constant bus voltage strategy, the static optimization strategy and the dynamic programming strategy, simulations in the Beijing bus driving cycle demonstrate that the obtained stochastic energy management strategy can achieve better performance in fuel economy in the same demand of dynamic.

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.

Most of the side impact air bag systems in the current market are designed to protect the thorax area only. The new Head and Thorax SRS Side Impact Air Bag system, which Nissan recently introduced into the market, was designed to help provide additional protection for the head in certain side impacts. The system may help protect occupant head contacts when the vehicle collides into a tree, or the high hood of a large striking vehicle. This paper introduces the additional features and function of the new Head and Thorax SRS Side Impact Air Bag system, and some evaluation results in laboratory testing.

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.

Studying traffic accidents by using naturalistic driving data has become increasingly appealing for its potential benefits in improving road safety. This paper presents findings from a field test which has been conducted on 50 taxis in the urban areas of Beijing for 10 months using Video Drive Recorders (VDRs). The VDR used in this study could record the information of vehicle front view video, vehicle states, as well as driver operations immediately before and after an event. The drivers were given no specific instructions during the test, and the instrumentation for data collection was unobtrusive. Important safety-relevant parameters, such as vehicle speed, pre-event maneuver, time headway, time-to-collision, and driver reaction time, were calculated with precision. Based on these parameters, an analysis into features and causes of rear-end conflicts is performed.

People often feel discomfort when entering or exiting a vehicle because of a static electric shock. In the electronics industry, ionizers have been developed to prevent electrostatic discharges and contamination sticking around or on circuit components. Ionizers incorporate corona discharge principles to neutralize the static electric field. Using this idea, we developed an in-vehicle system to neutralize the human body charge. To accomplish this, the mechanism by which the human body attains a charge when exiting a vehicle was first defined. That definition was then used to determine the design characteristics of the system.

Natural speech contains a wide variety of expressions, making it much more difficult to recognize than specified verbal commands. We have developed a method using a language model template to generate language models capable of recognizing manifold expressions. This template method is designed on the basis of the modification structure of keywords. The evaluation results for a language model generated with this method showed that it allowed 630,000 command patterns with a high recognition rate of 96%. The results also revealed that the processing speed and memory used for speech recognition with this language model were at a practical level.