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1. On page 111, the authors have described a method to assess driver distraction. In this method, participants maintained a white square size on a forward display by using a game gas pedal of like in car-following situation. The size of the white square is determined by calculating the distance to a virtual lead vehicle. The formulas to correct are used to explain variation of acceleration of the virtual lead vehicle. The authors inadvertently incorporated old formulas they had used previously. In the experiments discussed in the article, the corrected formulas were used. Therefore, there is no change in the results. The following from the article:

LCDs are effective to display abundant information in a compact space. Therefore, the use of TFT or DOT metric displays in dashboard instrument display is getting popular in recent years. However, it is important issue for car makers how to let users know information about vehicle functions or outside environment and manage plentiful information. In this paper, the Rapid Control Prototyping (RCP) tool is proposed to design and standardize HMI logic associated with display contents in TFT or dot type LCD applied to an instrument cluster. In addition, it is possible to estimate HMI logic in advance by using this RCP. By this process, we can minimize the design and validation time of the vehicle specific HMI logic and improve the quality. As a result, we can dramatically reduce the total period of developing an instrument cluster.

A driving simulator capable of duplicating the critical sensations incurred during a spin, or when a driver is engaged in drift cornering, was constructed by Mitsubishi Heavy Industries, Ltd., and Hiromichi Nozaki of Kogakuin University. Specifically, the simulator allows independent movement along three degrees of freedom and is capable of exhibiting extreme yaw and lateral acceleration behaviors. Utilizing this simulator, the control characteristics of drift cornering have become better understood. For example, after a J-turn behavior experiment involving yaw angle velocity at the moment when the drivers attention transitions to resuming straight ahead driving, it is now understood that there are major changes in driver behavior in circumstances when simulator motions are turned off, when only lateral acceleration motion is applied, when only yaw motion is applied, and when combined motions (yaw + lateral acceleration) are applied.

The MX-2 neutral buoyancy space suit analogue has been designed and developed at the University of Maryland to facilitate analysis of space suit components and assessment of the benefits of advanced space suit technologies, The MX-2 replicates the salient features of microgravity pressure suits, including the induced joint torques, visual, auditory and thermal environments, and microgravity through the use of neutral buoyancy simulation. In this paper, design upgrades and recent operations of the suit are outlined, including many experiments and tests of advanced space suit technologies, This paper focuses on the work done using the MX-2 to implement and investigate various advanced controls and displays within the suit, to enhance crewmember situational awareness and effectiveness, and enable human-robotic interaction.

Driver distraction is a topic of considerable interest, with the public debate centering on the use of cell phones and texting while driving. However, the driver distraction/overload issue is really much larger. It concerns specific tasks such as entering destinations on navigation systems, retrieving songs on MP3 players, accessing web pages, checking stocks, editing spreadsheets, and performing other tasks on smart phones, as well as, more generally, using in-vehicle information systems. Five major problems related to distraction/overload research and engineering and their solutions are addressed in this paper.

With Ford SYNC, Microsoft Corporation and Ford Motor Company have democratized in-vehicle infotainment systems - delighting consumers and bringing a new kind of agility to the automobile industry. Built on Microsoft Auto (now Windows Embedded Automotive), Ford SYNC is a factory-installed, voice-controlled communications and entertainment system that allows drivers to converge their digital lifestyle with their life on the road. Windows Embedded Automotive is an industry leading technology platform that provides integrated infotainment features and a rich user interface. Car manufacturers and suppliers worldwide can use this software to create differentiated, infotainment in-vehicle systems that are immediately attractive to consumers.

The use of model-based software development in automotive applications has increased in recent years. Current vehicles contain millions of lines of code, and millions of dollars are spent each year fixing software issues. Most new features are software controlled and many times include distributed functionality, resulting in increased vehicle software content and accelerated complexity. To handle rapid change, OEMs and suppliers must work together to accelerate software development and testing. As development processes adapt to meet this challenge, model-based design can provide a solution. Model-based design is a broad development approach that is applied to a variety of applications in various industries. This paper reviews a project using the MATLAB/Simulink/Stateflow environment to complete a functional model of a low cost radio.

This study presents an on-road evaluation of driver performance when controlling in-car technology via a handheld or voice-controlled interface. Participants drove with an experimenter on public roads while making mobile phone calls, having brief phone conversations, and playing tracks from a portable music player using both types of interface. The test vehicle was an instrumented 2010 Mercury Mariner equipped with the Ford SYNC® system, which allows for voice control of mobile phones and portable music devices. Twenty-one participants were tested, including 12 younger (19-34) and 9 older (39-51). All participants were owners of a vehicle equipped with the voice-control system, and all used the system regularly for phone calls and music playback.

The statistical analysis of vehicle crash accident data is generally problematic. Data from commonly used sources is almost never without error and complete. Consequently, many analyses are contaminated with modeling and system identification errors. In some cases the effect of influential factors such as crash severity (the most significant component being speed) driver behavior prior to the crash, etc. on vehicle and occupant outcome is not adequately addressed. The speed that the vehicle is traveling at the initiation of a crash is a significant contributor to occupant risk. Not incorporating it may make an accident analysis irrelevant; however, despite its importance this information is not included in many of the commonly used crash data bases, such as the Fatality Analysis Reporting System (FARS). Missing speed information can result in potential errors propagating throughout the analysis, unless a method is developed to account for the missing information.

This paper proposes a novel modeling and simulation environment developed under Matlab/Simulink with friendly and intuitive graphic user interfaces, aimed to enable math-based virtual development and test of intelligent driving systems. Six typical driving maneuvers are first proposed, which are further abstracted into two atomic sub-maneuvers: lane following and lane change, as any maneuvers can be the combinations of these two. A generic trajectory planning and path tracking control algorithm are developed to deal with the generality and commonality of the lane change function with optimization among safety, comfort and efficiency in performing the lane change maneuver. Some typical simulations are conducted with results demonstrating the practical usefulness, efficiency and convenience in using this proposed tool.

Advanced driver assistance systems like cooperative adaptive cruise control (CACC) are designed to exploit information provided by vehicle-to-vehicle (V2V) and/or infrastructure-to-vehicle (I2V) communication systems to achieve desired objectives such as safety, traffic fluidity or fuel economy. In a day to day traffic scenario, the presence of unknown disturbances complicates achieving these objectives. In particular, CACC benefits in terms of fuel economy require the prediction of the behavior of a preceding vehicle during a finite time horizon. This paper suggests an estimation method based on actual and past inter-vehicle distance data as well as on traffic and upcoming traffic lights. This information is used to train a set of nonlinear, autoregressive (NARX) models. Two scenarios are investigated, one of them assumes a V2V communication with the predecessor, the other uses only data acquired by on-board vehicle sensors.

The last years have seen an increasing amount of innovations in the functionality of car electronics (e.g. advanced driver assistant systems (ADAS) and in-vehicle infotainment systems (IVIS)). These electrical systems are not reserved for premium cars anymore, but additionally reach mid-size, compact, and subcompact cars. The growing number of functionalities in these cars entails increasing amount of interfaces, which may confuse, overload, or annoy the driver. Accompanying this, there is a trend towards the integration of capacitive touchscreens as user interfaces. These touchscreens were implemented first in consumer electronics and had a substantial impact on the way in which users interact with technology. This in turn has led to an increased user driven demand for the technology to be implemented in other domains, even in safety-critical ones like the automotive area.

A key aim of research into cell phone tasks is to obtain an unbiased estimate of their relative risk (RR) for crashes. This paper re-examines five RR estimates of cell phone conversation in automobiles. The Toronto and Australian studies estimated an RR near 4, but used subjective estimates of driving and crash times. The OnStar, 100-Car, and a recent naturalistic study used objective measures of driving and crash times and estimated an RR near 1, not 4 - a major discrepancy. Analysis of data from GPS trip studies shows that people were in the car only 20% of the time on any given prior day at the same clock time they were in the car on a later day. Hence, the Toronto estimate of driving time during control windows must be reduced from 10 to 2 min.

This paper presents a novel methodology to develop and validate fuel consumption models of Refuse Collecting Vehicles (RCVs). The model development is based on the improvement of the classic approach. The validation methodology is based on recording vehicle drive cycles by the use of a low cost data acquisition system and post processing them by the use of GPS and map data. The corrected data are used to feed the mathematical energy models and the fuel consumption is estimated. In order to validate the proposed system, the fuel consumption estimated from these models is compared with real filling station refueling records. This comparison shows that these models are accurate to within 5%.

During a car launch, the driving torque from driveline acts on brake disk, and may lead the pad to slip against the disk. Especially with slow brake pedal release, there is still brake torque applies on the disk, which will retard the rotation of disk, and under certain conditions, the disk and pad may stick again, so the reciprocated stick and slip can induce the noise and vibration, which can be transmitted to a passenger by both tactile and aural paths, this phenomenon is defined as brake groan. In this paper, we propose a nonlinear dynamics model of brake for bidirectional, and with 7 Degrees of Freedom (DOFs), and phase locus and Lyapunov Second Method are utilized to study the mechanism of groan. Time-frequency analysis method then is adopted to analyze the simulation results, meanwhile a test car is operated under corresponding conditions, and the test signals are sampled and then processed to acquire the features.

We present a method for the estimation of vehicle mass and road gradient for a light passenger vehicle. The estimation method uses information normally available on the vehicle CAN bus without the addition of extra sensors. A composite parameter estimation algorithm incorporating a nonlinear adaptive observer structure uses vehicle speed over ground and driving torque to estimate mass and road gradient. A system of filters is used to avoid deriving acceleration directly from wheel speed. In addition, a novel data fusion method makes use of the regressor structure to introduce information from other sensors in the vehicle. The dynamics of the additional sensors must be able to be parameterised using the same parameterisation as the complete vehicle system dynamics. In this case we make use of an Inertial Measurement Unit (IMU) which is part of the vehicle safety and Advanced Driver Assist Systems (ADAS).

The goal of reducing fuel consumption and CO2-Emission is leading to turbo-charged combustion engines that deliver high torque at low speeds (down speeding). To meet NVH requirements damper technologies such as DMF (Dual Mass Flywheel) are established, leading to reduced space for the clutch system. Specific measures need to be considered if switching over from SMF (Single Mass Flywheel) to DMF [8]. Doing so has an impact on thermal behavior of the clutch system, for example due to reduced and different distribution of thermal masses and heat transfer to the surroundings. Taking these trends into account, clutch systems within vehicle powertrains are facing challenges to meet requirements e.g. clutch life, cost targets and space limitation. The clutch development process must also ensure delivery of a clutch system that meets requirements taking boundary conditions such as load cycles and driver behavior into account.

The interior floor of a vehicle cabin occupies a significant amount of surface area in proportion to the cabin as a whole, and as such provides a prime opportunity for acoustic treatment. Generally speaking, floor materials must be relatively limp to achieve high acoustic performance. However, the tactile quality of a vehicle floor is very important. The end customer has an expectation for how it should feel to step onto the floor of a vehicle: a carpet should “give” slightly, but not compress fully, under pressure. A carpet that is too stiff or not stiff enough may be perceived as indicative of low quality. Thus, acoustic targets and stiffness targets tend to be at odds. A vehicle interior floor is a trim component which consists of different layers and which can have different pile-up configurations. Such a pile-up typically consists of a soft layer, called a decoupler, and a top layer.

In the last decade, the equivalent circuit model has been utilized to model lithium-ion batteries for electric vehicle applications. Different researchers have proposed a variety of equivalent circuit models from simple to complex ones. The parameters required to describe and build these equivalent circuit models are being extracted from the Hybrid Pulse Power Characterization (HPPC) Test data. This paper describes the process of the extraction of the equivalent circuit model parameters to build the battery models using different test methodologies such as HPPC and its modified versions. It also presents a case study with validated test results for a commercial light weight EV. Firstly, showing how the cell is characterized and then how the pack level cooling is developed to reach the required range based on an aggressive drive cycle.

To prevent the severe consequences of unsafe driving behaviors, it is crucial to monitor and analyze the state of the driver. Developing an effective driver state monitoring (DSM) systems is particularly challenging due to limited computation capabilities of embedded systems in automobiles and the need for finishing processing in real-time. However, most of the existing research work was conducted in a lab environment with expensive equipment while lacking in-car benchmarking and validation. In this paper, a DSM system that estimates driver's alertness and drowsiness level as well as performs emotion detection built with a cost-effective embedded system is presented. The proposed system consists of a mono camera that captures driver's facial image in real-time and a machine learning based detection algorithm that detects facial landmark points and use that information to infer driver's state.