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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:

An automated process was developed for the calibration of numerical aftertreatment models. The chemical kinetic mechanism examined in this case was part of a simplified SCR model. The process adopted for calibrating the SCR model was based on a micro-population multi-objective genetic algorithm. The algorithm developed was used to calibrate the SCR model using data derived from another, more detailed model to ensure that the evaluation focused only on the effectiveness of the calibration process and was not affected by issues of experimental inaccuracies or details of the model chemistry involved.

In order to detect degradation of engine oil lubricant, bench testing along with a number of diesel-powered Ford trucks were instruments and tested. The purpose of the bench testing was primarily to determine performance aspects such as repeatability, hysteresis effects and so on. Vehicle testing was conducted by designing and installing a separate oil reservoir along with a circulation system which was mounted in the vicinity of the oil pan. An innovative oil sensor was directly installed on the reservoir which can measure five (5) independent oil parameters (viscosity, density, permittivity, conductance, temperature). In addition, the concept is capable of detecting the oil level continuously during normal engine operation. The sensing system consists of an ultrasonic transducer for the oil level detection as well as a Tuning Fork mechanical resonator for the oil condition measurement.

Engine operating strategies typically geared towards higher fuel economy and lower NOx widely affect exhaust composition and temperature. These exhaust variables critically drive the performance of After Treatment (AT) components, and hence should guide their screening and selection. Towards this end, the effect of H2 level in diesel exhaust on the performance of a Diesel Oxidation Catalyst (DOC) was studied using flow reactor experiments, vehicle emission measurements and mathematical models. Vehicle chassis dynamometer data showed that exhaust from light-duty and heavy-duty diesel trucks contained very little to almost no H2 (FTP average CO/H2 ∼ 40 to 70) as compared to that of a gasoline car exhaust (FTP average CO/H2 ∼ 3). Two identical flow reactor experiments, one with H2 (at CO/H2 ∼ 3) and another with no H2 in the feed were designed to screen DOCs under simulated feed gas conditions that mimicked these two extremes in the exhaust H2 levels.

A thorough understanding of vehicle exhaust aftertreatment system performance requires time-resolved emissions measurements that accurately follow driving transients, and that are correctly time-aligned with exhaust temperature and flow measurements. The transient response of conventional gas analyzers is characterized by both a time delay and an attenuation of high-frequency signal components. The distortion that this imposes on transient emissions measurements causes significant errors in instantaneous calculations of aftertreatment system efficiency, and thus in modal mass analysis. This creates difficulties in mathematical modeling of emissions system performance and in optimization of powertrain control strategies, leading to suboptimal aftertreatment system designs. A mathematical method is presented which improves the response time of emissions measurements. This begins with development of a model of gas transport and mixing within the sampling and measurement system.

This paper focuses on full body dynamical analysis of car ingress/egress motion. It aims at proposing an experimental protocol adapted for analysing joint loads using inverse dynamics. Two preliminary studies were first performed in order to 1/ define the main driver/car interactions so as to allow measuring the contact forces at all possible contact zones and 2/ identify the design parameters that mainly influence the discomfort. In order to verify the feasibility of the protocol, a laboratory study was carried out, during which two subjects tested two car configurations. The experimental equipment was composed of a variable car mock-up, an optoelectronic motion tracking system, two 6D-force plates installed on the ground next to the doorframe and on the car floor, a 6D-Force sensor between the steering wheel and the steering column, and two pressure maps on the seat. Motions were reconstructed from measured surface markers trajectories using inverse kinematics.

Piezoelectric self-sensing allows to measure frequency response functions of dynamical systems with one single piezoelectric element. This piezoceramics is used as actuator and sensor simultaneously. In this study, a model-based piezoelectric self-sensing technique is presented to obtain potential squealing frequencies of an automotive disc brake. The frequency-response function of the brake system is obtained during operation by measuring the current flowing through the piezoelectric element while the piezoelectric element is driven by a harmonic voltage signal with constant amplitude. The current flow is composed of the part which is required to drive the piezoelectric element as an actuator and a second part which is the sensor signal that is proportional to the vibration amplitude of the attached mechanical system. Typically the first part is dominant and the influence of the mechanical system is marginal.

This paper describes the joint development by Tenneco and Pi Shurlok of a complete diesel engine aftertreatment system for controlling particulate matter emissions. The system consists of a DOC, DPF, sensors, controller and an exhaust fuel injection system to allow active DPF regeneration. The mechanical components were designed for flow uniformity, low backpressure and component durability. The overall package is intended as a complete PM control system solution for OEMs, which does not require any significant additions to the OEM's engine control strategies and minimizes integration complexity. Thus, to make it easier to adapt to different engine platforms, ranging from small off-road vehicle engines to large locomotive engines, model-based control algorithms were developed in preference to map-based controls.

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.

Complexity and nonlinearity of engines makes precise first principle engine models often difficult to obtain, as for instance for emissions. System identification is a well known possible alternative, successfully used in several automotive applications. In most cases system identification is concerned with the estimation of the unknown parameters of a known set of equations. Unfortunately, for many engine subsystems, there is no sufficiently precise or real time suitable model. This paper presents a sequential algorithm which allows to derive real time suitable models on line by a combination of model structure hypothesis of increasing complexity and an associated optimal input design and selection process. This paper introduces the method and shows its use both for a rather simple and a very difficult engine identification task, a dynamical model of the airpath of a Diesel engine and a dynamical model of nitrogen oxides and particulate matter.

This paper develops a novel integrated navigational system for autonomous vehicle motion control. Vehicle control is defined in terms of the required vehicle steering angle, rate of steering change and speed. This paper proposes predictive control in the image plane. The proposed predictive control enables the navigation on the desired path, reduces the control complexity and increases the application space for multiple types of vehicles. The paper investigates vehicle control stability; especially in scenarios containing varying curvature turns and variable vehicle speeds. The primary emphasis of this paper is on vehicle control rather than scene analysis. To demonstrate the proposed vehicle control, a computer vision based multi-lane detection algorithm is introduced. The control strategy is applied such that the vehicle maintains position within the lane boundaries. Stability of the control algorithm is tested and demonstrated in multiple scenarios using 3-D simulation results.

The ride dynamics of typical North-American soil compactors were investigated via analytical and experimental methods. A 12-degrees-of-freedom in-plane ride dynamic model of a single-drum compactor was formulated through integrations of the models of various components such as driver seat, cabin, roller drum and drum isolators, chassis and the tires. The analytical model was formulated for the transit mode of operation at a constant forward speed on undeformable surfaces with the roller vibrator off. Field measurements were conducted to characterize the ride vibration environments during the transit mode of operation. The measured data revealed significant magnitudes of whole-body vibration of the operator-station along the vertical, lateral, pitch and roll-axes. The model results revealed reasonably good agreements with ranges of the measured vibration data.

In 2006, there were approximately 23,500 rear-end crashes involving heavy trucks (i.e., gross vehicle weight greater than 4,536 kg). The Enhanced Rear Signaling (ERS) for Heavy Trucks project was developed by the Federal Motor Carrier Safety Administration (FMCSA) to investigate methods to reduce or mitigate those crashes where a heavy truck has been struck from behind by another vehicle. Visual warnings have been shown to be effective, assuming the following driver is looking directly at the warning display or has his/her eyes drawn to it. A visual warning can be placed where it is needed and it can be designed so that its meaning is nearly unambiguous. FMCSA contracted with the Virginia Tech Transportation Institute (VTTI) to investigate potential benefit of additional rear warning-light configurations as rear-end crash countermeasures for heavy trucks.

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.

Electrification of the automobile is a growing trend and will create both challenges and opportunities for the vehicle manufacturer, road network infrastructure and driver. In addition to innovative fundamental battery and power transfer technologies, electric vehicles will integrate unique driver interfaces, road intelligence, traffic awareness and wireless data communication to provide a complete support system. This networked vehicle will improve efficiency, increase cruising range and contribute to the overall driving enjoyment of an electric or plug-in hybrid-electric vehicle. Through tailored applications created by content and service providers the driver will identify the most efficient travel routes, learn efficient driving behaviors, avoid energy-wasting situations, locate charging stations and have confidence in reaching a destination and returning home.

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.

Vehicle-to-Vehicle (V2V) and Vehicle-to-Infrastructure (V2I) networks within the Intelligent Transportation System (ITS) lead to safety and mobility improvements in vehicle road traffic. This paper presents case studies that support the realization of the ITS architecture as an evolutionary process, beginning with driver information systems for enhancing feedback to the users, semi-autonomous control systems for improved vehicle system management, and fully autonomous control for improving vehicle cooperation and management. The paper will also demonstrate how the automotive, telecom, and data and service providers are working together to develop new ITS technologies.

The design of a safe transportation system requires numerous design decisions that should be based on data acquired by rigorous scientific method. Naturalistic data collection and analysis methods are a relatively new addition to the engineer's toolbox. The naturalistic method is based on unobtrusively monitoring driver and vehicle performance under normal, everyday, driving conditions; generally for extended collection periods. The method generates a wealth of data that is particularly well-suited for identifying the underlying causes of safety deficiencies. Furthermore, the method also provides robust data for the design and evaluation of safety enhancement systems through field studies. Recently the instrumentation required to do this type of study has become much more cost effective allowing larger numbers of vehicles to be instrumented at a fraction of the cost. This paper will first provide an overview of the naturalistic method including comparisons to other available methods.

Virtual testing is a method that simulates lab testing using multi-body dynamic analysis software. The main advantages of this approach include that the design can be evaluated before a prototype is available and virtual testing results can be easily validated by subsequent physical testing. The disadvantage is that accurate specimen models are sometimes hard to obtain since nonlinear components such as tires, bushings, dampers, and engine mounts are hard to model. Therefore, virtual testing accuracy varies significantly. The typical virtual rigs include tire and spindle coupled test rigs for full vehicle tests and multi-axis shaker tables for component tests. Hybrid simulation combines physical and virtual components, inputs and constraints to create a composite simulation system. Hybrid simulation enables the hard to model components to be tested in the lab.

Intelligent tires are envisioned to be an important part of the future vehicle control systems and the three dimensional wireless MEMS accelerometers embedded inside the tire stand out as a promising candidate for the development of intelligent tires. The first part of the paper focuses on accelerometer based tire sensors for the estimation of slip angle and tire/road friction coefficient. We use a simple tire finite element model to generate lateral, tangential and radial tire accelerations for a fixed load and slip angle. The profiles are validated by using experimental data. The simulated acceleration profiles are used for the estimation of slip angle and tire/road friction coefficient. We present the estimation algorithms, promising simulative results and output sensitivities studies focused on the effects of changes in normal load, tire pressure and vehicle velocity.