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When vehicles share certain information wirelessly via Dedicated Short Range Communications (DSRC), they enable a new layer of electronic vehicle safety that, when needed, can generate warnings to drivers and even initiate automatic preventive actions. Vehicle location and velocity provided by Global Navigation Systems (GNSS), including GPS, are key in allowing vehicle path estimation. GNSS is effective in accurately determining a vehicle's location coordinates in most driving environments, but its performance suffers from obstructions in dense urban environments. To combat this, augmentations to GNSS are being contemplated and tested. This testing has been typically done using a reference GNSS system complimented by expensive military-grade inertial sensors, which can still fail to provide adequate reference performance in certain environments.

We report here results from first year of the BMW MINI E deployment. BMW deployed 450 MINI E?s to North America. Nearly 50% were leased by households in Los Angeles and the New York area. PH&EV Center researchers surveyed MINI E drivers throughout their year with the vehicles, focusing on the experiences of 50 households who volunteered for more detailed interviews. We report here their experiences with driving electric vehicles, adaptions to daily range limitations, and using electricity as a fuel. Presenter Thomas Turrentine, Univ. of California-Davis

ECOtality North America, in partnership with the Idaho National Laboratory (INL), Nissan North America, General Motors, and over 40 government, electric utility, and private organizations, has launched a large-scale demonstration of electric vehicle charging infrastructure. This demonstration, called The EV Project, will deploy more than 15,000 level 2 and DC fast chargers in private residence, commercial, and public locations in seven market areas in Arizona, California, Oregon, Tennessee, Texas, Washington state, and Washington, D.C. The EV Project will also include a total of 5,700 Nissan Leaf battery electric vehicles and 2,600 Chevrolet Volt extended range electric vehicles, operated by consumers and fleets in each of the market areas. This demonstration, which is funded by the U.S. Department of Energy�s (DOE) Vehicle Technologies Program, represents the largest ever deployment of electric vehicles and charging infrastructure.

In Aeronautic industry, when we launch a new industrialization for an aircraft sub assembly we always have the same questions in mind for drilling operations, especially when focusing on lean manufacturing. How can we avoid dismantling and deburring parts after drilling operation? Can a drilling centre perform all the tasks needed to deliver a hole ready to install final fastener? How can we decrease down-time of the drilling centre? Can a drilling centre be integrated in a pulse assembly line? How can we improve environmental efficiency of a drilling centre? It is based on these main drivers that AIRBUS has developed, with SPIE and SOS, a new generation of drilling centre dedicated for hard materials such as titanium, and high thicknesses. The first application was for the assembly of the primary structure of A350 engine pylons. The main solution that was implemented meeting several objectives was the development of orbital drilling technology in hard metal stacks.

ISO 26262 is the actual standard for Functional Safety of automotive E/E (Electric/Electronic) systems. One of the challenges in the application of the standard is the distribution of safety related activities among the participants in the supply chain. In this paper, the concept of a Safety Element out of Context (SEooC) development will be analyzed showing its current problematic aspects and difficulties in implementing such an approach in a concrete typical automotive development flow with different participants (e.g. from OEM, tier 1 to semiconductor supplier) in the supply chain. The discussed aspects focus on the functional safety requirements of generic hardware and software development across the supply chain where the final integration of the developed element is not known at design time and therefore an assumption based mechanism shall be used.

Selective catalytic reduction (SCR) catalysts will be used to reduce oxides of nitrogen (NOx) emissions from internal combustion engines in a number of applications [1,2,3,4]. Southwest Research Institute® (SwRI)® performed an Internal Research & Development project to study SCR catalyst thermal deactivation. The study included a V/W/TiO2 formulation, a Cu-zeolite formulation and an Fe-zeolite formulation. This work describes NOx timed response to ammonia (NH3) transients as a function of thermal aging time and temperature. It has been proposed that the response time of NOx emissions to NH3 transients, effected by changes in diesel emissions fluid (DEF) injection rate, could be used as an on-board diagnostic (OBD) metric. The objective of this study was to evaluate the feasibility and practicality of this OBD approach.

Abstract A number of studies have shown that driving an unfamiliar vehicle has the potential to introduce additional risk, especially for novice drivers. However, such studies have generally used statistical methods based on analyzing crash and near-crash data from a range of driver groups, and therefore the evaluation has the potential to be subjective and limited. For a more objective perspective, this study suggests that it would be worthwhile to consider vehicle dynamic signals obtained from the Controller Area Network (CAN-Bus) and smartphones. This study, therefore, is focused on the effect of driver experience and vehicle familiarity for issues in driver modeling and distraction. Here, a group of 20 drivers participated in our experiment, with 13 of them having participated again after a one-year time lapse in order for analysis of their change in driving performance.

Abstract Lane changes are stressful maneuvers for drivers, particularly during high-speed traffic flows. However, modeling driver’s lane-changing decision and implementation process is challenging due to the complexity and uncertainty of driving behaviors. To address this issue, this article presents a personalized Lane-Changing Model (LCM) for Advanced Driver Assistance System (ADAS) based on deep learning method. The LCM contains three major computational components. Firstly, with abundant inputs of Root Residual Network (Root-ResNet), LCM is able to exploit more local information from the front view video data. Secondly, the LCM has an ability of learning the global spatial-temporal information via Temporal Modeling Blocks (TMBs). Finally, a two-layer Long Short-Term Memory (LSTM) network is used to learn video contextual features combined with lane boundary based distance features in lane change events.

Abstract Introduction: This study evaluates driving ability in those with Charcot Marie Tooth Disease Type 1A, a hereditary peripheral neuropathy. Methods: Individuals with Charcot Marie Tooth Disease Type 1A (n = 18, age = 42 ± 7) and controls (n = 19; age = 35 ± 10) were evaluated in a driving simulator. The Charcot Marie Tooth Neuropathy Score version 2 was obtained for individuals. Rank Sum test and Spearman rank correlations were used for statistical analysis. Results: A 74% higher rate of lane departures and an 89% higher rate of lane deviations were seen in those with Charcot Marie Tooth Disease Type 1A than for controls (p = 0.005 and p < 0.001, respectively). Lane control variability was 10% higher for the individual group and correlated with the neuropathy score (rS = 0.518, p = 0.040), specifically sensory loss (rS = 0.710, p = 0.002) and pinprick sensation loss in the leg (rS = 0.490, p = 0.054).

Abstract In today’s competitive automobile market, driver comfort is at utmost importance and the bar is being raised continuously. Gear Shifting is a crucial customer touch point. Any issue or inconvenience caused while shifting gear can result into customer dissatisfaction and will impact the brand image. While there are continual efforts being taken by most of the car manufactures, “Double Bump” in gearshift has remained as a pain area and impact severely on the shift feel. This is more prominent in North-South (N-S) transmissions. In this paper ‘Double Bump’ is a focus area and a mathematical / analytical approach is demonstrated by analyzing ‘impacting parameters’ and establishing their co-relation with double bump. Additionally, the results are also verified with a simulation model.

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:

Abstract A key element in an ergonomically designed driver’s seat in a car is the correct identification of driver seating position and posture accommodation. Current practice by the automotive Original Equipment Manufacturer (OEM) is to utilize the Society of Automotive Engineering (SAE) J1517 standard practice as a reference. However, it was found that utilizing such guidelines, which were developed based on the American population, did not fit well with the anthropometry and stature of the Malaysian population. This research seeks to address this issue by comparing the SAE J1517 Model against Malaysian preferred driving position. A total of 62 respondents were involved for the driver seating position and accommodation study in the vehicle driver’s seat buck mockup survey and measurements. The results have shown that the Malaysian drivers prefer to sit forward as compared to the SAE J1517 Model and have shorter posture joint angle.

Abstract The advancement towards development of autonomy follows either the bottom-up approach of gradually improving and expanding existing Advanced Driver Assist Systems (ADAS) technology where the driver is present in the control loop or the top-down approach of directly developing autonomous vehicle hardware and software using alternative approaches without the driver present in the control loop. Most ADAS systems today fall under the classification of SAE Level 1 which is also referred to as the driver assistance level. The progression from SAE Level 1 to SAE Level 2 or partial automation involves the critical task of merging automated lateral control and automated longitudinal control such that the tasks of steering and acceleration/deceleration are not required to be handled by the driver under certain conditions [1].

Abstract To evaluate that automated vehicle is as safe as a human driver, a following question is studied: how does an automated vehicle react under extreme conditions close to collision? In order to understand the collision avoidance capability of an automated vehicle, we should analyze not only such post-extreme condition behavior but also pre-extreme condition behavior. We present a theory to analyze the collision avoidance capability of automated driving technologies. We also formulate a collision avoidance equation on the theory. The equation has two types of solutions: response driving plans and preparation driving plans. The response driving plans are supported by response strategy on which the vehicle reacts after detection of a hazard and they are highly efficient in terms of travel time.

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.

Due to the stringent requirements to reduce the tail pipe emissions of NOx, Selective Catalytic Reduction (SCR) systems are used to remove NOx using ammonia. When a urea solution is injected into the exhaust system, urea will undergo hydrolysis and decomposition reaction that produces ammonia. At the catalyst surface, ammonia will react with the exhaust gases to convert NOx into nitrogen, N2 and water, H2O. One of the challenging problems is to make sure the urea solution is available for the SCR system at cold start conditions. At extreme cold temperatures, the urea solution will begin to freeze at −12°C. At the start up of a vehicle under such low ambient temperatures, a heating system is used to provide the heat required for melting the frozen urea. Therefore, there will be a time lag between the vehicle start up and the availability of urea solution to the SCR system.

This recommended practice defines methods for the measurement of periodic, random and transient whole-body vibration. It indicates the principal factors that combine to determine the degree to which a vibration exposure will cause discomfort. Informative appendices indicate the current state of knowledge and provide guidance on the possible effects of motion and vibration on discomfort. The frequency range considered is 0.5 Hz to 80 Hz. This recommended practice also defines the principles of preferred methods of mounting transducers for determining human exposure. This recommended practice is applicable to light passenger vehicles (e.g., passenger cars and light trucks). This recommended practice is applicable to motions transmitted to the human body as a whole through the buttocks, back and feet of a seated occupant, as well as through the hands of a driver.

This recommended practice defines methods for the measurement of periodic, random and transient whole-body vibration. It indicates the principal factors that combine to determine the degree to which a vibration exposure will cause discomfort. Informative appendices indicate the current state of knowledge and provide guidance on the possible effects of motion and vibration on discomfort. The frequency range considered is 0.5 Hz to 80 Hz. This recommended practice also defines the principles of preferred methods of mounting transducers for determining human exposure. This recommended practice is applicable to light passenger vehicles (e.g., passenger cars and light trucks). This recommended practice is applicable to motions transmitted to the human body as a whole through the buttocks, back and feet of a seated occupant, as well as through the hands of a driver.

This recommended practice defines methods for the measurement of periodic, random and transient whole-body vibration. It indicates the principal factors that combine to determine the degree to which a vibration exposure will cause discomfort. Informative appendices indicate the current state of knowledge and provide guidance on the possible effects of motion and vibration on discomfort. The frequency range considered is 0.5 Hz to 80 Hz. This recommended practice also defines the principles of preferred methods of mounting transducers for determining human exposure. This recommended practice is applicable to light passenger vehicles (e.g., passenger cars and light trucks). This recommended practice is applicable to motions transmitted to the human body as a whole through the buttocks, back and feet of a seated occupant, as well as through the hands of a driver.

A generalized MADYMO minor rear crash vehicle model with BioRIDII ATD was developed and validated using the mean response of previously published 12 km/h delta-V rear crash tests. BioRIDII simulation pelvis, thorax and head x-axis accelerations, as well as head y-axis angular acceleration, fell within corridors defining +/- one standard deviation of the mean BioRIDII crash test responses. Peak sagittal plane BioRIDII upper neck forces and moments in the simulation were on par with the mean values observed from the crash tests. After the model was validated for 12 km/h delta-V, the model was further exercised by performing simulations with (1) a Hybrid III 50th percentile occupant and (2) by reducing the pulse by 40% of its original value. Results indicate that this generalized minor rear crash model could be useful in accurately estimating occupant kinematics and kinetics in minor crashes up to at least 12 km/h delta-V as an alternative to expensive and time consuming crash testing.