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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.

The aerospace industry has long sought a solution for storing maintenance history information directly on aircraft parts. In 2005 leading airframe manufacturers determined that passive Radio Frequency Identification (RFID) technology presented a unique opportunity to address this industry need. Through the efforts of the Air Transport Association (ATA) RFID on Parts Committee and SAE International testing standards and data specifications are in place to support the broad adoption of passive RFID for storing parts history information directly on aircraft parts. The primary focus of the paper will be on the SAE AS-5678 environmental testing standard for passive RFID tags intended for aircraft use. Detail will be provided to help aerospace manufacturers understand their role and responsibilities for current programs and understand how this may impact their parts certification process.

The presentation provides an overview about the activities of Eurocae Working Group 72 (WG-72) starting with a brief synopsis of the context which suggested why such a committee should be established in 2006. It then goes into further detail about the drivers for the work of the committee, which call for the products to be delivered. It addresses some of the challenges with respect to its users. It points out that one of the lessons the committee learned was importance of the focus on the users, such that the products provide their maximum utility. Hence, the users should better be among the participants to achieve this objective. Other industries have dealt with the subject of Information System (or Cyber-Physical) Security long before this industry was forced to consider it. Consequently there are many industry standards and national or international norms, which may help to develop what is deemed needed for Civil Aviation.

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.

Probabilistic methods are used in calculating composite part design factors for, and are intended to conservatively compensate for worst case impact to composite parts used on space and aerospace vehicles. The current method to investigate impact damage of composite parts is visual based upon observation of an indentation. A more reliable and accurate determinant of impact damage is to measure impact energy. RF impact sensors can be used to gather data to establish an impact damage benchmark for deterministic design criteria that will reduce material applied to composite parts to compensate for uncertainties resulting from observed impact damage. Once the benchmark has been established, RF impact sensors will be applied to composite parts throughout their life-cycle to alert and identify the location of impact damage that exceeds the maximum established benchmark for impact.

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.

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 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.

Abstract Commercial vehicles contribute to the majority of freight transportation in the United States. They are also significant fuel consumers, with over 23% of fuel used in transportation in the United States. The gas price volatility and increasingly stringent regulation on greenhouse-gas emissions have driven manufacturers to adopt new fuel-efficient technologies. Among others, an advanced transmission control strategy, which can provide tangible improvement with low incremental cost. In the commercial sector, individual drivers have little or no interest in vehicle fuel economy, contrary to fleet owners. Aggressive driving behavior can greatly increase the real-world vehicle fuel consumption. However, the effectiveness of transmission calibration to match the shift strategy to the driving characteristics is still a challenge.

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 When commercial vehicles drive in a mountainous area, the complex road condition and long slopes cause frequent acceleration and braking, which will use 25% more fuel. And the brake temperature rises rapidly due to continuous braking on the long-distance downslopes, which will make the brake drum fail with the brake temperature exceeding 308°C [1]. Meanwhile, the kinetic energy is wasted during the driving progress on the slopes when the vehicle rolls up and down. Our laboratory built a model that could calculate the distance from the top of the slope, where the driver could release the accelerator pedal. Thus, on the slope, the vehicle uses less fuel when it rolls up and less brakes when down. What we do in this article is use this model in a real vehicle and measure how well it works.