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This technical paper collection contains 11 papers by leading experts in the field of intelligent vehicle technologies. Topics include vehicle navigation, collision avoidance, sensor and camera-based autonomous driving and parking, and vehicle to vehicle communications. Practical examples include the use of sensors, software, data and control logic to assist or guide the driver and/or to control the vehicle.

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.

Several technological advancements have enabled hybrid technology to become a viable option in the commercial truck market. Although hybrid trucks are becoming more mainstream, they are not the right alternative fuel solution for every application. When matched with the right duty cycle, hybrid technology can provide a significant cost savings. Due to these advancements and anticipated benefits, hybrid commercial trucks are forecasted to become a significant part of the commercial truck market. Presenter Glenn Ellis, Hino Motors Sales USA Inc.

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.

Automotive journalists are uniquely located to gain a broad perspective of the field. We learn from specialists, the engineers who perform the actual work, in relatively neutral settings. We also communicate with our readers, the ultimate consumers of both your products and ours. Here I propose to share elements of several of these interactions, especially those pertaining to the coming array of plug-in hybrids from GM, Toyota and Porsche. I also propose to give a brief update of KERS, Kinetic Energy Recovery Systems, in Formula 1. Presenter Dennis J. Simanaitis, Road & Track Magazine

Dramatic changes in transportation are coming. Cities and states looking to be at the forefront and reap the benefits, need an engaged and informed citizenry. Hear how the SAE Demo Day in Tampa supported Florida's AV initiatives and can benefit states nationwide.

In May 2018, SAE International in partnership with THEA and leading AV technology companies gave citizens in Tampa a chance to test ride the future. The event included a pre- and post-ride survey, a ride in an automated vehicle, interactive displays and engagement with industry experts. See highlights of the event and feedback from participants.

The worldwide drive to improved energy efficiency for engine systems is being supported by several engine R&D programs at Southwest Research Institute (SwRI). This research includes large programs in major-market engine categories, such as heavy-duty, non-road, and light-duty; and includes diesel, gasoline, and alternative fuel aspects. This presentation describes several key diesel engine programs being pursued under the SwRI Clean High Efficiency Diesel Engine consortium (CHEDE-VI), whose goal is to demonstrate future diesel technology exceeding 50% brake thermal efficiency. Additionally, SwRI?s High Efficiency Dilute Gasoline Engines consortium (HEDGE-II), is reviewed, where advanced technology for ultra-high efficiency gasoline engines is being demonstrated. The HEDGE-II program is built upon dilute gasoline engine research, where brake thermal efficiencies in excess of 42% are being obtained for engines applicable to the light-duty market. Presenter Charles E.

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.

This paper proposes a current limits distribution control strategy for a parallel hybrid electric vehicle (parallel HEV) which includes an advanced powertrain concept with two electrical driving axles. One of the difficulties of an HEV powertrain with two electrical driving axles is the ability to distribute the electrical current of one high voltage battery appropriately to the two independent electrical motors. Depending on the vehicle driving condition (i.e., car maneuver) or the maximization of the entire efficiency chain of the system, a suitable control strategy is necessary. We propose an input-output feedback linearization strategy to cope with the nonlinear system subject to input constraints. This approach needs an external, state dependent saturation element, which translates the state dependent control input saturation to the new feedback linearizing input and therefore preserves the properties of the differential geometric framework.

This paper presents a new concept for a 100% plastic prototype automotive door panel. This concept has the potential of providing a weight reduction of up to 40% compared to conventional steel door panels, but with equivalent performance (static strength). This innovative technology can be used for a variety of exterior automotive parts. The concept includes a composite sandwich panel combination of GFRP (glass fiber reinforced polymer), and LACTIF®, which is expanded beads foam made from PLA (polylactic acid) and developed by JSP Corporation. This GFRP+LACTIF® composite design offers the following characteristics: Excellent environmental resistance Strong adhesion Equivalent static strength (vs. conventional door panels) Design flexibility This concept also offers an alternative to conventional steel door panel systems by using unsaturated polyester material of plant origin as part of the GFRP composite.

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.

The 16 papers in this technical paper collection cover pre-crash detection systems, increased maneuverability of electric vehicles, interactive cruise control, stereo vision based parking assist systems, performance of a rear-end crash avoidance system, and more.

This technical paper collection features 15 papers covering electrification of the commercial vehicle, techniques for efficiency and reliability; developments in sensors; model based design and embedded software development; heavy duty electronic technology; autonomous vehicles; electronic control module development and test; and vehicle structure.

The 7 papers in this technical paper collections focus on intelligent vehicle initiative (IVI) technology advanced controls and navigation systems. Topics covered include Curvilinear Coordinate system, PHEV Energy Management, DSRC Communication, and more. The 7 papers in this technical paper collections focus on intelligent vehicle initiative (IVI) technology advanced controls and navigation systems. Topics covered include Curvilinear Coordinate system, PHEV Energy Management, DSRC Communication, and more.

The 8 papers in this technical paper collection discuss intelligent transportation systems. Topics covered include vision based driver alert system, human sensor vehicle traffic control system, DSRC performance comparison, intelligent driver feedback, and more. The 7 papers in this technical paper collection discuss intelligent transportation systems. Topics covered include vision based driver alert system, human sensor vehicle traffic control system, DSRC performance comparison, intelligent driver feedback, and more.

This technical paper collection presents papers by leading experts in the field of Intelligent Vehicle Technologies, such as: vehicle communications and networks, driver drowsiness and driving pattern detection, sensors and GPS, vehicle and chassis control and autonomous vehicles, route prediction, head-up displays and power transmission for electric vehicles.

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.