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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.

Moir� method is useful to measure the shape and the whole-field distributions of displacement and strain of structures. There are many kinds of moir� methods such as geometric moir� method, sampling moir� method, Fourier transform moir� method, moir� interferometry, shadow moir� method and moir� topography. Grating method analyzing directly deformation of a grating without any moir� fringe pattern is considered as an extended technique of moire method. Phase analysis of the moire fringe patterns and the grating patterns provides accurate measurements of shapes or displacement and strain distributions. Some applications of these moir� methods and grating methods to dynamic shape and strain distribution measurements of a rotating tire, sub-millimeter displacement measurements from long distance for landslide prediction, real-time shape measurements with micro-meter order accuracy, etc. are shown. Presenter Yoshiharu Morimoto, Moire Institute Inc.

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.

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

Hybrid technology has the potential to enable dramatic reductions in greenhouse gases (GHG), such as the California goal of reducing GHG by 80 percent from 1990 levels by 2050. As a result it is expected that hybrid systems will occupy a growing proportion of the market. However, introducing a hybrid system in a vehicle may adversely affect the performance of the engine OBD system in monitoring malfunctions impacting pollutant emissions. For example, a hybrid system that reduces time of the engine in idle or deceleration overrun conditions could make a well-performing engine OBD system noncompliant, by reducing in-use frequency of some OBD monitors below acceptable levels. In this presentation, Ricardo will present a process for evaluating the impact that a hybrid system which has been optimised to minimise GHG emission over a specified drive-cycle will have on the effectiveness of engine OBD monitors.

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.

“Spotlight on Design” features video interviews and case studies, focusing on technology breakthroughs, hands-on testimonials, and the importance of fundamentals. Viewers are virtually taken to industry labs and research centers to learn how design engineers solve real-life problems. These challenges include enhancing product performance, reducing cost, improving quality and safety, while decreasing environmental impact, and achieving regulatory compliance. In the episode “Engine Development for Performance and Efficiency” (22:00), engineers from Ricardo and General Motors explain the importance of lessons learned on the race tracks, how using the appropriate design and simulation tools expedite development, and present the new testing frontiers now available with 3D printing.

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.

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.

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 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 Future SAE Level 4 and Level 5 autonomous vehicles (AV) will require novel applications of localization, perception, control, and artificial intelligence technology in order to offer innovative and disruptive solutions to current mobility problems. This article concentrates on low-speed autonomous shuttles that are transitioning from being tested in limited traffic, dedicated routes to being deployed as SAE Level 4 automated driving vehicles in urban environments like college campuses and outdoor shopping centers within smart cities. The Ohio State University has designated a small segment in an underserved area of the campus as an initial AV pilot test route for the deployment of low-speed autonomous shuttles. This article presents initial results of ongoing work on developing solutions to the localization and perception challenges of this planned pilot deployment.

The 11 papers in this technical paper collection cover intelligent vehicle technologies. Topics include: 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 Management of expressway networks has been mainly focused on defect management without looking at the correlations with accidental risks. This causes unsustainability in expressway infrastructure maintenance since such defects may not be a contributing factor toward public safety. Thus it is necessary to incorporate accidental events for decision-making in infrastructure management. This study has developed a novel approach to machine learning (ML) that incorporates actual primary data from the last 10 years of single-vehicle accidents (SVA) by collisions with motorway facilities, or so-called single-vehicle collisions with fixed objects. The ML is firstly aimed at identifying the influential factors of SVA in relation to finding effective countermeasures for accidents by integrating the correlation analysis, multiple regression analysis, and ML techniques. The study reveals that wet pavement conditions have a significant effect on SVA.