Craig John Simonds

Intelligent pervasive middleware for context-based and localized telematics services

Telematics is arguably the next-wave in mobile computing: with most cars already equipped with multiple embedded computing platforms, we shall witness the development of a variety of mobile services and applications with significant commercial potential. Telematics will only become a commercial reality when the underlying architecture is able to address significant concerns related to the security and privacy of telematics data, and is able to provide context information from and to a large number of mobile data sources in a scalable and device-independent manner. A telematics platform should utilize existing Internet components and technologies but cannot rely exclusively on these, especially since mobile commerce applications in the telematics environment impose specific requirements on the relationships between various services and data providers. In this paper we describe how we are developing an open standards telematics platform based on the ts-PWLAN wireless service environment and the Telematics Resource Manager middleware. Our design employs existing web service interfaces coupled with novel technology for connecting to these through a wireless gateway. Our middleware acts as a common substrate for building and deploying a wide range of telematics applications. We describe how several of these applications are currently being built on our infrastructure.

An embedded architectural framework for interaction between automobiles and consumer devices

The last two and one half decades have seen rapid growth in the amount and importance of software in automobiles. This growth is bringing about a shift from treating software as a part of the hardware it controls to viewing it as an implementation of a set of services that mediate between the hardware and the functionality seen by the user. This paper describes an in-vehicle computing platform based on the software service platform to provide entertainment and information functions that has been implemented in two prototype vehicles at Ford Motor Company.

Effects of Adaptive Lane Departure Warning System on Driver Response to a Surprise Event

A lane departure warning (LDW) system monitors the current lane position of a vehicle and presents a driver alert when one of the vehicles front tires crosses a threshold, for example, the nearest lane line. The primary intent of such warning systems is to prevent or mitigate road departures and related crashes caused by driver distraction or drowsiness. The present evaluation compared adaptive and nonadaptive versions of an LDW system. The adaptive version adapted to the drivers state, whereas the nonadaptive version did not. The adaptive LDW system alerted the driver only if a driver state monitor (DSM) indicated that the driver was looking away from the road ahead for 2 s or longer at about the time when a lane line was crossed. Forty volunteers drove a high-fidelity, moving-base driving simulator in a study to compare driver responses to a surprise lane departure when they used a nonadaptive LDW system and then an adaptive LDW system or vice versa. The results indicated that in the adaptive LDW mode, 13 subjects (34%) either experienced delayed activation of the LDW alert or received no LDW alert at all when they should have, primarily because of both the 2-s rule in the adaptive LDW algorithm and DSM registration issues. The adaptive LDW resulted in significantly larger lane excursions at the onset of the LDW alert compared with those that occurred in the non-adaptive LDW mode. These results highlight the dependence of the performance effects of adaptive systems on system hardware, algorithms, and algorithm parameters.

Simulator Study of Effects of Alternative Distraction Mitigation Strategies in Driver Workload Manager

This simulator study examined a workload manager developed by Delphi Electronics for the SAVE-IT program and the effects of several different workload mitigation strategies on driver response to a surprise forward collision hazard. The strategies included no in-vehicle task or distraction (baseline); task allowed; task interrupted; and task denied. Forty-eight test participants (24 males and 24 females) between 35 and 55 years of age were randomly assigned in groups of 12 (balanced for gender) to each of the four conditions. Each participant then drove in the Ford VIRTTEX moving-base driving simulator on simulated urban and rural roads and was asked to perform various in-vehicle tasks. During a requested in-vehicle information system task, a vehicle parked on the side of the road would suddenly enter the travel lane, and the drivers response was assessed. Braking response to this critical event indicated no significant differences in mean brake response time as a function of type of mitigation strategy or gender. However, variability in driver responses was significantly less in the task denied condition as compared with the other conditions, possibly because drivers were sensitized to an increased driving demand. Three of 12 test participants in the task interrupted condition showed relatively large brake reaction times attributable to long delays between initial foot motion and braking onset. This delay may indicate an additional delay associated with processing the task interruption and the forward collision warning event itself. Recommendations are provided for further research and for mitigation and driver alerting on the basis of a workload managers assessment of the driving situation.

A Novel Approach to the Design and Development of an Interactive Learning App for Automotive IVI Systems

Since its launch Ford SYNC™ with MyFord Touch™ in-vehicle infotainment (IVI) system has migrated to many vehicle programs and had multiple software updates, which presented Ford dealers with the ever-increasing challenge of training new owners effectively and efficiently. This paper presents the design, architecture and implementation of “MyFord Touch Guide”, a novel, cross-platform mobile app that delivers a unique MyFord Touch learning and familiarization experience for dealers and consumers alike. This app incorporates the production MyFord Touch graphical user interface for an interactive learning experience. Additionally, it integrates a host of video tutorials featuring a computer-animated character, which offers an insightful, personalized and self-guided tour experience of the essential features and functions of the system. MyFord Touch Guide is a cross-platform app and based on a “hybrid” app architecture that uses both native mobile and web technologies. Feedback gathered from multiple nation-wide surveys indicates that the proposed approach provides a highly effective and scalable solution towards developing a diverse range of cross-platform, interactive, mobile learning apps.Copyright