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The goal of this interview analysis was to explore and document the perceptions of two unique lane centering systems (S90’s Pilot Assist and CT6’s Super Cruise). Both systems offer a similar type of functionality (adaptive cruise control and lane centering), but have significantly different design philosophies and HMI (Human-Machine Interface) implementations. Twenty-four drivers drove one of the two vehicle models for a month as part of a field operational test (FOT) study. Upon vehicle return, drivers took part in a 60-minute semi-structured interview covering their perceptions of the vehicle’s various advanced driver-assistance systems (ADAS). Transcripts of the interviews were coded by two researchers, who tagged each statement with relevant system and perception code labels. For analysis, the perception codes were grouped into larger thematic bins of safety, comfort, driver attention, and system performance.

The fuel energy consumption of subsonic air transportation is examined. The focus is on identification and quantification of fundamental engineering design tradeoffs which drive the design of subsonic tube and wing transport aircraft. The sensitivities of energy efficiency to recent and forecast technology developments are also examined.

Extensive crash sled testing and analysis has recently led to the development of a new HANS prototypes for use in FIA F1. The performance of HANS prototypes has been studied with various conditions of HANS design geometry and impact direction. The new HANS prototypes have been found to substantially reduce injurious motions and forces of the head and neck, and the new HANS is lighter, more compact, and performs better than the currently available HANS. Use of HANS by FIA F1 drivers has been initiated.

This paper presents the results of a study of how people interacted with a production voice-command based interface while driving on public roadways. Tasks included phone contact calling, full address destination entry, and point-of-interest (POI) selection. Baseline driving and driving while engaging in multiple-levels of an auditory-vocal cognitive reference task and manual radio tuning were used as comparison points. Measures included self-reported workload, task performance, physiological arousal, glance behavior, and vehicle control for an analysis sample of 48 participants (gender balanced across ages 21-68). Task analysis and glance measures confirm earlier findings that voice-command interfaces do not always allow the driver to keep their hands on the wheel and eyes on the road, as some assume.

The challenge of developing a robust, real-time driver gaze classification system is that it has to handle difficult edge cases that arise in real-world driving conditions: extreme lighting variations, eyeglass reflections, sunglasses and other occlusions. We propose a single-camera end-toend framework for classifying driver gaze into a discrete set of regions. This framework includes data collection, semi-automated annotation, offline classifier training, and an online real-time image processing pipeline that classifies the gaze region of the driver. We evaluate an implementation of each component on various subsets of a large onroad dataset. The key insight of our work is that robust driver gaze classification in real-world conditions is best approached by leveraging the power of supervised learning to generalize over the edge cases present in large annotated on-road datasets.

Advanced driver assistance systems (ADAS) are an increasingly common feature of modern vehicles. The influence of such systems on driver behavior, particularly in regards to the effects of intermittent warning systems, is sparsely studied to date. This paper examines dynamic changes in physiological and operational behavior during lane departure warnings (LDW) in two commercial automotive systems utilizing on-road data. Alerts from the systems, one using auditory and the other haptic LDWs, were monitored during highway driving conditions. LDW events were monitored during periods of single-task driving and dual-task driving. Dual-task periods consisted of the driver interacting with the vehicle’s factory infotainment system or a smartphone to perform secondary visual-manual (e.g., radio tuning, contact dialing, etc.) or auditory-vocal (e.g. destination address entry, contact dialing, etc.) tasks.

In today's business climate rapid access to, and implementation of, new technology is essential to enhance competitive advantage. In the past, universities have been used for research contracts, but to fully utilize the intellectual resources of education institutions, it is essential to approach these relationships from a new basis: alliance. Alliances permit both parties to become active participants and achieve mutually beneficial goals. This paper will examine the drivers and challenges for industrial -- university alliances from both the industrial and academic perspectives.

Daimler-Benz considers safety belts as the fundamental and essential restraining system. The company began offering a Supplemental Restraint System option consisting of a driver airbag system and an emergency tensioning belt retractor for the passenger in December 1980. The functional reliability of the system has proven satisfactory.

Among many tasks of car development, safety, economy, environmental benefits and convenience, safety should have a high priority. One of the main goals is the reduction of the number of accidents. Environment and situation recognition by autonomous vehicle-electronic systems can contribute to the recognition of problems together with information to the driver or direct intervention in the car's behaviour. This paper describes some techniques for environment recognition, the status of a present project, and the goals of some PROMETHEUS (Program for a European Traffic with Highest Efficiency and Unprecedented Safety) projects.

The ultimate goal of drive-line management is low fuel consumption as well as providing the highest possible driving performance within the bounds of good driving safety. This can only be achieved by shifting the operating region on the performance diagram. In order to do this the technical characteristics of the drive-line components must be taken into account. The development of drive-line optimization can be separated into two phases. In the first phase the driver is partially or entirely integrated into the control circuit via external visual and acoustic feedback inputs. In the second phase automatic controls take-over the drive-line management without putting stress on the driver so that the vehicle in effect controls itself.

Information on the driving stability can be obtained in the form of oversteer or understeer tendencies and acceleration limits on a circular path. Up to now the calculations have only been made on an ideal, even roadway. Significant dynamic characteristics, such as the tuning of the shock absorbers, which also play a role in evaluating the stability of a vehicle in a driving test, are thereby not included in the calculations. In this paper the unevenness of the roadway is taken into consideration in calculating steady state cornering tests. Different vehicle models can be evaluated in regard to their handling or active safety with the aid of the driver's steering actions required to keep the car on course.

Daimler-Benz have developed an automatically/electronically controlled traction system, the 4MATIC. Great store has been set by active safety. This paper deals with the problems involved in 4-Wheel drive and analyzes the reasons which led to the 4MATIC concept. Depending on the conditions encountered, the drive components engage automatically one after the other in the sequence front-wheel drive - interaxle differential lock - rear axle differential lock. The engagement, and thus the approaching limits of driving dynamics, is indicated to the driver by an indicator lamp so that he can adjust to the deteriorated conditions in time. A further important advantage of this system is the automatic disengagement of the differential locks when braking so that the anti-lock braking remains fully effective.

This report deals with the development and use of the Daimler-Benz Isohuman Simulation Model for the mathematical simulation of dummy behaviour in an impact environment. Designated ISM, this computer program package is capable of handling both automobile occupant and pedestrian kinematics. Daimler-Benz safety engineers use the ISM to evaluate new safety designs before performing actual laboratory tests. The ISM code uses the theoretical algorithm of Prof. Wittenburg. The dummy is represented by 11 rigid body elements. Realistic and accurate simulations are assured by the fact that a considerable number of functional and sophisticated algorithms were developed to involve the different interactions of dummy-to-belt or dummy-to-vehicle. In particular, considerable work is being done to introduce a more precise and realistic dummy and vehicle geometry.

A method for detecting drivers' intentions is essential to facilitate operating mode transitions between driver and driver assistance systems. We propose a driver behavior recognition method using Hidden Markov Models (HMMs) to characterize and detect driving maneuvers and place it in the framework of a cognitive model of human behavior. HMM-based steering behavior models for emergency and normal lane changes as well as for lane keeping were developed using a moving base driving simulator. Analysis of these models after training and recognition tests showed that driver behavior modeling and recognition of different types of lane changes is possible using HMMs.

The nearly 77 million baby boomers, born between 1946 and 1964, can say that they are the automobile generation. Now turning 60 one every seven seconds, what are the new safety challenges and opportunities posed by the next generation of older adults? This paper presents a modified Haddon matrix to identify key product development, design and liability issues confronting the automobile industry and related stakeholders. The industry is now at a critical juncture to address the development of key technological innovations as well as the changing policy and liability environments being reshaped by an aging population.

Accurately predicting real-world vehicle energy consumption is essential for optimizing vehicle designs, enhancing energy efficiency, and developing effective energy management strategies. This paper presents a data-driven approach that utilizes machine learning techniques and a comprehensive dataset of vehicle parameters and environmental factors to create precise energy consumption prediction models. The methodology involves recording real-world vehicle data using data loggers to extract information from the CAN bus systems for ICE and hybrid electric, as well as hydrogen and battery fuel cell vehicles. Data cleaning and cycle-based analysis are employed to process the dataset for accurate energy consumption prediction. This includes cycle detection and analysis using methods from statistics and signal processing, and then pattern recognition based on these metrics.