Search Results

One of the ways to reduce city congestion is to balance the traffic flow on the road network and maximally utilize all road capacities. There are examples showing that, if the drivers are not competitive but cooperative, the road network usage efficiency and the traffic conditions can be improved. This motivates the idea of designing a cooperative routing algorithm to benefit most vehicles on the road. This paper presents a semi-cooperative social routing algorithm for large transportation network with predictive traffic density information. The goal is to integrate a cooperative scheme into the individual routing and achieve short traveling time not only for the traveler itself, but also for all vehicles in the road network. The most important concept of this algorithm is that the route is generated with the awareness of the total travel time added to all other vehicles on the road due to the increased congestion.

We present research in progress to develop and implement a transportable instrumentation package (TIP) to collect driver data in a vehicle. The overall objective of the project is to investigate the symbiotic relationship between humans and their vehicles. We first describe the state-of-art technologies to build the components of TIP that meet the criteria of ease of installation, minimal interference with driving, and sufficient signals to monitor driver state and condition. This method is a viable alternative to current practice which is to first develop a fully instrumented test vehicle, often at great expense, and use it to collect data from each participant as he/she drives a prescribed route. Another practice, as for example currently being used in the SHRP-2 naturalistic driving study, is to install the appropriate instrumentation for data collection in each individual's vehicle, often requiring several hours.

This study investigated the effects of three navigation system human-machine interfaces (HMIs) on driver eye-glance behavior, navigational errors, and subjective assessments. Thirty-six drivers drove an unfamiliar 3-segment route in downtown Detroit. HMIs were 2D or 3D (level-of-detail) electronic map display + standard voice prompts, or 3D map-display augmented by photorealistic images + landmark-enhanced voice prompts. Participants drove the same three route segments in order but were assigned a different HMI condition/segment in a 3-period/3-treatment crossover experimental design. Results indicate that drivers’ visual attention using the advanced navigation systems HMIs were within US Department of Transportation recommended visual distraction limits. More turns missed in the first route segment, regardless of HMI, were attributable to greater route complexity and a late-onset voice prompt. Participant’s ratings of HMIs were influenced by the context in which that HMI was used.

This study presents a methodology for comparative analysis of seat and suspension parameters on a system level to achieve minimum occupant head displacement and acceleration, thereby improving occupant ride comfort. A lumped-parameter full-vehicle ride model with seat structures, seat cushions and five occupants has been used. Two different vehicle masses are considered. A low amplitude pulse signal is provided as the road disturbance input. The peak vertical displacement and acceleration of the occupant’s head due to the road disturbance are determined and used as measures of ride comfort. Using a design of experiments approach, the most critical seat cushion, seat structure and suspension parameters and their interactions affecting the occupant head displacement and acceleration are determined. An optimum combination of parameters to achieve minimum peak vertical displacement and acceleration of the occupant’s head is identified using a response surface methodology.

Position of the H-point plays a vital role during designing the seating system. The seating system provides support and comfort to the occupants while they are operating the vehicle. The traditional way to design a seat system is to use rules of thumb and experience, which often results in several costly design iterations. The purpose of this paper is to demonstrate the capability of CAE analytical tool to find the H-point at the early phase of the seating system design without compromising the comfort level of the occupant. The recently launched Lincoln Continental front seating system was used to validate this purpose. The Continental seating system has unique design features which provide special challenges in designing and simulating the seat. With the help of CAE analytical tool, the traditional process is streamlined and a seat design could be achieved in a shorter period with greater accuracy.

The rapid development of connected and automated vehicle technologies together with cloud-based mobility services are revolutionizing the transportation industry. As a result, huge amounts of data are being generated, collected, and utilized, hence providing tremendous business opportunities. However, this big data poses serious challenges mainly in terms of data privacy. The risks of privacy leakage are amplified by the information sharing nature of emerging mobility services and the recent advances in data analytics. In this paper, we provide an overview of the connected vehicle landscape and point out potential privacy threats. We demonstrate two of the risks, namely additional individual information inference and user de-anonymization, through concrete attack designs. We also propose corresponding countermeasures to defend against such privacy attacks. We evaluate the feasibility of such attacks and our defense strategies using real world vehicular data.

This paper presents a comparison of aqueous corrosion rates in 5% NaCl solution for eight experimental creep-resistant magnesium alloys considered for automotive powertrain applications, as well as three reference alloys (pure magnesium, AM50B and AZ91D). The corrosion rates were measured using the techniques of titration, weight loss, hydrogen evolution, and DC polarization. The corrosion rates measured by these techniques are compared with each other as well as with those obtained with salt-spray testing using ASTM B117. The advantages and disadvantages of the various corrosion measurement techniques are discussed.

As automakers begin to design the autonomous vehicle (AV) for the first time, they must reconsider customer interaction with the Automatic Speech Recognition (ASR) system carried over from the traditional vehicle. Within an AV, the voice-to-ASR system needs to be capable of serving a customer located in any seat of the car. These shifts in focus require changes to the microphone selection and placement to serve the entire vehicle. Further complicating the scenario are new sources of noise that are specific to the AV that enable autonomous operation. Hardware mounted on the roof that are used to support cameras and LIDAR sensors, and mechanisms meant to keep that hardware clean and functioning, add even further noise contamination that can pollute the voice interaction. In this paper, we discuss the ramifications of picking up the intended customer’s voice when they are no longer bound to the traditional front left “driver’s” seat.

Seat assessment is an important necessity for the growing auto industry. The design of seats is driven by customer’s demand of comfort and aesthetics of the vehicle interiors. Some of the few seat assessments are H-point prediction with H-point Machine (HPM); backset prediction with Head Restraint Measuring Device (HRMD); seat hardness and softness. Traditional seat development was through developing series of prototypes to meet requirements which involved higher costs and more time. The seat requirement of H-Point measurement is of focus in this paper. Though there are other commercial available software/methods to perform the H-point measurement simulations, the aim here was to assess the capabilities of an alternate Computer Aided Engineering (CAE) methodology using CAE tools - PRIMER and LS-Dyna. The pre-processing tools - Hypermesh and ANSA have been used for modeling and Hyperview tool used for reviewing the simulations.

This paper presents results of two surveys, namely, a photographic measurements survey and a rider survey, conducted to determine how the type and origin of a motorcycle related to motorcycle dimensions, rider characteristics, seating posture, and motorcycle controls and displays. In the photographic survey, 12 most popular motorcycles covering three types (cruiser, sport, and touring) and three origins (Europe, Asia and North America) were measured from photographs taken in a standardized procedure with and without a rider. The data showed that the Asian and North American cruisers were very similar in all dimensions. These include seat height, seat to handlebar location, seat to foot rest location, foot rest size, and handgrip stance. This resulted in similar rider posture. North American sport motorcycles were more like cruisers than the Asian and European sport motorcycles.

This paper presents results of a study conducted to compare driving behavior and performance of drivers in two different fixed-base driving simulators (namely, FAAC and STI) while performing a same set of distracting tasks under geometrically similar freeway and traffic conditions. The FAAC simulator had a wider three-screen road view with steering feedback as compared to the STI simulator which had a single screen and narrower road view and had no steering feedback. Twenty four subjects (12 younger and 12 mature) drove each simulator and were asked to perform a set of nine different tasks involving different distracting elements such as, using a cell phone, operating the car radio, retrieving and selecting a map from map pocket in the driver's door, collecting coins to pay toll, etc.

This paper presents results of a three-phase research project aimed at understanding how future automotive interior materials should be selected or designed to satisfy the needs of the customers. The first project phase involved development of 22 five-point semantic differential scales to measure visual, visual-tactile, and evaluative characteristics of the materials. Some examples of the adjective pairs used to create the semantic differential scales to measure the perceptual characteristics of the material are: a) Visual: Light vs. Dark, Flat vs. Shiny, etc., b) Visual-Tactile: Smooth vs. Rough, Slippery vs. Sticky, Compressive vs. Non-Compressive, Textured vs. Non-Textured, etc., c) Evaluative (overall perception): Dislike vs. Like, Fake vs. Genuine, Cheap vs. Expensive, etc. In the second phase, 12 younger and 12 older drivers were asked to evaluate a number of different automotive interior materials by using the 22 semantic differential scales.

This paper describes a research project currently in-progress to develop a parametric model of a vehicle for use in early design stages of a new vehicle program. The model requires key input parameters to define the kind of new vehicle to be designed — in terms of details such as its intended driver/user population, vehicle type (e.g. 2-box, 3-box designs), and some key exterior and interior dimensions related to its size and proportions. The model computes and graphically displays interior package, ergonomics zones for driver controls and displays, and field of views through window openings. It also allows importing or inputting and superimposing and manipulating exterior surfaces created by a designer to assess compatibility between the interior occupant package and the vehicle exterior.

Level 2 (L2) partially automated vehicle systems require the driver to continuously monitor the driving environment and be prepared to take control immediately if necessary. One of the main challenges facing developers of these systems is how to ensure that drivers understand their role and stay alert as the systems require. With little real world data, it has been difficult to understand user attitudes and behaviors toward the implementation and use of partially automated vehicles. At the time of this study, Tesla was one of the few OEMs with a partially automated vehicle feature available on the market; Autopilot. In order to understand how customers interact with a partially automated vehicle, a study was conducted to observe people driving their own Tesla vehicles while autopilot was engaged. Sixteen Tesla owners (14 males and 2 females) between ages 25 to 60 had their vehicles instrumented with video/audio data collection systems for three consecutive days.

As intelligent automated vehicle technologies evolve, there is a greater need to understand and define the role of the human user, whether completely hands-off (L5) or partly hands-on. At all levels of automation, the human occupant may feel anxious or ill-at-ease. This may reflect as higher stress/workload. The study in this paper further refines how perceived workload may be determined based on occupant physiological measures. Because of great variation in individual personalities, age, driving experiences, gender, etc., a generic model applicable to all could not be developed. Rather, individual workload models that used physiological and vehicle measures were developed.

This paper presents results of a study conducted to determine differences in older (over age 55) and younger (under age 35), male and female drivers while entering and exiting vehicles with three different body styles - namely, a large sedan, a minivan and a full-size pick-up truck. Thirty-six drivers (males and females, ages 25 to 89 years) who participated in this study were first measured for their anthropometric, strength and body flexibility measures relevant to the entry/exit tasks. They were asked to first get in each vehicle and adjust their preferred seating position. Then, they were asked to get in the vehicle and their entry time was measured. Their entry maneuver was also video taped and they were asked to rate the level of ease/difficulty (using a 5-point scale) in entering. Similar procedure and measurements were conducted during their exit from each vehicle.

This paper discusses the evolution of graduate education in manufacturing engineering and the curriculum needed to educate manufacturing engineers in the automotive industry. This paper examines the master's and doctoral curriculum in manufacturing engineering at the University of Michigan-Dearborn. Finally, it proposes future direction for graduate education in manufacturing that will be needed for the automotive industry of the future.

The advancement towards development of autonomy follows either the bottom-up approach of gradually improving and expanding existing Advanced Driver Assist Systems (ADAS) technology where the driver is present in the control loop or the top-down approach of directly developing Autonomous Vehicles (AV) hardware and software using alternative approaches without the driver present in the control loop. Most ADAS systems today fall under the classification of SAE Level 1 which is also referred to as the driver assistance level. The progression from SAE Level 1 to SAE Level 2 or partial automation involves the critical task of merging autonomous lateral control and autonomous longitudinal control such that the tasks of steering and acceleration/deceleration are not required to be handled by the driver under certain conditions [1].

With recent advances in microprocessors and data storage technologies, vehicle users can now bring or access large amounts of data in vehicles for purposes such as communication (e.g. e-mail, phone books), entertainment (e.g. music and video files), browsing and searching for information (e.g. on-board computers and internet). The challenge for the vehicle designer is how to design data displays and retrieval methods to allow data search and manipulation tasks by managing driver workload at safe acceptable levels. This paper presents a data retrieval menu system developed to assess levels of screens (depth of menu) that may be needed to select required information when a vehicle is equipped with the capability to access audio files, cell phone, PDA, e-mail and “On-star” type functions.

Considerable research has been conducted in terms of attempting to reduce lower leg injury risk in full frontal impacts, in some cases by the use of a knee airbag (KAB). However, there has been limited research into the performance of KAB systems during a crash test with increased oblique loading, such as the IIHS small overlap frontal test, an oblique moving deformable barrier test (OI) being researched by NHTSA, and a mobile progressive deformable barrier test (MPDB) that is expected to be implemented by Euro NCAP in the next few years. The objective of the current numerical study was concentrated on the evaluation of an innovative KAB concept design intended to reduce ATD right inboard lower leg/foot responses under small overlap and oblique loading conditions. A novel appendage KAB concept design was developed with the help of morphing and computational studies which were performed with different ATD sizes.