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With the proliferation of ADAS and autonomous systems, the quality and quantity of the data to be used by vehicles has become crucial. In-vehicle sensors are evolving, but their usability is limited to their field of view and detection distance. V2X communication systems solve these issues by creating a cooperative perception domain amongst road users and the infrastructure by communicating accurate, real-time information. In this paper, we propose a novel Consolidated Object Data Service (CODS) for multi-Radio Access Technology (RAT) V2X communication. This service collects information using BSM packets from the vehicular network and perception information from infrastructure-based sensors. The service then fuses the collected data, offering the communication participants with a consolidated, deduplicated, and accurate object database. Since fusing the objects is resource intensive, this service can save in-vehicle computation costs.

There is a strong business case for automotive companies to improve by understanding what consumers want, like and dislike. Various aspects of ergonomics such as reach, visibility, usability, feel are dependent on measuring consumer’s ability, opinions and satisfaction. Rating scales (such as adjective, continuous, logarithmic, etc.) are used to measure these complex attitudes. It is essential the correct rating scale and appropriate analysis methods are used to capture these attitudes. Previous psychology research has been conducted on the performance of different rating scales. This ratings scale research focused on scales and their reliability and validity for various applications. This paper will summarize past research, discuss the use of rating scales specific to vehicle ergonomics, and analyze the results of an automotive interface study that correlates the seven-point adjective rating scale to the system usability score (SUS).

Age and experience influence driver ability to cope with transitions between automated and manual driving, especially when drivers are engaged in media use. This study evaluated three age cohorts (young/new drivers, adults, and seniors) on their performance in transitions from automated driving to manual vehicle control in a laboratory driving simulator. Drivers were given three tasks to perform during the automated driving segments: to watch a movie on a tablet, to read a story on a tablet, or to supervise the car's driving. We did not find significant differences in people's driving performance following the different tasks. We also did not find significant differences in driving performance between the people in each age group who successfully completed the study; however, the rejection rate of the senior age group was over 30% because many of the people in this age group had difficulty hearing instructions, understanding tasks, or remembering what to do.

A provisional, age-dependent thoracic risk equation (or, “risk curve”) was derived to estimate moderate-to-fatal injury potential (AIS2+), pertaining to men with responses gaged by the advanced mid-sized male test dummy (THOR50). The derivation involved two distinct data sources: cases from real-world crashes (e.g., the National Automotive Sampling System, NASS) and cases involving post-mortem human subjects (PMHS). The derivation was therefore more comprehensive, as NASS datasets generally skew towards younger occupants, and PMHS datasets generally skew towards older occupants. However, known deficiencies had to be addressed (e.g., the NASS cases had unknown stimuli, and the PMHS tests required transformation of known stimuli into THOR50 stimuli).

A set of risk equations was derived to estimate the probability of sustaining a moderate-to-serious injury to the knee-thigh-hip complex (KTH) in a frontal crash. The study consisted of four parts. First, data pertaining to knee-loaded, whole-body, post-mortem human subjects (PMHS) were collected from the literature, and the attendant response data (e.g., axial compressive load applied to the knee) were normalized to those of a mid-sized male. Second, numerous statistical analyses and mathematical constructs were used to derive the set of risk equations for adults of various ages and genders. Third, field data from the National Automotive Sampling System (NASS) were analyzed for subsequent comparison purposes.

The abdomen is the second most commonly injured region in children using adult seat belts, but engineers are limited in their efforts to design systems that mitigate these injuries since no current pediatric dummy has the capability to quantify injury risk from loading to the abdomen. This paper develops a porcine (sus scrofa domestica) model of the 6-year-old human's abdomen, and then defines the biomechanical response of this abdominal model. First, a detailed abdominal necropsy study was undertaken, which involved collecting a series of anthropometric measurements and organ masses on 25 swine, ranging in age from 14 to 429 days (4-101 kg mass). These were then compared to the corresponding human quantities to identify the best porcine representation of a 6-year-old human's abdomen. This was determined to be a pig of age 77 days, and whole-body mass of 21.4 kg.

An age-dependent, serious-to-fatal (AIS3+), thoracic risk curve was derived and evaluated for frontal impacts. The study consisted of four parts. In Part 1, two datasets of post mortem human subjects (PMHS) were generated for statistical and sensitivity analyses. In Part 2, logistic regression analyses were conducted. For each dataset, two statistical methods were applied: (1) a conventional maximum likelihood method, and (2) a modified maximum likelihood method. Therefore, four statistical models were derived — one for each dataset/statistical method combination. For all of the resulting statistical models (risk curves), the linear combination of maximum normalized sternum deflection and age of the PMHS was identified as a feasible predictor of AIS3+ thoracic injury probability. In Part 3, the PMHS-based risk curves were transformed into test-dummy-based risk curves. In Part 4, validation studies were conducted for each risk curve.

Maintaining adequate visibility at all times, through a vehicle windshield, is critical to the safe usage of the vehicle. The ability of the windshield defrosting and demisting system to quickly and completely melt ice on the outer windshield surface and remove mist formed on the inner surface is therefore of paramount importance. The objectives of this paper are to investigate the fluid flow and heat transfer on the windshield as well the effect of the air discharge from the defroster vents on passenger comfort. The results presented are from numerical simulations validated by experimental measurements both carried out a model and full-scale. The numerical predictions compare well with the experimental measurements at both scales. The effects of the defrosting and demisting air on occupants' comfort and safety are examined.

In 1996, the European Enhanced Vehicle Safety Committee, Working Group 17 (EEVC WG17) proposed a set of impact procedures to evaluate the pedestrian injury risk of vehicle fronts. These procedures address three aspects of pedestrian protection – head impacts, lower limb impacts, and thigh impacts – through vehicle subsystem tests. The criteria assessed during these impact tests are affected by the design of most parts of the vehicle body front-end. One of the challenges to vehicle design introduced by these tests is the impact of an adult pedestrian headform to the top of the fender. The proposed acceptance level for Head Injury Criterion (HIC) is less than 1000 during impacts at 40 km/h. This paper uses the finite element (FE) method to predict the influence of proposed fender and shotgun design modifications aimed at meeting this target. In addition, the known issues with the implementation of these proposed changes are discussed.

Federal Motor Safety Standard (FMVSS) 225 establishes requirements for child restraint anchorage systems to ensure their proper location and strength for the effective securing of child restraints, to reduce the likelihood of the anchorage systems failure and to increase the likelihood that child restraints are properly secured and thus more fully achieve their potential effectiveness in motor vehicles. Current CAE simulations are focused on evaluating localized structural strength by applying the loads as vectors to the child tether anchorages to approximate the loading. This method cannot be used to determine the displacement requirements of child tether that was added recently to FMVSS 225 specifications. A new CAE procedure that takes into account the effect of seat structure and belt system has been developed and successfully applied to truck programs.

Recent crash data was used to evaluate the safety performance of drivers who transport children. The age difference between drivers and children was found to be an important predictor of crash-related driving behavior and choices. Also, certain driver behaviors and choices when transporting children were identified as creating elevated risk. This study provides information that parents might use to reduce risk when their children are riding with other drivers. The results may also be of interest to professionals concerned with graduated licensing and the establishment and enforcement of laws relating to child endangerment such as drinking and driving with child passengers.

An improved defect detection system for painted surfaces has been developed which significantly increases topographic defect visibility (dirt-in-paint, sags/runs/drips, sealer-under-paint, spits, craters, etc.) for the final inspector / polisher. These minor defects can then be repaired before leaving the “spillout” deck. A new luminaire was designed to maximize the contribution of several applicable principles. The new process has significantly reduced the number of defects leaving the spillout area, doubled the number of “zero defect” vehicles, and increased energy savings from 25-40%. The improved Paint Inspection Lighting process was issued as a Uniform Process specification by the Ford Motor Company Vehicle Operations and was implemented in all of the Ford North American assembly plants.