THE USE of VEHICLE DATA in ADAS DEVELOPMENT, VERIFICATION and FOLLOW-UP on the SYSTEM

Advanced Driver Assistance Systems (ADAS) require a high level of interaction between the driver and the system, depending on driving context at a particular moment. Context-aware ADAS evaluation based on vehicle data is the most prominent way to assess the complexity of ADAS interactions. In this study, we conducted interviews with the ADAS development team at Volvo Cars to understand the role of vehicle data in the ADAS development and evaluation. The interviews\u27 analysis reveals strategies for improvement of current practices for vehicle data-driven ADAS evaluation

Real-time Personalized Driver Support System for Pilot Assist Promotion in Different Traffic Conditions

The complexity of advanced in-vehicle systems and level of automation provided is currently increasing, making the understanding of smart systems design and limitations challenging to a driver. As a result, misinterpretation of the system\u27s capabilities can be detrimental to perceived usefulness and the system\u27s usage. The personalized real-time driver support concept presented in this paper is designed to improve the driver\u27s understanding of Pilot Assist (PA) and increase PA usage effectiveness in various traffic contexts. The designed communication informs drivers about PA capabilities in various traffic conditions, helping drivers recognize the appropriate context for PA activation and reflect on their own PA use strategy

Naturalistic driving study for automated driver assistance systems (ADAS) evaluation in the Chinese, Swedish and American markets

In recent years, Automated Driver Assistance Systems (ADAS) have received great promotion and acceptance in the European market. However, transferring ADAS to other markets may affect driver behavior due to the cultural and contextual differences in various markets. Methods used for capturing these differences are based on subjective data collection. This study shows how vehicle data collected in the ND study helps to identify and investigate further the differences in driver behavior and the driving context in the Chinese, Swedish and US markets. This paper discusses a better way to consider the infrastructural and cultural differences in ADAS design

WORKING AGILE TO SPEED UP RESEARCH WITH INDUSTRY: FIVE INDEPENDENCE PRINCIPLES

One of the obstacles to the ability of research to make an impact on industry resides on the research process itself. Today, there is a need to accelerate the means for research to support industrial transformation. At the same time, there is the need to maintain scientific rigorousness, which often requires time. To solve this trade-off, this paper evaluates existing research approaches through the lenses of agile development. The analysis is based on a simulation of research process architectures, and on observations made over several research projects with industry. The results of this analysis highlight five light-but-sufficient rules of research project behavior to keep momentum, motivation and trust when doing research with industry. The paper demonstrates the use of these five rules in a research sprint conducted iwith two automotive OEMs

Design of a data-driven communication framework as personalized support for users of ADAS

Recently the automotive industry has made a huge leap forward in Automated Driver Assistance Systems (ADAS) development, increasing the level of driving processes automation. However, ADAS design does not imply any individual support to the driver; this results in a poor understanding of how the ADAS works and its limitations. This type of driver uncertainty regarding ADAS performance can erode the user\u27s trust in the system and result in decreasing situations when the system is in use. This paper presents the design of a data-driven communication framework that can utilize historical and real-time vehicle data to support ADAS users. The data-driven communication framework aims to illustrate the ADAS capabilities and limitations and suggests effective use of the system in real-time driving situations. This type of assistance can improve a driver\u27s understanding of ADAS functionality and encourage its usage

Cognitive Quality: An Unexplored Perceived Quality Dimension in the Automotive Industry

Well known, perceived quality is a game-changer in consumers’ decision-making processes and is seen as one key predictor of a product’s and company’s success. Today, the automotive industry faces challenges not only to deliver superior manufacturing quality in order to excel in perceived quality, but also to induce a positive sensory and cognitive response from its customers. Previous research aimed to quantify and unpick consumers’ perception of quality in order to meet consumer expectations and requirements. Cognitive processes related to product design have been explored in a variety of disciplines, ranging from the design research, specifically in the field of aesthetics, to sociopsychology. In the engineering and manufacturing research field, however, there is a significant gap regarding ‘intangibles’ related to car design. In this conceptual paper, we extend our previous work by presenting the concept of\ua0Cognitive Quality\ua0as a new dimension of the Perceived Quality Framework (PQF). The PQF, in its turn, illustrates the sensory, attribute-centric engineering viewpoint on quality perception. Therefore, the new\ua0Cognitive Quality\ua0dimension significantly contributes to the theoretical foundation of perceived quality in engineering and manufacturing research, specifically in the automotive field

Perceived quality of products: a framework and attributes ranking method

Perceived quality is one of the most critical aspects of product development that defines the successful design. This paper presents a new approach to perceived quality assessment by examining its elements, decomposed into a structure with the bottom-up sensory approach from the level of basic (‘ground’) attributes, covering almost every aspect of quality perception from the engineering viewpoint. The paper proposes a novel method for perceived quality attributes relative importance ranking, resulting in the balanced perceived quality of the final product within the given conditions. The proposed method helps to reach the equilibrium of the product’s quality equation from the perspective of design effort, time, and costs estimations. The authors introduce the Perceived Quality Framework (PQF), which is the taxonomy system for perceived quality attributes and the core of the attributes importance ranking (PQAIR) method. The research outcomes are based on findings of the qualitative exploratory study, including European and North American premium and luxury automotive manufacturers. An empirical structural validity test was performed to assess the usability and rigour of the proposed method. The results indicate that perceived quality evaluation can be significantly improved during all stages of product development

A new surrogate model–based method for individualized spot welding sequence optimization with respect to geometrical quality

In an individualized sheet metal assembly line, form and dimensional variation of the in-going parts and different disturbances from the assembly process result in the final geometrical deviations. Securing the final geometrical requirements in the sheet metal assemblies is of importance for achieving aesthetic and functional quality. Spot welding sequence is one of the influential contributors to the final geometrical deviation. Evaluating spot welding sequences to retrieve lower geometrical deviations is computationally expensive. In a geometry assurance digital twin, where assembly parameters are set to reach an optimal geometrical outcome, a limited time is available for performing this computation. Building a surrogate model based on the physical experiment data for each assembly is time-consuming. Performing heuristic search algorithms, together with the FEM simulation, requires extensive evaluations times. In this paper, a neural network approach is introduced for building surrogate models of the individual assemblies. The surrogate model builds the relationship between the spot welding sequence and geometrical deviation. The approach results in a drastic reduction in evaluation time, up to 90%, compared to the genetic algorithm, while reaching a geometrical deviation with marginal error from the global optimum after welding in a sequence

Evaluating different strategies to achieve the highest geometric quality in self-adjusting smart assembly lines

Digital twin-driven productions have opened great opportunities to increase the efficiency and quality of production processes. Smart assembly lines are one of these opportunities in which the effects of geometric variations of the mating parts on the assemblies can be minimized. These assembly lines utilize different techniques, including selective assembly and locator adjustments, to improve the geometric quality. This paper signifies that the achievable improvements through these techniques are highly dependent on the utilized fixture layout for the assembly process. Hence, different design methods and productions that can be followed in a smart assembly line are discussed. Furthermore, different scenarios are applied to two industrial sample cases from the automotive industry. The aptest design strategy for each improvement technique is determined. Moreover, the strategy that can result in the highest geometric quality of assemblies through a smart assembly line is defined

Addressing information asymmetry during design: Customer-centric approach to harmonization of car body split-lines

Implementation of methods for perceived quality evaluation is an integral part of the automotive manufacturers\u27 strategic development plans. The development of models for objective assessment of perceived quality is a very important task, addressing information asymmetry between designers and customers. This study seeks to understand how customers perceive and prioritize attributes associated with the car body split lines. We applied best-worst scaling methodology (BWS) to understand the importance of different shape design forms from a customer perspective. This approach was tested on 125 respondents. Our results indicate the improvement of engineering practices regarding complex product development solutions and their evaluation