Exploring the key services and players in the smart car market

et al. 2020

Applied Sciences

118

Self-driving cars are a hot research topic in science and technology, which has a great influence on social and economic development. Deep learning is one of the current key areas in the field of artificial intelligence research. It has been widely applied in image processing, natural language understanding, and so on. In recent years, more and more deep learning-based solutions have been presented in the field of self-driving cars and have achieved outstanding results. This paper presents a review of recent research on theories and applications of deep learning for self-driving cars. This survey provides a detailed explanation of the developments of self-driving cars and summarizes the applications of deep learning methods in the field of self-driving cars. Then the main problems in self-driving cars and their solutions based on deep learning methods are analyzed, such as obstacle detection, scene recognition, lane detection, navigation and path planning. In addition, the details of some representative approaches for self-driving cars using deep learning methods are summarized. Finally, the future challenges in the applications of deep learning for self-driving cars are given out.

Section: Development Of Self-driving Carsmentioning

confidence: 99%

A Survey on Theories and Applications for Self-Driving Cars Based on Deep Learning Methods

et al. 2020

Applied Sciences

118

“…However, for the vast majority of consumers, it is not the technology itself that cares about them, but how they feel in the cockpit (Park et al, 2019). The benefits of intelligent cars include increased safety, reduced need for infrastructure investment, improved fuel economy, and reduced congestion.…”

Section: Introductionmentioning

confidence: 99%

“…Beggiato et al (2019) believe that comfort plays an important role in the wide acceptance of intelligent vehicles. For some products such as smart cars, consumer satisfaction is a factor for business success (Park et al, 2019; Salomo et al, 2003). Industry and research are working to develop systems that can automatically adapt to maximize well‐being (Olugbade et al, 2021).…”

Section: Introductionmentioning

confidence: 99%

A comfort evaluation method based on an intelligent car cockpit

Yang

Xing

et al. 2022

Hum Ftrs & Erg Mfg Svc

With the rapid development of automobiles, car cockpits are becoming more and more intelligent and advanced, and the intelligent requirements of automobile cockpits are gradually increasing. However, the real value of intelligence can only be realized when it makes passengers in a cockpit feel comfortable. In this study, seven factors that affect passenger comfort in intelligent cockpits are defined. Under these factors, a total of 33 evaluation indicators were developed. The core of the method was to determine the dissatisfaction indicators and degree of dissatisfaction in the intelligent cockpit by analyzing the relationship between people's perceived performance and their expectations. This method was used to evaluate the Tesla Model 3, and it was found in the results that the higher the degree of dissatisfaction with the indicator, the more subjective feedback it had, which in turn proved the effectiveness of the model. According to the degree of dissatisfaction, the indicators affecting comfort were also divided into three levels. This hierarchical division helps clarify which indicators should be prioritized for improvement. Generally, this method has a certain feasibility, which is helpful for the development and redesign of an intelligent car cockpit, and provides some reference strategies for other transportation fields.comfort, evaluation method, expectation, intelligent cockpit, the degree of dissatisfactionWith the rapid development of technology, the number of intelligent cars has also increased in recent years (Arena et al., 2020). Related research describes the intelligent car of the future as not only improving traffic safety like a robot but also further meeting people's demands by connecting to the Internet (Huang et al., 2016;James, 2012). Intelligent vehicles have become a trend now. Companies such as Tesla, Jaguar, and Google are now launching more intelligent vehicles from innovative materials and innovative technologies (Sun et al., 2021).However, for the vast majority of consumers, it is not the technology itself that cares about them, but how they feel in the cockpit (Park et al., 2019). The benefits of intelligent cars include increased safety, reduced need for infrastructure investment, improved fuel economy, and reduced congestion. But most importantly, they make passengers more relaxed and comfortable (Jorlöv et al., 2017). The real benefits of intelligent cars can only be realized when the human driver is comfortable in the intelligent cockpit and the interaction between the driver and the automated system is at a reasonable level (Helldin et al., 2013). Beggiato et al. (2019 believe that comfort plays an important role in the wide acceptance of intelligent vehicles. For some products such as smart cars, consumer satisfaction is a factor for business success (Park et al., 2019;Salomo et al., 2003). Industry and research are working to develop systems that can automatically adapt to maximize well-being (Olugbade et al., 2021). Therefore, making people feel comfortable is

“…The objective assignment method is a method based on the information of the decision matrix, such as the entropy weighting method, multi-objective optimization method, principal component analysis, and the multiple attribute decision-making model (MADM) 28 – 31 . Among them, AHP was used to evaluate the relative importance among various services provided by intelligent automobiles, such as driver assistance, infotainment, and IoT hubs 32 . As a subjective empowerment method, AHP is widely used in multicriteria decision-making and is suitable to help solve decision problems characterized by many interrelated factors 33 , 34 .…”

Section: Introductionmentioning

confidence: 99%

A comprehensive evaluation model for the intelligent automobile cockpit comfort

Yang

Xing

et al. 2022

Sci Rep

Under the background of automobile intelligence, cockpit comfort is receiving increasing attention, and intelligent cockpit comfort evaluation is especially important. To study the intelligent cockpit comfort evaluation model, this paper divides the intelligent cockpit comfort influencing factors into four factors and influencing indices: acoustic environment, optical environment, thermal environment, and human–computer interaction environment. The subjective and objective evaluation methods are used to obtain the subjective weights and objective weights of each index by the analytic hierarchy process and the improved entropy weight method, respectively. On this basis, the weights are combined by using the game theory viewpoint to obtain a comprehensive evaluation model of the intelligent automobile cockpit comfort. Then, the cloud algorithm was used to generate the rank comprehensive cloud model of each index for comparison. The research results found that among the four main factors affecting the intelligent automobile cockpit comfort, human–computer interaction has the greatest impact on it, followed by the thermal environment, acoustic environment, and optical environment. The results of the study can be used in intelligent cockpit design to make intelligent cockpits provide better services for people.