Zhen Yang

Conditional automated driving [level 3, Society of Automotive Engineers ] requires drivers to take over the vehicle when an automated system’s failure occurs or is about to leave its operational design domain. Two-stage warning systems, which warn drivers in two steps, can be a promising method to guide drivers in preparing for the takeover. However, the proper time intervals of two-stage warning systems that allow drivers with different personalities to prepare for the takeover remain unclear. This study explored the optimal time intervals of two-stage warning systems with insights into the drivers’ neuroticism personality. A total of 32 drivers were distributed into two groups according to their self-ratings in neuroticism. Each driver experienced takeover under the two-stage warning systems with four time intervals. The takeover performance and subjective opinions for time intervals and situation awareness were recorded. The results showed that drivers in the 5-s time interval had the best takeover preparation. Furthermore, both the 5- and 7-s time intervals resulted in more rapid takeover reactions and were rated more appropriate and useful than the 3- and 9-s time intervals. In terms of personality, drivers with high neuroticism tended to take over immediately after receiving takeover messages, at the cost of SA deficiency. In contrast, drivers with low neuroticism responded safely by judging whether they gained enough SA. We concluded that the 5-s time interval was optimal for drivers in two-stage takeover warning systems. When considering personality, drivers with low neuroticism had no strict requirements for time intervals. However, the extended time intervals were favorable for drivers with high neuroticism in developing SA. The present findings have reference implications for designers and engineers to set the time intervals of two-stage warning systems according to the neuroticism personality of drivers.

Financial literacy is essential for every individual concerned with public welfare and household portfolio choices. In this study, we investigate the impact of household financial literacy on individuals’ financial behavior using the China Household Financial Survey Data of 2015 and 2017. The results show that financial knowledge has significant current, long-term, and dynamic effects on financial behavior. This finding suggests that financial literacy is an important factor in shaping and improving financial behavior. Second, financial literacy can improve residents’ limited attention, and residents with high attention tend to have formal bank accounts, participate in the stock market, and engage in financial behaviors in situations such as risky financial markets. High attention also helps to improve residents’ financial behavior. This relationship suggests that financial literacy positively impacts formal bank account holding, participation in financial markets, participation in commercial insurance, participation in pension plans, and credit card holdings through limited attention channels that facilitate access to specific financial information. In addition, heterogeneity analysis showed that the impact of financial literacy on financial behavior differs significantly between urban and rural households, between men and women, and between high and low education levels. The study provides valuable insights for policy implications to enhance financial literacy, such as carrying out financial training to improve residents’ knowledge about financial aspects, which further helps to optimize household financial decision-making.

Auditory warnings have been shown to interfere with verbal working memory. However, the impact of different types of auditory warnings on working memory tasks must be further researched. This study investigated how different kinds of auditory warnings interfered with verbal and spatial working memory. Experiment 1 tested the potential interference of auditory warnings with verbal working memory. Experiment 2 tested the potential interference of auditory warnings with spatial working memory. Both experiments used a 3 × 3 mixed design: auditory warning type was between groups, and task condition was within groups. In Experiment 1, earcons and spearcons but not auditory icons worsened the performance on the verbal serial recall task in the identify-warning condition, compared with that in the no-warning or ignore-warning conditions. In Experiment 2, only identifying earcons worsened the performance on the location recall task compared with performance without auditory warnings or when auditory warnings were ignored. Results are discussed from the perspective of working memory resource interference, and their practical application in the selection and design of auditory warning signals is involved.

In spectrum sharing cognitive radio networks, unauthorized users are allowed to use the spectrum of authorized users to improve spectrum utilization. Due to limited spectrum resources, how to formulate a reasonable spectrum allocation scheme is very important. As a mathematical analysis tool, game theory can solve the problem of resource allocation well. In recent years, it has been applied to the research of resource allocation in spectrum sharing networks by some literatures. In a cellular network consisting of multiple cellular users and full-duplex end-to-end communication users D2D, the self-interference caused by full-duplex communication and the interference caused by the D2D users to the cellular users will significantly reduce system throughput. In order to reduce the interference in the network, this paper introduces a power control algorithm based on Stackelberg game, which sets the cellular users and D2D users as the leaders and followers, respectively. The cellular users and the D2D users compete with each other to minimize the cost, and we propose new utility functions. We build an optimization problem under the outage probability constraint and power constraint and the transmission power of the users is obtained by using the Lagrangian dual decomposition method. The simulation results show that the proposed game algorithm improves network performance compared with other existing schemes.