Distracted driving increases the risk of driving errors and accidents, and it has become the main factor leading to accidents. Currently, a large amount of information is displayed on in-vehicle panels, which possibly distract drivers' attention, diverting their gaze from the road. To minimize the negative impact of distracted driving, this study sought to optimize the design of icons presented on vehicle screens. We investigated the effect of icon size, icon position, driving state, and age on drivers' perception time, driving performance, and subjective evaluations. A total of 42 drivers (26 men and 20 women) between the ages of 22 and 70 years participated in the study, completing a simulated driving task and a secondary visual task. The results demonstrated significant main effects of icon size, driving state, icon position, and interaction effects. Participants spent a longer time perceiving smaller icons on the center control panel in the driving state. As the icon size increases, perception time decreases at a reduced speed. During the static state, perception time leveled out from 44′ while during the driving state, perception time leveled out from 80′. On the instrument panel, perception time leveled out from 60′ while on the center control panel, perception time leveled out from 80′. Subjective evaluations supported behavioral data on the effect of icon size. Our results indicated the importance of strategic design for icons on vehicle screens, which could reduce the visual workload, then reduce the risk of traffic accidents. According to the results, enterprises or designers could target the design of icon size according to different types of in-vehicle panels or screens.
We formulate and study a broadcast problem arising in multichannel duty-cycling wireless body area networks (WBANs) which the sink needs to broadcast control information to all sensor nodes on or implanted in the human body. Despite its fundamental importance for the network configuration and secure key management, the multichannel broadcast problem is largely unaddressed in duty-cycling WBANs. In this paper, we devise novel 2-D scheduling specifying the rule of channel hopping and wake-up time slot selection, which achieves the order-minimal worst-case broadcast delay while guaranteeing the full broadcast diversity regardless of clock drifts and asymmetric duty cycles and channel perceptions. Specifically, we first employ the Chinese remainder theorem to design an effective multichannel broadcast (MCB) algorithm and further propose improved MCB that enhances the granularity of MCB in matching actual duty cycles and number of channels, reducing the theoretically worst-case broadcast delay of MCB by up to 75%. We demonstrate the performance of the proposed algorithms through theoretical analysis and extensive simulations.
Monitoring the mechanical behaviors of cross-laminated timber (CLT) connections is of great importance to the condition assessment of timber structures. To date, numerous researches have demonstrated that PZT-enabled active sensing approaches can achieve structural healthy state monitoring under monotonic loads, whereas their effectiveness for reciprocating loads still needs to be further studied. Moreover, PZT-enabled active sensing approaches depend on prior knowledge and human judgment, restricting its field applications. Based on the above background, this research proposes an innovative method to monitor the mechanical behaviors of CLT connections under external reciprocating loading by integrating PZT-enabled active sensing, and eight machine learning (ML) approaches. Meanwhile, a new damage index based on wavelet packet decomposition and multiple signal path fusion is designed to improve the precision of ML methods. Finally, cyclic loading tests on CLT connections are conducted to demonstrate the outstanding capabilities of the proposed method than convention PZT-enabled active sensing approaches.
Tag population estimation has recently attracted significant research attention due to its paramount importance on a variety of radio-frequency identification (RFID) applications. However, most, if not all, of the existing estimation mechanisms are proposed for the static case where tag population remains constant during the estimation process, thus leaving the more challenging dynamic case unaddressed, despite the fundamental importance of the latter case on both the theoretical analysis and the practical application. In order to bridge this gap, we devote this paper to designing a generic framework of stable and accurate tag population estimation schemes based on the Kalman filter for both the static and dynamic RFID systems. Technically, we first model the dynamics of RFID systems as discrete stochastic processes and leverage the techniques in the extended Kalman filter and cumulative sum control chart to estimate tag population for both the static and dynamic systems. By employing the Lyapunov drift analysis, we mathematically characterize the performance of the proposed framework in terms of estimation accuracy and convergence speed by deriving the closed-form conditions on the design parameters under which our scheme can stabilize around the real population size with bounded relative estimation error that tends to zero with exponential convergence rate.
We formulate and study a broadcast problem arising in multi-channel duty cycling wireless body area networks (WBANs), where the sink needs to broadcast the control message to all sensor nodes. The objective is to design robust multichannel wake-up schedule with minimum worst-case broadcast delay while guaranteeing the full broadcast diversity regardless of clock drifts and asymmetric duty cycles. To that end, we first derive the lower-bound of worst-case broadcast delay with full diversity of any broadcast protocol and then design a multichannel broadcast protocol (MCB) that satisfies the performance requirement for the latency and diversity. Finally, the simulation results demonstrate the capability of MCB of ensuring successful broadcast delivery on every channel within the theoretical worst-case broadcast delay, even under asymmetric duty cycles and any amount of clock drifts.
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