Saliency difference based objective evaluation method for a superimposed screen of the HUD with various background

The head-up display (HUD) is an emerging device which can project information on a transparent screen. The HUD has been used in airplanes and vehicles, and it is usually placed in front of the operator's view. In the case of the vehicle, the driver can see not only various information on the HUD but also the backgrounds (driving environment) through the HUD. However, the projected information on the HUD may interfere with the colors in the background because the HUD is transparent. For example, a red message on the HUD will be less noticeable when there is an overlap between it and the red brake light from the front vehicle. As the first step to solve this issue, how to evaluate the mutual interference between the information on the HUD and backgrounds is important. Therefore, this paper proposes a method to evaluate the mutual interference based on saliency. It can be evaluated by comparing the HUD part cut from a saliency map of a measured image with the HUD image.Comment: 10 pages, 5 fighres, 1 table, accepted by IFAC-HMS 201

Adaptive multi-modal interface model concerning mental workload in take-over request during semi-autonomous driving

With the development of automated driving technologies, human factors involved in automated driving are gaining increasing attention for a balanced implementation of the convenience brought by the technology and safety risk in commercial vehicle models. One influential human factor is mental workload. In the take-over request (TOR) from autonomous to manual driving at level 3 of International Society of Automotive Engineers' (SAE) Levels of Driving Automation, the time window for the driver to have full comprehension of the driving environment is extremely short, which means the driver is under high mental workload. To support the driver during a TOR, we propose an adaptive multi-modal interface model concerning mental workload. In this study, we evaluated the reliability of only part of the proposed model in a driving-simulator experiment as well as using the experimental data from a previous study

Comparing eye-tracking metrics of mental workload caused by NDRTs in semi-autonomous driving

The objective of this study was to verify the effectiveness of eye-tacking metrics in indicating driver’s mental workload in semi-autonomous driving when the driver is engaged in different non-driving related tasks (NDRTs). A driving simulator was developed for three scenarios (high-, medium-, and low-mental workload presented by SAE (Society of Automotive Engineers) Levels 0, 1, and 2) and three uni-modality secondary tasks. Thirty-six individuals participated in the driving simulation experiment. NASA-TLX (Task Load Index), secondary task performance, and eye-tracking metrics were used as indicators of mental workload. The subjective rating using the NASA-TLX showed a main effect of autonomous level on mental workload in both visual and auditory tasks. Correlation-matrix calculation and principal-component extraction indicated that pupil diameter change, number of saccades, saccade duration, fixation duration, and 3D gaze entropy were effective indicators of a driver’s mental workload in the visual and auditory multi-tasking situations of semi-autonomous driving. The accuracy of predicting the mental-workload level using the K-Nearest Neighbor (KNN) classifier was 88.9% with bootstrapped data. These results can be used to develop an adaptive multi-modal interface that issues efficient and safe takeover requests

Enhancing the Driver's Comprehension of ADS's System Limitations: An HMI for Providing Request-to-Intervene Trigger Information

Level 3 automated driving systems (ADS) have attracted significant attention and are being commercialized. A Level 3 ADS prompts the driver to take control by requesting to intervene (RtI) when its operational design domain (ODD) or system limitations are exceeded. However, complex traffic situations may lead drivers to perceive multiple potential triggers of RtI simultaneously, causing hesitation or confusion during take-over. Therefore, drivers must clearly understand the ADS's system limitations to understand the triggers of RtI and ensure safe take-over. In this study, we propose a voice-based HMI for providing RtI trigger cues to help drivers understand ADS's system limitations. The results of a between-group experiment using a driving simulator showed that incorporating effective trigger cues into the RtI enabled drivers to comprehend the ADS's system limitations better and reduce collisions. It also improved the subjective evaluations of drivers, such as the comprehensibility of system limitations, hesitation in response to RtI, and acceptance of ADS behaviors when encountering RtI while using the ADS. Therefore, enhanced comprehension resulting from trigger cues is essential for promoting a safer and better user experience using ADS during RtI

Design support method for implementing benefits of inconvenience inspired by TRIZ

TRIZ and Knowledge-Based Innovation in Science and IndustryIn most cases, system design develops products for reducing human work based on the assumption that the more convenient life is, the richer it is. This assumption has yielded technical developments and outcomes that we generally appreciate. However, such development is not always the best for users or human-machine systems. Solely pursuing convenience causes such problems as excluding users, limiting their ability, and depriving the pleasure of using the systems. On the other hand, inconvenient systems or methods sometimes provide users with such benefits as enhanced awareness, increased creative contributions, and a fostering of affirmative feelings. We call such benefits of inconvenience fuben-eki: Further BENEfit of a Kind of Inconvenience. The present paper proposes a systematic way to implement such benefits. By focusing on the contradiction between convenience and such benefits, this study introduces the Contradiction Matrix of TRIZ. By analyzing many inconvenient tools and methods, principles, which relate inconveniences to their benefits, are derived and placed in what we call a fuben-eki matrix. This paper demonstrates how to utilize the matrix, which resembles the Contradiction Matrix of TRIZ, to support the idea generation for implementing the benefits of inconvenience

A point mutation found in the WT1 gene in a sporadic Wilms' tumor without genitourinary abnormalities is identical with the most frequent point mutation in Denys-Drash syndrome

AbstractWe have analyzed exon 9 of the WT1 gene of 18 non-familial/sporadic unilateral Wilms' tumors (WTs) from Japanese patients, by the polymerase chain reaction single-strand conformation polymorphism (PCR-SSCP) method. After screening these WTs, a nucleotide alternation, which was present on both alleles, was found in only one case. Furthermore, PCR-SSCP analysis of the constitutional DNA revealed that this patient carried the mutation on only one allele in the germline. Sequence analysis showed that the tumor carried a point mutation (C-1180 to T-1180) in WT1 exon 9 of both alleles, resulting in an Arg-394 to Trp-394 amino acid substitution within the third zinc finger domain of the WT1 product. Interestingly, this mutation is identical with the most frequent point mutation associated with the Denys-Drash syndrome. However, the classical triad of Denys-Drash syndrome does not apply to this patient. This is in the first report of the point mutation in the zinc finger domain of both WT1 alleles in a sporadic unilateral WT without genitourinary abnormalities, and the mutation suggests that some sporadic WTs carry the Denys-Drash WT1 mutations

Development of Safety Measures of Bicycle Trafflc by Observation wffh Deep-Leamlng, Drive Recorder Data, Probe Blcycle wlth LIDAR, and Connected Simulators

This research outlines the development of evaluating safety measures for bicycle traffic using state-of-the-art technology, which was started since 2020 as a four-year project. The project is funded by the Commission on Advanced Road Technology in the Ministry of Land, Infrastructure, Transport and Tourism(MLIT). While Japan has a high bicycle modal share of 12% (2010), bicycle-related fatalities are relatively high among other countries in the IRTAD database (2019). Under these circumstances, since 2007, various measures for bicycle traffic measures have been implemented to improve the safe bicycle traffic environment, including the revision of the Road Traffic Act and the formulation of a national plan to promote bicycle use. However, serious accidents involving bicycles are remained in some specific cases. According to the government's traffic accident analysis results (2019), right-hook crash at signalized intersections are one of the most serious types of collision involving bicycles, along with accidents at unsignalized intersections involving vehicles turning left, rear-end collisions, and single vehicle accidents due to off-road deviation. In particular, proactive safety measures are required at signalized intersections along arterial roads, where electric personal mobility vehicles traveling at speeds of up to 20 km/h are expected to share with bicycles in the future. In order to evaluate safety measures for bicycle-vehicle crashes, this project set the following goals. 1) Identify factors influencing near-miss incidents and collisions through analysis of drive recorder data and accident statistical data. 2) Detailed analysis of traffic conditions from the cyclist's perspective using a probe bicycle equipped with a LiDAR sensor. 3) Development of an experimental environment using a connected simulator for evaluation of cooperative driving behavior. 4) Clarification of experimental conditions to evaluate different scenarios and conditions with and without intervention. 5) Proposal of effective interventions to improve crash cases based on experiments