Japan Automobile Research Institute

自動車の電動化や通信技術の進展等に伴い，運転中における情報提示の多様化が予想される．本研究では，一定時間の中で情報が変化する動画の特性に着目し，運転中の動画提示がドライバの運転に及ぼす影響を運転シミュレータ実験によって調べた．24名の一般ドライバを対象に「31文字以上静止画」，「文字スクロール動画」，「短時間繰り返し動画」の各タスク難易度2水準と，「情報提示なし」について，視認行動，運転挙動および主観的不安感を調べた．実験の結果，静止画に対して，動画の特性を有する文字スクロール動画では，1回の視認時間は短いものの，何度も繰り返し視認するため総視認時間が長くなる傾向がみられ，タスク難易度によらず運転への影響が大きいことが明らかになった．したがって，少ない情報を対象に表示時間自体を短くすることで，総視認時間を抑制できるような配慮による，視覚的なディストラクション対策が考えられる．一方，動画の特性を抑制した短時間繰り返し動画は，静止画と同様タスク難易度による影響が大きいことから，記憶操作や保持をさせず容易に情報が取得できる工夫が重要と示唆された．

Gaseous air pollutants emitted primarily by anthropogenic sources form secondary products through photochemical reactions, complicating the regulatory analysis of anthropogenic emissions in the atmosphere. We used an environmental chassis dynamometer and a photochemical smog chamber to conduct a parameter sensitivity experiment to investigate the formation of secondary products from a gasoline passenger car. To simulate the mitigation of ammonia emissions from gasoline vehicle exhausts assuming future emission controls and to allow photochemical oxidation and aging of the vehicle exhaust, ammonia was selectively removed by a series of five denuders installed between the vehicle and photochemical smog chamber. Overall, there were no differences in the formation of secondary organic aerosols and ozone with or without ammonia mitigation. However, the potential for ammonium nitrate particle formation was significantly reduced with ammonia mitigation. In addition, ammonia mitigation resulted in increased aerosol acidity due to nitric acid in the gas phase not being neutralized by ammonia and condensing onto the liquid particle phase, indicating a potentially important secondary effect associated with ammonia mitigation. Thus, we provide new insights into the effects of ammonia mitigation on secondary emissions from gasoline vehicle exhaust and into a potentially useful experimental approach for determining primary and secondary emissions.

BackgroundOne of the most cost-effective measures to prevent road traffic deaths is to enforce the vehicle safety standards recommended by the UN World Forum for Harmonization of Vehicle Regulations and related UN conventions. In Mexico, new, improved vehicle safety standards were approved in 2022. However, they did not include front/end vehicle designs for pedestrian protection and advanced driver assistance features for collision avoidance, such as the autonomous emergency braking system (AEBS). These features are critical, considering that approximately 63% of road traffic deaths involve vulnerable road users (i.e., pedestrians, cyclists, and motorcyclists). A lack of robust country-specific evidence on the cost-effectiveness and potential public health impact of full implementation of vehicle safety standards has limited local road safety advocacy efforts.ObjectiveThis study aims to estimate the potential public health and economic impact of increasing the availability of proven vehicle safety technologies in Mexico.MethodsThis study applied a comparative risk assessment approach. First, we estimated road traffic deaths and injuries in Mexico in 2019 to calculate the Disability-adjusted life years (DALYs) lost and the overall economic burden of traffic-related mortality and morbidity. Second, we searched the literature to obtain the expected relative reductions in deaths and injuries associated with anti-lock braking systems (ABS), electronic stability control (ESC), seatbelts, frontal and side airbags, side structure and padding, child restraint systems, crashworthiness, motorcycle helmets, and AEBS. Simultaneously, we estimated the technology penetration and use in the current and new vehicle fleet. Then we used a counterfactual analysis to assess the expected reduction in deaths, DALYs, and economic cost if all cars had these technologies and all road users used protective technologies.Expected ResultsResults on number of averted deaths, DALY’s and costs associated with improving vehicle safety standards in Mexico are expected by July 2024. Based on previous evidence, it is anticipated that between 25% and 50% of road traffic deaths can be avoided by complying with UN vehicle safety standards.ConclusionsThese findings will contribute to the technical arguments to upgrade current Mexican regulations to international standards.

Abstract The computational balance between the model grid resolution and the complexity of the data assimilation technique is essential for accurate aerosol forecasting and obtaining aerosol reanalysis data sets. This study aimed to develop a high‐resolution aerosol assimilation system. A 2‐dimensional variational method (2DVar) was implemented in a non‐hydrostatic icosahedral atmospheric model (NICAM). This new model (NICAM/2DVar), with a global grid size of 56 km, assimilated the observed aerosol optical depth (AOD) that is estimated by combining multiple products of geostationary and polar‐orbital satellites. The model results were evaluated against ground‐based AOD observations on a global scale. They exhibited higher correlations, lower uncertainties, and lower biases than those obtained without the 2DVar. The model also reproduced the observed surface aerosols (PM2.5) mass concentrations, especially in Kyushu, Japan. This occurred because the satellite‐estimated AODs over ocean close to air pollution sources were obtained for many occasions. The correlation coefficient values against the PM2.5 observations increased from 0.44 to 0.65 compared to the results without the 2DVar. The impact of the 2DVar on the forecast results was investigated, and the forecast values for 2–3 days were improved. Because satellite‐retrieved AODs are often lacking over land owing to retrieval difficulties, the use of ground‐based AODs in assimilations is essential for precise processing the of aerosol reanalysis data sets. The computational cost with the use of the 2DVar was only 0.6% more than that without its use. Thus, aerosol assimilation using the NICAM/2DVar can be realistically extended to finer grid sizes.

This study takes a fresh perspective by focusing on the drivers of surrounding cars near to level 3 automated vehicles (AVs). We advocates for level 3 AVs using an external human-machine interface (eHMI) to provide high-risk warning information to drivers of surrounding cars during AVs issuing a request-to-intervene (RtI). Through a driving simulator-based subjects experiments, we have established that the proposed eHMI can assist the surrounding MV’s driver in better comprehending the AV’s driving intentions and predicting its driving behavior. This leads to increased the surrounding MV’s driver confidence in handling potential risks from the AV during the take-over period. Although we did not observe a significant impact of the proposed eHMI on the driving behavior of the MV drivers, i.e. participants, they reported a greater willingness to have AVs equipped with the proposed eHMI drive around them in their daily life.

With a large number of fatalities reported over the years, traffic congestion and road safety have been major concerns all over the world. To address these issues and improve driving comfort and safety, this research proposes a vehicle control model based on typical human driving behaviors. Specifically, the focus is on developing an Artificial Neural Network (ANN) model for guidance during cornering and emergency collisions. The proposed ANN model takes three significant inputs—relative distance, yaw rate, and relative velocity—in order to simulate steering based on human driving behavior. Through extensive simulations, a total of 36 drivers successfully executed the driving task, and the ANN-based steering model demonstrated a close resemblance to human drivers’ responses in emergency situations. The results highlight the accuracy of the predicted steering angle, with the optimal number of neurons located at the 17<sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">th</sup> neuron with the lowest RMSE. These findings showcase the potential of a guidance system to replicate human behavior while averting potential dangers. This research contributes to the advancement of driver assistance systems or automated driving systems, laying the groundwork for future enhancements in driving safety and comfort, particularly for emergency maneuvers.

Iron (Fe), the main component of non-exhaust particulates, is known to have variable health effects that depend on the chemical species of iron. This study characterized the possible contribution of iron oxides and hydroxides to airborne brake wear particles under realistic vehicle driving and braking conditions with different brake pad friction materials. We found significant differences in wear factors and PM10 and PM2.5 emissions between non-asbestos organic (NAO) and European performance (ECE) brake pads. Iron was the dominant contributor to PM10 and PM2.5 brake wear particles for both NAO and ECE. The iron concentration ratio in the particle mass (PM) was comparable to the disc-to-pads ratio measured by wear mass. The fact that magnetite, which is of interest with respect to health effects, was less abundant in NAO than in ECE suggested that tribo-oxidations occurred in NAO. Metallic iron is generated not only from abrasive wear but also from tribo-chemical reduction with magnetite as the starting material. We found that there were differences in PM emissions between brake friction materials, and that the phase transformations of iron differed between friction materials. These differences were apparent in the distribution of iron oxides and hydroxides. Heat, tribo-oxidation, and tribo-reduction are intricately involved in these reactions.

<strong class="journal-contentHeaderColor">Abstract.</strong> This study, performed under the umbrella of the Task Force on Hemispheric Transport of Air Pollution (TF-HTAP), responds to the need of the global and regional atmospheric modelling community of having a mosaic emission inventory of air pollutants that conforms to specific requirements: global coverage, long time series, spatially distributed emissions with high time resolution, and a high sectoral resolution. The mosaic approach of integrating official regional emission inventories based on locally reported data, with a global inventory based on a globally consistent methodology, allows modellers to perform simulations of a high scientific quality while also ensuring that the results remain relevant to policymakers. HTAP_v3, an ad-hoc global mosaic of anthropogenic inventories, has been developed by integrating official inventories over specific areas (North America, Europe, Asia including Japan and Korea) with the independent Emissions Database for Global Atmospheric Research (EDGAR) inventory for the remaining world regions. The results are spatially and temporally distributed emissions of SO₂, NO_x, CO, NMVOC, NH₃, PM₁₀, PM_2.5, Black Carbon (BC), and Organic Carbon (OC), with a spatial resolution of 0.1 x 0.1 degree and time intervals of months and years covering the period 2000&ndash;2018 (DOI <a href="http://dx.doi.org/10.5281/zenodo.7516361" target="_blank" rel="noopener">10.5281/zenodo.7516361</a>, <a href="https://edgar.jrc.ec.europa.eu/dataset_htap_v3" target="_blank" rel="noopener">https://edgar.jrc.ec.europa.eu/dataset_htap_v3</a>). The emissions are further disaggregated to 16 anthropogenic emitting sectors. This paper describes the methodology applied to develop such an emission mosaic, reports on source allocation, differences among existing inventories, and best practices for the mosaic compilation. One of the key strengths of the HTAP_v3 emission mosaic is its temporal coverage, enabling the analysis of emission trends over the past two decades. The development of a global emission mosaic over such long time series represents a unique product for global air quality modelling and for better-informed policy making, reflecting the community effort expended by the TF-HTAP to disentangle the complexity of transboundary transport of air pollution.