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Perception has been identified as the main cause underlying most autonomous vehicle related accidents. As the key technology in perception, deep learning (DL) based computer vision models are generally considered to be black boxes due to poor interpretability. These have exacerbated user distrust and further forestalled their widespread deployment in practical usage. This paper aims to develop explainable DL models for autonomous driving by jointly predicting potential driving actions with corresponding explanations. The explainable DL models can not only boost user trust in autonomy but also serve as a diagnostic approach to identify any model deficiencies or limitations during the system development phase.

This paper proposes an explainable end-to-end autonomous driving system based on “Transformer,” a state-of-the-art self-attention (SA) based model. The model maps visual features from images collected by onboard cameras to guide potential driving actions with corresponding explanations, and aims to achieve soft attention over the image’s global features.

The results demonstrate the efficacy of the proposed model as it exhibits superior performance (in terms of correct prediction of actions and explanations) compared to the benchmark model by a significant margin with much lower computational cost on a public data set (BDD-OIA). From the ablation studies, the proposed SA module also outperforms other attention mechanisms in feature fusion and can generate meaningful representations for downstream prediction.

In the contexts of situational awareness and driver assistance, the proposed model can perform as a driving alarm system for both human-driven vehicles and autonomous vehicles because it is capable of quickly understanding/characterizing the environment and identifying any infeasible driving actions. In addition, the extra explanation head of the proposed model provides an extra channel for sanity checks to guarantee that the model learns the ideal causal relationships. This provision is critical in the development of autonomous systems.

The anticipated benefits of connected and autonomous vehicles (CAVs) include safety and mobility enhancement. Small headways between successive vehicles, on one hand, can cause increased capacity and throughput and thereby improve overall mobility. On the other hand, small headways can cause vehicle occupant discomfort and unsafety. Therefore, in a CAV environment, it is important to determine appropriate headways that offer a good balance between mobility and user safety/comfort.

In addressing this research question, this study carried out a pilot experiment using a driving simulator equipped with a Level-3 automated driving system, to measure the threshold headways. The Method of Constant Stimuli (MCS) procedure was modified to enable the estimation of two comfort thresholds. The participants (drivers) were placed in three categories (“Cautious,” “Neutral” and “Confident”) and 250 driving tests were carried out for each category. Probit analysis was then used to estimate the threshold headways that differentiate drivers' discomfort and their intention to re-engage the driving tasks.

The results indicate that “Cautious” drivers tend to be more sensitive to the decrease in headways, and therefore exhibit greater propensity to deactivate the automated driving mode under a longer headway relative to other driver groups. Also, there seems to exist no driver discomfort when the CAV maintains headway up to 5%–9% shorter than the headways they typically adopt. Further reduction in headways tends to cause discomfort to drivers and trigger take over control maneuver.

In future studies, the number of observations could be increased further.

The study findings can help guide specification of user-friendly headways specified in the algorithms used for CAV control, by vehicle manufacturers and technology companies. By measuring and learning from a human driver's perception, AV manufacturers can produce personalized AVs to suit the user's preferences regarding headway. Also, the identified headway thresholds could be applied by practitioners and researchers to update highway lane capacities and passenger-car-equivalents in the autonomous mobility era.

The study represents a pioneering effort and preliminary pilot driving simulator experiment to assess the tradeoffs between comfortable headways versus mobility-enhancing headways in an automated driving environment.

This paper aims to present a method of optimal singularity-free motion planning under multiple objectives and multiple constrains for the 6-DOF parallel manipulator, which is used as an execution mechanism for the automated docking of components.

First, the distribution characteristics of the Jacobian matrix determinant in local workspace are studied based on the kinematics and a sufficient and necessary condition of singularity-free path planning in local workspace is proposed. Then, a singularity-free motion path of the end-effector is generated by a fifth-order B-spline curve and the corresponding trajectories of each actuator are obtained via the inverse kinematics. Finally, several objective functions are defined to evaluate the motion path and an improved multi-objective particle swarm optimization algorithm-based on the Pareto archive evolution is developed to obtain the optimal singularity-free motion trajectories.

If the initial pose and the target pose of the end-effector are both singularity-free, a singularity-free motion path can be planned in the local workspace as long as all the values of each pose elements in their own directions are monotonous. The improved multi-objective particle swarm optimization (IMPSO) algorithm is effective and efficient in the optimization of multi-objective motion planning model. The optimal singularity-free motion path of the end-effector is verified in the component docking test. The docking result is that the movable component is in alignment with the fixed one, which proves the feasibility and practicability of the proposed motion path method to some extent.

The proposed method has a certain novelty value in kinematic multi-objective motion planning of parallel manipulators; it also increases the application prospect of parallel manipulators and provides attractive solutions to component assembly for those organizations with limited cost and that want to find an option that is effective to be implemented.

This study aims to investigate the morphology and physicochemical properties of BiOBr/Polyvinylidene fluoride (PVDF) composite membranes and the differences in the properties of BiOBr/PVDF composite membranes made by adding different precursor ratios during the casting process.

In this paper, sodium bromide and Bi(NO3)3 were used as precursors for the preparation of BiOBr photocatalysts, and PVDF membranes were modified by using the phase conversion method in conjunction with the in situ deposition method to produce BiOBr/PVDF hydrophilic composite membranes with both membrane separation and photocatalytic capabilities.

The characterization results confirmed that the composites were successfully and homogeneously co-mingled in the PVDF membranes. The related performance of the composite membrane was tested, and it was found that the composite membrane with the optimal precursor incorporation ratio had good photocatalytic efficiency and antipollution ability; the removal efficiencies of methyl orange, rhodamine B and methylene blue were 80.43%, 85.02% and 86.94%, respectively, in 2.5 h. The photocatalytic efficiency of composite membranes with different precursor ratios increased and then decreased with the increase of the precursor addition ratio.

The composite membrane is prepared by phase conversion method with in situ deposition method, and the BiOBr material has unique advantages for the degradation of organic dyes. The comprehensive experimental data can be known that the composite membrane prepared in this paper has high degradation efficiency and good durability for organic dyes.

This paper aims to examine Korean jewelry manufacturers operating in China to assess the relationship between their perceptions of external risks and their intentions to relocate. The authors hypothesize that foreign firms finding risk in the current external environment are more likely to consider moving their facilities outside China. In particular, this paper explores whether firm performance and technological capability moderate the relationship between perceived external risk and relocation intentions.

Korean jewelry manufacturers were among the first Korean firms entering China in the early 1990s to avoid Korea’s rising labor costs. After 20 years, they face similar external risks in China. The authors collected and analyzed 238 survey samples from Korean jewelry manufacturers operating in China to determine whether perceived external risks affect decisions to relocate. Logistic regression was used to examine the hypotheses. In addition to an empirical method, five case studies related to empirical results have been included.

Analysis results suggest that firms perceiving riskier managerial and competitive environments are more likely to have relocation intentions. Perceptions of risks from the governmental/political environment and macroeconomic environment have no significant relationship with relocation intentions. Also, firms’ performance and technological capability negatively moderate the relationship between perceptions of managerial competitive environment risks and relocation intentions.

This study contributes to the literature on international business relocation strategies by examining perceptions of external risks that determine whether foreign manufacturing firms will relocate. In addition, the research sheds light on the transformation of Chinese economics from labor-intensive to capital-, technological- and knowledge-intensive structures. By applying multi-methods, this research further elaborates empirical results with five case studies.

The purpose of this paper is to analyze the optimal competition or cooperation decision between technology service platforms and governments in the context of fierce competition within urban agglomerations.

Based on the cooperation and competition game model, this study builds a two-level model for government and technology service platforms considering three cases: perfect competition, platform cooperation and government-led cooperation.

By analyzing the optimal strategies of the government and a platform in three cases, the research shows that choosing appropriate cooperation in a competitive situation is beneficial to both the government and the platform. Government-led cooperation is conducive to increasing social welfare. From the perspective of the platforms, if they actively seek cooperation, they can obtain higher subsidies and profits. The more intense the competition is, the higher the profits and social welfare generated from the platforms' active cooperation.

The contribution of this study relates to the development of technology service platforms in urban agglomerations. As local governments and platforms continuously undertake decision-making processes, this study constructs quantitative models to analyze the advantages and disadvantages of competition and cooperation. It is worth noting that relying on government subsidies to maintain the sustainable development of technology service platforms is not a long-term solution. Government subsidies play a vital role in the initial development of technology service platforms. The analysis results are in line with Guo et al. (2016), Jung and Feng (2020) and Li (2021) conclusions. Furthermore, long-term government subsidies will make platforms dependent on these subsidies. These are the contributions to the scientific literature.

Instead of focusing on vertical relationships, this study emphasizes the horizontal cooperation and competition relationship between platforms and local governments in an urban agglomeration. Thus, the vertical effects of government subsidies on platforms can be investigated. Another innovation is the social welfare policy goal, which is an important index for the development of urban agglomerations.

The purpose of this paper is to reveal the unique thermal property of Mongolian clothing from the current western clothing and explain their environmental adaptation to the climate of Mongolian plateau in China.

Thermal insulation and the temperature rating (TR) of eight Mongolian robe ensembles and two western clothing ensembles were investigated by manikin testing and wearing trials, respectively. The clothing area factor (f_cl) of these Mongolian clothing was measured by photographic method and estimated equation from ISO 15831. Finally, the TR prediction model for Mongolian clothing was built and compared with current models for western clothing in ISO 7730 and for Tibetan clothing in previous article.

The results demonstrated that the total thermal insulation of Mongolian robe ensembles was much bigger than that of western clothing ensembles and ranged from 1.81clo to 3.11clo during the whole year. The f_cl of the Mongolian clothing should be determined by photographic method because the differences between these two methods were much bigger from 0.6 to 13.9 percent; the TR prediction model for Mongolian robe ensembles is TR=25.57−7.13Icl, which revealed that the environmental adaptation of Mongolian clothing was much better than that of western clothing and similar to that of Tibetan clothing.

The research findings give a detailed information about the thermal property of China Mongolian clothing, and explain the environmental adaptation of Mongolian clothing to the cold and changing climate.

This paper aims to introduce the history and major achievement of the Chinese private enterprise survey (CPES), which is one of the most enduring large-scale nationwide sample surveys in China, providing important micro firm-level data for understanding and studying the development of Chinese enterprises and entrepreneurs over the past 26 years.

The main body of this paper is based on a bibliometric analysis of all literature using CPES until 2017.

This paper discusses problems that users may encounter during data mining. By doing so, it can assist other researchers to get a better understanding of what has been done (e.g. journals, topics, scholars and institutions) and do their research in a more targeted way.

As members of the survey project team, the authors also take a prospect of the future data design and use, as well as offer some suggestions about how to use the CPES data to improve high-quality development and business environment evaluation in China.

This paper is the first to provide an overall picture of academic papers in China and abroad that have used the CPES data.

This chapter provides a thorough historical overview of policies that have governed and guided scientific research in China since 1949 and illustrates changes in scientific publications that accompanied these policy reforms and programs.

We divide this historical period into four stages, each with distinct R&D policies: (1) 1949–1955, a period of socialist transformation; (2) 1956–1965, a period of struggle for higher education and research development in a rapidly changing political environment; (3) 1966–1976, the lost decade of the Cultural Revolution; and (4) 1976–present, a period when major national policies have significantly promoted scientific research in China. We use the SPHERE project’s comprehensive historical dataset based on Thomson Reuters’ Web of Science and data from a set of research universities in China to analyze changes in scientific publication rates concurrent with these policy reforms and programs.

The analysis suggests a tight connection between national policy and scientific research productivity in higher education. The central government controlled scientific research through direct administration in early periods and has guided research activities through funding specific programs in recent decades. Due to their resource dependency on the central government, higher education institutions have been quite responsive to the common goals set by the central government. As a result, what is measured tends to be accomplished.

The chapter provides an in-depth description about the rise of higher education and science in China and produces recommendations for future development.

The type 120 emergency valve is an essential braking component of railway freight trains, but corresponding diaphragms consisting of natural rubber (NR) and chloroprene rubber (CR) exhibit insufficient aging resistance and low-temperature resistance, respectively. In order to develop type 120 emergency valve rubber diaphragms with long-life and high-performance, low-temperatureresistant CR and NR were processed.

The physical properties of the low-temperature-resistant CR and NR were tested by low-temperature stretching, dynamic mechanical analysis, differential scanning calorimetry and thermogravimetric analysis. Single-valve and single-vehicle tests of type 120 emergency valves were carried out for emergency diaphragms consisting of NR and CR.

The low-temperature-resistant CR and NR exhibited excellent physical properties. The elasticity and low-temperature resistance of NR were superior to those of CR, whereas the mechanical properties of the two rubbers were similar in the temperature range of 0 °C–150 °C. The NR and CR emergency diaphragms met the requirements of the single-valve test. In the low-temperature single-vehicle test, only the low-temperature sensitivity test of the NR emergency diaphragm met the requirements.

The innovation of this study is that it provides valuable data and experience for future development of type 120 valve rubber diaphragms.