Yang Shao

Fragmentation in road networks and hierarchical imbalances among nodes increase circulation impedance in China’s county-level delivery networks, hindering efficient county–township–village circulation. This study integrates spatial syntax, complex network analysis, hierarchical connection-cost analysis, and a coupling–coordination degree model to develop a network evaluation framework for identifying structural bottlenecks and analyzing circulation efficiency. Using eight counties in Shaanxi Province as empirical cases, we quantify road-network accessibility using a spatial syntax axial model and examine hierarchical node organization across county, township, and village tiers using complex network indicators. Network-level circulation efficiency is analyzed using road accessibility, hierarchical connection costs, county–village connection impedance, and average path length. Correlation and regression analyses are further used to examine the relationship between morphology–structure coordination and network impedance. The results show that higher road-network integration is generally associated with lower hierarchical connection costs, and higher morphology–structure coordination is significantly associated with lower county–village connection impedance and shorter average path length. The proposed network-level evaluation framework provides a structural basis for identifying accessibility deficiencies, hierarchical connectivity constraints, and morphology–structure mismatches, thereby informing efforts to reduce circulation impedance in county–township–village delivery networks.

Cross-border multimodal transportation systems are essential for regional connectivity, yet their structural concentration, modal imbalance, community organization, and accessibility differentiation remain insufficiently understood from an entropy perspective. Based on 2024 data, this study constructs railway, highway, aviation, and integrated transportation networks between Western China and the five Central Asian countries. It integrates complex network analysis, structural entropy, modal diversity entropy, Louvain community detection, and accessibility assessment within a structure–organization–function framework. The results reveal a core–periphery pattern, with Xi’an, Urumqi, Almaty, and Tashkent serving as hubs. Structural entropy shows that highway connections are balanced, aviation links are concentrated around core hubs, and the integrated network reflects the coexistence of core-hub agglomeration and multimodal coverage expansion. Modal diversity entropy indicates that high connectivity does not necessarily imply balanced modal configuration, and 41.8% of nodes remain dependent on a single mode. Community detection reveals local cohesion and global segmentation, while accessibility analysis identifies a Western China core and Central Asian periphery. Sensitivity analyses based on common-node normalization, travel-time weighting, and alternative modal weights confirm the robustness of the findings. These results provide an integrated diagnostic framework for identifying structural concentration, modal imbalance, and accessibility inequality in cross-border multimodal transportation networks.

This study examines the application of large language models (LLMs) in analyzing subjective driver perceptions during tunnel driving simulations, comparing the effectiveness of questionnaires and interviews. Building on previous research involving driver simulations, we recruited 29 new participants, collected their perceptions via questionnaires, and conducted follow-up interviews. The interview data were analyzed using three LLMs: GPT-3.5, GPT-4, and Google-Gemini. The results revealed that while GPT-4 provides more in-depth and accurate analysis, it is significantly slower than GPT-3.5. Conversely, Google-Gemini demonstrated a balance between analysis quality and speed, outperforming the other models overall. Despite the challenge of occasional misunderstandings, LLMs still have the potential to enhance the efficiency and accuracy of subjective data analysis in transportation research.

Scientifically evaluating net carbon dioxide (CO₂) emissions is the pivotal strategy for mitigating global climate change and fostering sustainable urban development. Shaanxi Province is situated in central China, and boasts robust energy resources in the north and a significant carbon-sink zone in the southern Qinling Mountains. Therefore, uncovering the spatial distributions of net CO₂ emissions and identifying its influencing factors across cities in Shaanxi Province would furnish a crucial theoretical foundation for advancing low-carbon development strategies. In this research, the net CO₂ emissions of cities in Shaanxi Province from 2005 to 2020 are calculated using the carbon-emission-factor calculation model, then the Geodetector is utilized to evaluate the single-factor explanatory power and two-factor interactions among the fourteen various influencing variables, and then the spatial econometric model is employed to analyze the spatial spillover effects of these key factors. The results show the following: (1) The net CO₂ emissions present significant regional differences among the ten cities of Shaanxi Province, notably Xi’an City, Yulin City, and Weinan City, which have recorded remarkable contributions with the respective totals reaching 72.2593 million tons, 76.3031 million tons, and 58.1646 million tons. (2) Regarding temporal trend changes, the aggregate net CO₂ emissions across whole province underwent a marked expansion from 2005 to 2019. Yulin City and Shangluo City exhibit remarkable surges, with respective average annual growth rates soaring at 7.38% and 7.39%. (3) From the perspective of influencing factors, GDP exhibits the most pronounced correlation spanning the entire province. Meanwhile, foreign investment emerges as a significant contributor specifically in Xi’an and Yulin City. Moreover, interaction detection reveals most factor combinations exhibit bi-enhancement, while a few exhibits intricate and non-linear enhancement. (4) The SDM regression and fixed-effect analysis reveal that city GDP had a positive spillover effect on neighboring cities’ net CO₂ emission, while investment in scientific research and technology services, along with per capita construction land, exhibit notable negative spillovers, suggesting potential emission reduction benefits across cities.

Reducing urban transportation carbon emissions is a fashionable task around the globe. Electric cars, fuel cell cars, hydrogen cars, restriction policies, etc. are all aimed at this goal. But they are all expensive to make them into reality. Transportation management can also provide some contribution to this, like optimizing operation rules such as Left-turn Waiting Area Twice Startup. From the stop line to the Left-turn Waiting Area (LWA), one vehicle will start twice with more emissions due to the engine’s inefficient operating range. We proposed an Accurate Left-turn One-time Startup Model (ALOSM) based on the LWA rule, which includes the intersection geometry parameters, traffic light timing schemes, vehicle start speeds, vehicle operation speeds, and fuel vehicle ratios. Make the Left-turn Vehicle (LV) waiting behind the stop line during the through vehicle light green. Calculate the left-turn green light adjustment duration and make the LV and the last through vehicle across at one moment. With real collected data in a symbolic intersection in Xi’an, China, the simulation result shows vehicle emission would be reduced by 13% and traffic efficiency would increase by 5% in this single intersection. The whole city of 5 million vehicles would reduce 2,087.88kg CO emission in one day due to estimation.

The connectivity of the urban public transport network and the convenience of transfers between modes of transit are important factors that affect whether passengers choose public transport. Identifying the key nodes that affect network connectivity, direct access, transfers, and clarifying the main factors that restrict the network efficiency play important roles in improving the efficiency of the public transport network and establishing a “green city”. On this premise, this paper constructs two single-layer networks and a composite network that can reflect the transfer relationship between ‘bus–bus’, ‘metro–metro’, and ‘metro–bus’ based on the method of Space-P. The composite network realizes the integration study of homogeneous and heterogeneous stops, lines, and transfer relationships in the public transport network. At the same time, five kinds of centrality indexes are applied to the transport transfer network, and the significance of these indexes in the network is explained. Through the comprehensive analysis of these five types of indexes, the key nodes affecting the network connectivity, direct access and transfer efficiency, can be identified more accurately. Taking the public transport network of Xi’an as an example, the structural characteristics of the networks, including scale-free and small-world characteristics, were empirically analyzed. The main stops that play important roles in networks were identified based on the integrated centrality, degrees, and weight degrees. The research results showed the following: (1) Xi’an’s metro network, bus network, and metro–bus composite network all have scale-free and small-world characteristics. (2) The influence of the key stops of the metro network is concentrated, while the influence of the key stops of the bus network is scattered. (3) The public transport network in the first ring road area of Xi’an has the highest degree of direct access, and the core areas of the south, west, and north of Xi’an also have high direct access. However, the direct access in the area east of Xi’an is slightly lower. (4) Xi’an’s bus transport network covers a large area, showing the characteristics of a dual-core “central + southern” network. (5) The metro–bus composite network demonstrates a closer connection between stops and a more balanced network. (6) Finally, the degree of direct access to stops in the bus transport network and metro transport network shows the characteristics of “the single core is dominant, and the circle diffusion weakens step by step”.

With the continuous construction of transportation infrastructure, intersection nodes have been increasing rapidly, bringing growing numbers of tunnel- and exit-adjacent sections (TEAS) in mountain expressways in China. With the complex variation in the surrounding environment, drivers always face congestion and confusion on tunnel and the exit connecting sections (TECS) without adequate length, meanwhile excessively long TECS create detours. To better provide a sustainable design strategy for TEAS, based on a certain section of expressway in Shaanxi, China, this paper establishes a theoretical calculation model through analysis. The characteristics of traffic flow and drivers’ light adaptation at tunnel exit are obtained through data collection and driving tests, and the length requirements of the tunnel and exit connecting sections (TECS) are discussed. A VISSIM microscopic simulation model is also built under various design schemes and entropy-based multi-attribute decision making (EBMADM) is used to objectively calculate the weights of the four selected evaluation indexes. Then, the design schemes of the TECS with different lengths have been comprehensively evaluated. The results show the match between the evaluation results of EBMADM with theoretical calculations under existing traffic conditions, which proves the rationality of EBMADM in such problems. For more cases, the results of the EBMADM evaluation show a positive correlation between the length of TECS for the best performing design scheme with traffic volume and diverging ratio.

Background: A consensus exists that the first author and corresponding author make the most contribution to the publication of an article. The Y-index has been proposed to assess the scientific achievements of authors, institutions, and countries/regions (AIC/R for short) based on the number of first-author publications (FPs) and corresponding-author publications (RPs). Nonetheless, the Y-index is defined in terms of count and radian (represented by j and h) instead of using the relative radius and angle degree to simplify understanding. In the literature, a method for drawing radar diagrams online with the Y-index is also lacking. This study was conducted to enhance the Y-index with an additional relative radius denoted by k and the angle degree represented by h* (named Yk-index), include easy-to-use features (e.g., copying and pasting) for the delivery of the online Radar-Yk, and identify which one of AIC/R contributed the most to a scientific journal. Methods: From the Web of Science (WoS) database, we downloaded 9498 abstracts of articles published in the journal of Medicine (Baltimore) in 2020 and 2021. Three visual representations were used, including a Sankey diagram, a choropleth map, and a radar diagram, to identify the characteristics of contributions by AIC/R to Medicine (Baltimore) using the Yk-index (j, k, h*). A demonstration of Rada-Yk with easy-to-use features was given using the copy-and-paste technique. Results: We found that Qiu Chen (China), Sichuan University (China), China, and South Korea (based on regions, e.g., provinces/metropolitan areas in China) were the most productive AIC/R, with their Yk equal to 27,715, 12415.1, and 2045, respectively; a total of 85.6% of the published articles in Medicine (Baltimore) came from the 3 countries (China, South Korea, and Japan); and this method of drawing the Radar-Yk online was provided and successfully demonstrated. Conclusion: A breakthrough was achieved by developing the online Radar-Yk to show the most contributions to Medicine (Baltimore). Visualization of Radar-Yk could be replicated for future academic research and applications on other topics in future bibliographical studies.

As the number of vehicles continues to grow in China, the problem of urban traffic congestion gets more serious, particularly at intersections. As a new type of unconventional intersection, the displaced left-turn (DLT) intersection has been widely recognized to improve the efficiency of intersections with heavy left-turn traffic flows. Converting an existing intersection into an intersection with additional DLT lanes is a valuable solution. However, the studies on DLT intersections mainly focus on performance, applicability, and safety. The guidelines on the specific engineering design process mostly come from experience, and the study on the considering multifactor design method is still insufficient. Therefore, this paper proposed an evaluation and analysis model of the lengths of added DLT lanes based on the entropy evaluation method, in which VISSIM and Surrogate Safety Assessment Model (SSAM) software were adopted for simulation. A design process for the length of the added DLT lanes was proposed with this model. An urban intersection in Xi’an was taken as a case study, and the application of the model and the design process was studied in detail. After selecting four evaluation indicators, the model was applied to calculate and analyze the optimal length of the added DLT lanes under 45 different traffic volume combinations. The recommended lengths of different situations were within the range recommended in the guidebook published by Federal Highway Administration. The results of the case study proved that the model proposed in this paper was advanced, reasonable, and practical.

As an unconventional design to alleviate the conflict between left-turn and through vehicles, Continuous Flow Intersection (CFI) has obvious advantages in improving the sustainability of roadway. So far, the design manuals and guidelines for CFI are not enough sufficient, especially for the displaced left-turn lane length of CFI. And the results of existing research studies are not operational, making it difficult to put CFI into application. To address this issue, this paper presents a methodological procedure for determination and evaluation of displaced left-turn lane length based on the entropy method considering multiple performance measures for sustainable transportation, including traffic efficiency index, environment effect index and fuel consumption. VISSIM and the surrogate safety assessment model (SSAM) were used to simulate the operational and safety performance of CFI. The multi-attribute decision-making method (MADM) based on an entropy method was adopted to determine the suitability of the CFI schemes under different traffic demand patterns. Finally, the procedure was applied to a typical congested intersection of the arterial road with heavy traffic volume and high left-turn ratio in Xi’an, China, the results showed the methodological procedure is reasonable and practical. According to the results, for the studied intersection, when the Volume-to-Capacity ratio (V/C) in the westbound and eastbound lanes is less than 0.5, the length of the displaced left-turn lanes can be selected in the range of 80 to 170 m. Otherwise, other solutions should be considered to improve the traffic efficiency. The simulation results of the case showed CFI can significantly improve the traffic efficiency. In the best case, compared with the conventional intersection, the number of vehicles increases by 13%, delay, travel time, number of stops, CO emission, and fuel consumption decrease by 41%, 29%, 25%, 17%, and 17%, respectively.