In response to the demand for high-density urban renewal and quality enhancement, the microclimate of street canyon spaces has become a critical factor influencing pedestrian experience and public space vitality. As key nodes connecting above-ground and underground spaces, the entrances and exits of underground commercial streets are particularly sensitive to temperature, humidity, and wind conditions. This study examined a semi-open street canyon adjacent to Entrance No. 11 of the Jianjun Road Underground Commercial Street in Yancheng City as a case study. Through continuous field measurements and numerical simulations using ENVI-met v5.5.1, we conducted a comprehensive analysis. Five monitoring points were established at a height of 1.5 m to simultaneously record the air temperature, relative humidity, wind speed, and thermal radiation images. The results indicate that ventilation acceleration zones form near openings and channel constrictions, whereas leeward sides and corners are prone to stagnant airflow and heat accumulation. During afternoon periods with strong solar radiation and low wind speeds, the predicted mean vote (PMV) values near the entrance increased significantly. The simulation results were in good agreement with the field observations in terms of both the trend and spatial distribution. On the basis of these findings, optimization strategies are proposed including controlling enclosure ratios and local height-to-width ratios, utilizing ventilation corridors and side openings to guide airflow, and incorporating shading devices and low-emissivity materials to improve pedestrian thermal comfort and accessibility.

In response to the demand for high-density urban renewal and quality enhancement, the microclimate of street canyon spaces has become a critical factor influencing pedestrian experience and public space vitality. As key nodes connecting above-ground and underground spaces, the entrances and exits of underground commercial streets are particularly sensitive to thermal, humidity, and wind conditions. This study examines a semi-open street canyon adjacent to Entrance No. 11 of the Jianjun Road Underground Commercial Street in Yancheng City as a case study. Through continuous field measurements and numerical simulations using ENVI-met v5.5.1, we conducted a comprehensive analysis. Five monitoring points were established at a height of 1.5 m to simultaneously record the air temperature, relative humidity, wind speed, and thermal radiation images. The results indicate that ventilation acceleration zones form near openings and channel constrictions, whereas leeward sides and corners are prone to stagnant airflow and heat accumulation. During afternoon periods with strong solar radiation and low wind speeds, the predicted mean vote (PMV) values near the entrance increase significantly. The simulation results are in good agreement with the field observations in terms of both the trend and spatial distribution. On the basis of these findings, optimization strategies are proposed, including controlling enclosure ratios and local height-to-width ratios, utilizing ventilation corridors and side openings to guide airflow, and incorporating shading devices and low-emissivity materials to improve pedestrian thermal comfort and accessibility.

Time headway is a key parameter for describing car-following behavior and microscopic traffic flow characteristics, and it is important for traffic safety analysis, road design, and optimizing intelligent-driving strategies. Existing research offers limited insight into the heterogeneity of time headway under different vehicle types and lane conditions. It is particularly important to investigate how time headway distributions differ across lane–vehicle-type combinations on highways, as these differences can affect safety evaluation and operational performance. This study is based on drone-captured vehicle trajectories from the publicly available HighD dataset. We select 378,751 vehicle–frame trajectory records; these records are used to construct valid follower–leader pairs and derive time headway (THW) samples for distribution fitting. Eight subsets are formed by combining two lane positions (inner vs. outer) and four follower–leader vehicle-type pairs (car–car, car–truck, truck–car, truck–truck). Six candidate distributions (Lognormal, Log-logistic, Burr, Weibull, Gamma, and Logistic) are fitted using maximum likelihood estimation, and their fit is evaluated using Kolmogorov–Smirnov, Anderson–Darling, and Chi-square tests, which are fused via an entropy-weighted composite score for model ranking. Results show pronounced heterogeneity across lane–vehicle-type subsets: Inner-lane samples exhibit smaller and more concentrated time gaps, whereas outer-lane samples show larger mean gaps, stronger dispersion, and heavier upper tails. Overall, Lognormal(3P) is selected as the top-ranked model in 5 of 8 subsets (62.5%), while Burr(4P) (car–truck, outer lane), Gamma(3P) (truck–car, outer lane), and Weibull(3P) (truck–truck, inner lane) are optimal in the remaining subsets. These findings indicate that lane position and vehicle-type pairing materially affect THW distributional characteristics, providing quantitative guidance for lane- and vehicle-aware traffic modeling, safety-oriented assessment, and intelligent-driving strategy design.

Against the backdrop of low-carbon transportation and urban logistics transformation, metro-based freight is regarded as an important pathway for emission reduction. This paper constructs a tripartite evolutionary game model involving the government, logistics enterprises, and metro operators, and analyzes multi-agent strategy evolution and the influence of key parameters using replicator dynamics equations and numerical simulation. The results show that well-designed subsidies and penalties can effectively promote a stable state characterized by “active government intervention, active response from logistics enterprises, and low-carbon integrated passenger and freight transportation by metro operators”. Reducing the cost of transformation can improve evolutionary efficiency, while excessively high subsidies may weaken the government’s willingness to intervene. This study provides insights for optimizing low-carbon transportation policies and supporting the development of metro-based freight systems.