Investigating the safety influence path of right-turn configurations on vehicle-pedestrian conflict risk at signalized intersections.

Right-turning vehicles and pedestrians share the right-of-way during the permitted signal phase at intersections in countries with right-handed traffic. Although right-turning vehicles are required to stop or yield to pedestrians according to the traffic rules, there still remains circumstances where the two will compete, posing significant safety risks to pedestrians. To investigate the impact mechanism of right-turn configurations, driver characteristics, and traffic operational features on vehicle-pedestrian conflict risk, a driving simulator experiment was conducted.

A Greedy Tabu Dual Heuristic algorithm for the cyclic pickup and delivery problem with 3D loading constraints.

The optimization of auto parts supply chain logistics plays a decisive role in the development of the automotive industry. To reduce logistics costs and improve transportation efficiency, this paper addresses the joint optimization problem of multi-vehicle pickup and delivery transportation paths under time window constraints, coupled with the three-dimensional loading of goods. The model considers mixed time windows, three-dimensional loading constraints, cyclic pickup and delivery paths, varying vehicle loads and volumes, flow balance, and time window constraints.

A parallel CNN architecture for sport activity recognition based on minimal movement data.

Novel Human Activity Recognition (HAR) methodologies, which are built upon learning algorithms and employ ubiquitous sensors, have achieved remarkable precision in the identification of sports activities. Such progress benefits all age groups of humanity, and in the future, AI will be used to address difficult problems in scientific research. A novel approach is introduced in this article to utilize motion sensor data in order to categorize and distinguish various categories of sports activities.

Evaluating spatial effect of transportation planning factors on taxi CO emissions.

In recent years, the impact of transportation activities on carbon (CO) emissions has gained global attention. In China, the severity of CO emissions from transportation is a pressing issue, necessitating the development of effective emission reduction strategies. This study uses taxi GPS data from Xi'an, China, to explore the spatial patterns and influencing factors of CO2 emissions.

Dynamic Response Mechanism of Bedding Slopes with Alternatively Distributed Soft and Hard Rock Layers Under Different Seismic Excitation Directions: Insights from Numerical Simulations.

The issue of slope stability in earthquakes has become increasingly prominent with the construction of many infrastructure projects such as highways, bridges, and tunnels. To explore the dynamic response characteristics of bedding rock slopes in an earthquake, the three-dimensional dynamic finite-difference method (TDD-FDM) in this study is used to establish simplified rock slope models, taking a bedding rock slope with alternatively distributed soft and hard rock layers in Yunnan, China as a prototype. The dynamic response mechanism of layered rock slopes containing different thicknesses, locations, and quantities of soft rock layers was studied under different excitation directions of seismic waves.

Strength Properties and Microscopic Experimental Study of Modified Sawdust Based on Solid Waste Synergistic Utilization.

Sawdust is the cutting tailings produced during stone processing, which is difficult to deal with and has a huge stock. Therefore, it is particularly important to enhance the comprehensive utilization of sawdust. The aim of this study was to synergistically utilize sawdust with other industrial wastes (fly ash, silt, and red mud), add cement as a curing agent to prepare modified sawdust, and analyze its performance through an unconfined compressive strength test, dry and wet cycle tests, and SEM.

Influence of Modified PVA Fiber on Ultra-High Performance Concrete and Its Enhancing Mechanism.

In this study, the properties of ultra-high-performance concrete (UHPC) were enhanced by adding modified polyvinyl alcohol (PVA) fibers. The specimens with different curing ages were evaluated in various aspects to investigate the effects of different dosages, lengths, and surface treatments of PVA fibers on the performance of UHPC. The performance was compared with that of steel fiber-reinforced UHPC with the same ratio and multiple dosages.

Does road environment aesthetics influence risky driving behavior of autonomous vehicles? An evaluation on road readiness using explainable machine learning and random parameters multinomial logit with heterogeneity.

Aesthetics has always been an advanced requirement in road environment design, because it can provide a pleasant driving experience and guide better driving behavior for human drivers. However, it remains unknown whether aesthetics-based road environment design also has an impact on autonomous vehicles (AVs), resulting in that current evaluation models on road readiness for AVs (RRAV) do not consider road environment aesthetics. Therefore, this study aims to explore the relationship between road environment aesthetics and risky driving behavior of AVs (RDBAV) and propose an RRAV evaluation model from the new perspective of road environment aesthetics.

Checkpoint data-driven GCN-GRU vehicle trajectory and traffic flow prediction.

With the development of information technology, massive traffic data-driven short-term traffic situation analysis of urban road networks has become a research hotspot in urban traffic management. Accurate vehicle trajectory and traffic flow prediction can provide technical support for vehicle path planning and road congestion warning. Unlike most studies that use GPS data to predict vehicle trajectories, this paper combines the broad coverage, high reliability, and lighter weight of traffic checkpoint data to propose a method that uses trajectory prediction technology to forecast the traffic flow in urban road networks accurately.

Assessment of the collision risk on the road around schools during morning peak period.

Road traffic injury is a leading cause of death among pupils worldwide, particularly around primary schools during rush hours, where heavy traffic, frequent parking, and unpredictable patterns increase accident risk. To mitigate these risks, this study employs the peak-over-threshold method with the generalized pareto distribution to evaluate the spatial-temporal collision risk near primary schools during rush hours. Specifically, the research quantifies collision risks spatially across different road segments (upstream, midstream, and downstream) and lanes (outside, middle, and inside).

V-FCW: Vector-based forward collision warning algorithm for curved road conflicts using V2X networks.

The implementation of advanced driver assistance systems (ADAS) has significantly impacted the prevention of traffic accidents, particularly through the forward collision warning (FCW) algorithm. Nevertheless, traffic conflicts on traffic routes remain a significant issue, since most FCW algorithms cannot accurately determine the distance between the host vehicle (HV) and remote vehicle (RV) on curved roads. Hence, this study proposes a vector-based FCW (V-FCW) algorithm to address the issue of false warnings on unconventional road sections.

Energy efficient strategy for heterogeneous truck platooning based on a non-uniform platooning model.

To investigate the energy-saving advantages of truck platoons, this study focused on two, three, and six-axle trucks as research subjects. A non-uniform platoon model of trucks was constructed based on braking performance differences. The aerodynamic characteristics of the non-uniform platoon fleet were analyzed in depth using numerical simulation methods, and the fuel consumption rate of the fleet was calculated.

Study on Springback Behavior in Hydroforming of Micro Channels for a Metal Bipolar Plate.

Bipolar plates are one of the most important components of proton exchange membrane fuel cells. With the miniaturization of bipolar plate flow channel sizes and the increasing demand for precision, springback has become a key focus of research in the bipolar plate forming process. In this paper, the hydroforming process for 316L stainless steel bipolar plates was studied, and an FEM model was built to examine the stress and strain at various locations on the longitudinal section of the plate.

Microstructural Evaluation and Linkage to the Engineering Properties of Metal-Ion-Contaminated Clay.

The rapid progress of urbanization and industrialization has led to the accumulation of large amounts of metal ions in the environment. These metal ions are adsorbed onto the negatively charged surfaces of clay particles, altering the total surface charge, double-layer thickness, and chemical bonds between the particles, which in turn affects the interactions between them. This causes changes in the microstructure, such as particle rearrangement and pore morphology adjustments, ultimately altering the mechanical behavior of the soil and reducing its stability.

Compressive behavior of elliptical concrete-filled steel tubular short columns using numerical investigation and machine learning techniques.

This paper presents a non-linear finite element model (FEM) to predict the load-carrying capacity of three different configurations of elliptical concrete-filled steel tubular (CFST) short columns: double steel tubes with sandwich concrete (CFDST), double steel tubes with sandwich concrete and concrete inside the inner steel tube, and a single outer steel tube with sandwich concrete. Then, a parametric and analytical study was performed to explore the influence of geometric and material parameters on the load-carrying capacity of elliptical CFST short columns. Furthermore, the current study investigates the effectiveness of machine learning (ML) techniques in predicting the load-carrying capacity of elliptical CFST short columns.

Numerical modeling the process of deep slab dehydration and magmatism.

This study uses a 2D high-resolution thermo-mechanical coupled model to investigate the dynamic processes of deep plate hydration, dehydration, and subsequent magmatic activity in ocean-continent subduction zones. We reveal the pathways and temporal evolution of water transport to the deep mantle during the subduction process. Plate dehydration plays a critical role in triggering partial melting of the deep mantle and related magmatic activity.

Land price, government debt, and land-use efficiency in the coastal cities of China under the constraint of land scarcity.

Land scarcity poses a significant challenge for coastal cities in supporting sustainable urban development. This study quantifies the Land Scarcity Index (LSI) for 51 Chinese coastal cities from 2008 to 2018, revealing a phased increase and a transition to high scarcity levels. The findings reveal significant differences in the land price dynamics and fragmentation between commercial-residential and industrial land plots.

Analyzing vehicle path optimization using an improved genetic algorithm in the presence of stochastic perturbation matter.

By analyzing the influence of stochastic perturbation matters on vehicle path optimization, a perturbation scheduling model for logistics and distribution with a carbon tax mechanism is established under the premise of time window variation and load capacity constraints. Herein, we propose an enhanced Genetic Algorithm (GA) based on a Gaussian matrix mutation (GMM) operator, which maintains the diversity of the population while speeding up the algorithm's convergence. The model builds a Gaussian probability matrix using the site positional order distribution characteristics implied in the original site data information, and applies the Gaussian probability matrix to individual gene mutations using a roulette-wheel-selection method; thus, the study guarantees the genetic diversity of the population while guiding it to evolve in the high-fitness direction.

Enhancing small target traffic sign detection with ML_SAP in YOLOv5s.

Detecting small traffic signs poses significant challenges due to the complex nature and dynamic conditions of real-world traffic scenarios. In response to these challenges, we propose an improved YOLOv5s target detection model incorporating the multilevel squeeze feature perception (ML_SAP) mechanism, aiming to increase the accuracy of small traffic sign detection. First, an additional detection layer is incorporated to enhance the model's capacity for detecting small-scale traffic signs.

Performance Study of Stabilized Recycled Aggregate Base Material with Two-Gray Components.

This article studies the practical road performance of recycled materials from construction waste, relying on the paving test section of the supporting project for the Qingdao Cross-Sea Bridge. The research focuses on the construction technology and road performance of using recycled construction waste materials in urban road sub-base construction. Through indoor tests such as sieving and unconfined compressive strength tests, relevant technical indicators were obtained and analyzed.

Mix proportion design and carbon emission assessment of high strength geopolymer concrete based on ternary solid waste.

To achieve dual optimization of the mechanical properties and environmental impacts of geopolymer concrete (GPC), this study proposes a high-strength geopolymer concrete (HSGPC) without coarse aggregate. The mix proportion of HSGPC was optimized using the response surface methodology, targeting compressive strength and splitting tensile strength to determine the optimal mix. Additionally, the carbon emission impact of HSGPC was assessed and compared with ordinary Portland cement concrete, ultra-high-performance concrete, and reactive powder concrete.

Performance Study of Asphalt Mixtures Reinforced with Gradated Basalt Fibers of Mixed Lengths.

The length of basalt fibers affects the performance of asphalt mixtures. To explore the influence of different lengths of basalt fibers on the performance of asphalt mixtures, this study selected basalt fibers with lengths of 6 mm, 9 mm, and 12 mm to design gradations that were incorporated into asphalt mixtures to prepare specimens. High-temperature rutting tests, immersion Marshall tests, freeze-thaw splitting tests, and low-temperature splitting tests were conducted, resulting in 11 test mix designs and 12 test indicators.

Identifying novice drivers in need of hazard perception ability improvement for takeover performance in Level 3 automated driving.

Takeover performance is a crucial constraint on deploying Level 3 automated driving. Not all drivers can adopt appropriate strategies to take over vehicle control during safety-critical situations. The hazard perception abilities of novice drivers may cause individual differences in urgent takeover performance.

Personalized forward collision warning model with learning from human preferences.

The Forward Collision Warning (FCW) system has been widely equipped on vehicles to reduce rear-end crashes, which are considered the most common type of crash. However, existing FCW systems have the problem of low response rates, which restrict their safety improvement effects. This study aims to address this issue by building personalized FCW models based on human risk preferences.

Laser Direct Writing of Setaria Virids-Inspired Hierarchical Surface with TiO Coating for Anti-Sticking of Soft Tissue.

In minimally invasive surgery, the tendency for human tissue to adhere to the electrosurgical scalpel can complicate procedures and elevate the risk of medical accidents. Consequently, the development of an electrosurgical scalpel with an anti-sticking coating is critically important. Drawing inspiration from nature, we identified that the leaves of Setaria Virids exhibit exceptional non-stick properties.