Browse Topic: Transportation Systems

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Suppression of Traffic Oscillations by Vehicular Platoons with Periodic Control Configuration12-10-01-000310/21/2026
Traffic oscillations degrade the operational efficiency and safety of vehicular platoons. This study proposes a predecessor-following platoon with periodically assigned feedback gains and investigates its frequency-selective disturbance attenuation mechanism. An auxiliary second-order undamped periodic model is first established, and the Bloch–Floquet formulation is used to derive the nominal dispersion relation and bandgap boundaries. Closed-loop disturbance attenuation is then evaluated separately using spacing-error transfer matrices that retain positive velocity feedback and actuator-response lag. Frequency-domain transmission analysis and time-domain simulations show that, under nominal homogeneous and fully controllable connected and automated vehicle (CAV) assumptions, the periodic gain configuration creates tunable attenuation bands and provides stronger downstream attenuation than a homogeneous-gain configuration. The results clarify the relationship among periodic gain assignment, bandgap formation, periodic-cell string stability, and finite-length traffic-wave suppression. The effects of vehicle heterogeneity, sensing delay, and mixed traffic remain topics for future investigation.
Yang, Xiujian, Fan, Yanwen, Zhuang, Qingyuan, Qiao, Feiyu
Deep Reinforcement Learning for Downlink User Scheduling in LEO Satellite Massive MIMO Systems2026-99-299010/19/2026
Low earth orbit (LEO) satellite communication system is expected to play a key role in the 6G wireless networks. Due to the limited communication resource and inter-user interference (IUI), the user equipments (UEs) must be well scheduled to maximize spectral efficiency. However, rapid channel variations and high mobility in LEO system make the conventional user scheduling strategies relying on instantaneous channel state information impractical. To address this challenge, this paper proposes a deep reinforcement learning (DRL) framework based on batch normalization in CrossQ algorithm to optimize the downlink user scheduling in a LEO satellite massive multi-input multi-output (MIMO) system. The scheduling task is modeled as a Markov decision process (MDP), where the observation space integrates high-dimensional features including large-scale fading (LSF) coefficients, channel matrix, and temporal features capturing the orbital progress of the satellite. Unlike traditional DRL methods, the CrossQ-based algorithm applies batch normalization (BN) within the critic networks to eliminate the need for slowly-moving target networks, fostering training stability and sample efficiency. A continuous priority score vector is mapped to discrete scheduling decisions through a top-z selection logic, allowing the agent to effectively identify spatially orthogonal user subsets to suppress the IUI. To guide the agent toward the true optimization direction, a differential reward mechanism is designed. Simulation results demonstrate that the proposed CrossQ-based scheduler consistently achieves nearly optimal performance at different signal-to-noise ratios (SNR), reaching at least 91% and 94% of the Monte Carlo search ceiling under different user densities. Moreover, the trained model provides scheduling strategy in millisecond inference time, making it a practical and robust solution for future 6G non-terrestrial networks.
Deng, Chaojun, Zhong, Yun, Meng, Xiangxu, Li, Wenfeng, Zhao, Kanglian
Physics-Constrained Procedural Generation of Synthetic Environments for the Robust Validation of Autonomous Maneuver and Logistics2026-01-75499/22/2026
The validation of Autonomous Ground Vehicles (AGVs) and intelligent logistics planners is frequently compromised by the ”Sim-to-Real” gap, where simulation environments fail to replicate the physical friction of operational deployment. Ideally, valid test cases must enforce strict mobility constraints and impose realistic sustainment penalties; however, many current generation tools rely on idealized terrain interactions and infinite-resource assumptions. We present a real-time procedural framework designed to generate high-friction validation environments that stress-test the robustness of the System Under Test (SUT). The architecture integrates gradient-based terrain analysis with a stochastic contested logistics model. It ingests synthetic heightmaps to precompute mobility corridors, ensuring that every generated evaluation episode adheres to vehicle-specific traversability limits. Simultaneously, a logistics kernel enforces fuel consumption scaled by terrain gradients and models supply chain interdiction as a parameterized Bernoulli process. We validate this framework through a ”Digital Twin” methodology, demonstrating that terrain-aware generation eliminates invalid initialization states (0% mobility violations) while the logistics model induces operationally relevant failure modes in the SUT. This unclassified, open-architecture approach supports DoD Verification, Validation, and Accreditation (VV&A) requirements by providing deterministic, reproducible edge cases for autonomous system evaluation.
Soykan, Bulent, Rabadi, Ghaith, Bochenek, Grace, Paul, Victor J.
AI-Driven Predictive Sonification for Human-on-the-Loop Ground Vehicle Autonomy2026-01-75039/22/2026
Ground vehicle autonomy increasingly depends on human-on-the-loop (HOTL) supervision, yet supervisors are often overloaded by visual interfaces that can obscure emerging risks. This paper presents an AI-driven predictive sonification architecture that converts short-horizon forecasts of platoon behavior into structured auditory cues for supervisory monitoring. A forecasting engine predicts future vehicle interaction states and evaluates predicted and active violations to generate a composite risk indicator. When risk exceeds defined thresholds, a sonification module conveys risk magnitude and trajectory through changes in pitch, loudness, modulation, and spatial panning. The paper describes the system architecture, sonification design, operational use cases, and a planned human-subject evaluation. The proposed framework is intended to improve early awareness of emerging instability and support more timely supervisory intervention.
Plotzke, Zachary R., Mohammadi, Alireza, Cheung, Calvin M.
SAE TOMORROW TODAY - Lessons From a 7,000-Mile EV Road Trip135859/22/2026
What does it take to drive an EV across America and back again? A 7,000-mile road trip is a great way to find out. Listen in as we sit down with science-comedian Sophie Shrand, Founder, Cool Jacket Productions and award-winning TV Host of Science with Sophie, to discuss The Great American ELECTRIC Road Trip, her exciting journey through 25 states in a Rivian R1S that puts EV infrastructure to the test and leads to unexpected discoveries along the way. From navigating EV charging networks to uncovering surprising economic opportunities, Shrand proves that curiosity and a sense of adventure can create meaningful connections with people from across the country. We'd love to hear from you. Share your comments, questions and ideas for future topics and guests to podcast@sae.org. Don't forget to take a moment to follow SAE Tomorrow Today--a podcast where we discuss emerging technology and trends in mobility with the leaders, innovators and strategists making it all happen--and give us a review on your preferred podcasting platform. Follow SAE on LinkedIn, Instagram, Facebook, X, and YouTube. Follow host Grayson Brulte on LinkedIn, X, and Instagram.
Patterson, Lori
SAE TOMORROW TODAY - Engineering Mobility Standards in the Age of AI135869/22/2026
Emerging technology is reshaping not only what engineers build, but how they build it. From software-defined and AI-powered vehicles to automation and electrification, the role of standards is changing as engineering workflows become increasingly digital, machine-readable, and AI-enabled. To learn how SAE International is navigating this next chapter, we sat down with Reuben Sarkar, CEO, to explore what's ahead for the 120-year-old organization as automotive, aerospace, commercial vehicles, and advanced air mobility increasingly converge. The conversation explores the importance of lifelong learning, the next generation of engineering talent, and how standards must evolve to keep pace in the age of AI. We'd love to hear from you. Share your comments, questions and ideas for future topics and guests to podcast@sae.org. Don't forget to take a moment to follow SAE Tomorrow Today--a podcast where we discuss emerging technology and trends in mobility with the leaders, innovators and strategists making it all happen--and give us a review on your preferred podcasting platform. Follow SAE on LinkedIn, Instagram, Facebook, X, and YouTube. Follow host Grayson Brulte on LinkedIn, X, and Instagram.
Patterson, Lori
Passive Thermal Management Through Vapor Chamber Integration of a PMSM E-Motor installed on UAV for Urban Mobility Applications2026-24-00109/21/2026
Thermal management is a critical design challenge for Permanent Magnet Synchronous Motors (PMSMs) employed in Unmanned Aerial Vehicle (UAV) propulsion systems, where high power density and compact integration lead to significant heat generation. Excessive temperatures can compromise efficiency, reliability, and component lifetime, making the development of effective and lightweight cooling solutions essential. This study investigates the integration of a vapor chamber as a passive thermal management solution for a commercially available PMSM intended for UAV applications, whose thermal performance is evaluated under external airflow conditions representative of low-speed flight and hovering. Unlike conventional active cooling systems, the proposed approach does not require moving parts, external power input, or additional control devices. Heat transfer is driven by phase-change mechanisms within a sealed enclosure: as the local thermal load increases, the working fluid evaporates in the hotter regions and condenses in the cooler ones, redistributing heat autonomously without external intervention — a self-regulating behavior particularly suited to the constraints of UAV propulsion systems. A simplified three-dimensional model of the motor housing was developed, and steady-state conjugate heat transfer simulations were performed in ANSYS Fluent to evaluate the thermal performance of the system. Three configurations were analyzed: a baseline motor without vapor chamber, a configuration with an integrated vapor chamber, and a configuration combining the vapor chamber with an external copper fin array. The vapor chamber was modeled using an equivalent porous-medium approach for the wick structure, coupled with a multiphase formulation to capture liquid–vapor interactions within the core. The results demonstrate that vapor chamber integration significantly reduces peak pole temperature, with reductions ranging from 38K to 159K (approximately 10% to 31% relative to the baseline configuration) depending on operating conditions. At higher thermal loads, the device transitions from a liquid-filled regime to an active two-phase operation, enhancing heat transfer through evaporation and condensation. The addition of an external copper fin array further improves thermal performance, achieving a maximum pole temperature reduction of 203K (approximately 33% relative to the baseline) under low-airflow, high-load conditions. A key finding of this study is the strong coupling between the external fin array and the internal phase-change behavior of the vapor chamber: by lowering the condensation-side temperature, the fins promote a more active two-phase regime, enhancing overall heat transfer performance beyond what either component achieves independently. These results highlight the potential of vapor chamber technology, particularly when combined with extended surfaces optimized for the dominant flight regime, as a lightweight, passive, and self-regulating cooling strategy for compact UAV electric propulsion systems.
Benedetti, Silvia, Lombardi, Simone, Federici, Leonardo, Chiappini, Daniele
How Micromobility is Reshaping Urban Mobility: A Systematic Literature Review2026-24-00259/21/2026
Micromobility is rapidly reshaping urban mobility by transforming travel behaviour, urban space, and transport systems. Its growing role in reducing car dependency and supporting low-carbon mobility has positioned cycling, e-scooters, and e-bikes as key components of sustainable urban transport. This study examines the role of micromobility in urban mobility through a systematic literature review. The review provides a structured synthesis of existing research, identifies major publications and thematic trends, and highlights gaps in current knowledge across several dimensions of urban mobility. The findings show that the effects of micromobility are neither uniformly positive nor negative. They depend particularly on infrastructure provision, governance arrangements, regulation, user behaviour, and integration with public transport. The review therefore suggests that micromobility should be considered as part of the wider urban transport system rather than as an isolated group of modes. The review identifies priorities for further research and provides evidence that can support transport planners and other stakeholders in developing approaches to micromobility and public transport integration.
Olkhova, Mariia, Comi, Antonio
From Crowdshipper Behavior to Urban Mobility Governance: Policy Insights for Sustainable Crowdshipping2026-24-00299/21/2026
Crowdshipping has recently attracted significant attention as a potentially sustainable solution for urban logistics, as it leverages individuals’ underutilized travel capacity to perform last-mile deliveries. While existing research has extensively examined crowdshipper participation through motivational patterns, considerably less attention has been devoted to the governance and policy implications emerging from crowdshipper behavior. This represents a critical gap, particularly in the context of sustainable urban mobility, where logistics innovations are often implicitly assumed to generate positive externalities without adequate regulatory design. This paper addresses this gap by translating crowdshipper motivational evidence into policy-relevant insights for sustainable urban mobility planning. The analysis is based on data collected through a structured questionnaire administered to potential and active crowdshippers. The survey collected information on socio-demographic characteristics, mobility habits, motivations, risk perception, trust, and willingness to participate under alternative crowdshipping conditions. While such conditions are commonly used to estimate participation patterns, this study reinterprets them through a governance-oriented lens to explore trade-offs between economic incentives, environmental motivations, and mobility-related impacts. Using a governance-oriented interpretation of survey data, the analysis highlights how different incentive structures activate heterogeneous crowdshipper participation patterns, with distinct mobility impacts. Results show that participation driven by strong economic incentives and operational flexibility may encourage additional vehicle-kilometers traveled, while participation embedded within routine trips and influenced by environmental considerations tends to operate within more limited spatial and temporal constraints. Taken together, these findings indicate that crowdshipping outcomes are not inherently aligned with sustainable urban mobility objectives, but critically depend on incentive design and regulatory integration within Sustainable Urban Mobility Plans (SUMPs).
Comi, Antonio, Idone, Ippolita
Taxonomy and Definitions for Terms Related to Driving Automation Systems for On-Road Motor VehiclesJ3016_202609 (Current)9/20/2026
This document describes [motor] vehicle driving automation systems that perform part or all of the dynamic driving task (DDT) on a sustained basis. It provides a taxonomy with detailed definitions for levels of driving automation, ranging from no driving automation (Level 0) to automated driving under all conditions in which humans can drive, with human driving not needed (Level 5), in the context of [motor] vehicles (hereafter also referred to as “vehicle” or “vehicles”) and their operation on roadways: Level 0: No driving automation Level 1: Driver support for steering OR speed, with continual driver supervision necessary and driver intervention when needed Level 2: Driver support for steering AND speed, with continual driver supervision necessary and driver intervention when needed Level 3: Automated driving under defined conditions, with human driving needed following an alert or evident vehicle malfunction Level 4: Automated driving under defined conditions, with human driving not needed to mitigate risk Level 5: Automated driving under all conditions in which humans can drive, with human driving not needed. The simple level descriptors have been changed to improve understanding of the differences among levels, but these are NOT the definitions of the levels of driving automation. See the definitions of each automation level in Sections 4 and 5 for explanation of these changes. These level definitions, along with additional supporting terms and definitions provided herein, can be used to describe the full range of driving automation features equipped on [motor] vehicles in a functionally consistent and coherent manner. “On-road” refers to publicly accessible roadways (including parking areas and private campuses that permit public access) that collectively serve all road users, including cyclists, pedestrians, and users of vehicles with and without driving automation features. The levels apply to the driving automation feature(s) that are engaged in any given instance of on-road operation of an equipped vehicle. As such, although a given vehicle may be equipped with a driving automation system that is capable of delivering multiple driving automation features that perform at different levels, the level of driving automation exhibited in any given instance is determined by the feature(s) that are engaged. This document also refers to three primary actors in driving: the (human) user, the driving automation system, and other vehicle systems and components. These other vehicle systems and components (or the vehicle in general terms) do not include the driving automation system in this model, even though as a practical matter a driving automation system may actually share hardware and software components with other vehicle systems, such as a processing module(s) or operating code. The levels of driving automation are defined by reference to the specific role played by each of the three primary actors in performance of the DDT and/or DDT fallback. “Role” in this context refers to the expected role of a given primary actor, based on the design of the driving automation system in question and not necessarily to the actual performance of a given primary actor. For example, a driver who fails to monitor the roadway during engagement of a Level 1 adaptive cruise control (ACC) system still has the role of driver, even while they are neglecting it. Active safety systems, such as electronic stability control (ESC) and automatic emergency braking (AEB), and certain types of driver assistance systems, such as lane keeping assistance (LKA), are excluded from the scope of this driving automation taxonomy because they do not perform part or all of the DDT on a sustained basis, but rather provide momentary intervention during potentially hazardous situations. Due to the momentary nature of the actions of active safety systems, their intervention does not change or eliminate the role of the driver in performing part or all of the DDT, and thus are not considered to be driving automation, even though they perform automated functions. In addition, systems that inform, alert, or warn the driver about hazards in the driving environment are also outside the scope of this driving automation taxonomy, as they neither automate part or all of the DDT, nor change the driver’s role in performance of the DDT (see 8.13). It should be noted, however, that crash avoidance features, including intervention-type active safety systems, may be included in vehicles equipped with driving automation systems at any level. For automated driving system (ADS) features (i.e., Levels 3 to 5) that perform the entire DDT, crash mitigation and avoidance capability is part of ADS functionality (see also 8.13). Note that this document provides a taxonomy and definitions and is not a safety standard. The document is not intended to provide guidance for safe vehicle operation by the driving automation system.
On-Road Automated Driving (ORAD) Committee
Geometric Design Consistency Evaluation Criteria for Horizontal Curves on Two-Lane Rural Highways Based on Vehicle Stability09-15-01-00039/17/2026
Rollovers are among the most severe road crashes, often leading to high fatalities and significant property damage, as reported by government and insurance agencies. This study investigates the impact of curve geometry and loading conditions on the rollover stability of a two-axle truck using validated vehicle dynamics simulations. The research highlights the importance of providing adequate curve radii and shows that larger radii are required to ensure design consistency. The study reveals that a 1 cm increase in center-of-gravity height results in a 0.82% decrease in the margin of safety against rollover, and that loading the truck to 93.75% of its full capacity over an equivalent platform length is the most critical loading condition in terms of rollover stability. To enhance safety, predictive models for lateral acceleration are developed along with geometric design consistency evaluation criteria based on vehicle rollover stability. Design guidelines for consistent curve design are also proposed. These models and criteria guide strategic improvements in road geometry, including optimized placement of rollover caution signage and targeted infrastructure refinements. The study underscores the need for enhanced curve design standards to improve truck stability and driver comfort while providing essential tools for advancing highway safety and mitigating rollover risks for heavy vehicles.
Remya, Y. K., Jacob, Anitha, Subaida, E. A.
Oxygen Considerations for High Elevation Airport Operations (HEAO)AIR6829A (Current)9/11/2026
This document covers information concerning the use of oxygen when flying into and out of high elevation airports for both pressurized and non-pressurized aircraft. Oxygen requirements for pressurized aircraft operating at high altitudes have for decades emphasized the potential failures that could lead to a loss of cabin pressurization coupled with the potential severe hypoxic hazard that decompressions represent. This document is intended to address the case where the relationship between cabin and ambient pressures are complicated by operations at high terrestrial altitudes. Operators who fly into these high-altitude airports should address the issues related to this environment because it carries the potential for insidious hypoxia and other conditions which can affect safety. It provides information to consider in developing operational procedures to address hypoxia concerns consistent with regulatory mandates. In some sections, procedures are discussed that may mitigate the deleterious effects of hypoxia in a non-flight regime yet still have the potential to represent risk factors associated with flight operations. All the information is provided as a framework for potential oxygen management and other procedures to facilitate responsible practices and facilitate compliance with existing regulatory requirements. This document cannot address every type of aircraft pressurization system, oxygen system, or operational condition the flight may encounter. Any threat or hazard not discussed in AIR6829 should be brought to the attention of the OEM, the regulatory authority, and the flight operations department for proper guidance.
A-10 Aircraft Oxygen Equipment Committee
Research on the Stability of Three-Axis Vehicles with Coordinated Steering under High-Speed Low-Adhesion Conditions2026-99-11369/11/2026
Three-axle vehicles are widely used in engineering, transportation, and other heavy-duty applications, but they are prone to lateral instability at high speeds or on low-adhesion road conditions, which severely degrades handling stability. To enhance their dynamic performance under extreme operating conditions, this paper proposes a direct yaw-moment control (DYC) strategy based on an incremental linear quadratic regulator (ILQR) for a distributed-drive three-axle vehicle equipped with active front-wheel steering (AFS) and differential drive assist steering (DDAS), thereby improving the accuracy and responsiveness of lateral stability control. Furthermore, to mitigate the mutual coupling and interference among multiple control subsystems, a coordinated steering strategy based on phase-plane analysis is proposed to achieve effective integration and dynamic coordination of AFS, DDAS, and DYC. Co-simulation studies conducted in Matlab/Simulink and TruckSim reveal that the proposed coordinated steering strategy substantially diminishes the peak yaw rate and vehicle sideslip angle across diverse driving conditions, thereby considerably enhancing the lateral stability of the three-axle vehicle during extreme maneuvers.
Hu, Jiadong, Wang, Tie
ASTDGCN: An Adaptive Spatial-Temporal Diffusion Graph Convolutional Network for Traffic Forecasting2026-99-15839/11/2026
Precise traffic flow prediction functions as the fundamental cornerstone for the efficient, safe, and reliable operation of intelligent transportation systems (ITS). It not only provides data-driven support for key applications, for instance, real-time traffic signal regulation, proactive congestion mitigation, and personalized route optimization, but also exerts a critical effect on reducing traffic accidents and improving overall urban travel efficiency. However, the traffic system belongs to a complex system, with spatio-temporal dynamics that are both intricate and variable, ranging from predictable fluctuations during morning and evening peak hours to localized propagation effects caused by accidents, as well as seasonal variations and significant nonlinear characteristics. These factors collectively pose substantial challenges to building accurate and reliable prediction models, creating a long-standing technical bottleneck in this field. With the aim of solving the dilemma that existing methods are hardly able to capture traffic flow’s spatio-temporal dependence effectively, we advance an adaptive spatial–temporal diffusion graph convolutional network (ASTD-GCN) for a traffic flow prediction model that integrates adaptive graph learning, diffusion convolution, and bi-directional long short-term memory network (Bi-LSTM) with attention mechanism. The model dynamically constructs the correlation between the nodes of the transportation network through the adaptive graph learning module and accurately describes the spatial topology. The diffusion convolution module realizes multi-order spatial information diffusion based on graph structure, which realizes the effective extraction of the traffic flow’s spatial dependence features. The Bi-LSTM module incorporating the attention mechanism captures the historical and future context information of traffic flow simultaneously through the bidirectional loop structure and the temporal attention mechanism, and strengthens the key time step features. Experimental results on -world traffic datasets PEMS03, PEMS04, PEMS07, and PEMS08 indicate that our proposed model exhibits better predictive precision in traffic flow forecasting tasks than baseline counterparts.
Li, Sumin, Gao, Yina, Zhu, Hongnian
Study on Nonlinear Dynamic Characteristics of High-Speed Train Braking Systems2026-99-11419/11/2026
To address the oversimplification in prior brake system models, this study develops a 10-degree-of-freedom (DOF) dynamic model of a disc brake system. A control-variable approach is employed to numerically simulate the effects of braking force, rotational inertia, brake pad tangential stiffness, suspension stiffness, and damping. The vibration responses under different braking conditions and in the presence of multi-parameter coupling are analyzed through bifurcation diagrams, phase trajectories, and Poincaré sections. The main findings indicate: (1) Increasing braking force induces a transition from period-1 to higher-order periodic motions (e.g., period-6), accompanied by significant vibration amplification; (2) Enhanced brake pad tangential stiffness suppresses vibration amplitude but extends the sticking phase duration; (3) Exceeding a critical primary suspension stiffness threshold triggers system instability. These results suggest that structural optimization of suspensions and reasonable selection of brake pad support stiffness are important measures to prevent stick-slip vibrations.
Li, Songge, Wang, Jingyue
Train Delay Reduction Approach based on a Virtually Coupled Trains Following Model with Timetable Recovery Process: A Case of High-Speed Rail2026-99-15169/11/2026
One challenge in railway operation is how to achieve high levels of punctuality and reliability. However, especially in peak hour operation, a high volume of train traffic will affect timetables, which are more sensitive to the increase in travel time. The concept of virtual coupling has been introduced for controlling train movement mainly to increase capacity. As the operation under virtual coupling requires a short separation distance between trains, it might be applied to reduce the delay and recover the train timetable. However, there is no approach proposed detailing how the coupling is applied to reduce delay. In this paper, the virtual coupling state movement approach based on a vehicle following model with the coupling conditions determined to couple a group of trains for reducing or preventing secondary delay is proposed. The train operation under the proposed approach is simulated in MATLAB software, then applied to the hypothetical case, High-speed line, Bangkok - Nakhon Ratchasima, Thailand. The delay analysis is performed, and the waiting probability is determined to prove the effectiveness of the proposed approach. The simulation results show that trains will be virtually coupled with their front train as a form of train convoy when they cannot proceed at the ideal speed. Thus, operating train movement based on the proposed approach can reduce secondary delay and bring a train to arrive on time compared to the operation under the moving block control.
Chansong, Sukanya, Ketphat, Naphat
Research on Passenger Flow Prediction of Urban Rail Transit Based on Grey Improvement Model2026-99-15649/11/2026
In recent years, China's urban rail transit sector has undergone rapid expansion, with passenger demand consistently increasing. Accurate passenger flow forecasting is essential for ensuring efficient and safe metro operations. This paper takes Nantong Metro Line 1 as a case study and applies an optimized forecasting approach that integrates a grey metabolism model with the Holt double-parameter exponential smoothing method. Based on an analysis of Automated Fare Collection (AFC) data from March 2023 to February 2024, passenger flow on this line demonstrates a clear linear growth trend, which aligns well with the assumptions of the grey metabolism model. The results indicate that the optimized grey metabolism model not only significantly enhances prediction accuracy but also greatly reduces the variance ratio, demonstrating high reliability in forecasting outcomes. This improved methodology provides a more robust tool for metro operators in planning services, managing capacity, and optimizing resource allocation.
Fan, Fan, Zhao, Zeheng, Zhang, Jin, Ma, Junhao, Qian, Beiyue
Conceptual Design of Steel Shell-UHPC Composite Pylon for Large-Span Suspension Bridges2026-99-15139/11/2026
With the rapid development of the transportation industry, heavy-duty traffic has become extremely common, particularly in some coastal port cities where the presence of container terminals leads to generally high vehicle axle loads. In these regions with an advanced transportation industry, large-scale cross-sea bridges are often required to ensure transport efficiency. However, conventional long-span bridge types, such as cable-stayed bridges and suspension bridges, face challenges in meeting the demands of heavy-duty traffic due to limitations imposed by the self-weight of pylons. In response, this paper proposes a prefabricated steel shell–ultra high performance concrete (SS–UHPC) composite pylon composed of basic SS–UHPC units, aiming to enhance both the load-carrying efficiency and seismic performance of the structure. A conceptual design of the SS–UHPC composite pylon was developed based on a super-long-span suspension bridge with a main span of 2180 m, and a comparative analysis was carried out against a conventional steel shell–normal concrete (SS–NC) composite pylon. The results show that, owing to the higher strength-to-self-weight ratio of UHPC, the SS–UHPC composite pylon achieves a 42.4% reduction in self-weight compared to the SS–NC composite pylon. Under the most unfavorable load condition, the axial force and transverse bending moment at the pylon base are reduced by 13.79% and 6.24%, respectively. Under maximum seismic load, the axial force and transverse bending moment at the base decrease by 14.12% and 28.92%, respectively, demonstrating improved load-carrying efficiency and seismic performance of the pylon. Although the life-cycle cost of the SS–UHPC composite pylon is higher than that of the SS–NC composite pylon, its superior mechanical behavior sufficiently offsets the cost difference. In conclusion, the superior mechanical behavior of the SS-UHPC composite pylon makes it better suited for application in long-span bridges subjected to heavy-duty transportation loads.
Chen, Jing Li, Liu, Yong Jian, Peng, Hong Bo, Sun, Li Peng, Yang, Ze Hong
Vehicle Multi-Target Tracking Algorithm Based on Improved CenterTrack2026-99-11029/11/2026
With the rapid increase in the number of vehicles worldwide in recent years, multi-vehicle tracking has become a critical and challenging research topic in smart transportation. Although many researchers have constructed classical multi-object tracking (MOT) models, these models often lose trajectories of objects in challenging traffic environments with frequent occlusions and high object density. This significantly hinders the practical deployment of such tracking systems. In order to improve tracking robustness and accuracy when faced with these challenges, we propose a new multi-vehicle tracking algorithm built upon the CenterTrack framework. The core of our work lies in three key improvements. Each overcomes a distinct weakness in existing approaches, and together they work to improve performance. First, we use the Wise Intersection over Union (WIoU) loss to guide the model optimization and reduce the impact of label noise during training, which results in better convergence. Second, we apply an attention mechanism to reduce feature interference caused by multiple inputs (current frame, previous frame, and heatmap) of the model. Third, we employ the Sigmoid Linear Unit (SiLU) in the backbone network to further improve nonlinear feature representation. We evaluate our algorithm on the standard KITTI multi-object tracking benchmark. Experimental results show that our method achieves a Multi-Object Tracking Accuracy (MOTA) of 65.94% and an Identification F1 (IDF1) of 84.01%. This represents an improvement of 2.93% in MOTA and 2.36% in IDF1 over the baseline method. The results demonstrate not only the effectiveness of our method but also its practical usefulness and robustness in challenging road environments.
Zhang, Hao, Huai, Chongfei, Wang, Ziming, Zhao, Zexuan, Ye, Shuai, Du, Xiaobing, Sun, Shenghai
An Improved Multi-Object Vehicle Detection Algorithm Based on YOLOv11s2026-99-11299/11/2026
For object detection in complex road situations, such as inadequate detection performance and difficulties caused by vehicle occlusion and cluttered environments, this paper pursues a YOLOv11s-based object detection framework. The algorithm successfully designed a novel PEConv module. This module integrates a partial convolutional network with an efficient multi-head attention mechanism. Through a Split operation, the input image is divided into locally enhanced channels and original channels. The locally enhanced channels undergo partial convolution and feature weight allocation via the efficient multi- head attention mechanism for feature extraction. Finally, these channels are fused with the original channels before undergoing convolution. This approach preserves the original features while minimising feature loss caused by the series of operations. Therefore, the PEConv module is based on a partially convolutional network and efficient multi-head attention. It improves the detection ability by precisely giving more weight to small objects and occluded parts with augmented partial channel attention and original channel fusion. This study further enhances the model’s detection precision and improves its performance in addressing small target vehicles and severe occlusion issues by refining and upgrading the original C3K2 architecture. The LSBlock is integrated into the original model’s bottleneck structure, replacing the traditional 3x3 convolution to create the C3K2 - LSBlock module. Experimental results show that on the UA - DETRAC dataset, compared with the original YOLOv11s, the optimized YOLOv11s has improved the original mAP @ 50 by 3.4%, reaching 61.3%, and improved the original mAP @ 50: 95 by 2%, which verifies the correctness of it.
Chen, Yulin, Wang, Yini, Wang, Jianwei, Zhang, Xin
Structural Design and Stability Research of a Two-DOF Transformable Wheel for Enhanced Obstacle-Crossing Performance on Complex Terrain2026-99-11309/11/2026
Under the constraints of conventional chassis layouts, traditional wheeled vehicles struggle to maintain stable obstacle-crossing performance on complex terrain. This study aims to enhance both the obstacle-crossing capability and stability of such vehicles. First, a transformable wheel capable of varying its effective radius and actively adjusting the wheel–ground contact configuration is designed, and its degrees of freedom are analyzed using screw theory. Next, based on screw theory and Lie group theory, position-level and velocity-level kinematic models of the transformable wheel are established, and system-level performance indices—including workspace, singular configurations, and force-transmission characteristics—are formulated. Finally, taking these performance indices as optimization objectives, a constrained optimization model of the mechanism’s geometric parameters is constructed, from which an optimal dimension set for the transformable wheel is obtained. The results show that the optimized transformable wheel has significantly improved minimum singularity and dexterity. The designed transformable wheel can achieve changes in wheel radius and wheel rim inclination angle, improving the vehicle's passability in complex terrain.
Lu, Shichuang, Wang, Tie
A Method for Resolving Two-Vehicle Conflicts at Unsignalized Intersections Based on Adaptive TTC and Traffic Rules2026-99-11409/11/2026
To address the challenges of unsignalized intersections—where the absence of traffic signals leads to high computational complexity and poor real-time performance in existing cooperative methods—this paper proposes a lightweight, real-time conflict resolution strategy for two-vehicle scenarios. First, a traffic rule matrix is constructed based on China’s Road Traffic Safety Law Implementation Regulations, digitizing right-of-way priorities to achieve millisecond-level conflict detection. Second, we introduce an adaptive TTC threshold function to dynamically adjust the warning time between vehicles based on the vehicle speed. Finally, based on the type and priority of the conflict, the speed adjustment value is obtained through the parsing method, enabling real-time calculation of the deceleration amount without the need for iterative optimization. Simulation results in SUMO demonstrate that, compared to the default uncoordinated mode, the strategy reduces the delay in converging conflicts from 4.87 s to 2.87ds and cuts the deceleration frequency by 37.5%. For crossing conflicts, high-priority vehicle deceleration events drop from 8 to 1, and speed standard deviation decreases from 1.27 m/s to 0.78dm/s. This method reduces the computational load while ensuring security, providing a practical solution for cooperative driving at unsignalized intersections in the V2X environment.
Wang, Xinxin, Zhang, Xin
Analysis of Differences Between the Current CLTC and China’s Current Traffic Operation Characteristics2026-99-15419/11/2026
With the significant increase in the ownership and market share of new energy vehicles, the current characteristics of China’s traffic operation have undergone remarkable changes compared with those before 2020. This paper focuses on a systematic study of the differences between the current China Light-duty Vehicle Test Cycle (CLTC) and the current traffic operation characteristics. Firstly, the data are derived from the actual on-road operation data of nearly 400 new energy vehicles collected during 2020-2025. Based on this, a comparative analysis framework is established from two dimensions: differences in variable characteristics and differences in test energy consumption. The results show that due to the substantial rise in new energy vehicle ownership and market share, the maximum speed on roads has increased significantly, and the acceleration and deceleration have become more intense. The significant changes in traffic operation characteristics have further widened the deviation between the energy consumption tested under the existing CLTC and the actual energy consumption. Comprehensive research indicates that the increased market penetration of new energy vehicles has brought about obvious changes to the traffic operation characteristics formed during the era dominated by traditional fuel vehicles. Therefore, launching a new round of revision work on the CLTC is of great practical significance for promoting the high-quality development of the new energy vehicle industry in the future.
Yu, Hanzhengnan, Cao, Xiaofei, Zhang, Hao, Yi, Junyu, Zhang, Yongren, Wang, Yang, Wang, Chuanjin, Liu, Te, Ma, Dehui
Emergency Rescue Resource Allocation Model and Reasoning Prediction Method for Expressway Reconstruction and Extension2026-99-15489/11/2026
During expressway reconstruction and extension, when a traffic accident occurs, how to make a scientific and reasonable allocation of emergency resources is the premise and basis for efficient rescue. In view of the reconstruction characteristics and the complexity of emergency rescue, the number of casualties, the damage degree of road facilities, the number of damaged vehicles, the range of hazardous chemicals, the size of the fire, and the traffic order were used as the accident attribute indexes to build a historical accident set (case database). The allocation of emergency rescue resources was predicted using case-based reasoning techniques. Also, the corresponding reasoning prediction method was proposed. The research shows that this model can accurately predict the demand for emergency rescue resources during the period of expressway reconstruction and extension, which has good availability and operability, and provides methodological and modeling support for the emergency rescue resource decision system.
Ran, Jin, Zhan, Shiyang, Kadir, Ahmetjan, Ma, Jiarui, Dai, Xiaomin
Track De-icing and Road Maintenance Method Based on Induction Heating Technology2026-99-15369/11/2026
In order to solve the problems of long preheating time and high energy consumption caused by the traditional resistance heating track deicing technology and large power supply load, this paper presents a track deicing and road maintenance method based on electromagnetic induction heating. This paper studies the operational bottlenecks of the resistance heating system in a certain marshalling yard. It explains the eddy current heating from the principle of electromagnetic induction heating and designs an appropriate coil for turnouts and derives its power calculation formula. A mathematical model for the 'solid-liquid' phase transformation in the melting of snow is created and the melting parameter α = 0.623. In comparative experiments, compared to a 4kW electromagnetic induction heating device with no preheating time which melts snow up to 5cm in 40 minutes and consumes 40kW · h of energy in 1 hour, a 13kW resistance heating device needs 150 minutes to preheat, 180 minutes to melt, and consumes 130kW · h of energy. Use 70% less energy and help with track and road de-icing and upkeep with this technology.
Song, Zongying, Li, Zhongming, Wei, Dong, Yang, Jin, Wang, Xingzhong, Liu, Jingwei, Zhang, Xiaoyu
Convoy Size Effects in Virtual Coupling: Analysis of How the Number of Trains in a Convoy Influences Capacity and Delay2026-99-15219/11/2026
Rail transportation capacity is related to the number of trains that can be grouped within a convoy under a virtual coupling (VC) system. Grouping trains into larger convoys allows them to operate as a single train, reducing headway and increasing track usage compared with classic signaling systems. However, grouping trains has limitations, such as increased communication requirements between trains and stricter safety conditions. On the other hand, smaller convoys may offer less capacity increase but give more flexibility and operational resilience. Therefore, convoy size is an important parameter in balancing system performance. The research investigates the operational impacts of varying convoy sizes on route capacity and delay using the UIC 406 standard methodology. Simulation results indicated that larger convoys increase route capacity, particularly as trains transition into convoy formation faster. In contrast, there are increased delays. These conclusions demonstrate that convoy size optimization is important for increasing capacity and managing delays, revealing the practical benefits of a convoy management system.
Prompianpong, Nammont, Ketphat, Naphat
Analysis of Traffic Capacity at the Intersection of Xiyou Road and Qianshan Road in Hefei City2026-99-15519/11/2026
With the advancement of urbanization and the popularization of automobiles, the traffic load on urban roads is becoming increasingly heavy, resulting in many traffic problems. Road intersections serve as crucial linchpins in the urban transportation grid, wielding considerable influence over the overall traffic capacity of a city’s road network. Enhancing intersection efficiency and cutting down on delays stand at the heart of tackling urban congestion challenges. This study zeroes in on the crossroads where Xiyou Road intersects with Qianshan Road in Hefei City. Employing hands-on observation and photographic documentation, the research examines traffic flow and signal configurations during the peak demand period (7:30-8:30). The analysis evaluates traffic capacity and utilization rates for through, left-turn, and right-turn lanes at this intersection. Findings reveal that the right-turn lane at the southern entrance and the left-turn lanes at both northern and eastern entries show relatively low saturation levels, while the saturation of other lanes is greater than or close to 1. Therefore, this intersection does not have sufficient capacity. The actual traffic operation at the intersection, particularly during peak traffic times, is analyzed to identify the reasons for congestion Finally, improvement plans for optimizing traffic organization at intersections are proposed, such as optimizing signal timing schemes and transforming traffic channelization. Simulation analysis using VISSIM shows a 9.34% reduction in total intersection parking time, a 34.26% decrease in average queue length, and an 8.12% reduction in average vehicle delay. These results provide a reference for future optimization work, including intersection signal timing and channelization.
Wang, Yanmei, Wang, Chen, Fu, Ziyue, Meng, Xianglong
Research on Planting Concrete Preparation and Alkali Reduction Technology2026-99-15189/11/2026
Planting concrete has drawn much attention due to its great potential in highway slope protection and ecological restoration. However, its practical application has been limited as its highly alkaline environment imposes severe restrictions on the germination of plant seeds and the growth of seedlings. To address this key issue, this paper conducted a systematic study on planting concrete preparation and alkali reduction technology. First, planting concrete samples that meet the basic physical and mechanical property requirements are prepared by optimizing the raw material ratio, mixing, molding, and curing processes. On this basis, the post-molding concrete samples are soaked in calcium superphosphate solution, so that the phosphate ions in it can have chemical reactions with the free calcium hydroxide in the concrete to make insoluble calcium phosphate salts, thus realizing chemical alkali reduction.
Liu, Ying, Yang, Wanting, Ma, Lijie
Real-Time Spatiotemporal Correlation Feature Analysis of Traffic Flow Based on CEEMD+BiGRU Combination Model2026-99-15559/11/2026
In the application process of real-time traffic flow data, the main reason affecting the analysis of spatiotemporal correlation features is the overlapping distribution of its own characteristic modes, which leads to poor representation of spatiotemporal features and the problem of inability to fit traffic flow with true values, failing to meet the requirements of confidence interval distribution. This paper proposes a CEEMD BiGRU combination model and uses the IMF components obtained by decomposing traffic flow data into CEEMD to represent spatiotemporal properties. A bidirectional time series model is constructed using BiGRU, and multi-scale features are used as inputs to fit traffic flow and true values. By bidirectionally calculating the hidden states of multi-scale features and considering the distribution requirements of confidence intervals, the spatiotemporal dependencies related to traffic flow are correlated and output. The case shows that the output flow of this method is highly consistent with the true value, which can improve the accuracy of prediction.
Gao, Bowen, Gu, Feifei
Multi-Criteria Decision-Making for Speed Limits at Median Opening Sections of Expressway Reconstruction and Extension2026-99-15599/11/2026
In expressway reconstruction and extension projects, median opening sections are safety bottlenecks and high-congestion areas. Decision-making for their speed limit schemes must balance multiple conflicting objectives, such as safety, efficiency, economy, and driver psychology, which traditional single-objective methods cannot adequately address. This study proposes a Multi-Criteria Decision-Making (MCDM) framework based on the Fuzzy Analytic Hierarchy Process (FAHP). First, three speed limit schemes were designed based on standards and investigations. Subsequently, a comprehensive evaluation hierarchy including six main criteria and 21 sub-criteria was constructed. Finally, expert questionnaires were used to acquire the weights and score the schemes. The results show that “Safety” is the dominant criterion with the highest weight, reaching 54.3%. Scheme 3 (the 80→70 km/h scheme) achieved the highest comprehensive score, as it realized the best balance across dimensions such as efficiency, economy, and driver acceptance. Sensitivity analysis verified the robustness of this ranking result. The FAHP framework proposed in this study provides a scientific and robust tool for speed limit decision-making in complex work zones.
Zhao, Wenzheng, Ran, Jin, Zhan, Shiyang, Kadir, Ahmetjan, Doheter, Jiangenle, Ma, Jiarui
Intelligent Connected Road Test Brake Throttle Robot Calibration Method2026-99-11209/11/2026
With the development of intelligent connected vehicle (ICV) technology, road testing has become a key guarantee for verifying the safety and reliability of automobiles. The brake pedal robot basically eliminates human differences in complex scenes by simulating human operation. Therefore, the accuracy of the actions performed by these robots directly determines the validity of the test results. However, the current study lacks a uniform calibration standard, resulting in reduced execution accuracy. In order to meet the requirements of precision and a unified standard for the test, this research analyzes the metrological characteristics of brake pedal robot. Based on this, a systematic calibration framework was established to verify key performance parameters. Specifically, the pedal speed is dynamically calibrated using high-precision accelerometers, and pedal force is verified through a dedicated calibration device that integrates standard force sensors. And the pedal space travel is measured using a portable three coordinate articulated arm system. Experimental verification shows that the proposed method can strictly control the pedal speed error within ± 5%, pedal force error within ± 3%, and pedal stroke error within ± 2 mm, fully meeting the requirements of ICV road testing. This study provides a standardized framework and scientific basis for calibration, improving the accuracy and credibility of road test data, thereby supporting safer deployment of intelligent driving systems.
Chen, Xi, Ma, Siyao, Feng, Zhu
Research on High-Reliability Testing Systems for Intelligent and Connected Vehicle2026-99-11119/11/2026
With the large-scale application of intelligent connected vehicles, the verification of their functional safety and reliability has become a core bottleneck in the industrial development. The traditional real- vehicle road test method can no longer meet the current demand for large-scale test verification due to problems such as high cost, low efficiency, and difficulty in reproducing dangerous scenarios. This paper studies the vehicle-in-the-loop simulation test system based on a digital twin. By constructing a virtual scenario highly consistent with the real world, physical-level multi-source perception signals are simulated and mapped to the system under test to enable high- reliability verification of real vehicles. In terms of lateral and longitudinal control functions, multiple sets of test cases are selected respectively for comparison between road tests and virtual simulation tests. The results show that the accuracy of key indicators is above 90%, which provides practical reference for the subsequent test and verification system of high-level autonomous driving.
Hou, Quanshan, Tang, Ke, Gao, Tian, Chen, Tao, Zhou, Si
Layout Design Evaluation of Expressway Guide Sign Based on Entropy Weight-TOPSIS Method2026-99-15609/11/2026
Expressway guide signs in multi-ethnic regions often show an imbalanced text proportion in real-world use. To address this issue, this paper examines three typical guide sign layouts, representing signs from interchanges, service areas, and tourist destinations. An eye-tracking study was implemented to gather eye-movement data from participants, and a comprehensive evaluation approach based on the entropy weight-TOPSIS approach was employed to evaluate the layout schemes of expressway guide signs. The results indicate that placing Character A above Character B provides better visual recognition performance. For information-complex guide signs, such as those in interchange and tourist areas, Character A should ideally have the same height as Character B. In contrast, for information-simple guide signs in service areas, Character A should be designed at two-thirds the height of Character B.
Lei, Ziyi, Wang, Sijing, Zhao, Wenzheng, Zhang, Yunlong, Wang, Zhenxing, Ran, Jin
Study on Shaking Table Model Test of Seismic Dynamic Response of Loess Multi-Arch Tunnels2026-99-15849/11/2026
Taking the Nieye Multi-Arch Tunnel in Zhuoni County as the engineering background, this study systematically explores the seismic dynamic response characteristics of loess multi-arch tunnels through shaking table model tests. The test results show that: (1) The strain distribution of the surrounding rock is significantly different. Under a peak acceleration of 0.6 g, the maximum strain in the tunnel portal section is concentrated on the right side, which is related to the incident direction of seismic waves and the stress concentration at the bottom of the central wall; the maximum strain in the tunnel body section is located on the left side, affected by the propagation characteristics of seismic waves, burial depth, and unsymmetrical pressure. (2) The acceleration amplification factors in the Z and ZX directions show nonlinear changes. Under bidirectional excitation, the Wenchuan wave-ZX combination exhibits the strongest response. The variation trend of acceleration at the soil-rock interface varies with wave types, and the slope damage undergoes three stages: elastic stage, elastoplastic stage, and plastic damage stage. (3) The ratio ω of tunnel burial depth to central wall thickness is positively correlated with the strains at key positions. For the seismic design of loess multi-arch tunnels, special attention should be paid to sensitive areas such as the bottom of the central wall and the left side of the tunnel body. It is suggested to improve the structural seismic performance by optimizing the lining reinforcement and adapting to regional seismic wave types. The research conclusions provide a reference for the seismic design of such tunnels under complex geological conditions.
Han, Tao, Cao, Xiaoping, Zhang, Shulin, Yang, Zibin
Mechanical Properties and Freeze-Thaw Resistance of Modified Portland Cement-Stabilized Soil for Road Engineering2026-99-15809/11/2026
Subgrade soil is related to the load on the upper part of the road, and its properties will affect the road surface conditions. Frost-thaw action will damage the soil in cold regions. This study focuses on the fine-grained sand in Jilin affected by seasonal frost-thaw, and explores the effects of mixing amount (0% - 6%), curing time (7 days, 28 days), and frost-thaw cycle times (0, 5, 10, 20 times) on the DRM (dynamic resilient modulus) and UCS (unconfined compressive strength) of Portland cement-stabilized soil. The results are: the increase of mixing amount and the extension of curing time will both increase the UCS and DRM; frost-thaw cycles will reduce the UCS and DRM. Roads in cold regions need to use 4% modifier mixture for maintenance for 28 days to achieve strength stability. Heavy subgrades use 6% modifier to obtain the best stiffness load - bearing. This study has insightful guidance for subgrade material improvement in seasonal frozen soil regions.
Wang, Shujuan, Duan, Yonggang, Qin, Weijun, Shen, Ruoting, Jin, Chenguang
2025 5th International Conference on Logistics System, Traffic and Transportation (LSTT 2025)2026-99-15009/11/2026
TOC
Tobolski, Sue
Nc5-PCS Based Heterogeneous Point Cloud Matching for Roads2026-99-15339/11/2026
Point cloud registration represents a fundamental task in geospatial informatics and 3D computer vision, aiming to align heterogeneous point clouds through rigid transformation estimation. While Super-4PCS serves as an efficient coarse registration method, it exhibits limitations when handling large-scale datasets, planar-distributed point clouds, and scenarios with unknown scale differences. To overcome these challenges, this paper proposes the Nc-5PCS (Neighborhood-constrained 5-Point Congruent Sets) algorithm. Nc-5PCS first performs approximate scale estimation through concavity-convexity similarity analysis within coarse overlap regions, addressing the inherent scale limitation in 4PCS-based approaches. Subsequently, the algorithm employs 3D Harris feature point extraction to significantly reduce data volume while preserving critical geometric characteristics. The core innovation lies in designing a non-coplanar 5-point basis with a corresponding hash-based retrieval mechanism, effectively resolving the feature degradation problem caused by coplanar 4-point bases. Furthermore, normal vector angular constraints are incorporated to enhance consensus evaluation during correspondence selection, substantially improving registration accuracy. Experimental validation demonstrates that Nc-5PCS achieves a point-to-point RMS error of ≤ 0.227 m, outperforming Super-4PCS to provide superior initial alignment for subsequent ICP refinement.
Liu, Lei, Yu, Keguang, Li, Xinyi, Sun, Guangde, Zhao, Xinyuan, Zhu, Dongni, Fan, Yabo, Guo, Shihao
Analysis of Traffic Characteristics and Research on Variable Speed Limit Control Method in the Confluence Area of Expressway under Ice and Snow Conditions2026-99-15359/11/2026
This study investigates the traffic characteristics and delays within expressway merging areas during ice and snow conditions. Using VISSIM-based simulations, the effects of such conditions on merging zones are thoroughly examined. Regression models are developed to describe the relationships between ramp delay, mainline travel time delay, mainline traffic flow, average ramp delay, and mainline traffic volume. Findings reveal that across all environmental scenarios, ramp vehicle delay increases with rising mainline traffic, with this effect being markedly more pronounced under ice and snow. Specifically, when mainline traffic remains below 2800 veh/h, ramp delay increases gradually, but beyond this threshold, the delay escalates rapidly. Building on these results, a variable speed limit control method leveraging the Q-learning algorithm is proposed. The outcomes of this research offer valuable insights for expressway design and traffic management strategies.
Liu, Yan, Luo, Ruiqi
Design and Analysis on a Traction-type Power-assisted Follow-up Vehicle for Emergency Rescue2026-99-15479/11/2026
To address problems in China’s emergency rescue scenarios—such as limited functionality, insufficient mobility, poor adaptability to complex terrain, the labor-intensive nature of manual carrying, and the lack of flexibility of fully automatic carts—a traction-type emergency rescue power-assisted follow-up vehicle was designed and developed. With the core design goals of “lightweight, high mobility, and human-machine collaboration”, this power-assisted follow-up vehicle has multiple advantages. At the structural level, it supports rapid folding and unfolding, enabling convenient operation and adaptation to transportation needs in various emergency rescue scenarios. In terms of material selection, it balances strength and lightweight properties, and its key components possess anti-cutting and flame-retardant capabilities, allowing adaptation to the harsh environment of emergency rescue. The power system adopts modular replaceable batteries and is equipped with a high-performance control unit, motor, and shock-absorbing suspension design. This enables normal operation in a variety of complex terrains. The control system is centered on human-machine collaboration. It features simple operation and automatic adjustment of operating status, effectively reducing the operational burden and physical exertion of rescuers. Meanwhile, it supports the master-slave expansion function, allowing flexible switching from a two-wheel structure to a four-wheel structure to meet diverse rescue needs such as material transportation and casualty transfer. This power-assisted follow-up vehicle can effectively solve the material transportation problem in the “last few kilometers” of emergency rescue.
Xu, Jiang, Hou, Yumeng, Yang, Han
Numerical Investigation of In-Plane Antisymmetric Failure Modes and Load-Carrying Mechanisms of Steel Portal Piers2026-99-15949/11/2026
A nonlinear finite element model was applied to study the in-plane instability of steel portal piers, in which initial geometric imperfections, welding residual stresses, and material nonlinearity were considered. The modeling procedure was compared with experimental results from box-section members, and consistent tendencies in load level and deformation evolution were observed. In the numerical analyses, the initial elastic buckling configuration exhibited an in-plane antisymmetric form. As loading continued beyond the elastic range, this deformation pattern persisted. With further loading, the deformation remained purely axial while combining compression with bending. During this stage, plastic hinges appeared near the column tops, while lateral displacement became clearly observable. Comparison models with different geometric proportions show that variations in the span-to-height ratio and the beam–column stiffness ratio influence how instability develops and where plastic deformation tends to localize. From a design perspective, these trends can be considered when distinguishing instability characteristics and selecting stiffness proportions between beams and piers.
Li, Jie, Shangguan, Bing, Cheng, Zhangxu, Ruan, Furong, Bai, Fan
Analysis of Capacity of Train Operation at Junction under the Virtual Coupling System with Speed Limit Difference and Train Sequence2026-99-15209/11/2026
A railway junction is a crucial point on a railway network where multiple routes intersect and many train services run through it. Its connectivity to different railway routes can increase demand and traffic in shared corridors, turning the junction into a bottleneck. Upgrading the signalling system is one of many solutions to manage the traffic utilization and increase the capacity at the junction. The Virtual Coupling System (VCS), as the latest signalling technology, has proven to improve the capacity of the railway. However, many junction-related factors remain inadequately addressed. In this paper, we introduce the constraint of differences in speed limits between the main route and the secondary route to design a merging process in which three trains from different routes can start merging or coupling into VCS mode as they approach the converging point at a junction under different train sequence scenarios. A Finite State Machine (FSM) model is developed to control the train motion under VCS. Secondly, simulations are performed to compare the travel time required for the following train to reach the last milepost under VCS with that under the traditional Moving Block (MB) system, as well as to compare overall capacity. The simulation results show that the second and third trains can arrive at the final milepost earlier under VCS mode than under the MB system. In addition, the theoretical operational capacity under VCS mode improves compared to MB mode when a proper train sequence design is selected.
Jaimonkong, Nitipat, Ketphat, Naphat
Emotional Impacts of Manual and Assisted Driving Modes under Varying Time Pressures: A Scenario-based Simulation Study2026-99-15089/11/2026
Emotion as a critical psychological variable in driving behavior has been extensively confirmed to exert a profound influence on traffic safety. With the advancement of autonomous driving technologies, the application value of emotion regulation mechanisms in intelligent transportation systems is gaining importance, given their proven impact on reducing unsafe driving tendencies and improving human-machine interaction quality. However, systematic research on the mechanisms underlying emotional variation across different driving modes remains relatively scarce. This study developed a questionnaire based on the Chinese version of the Driving Anger Scale (DAS), incorporating 19 traffic scenarios and corresponding video stimuli, to examine the impact of manual and assisted driving on driving anger under varying levels of time pressure. In addition, the moderating effects of individual factors such as age and education were analyzed. Descriptive statistics, independent samples t-tests, and one-way ANOVA were applied to 113 valid responses to construct a three-dimensional analytical framework involving driving mode, time pressure, and demographic variables. The results indicate that under high time pressure, assisted driving systems significantly reduce drivers' anger levels in typical delay-related scenarios compared with manual driving. Age is identified as a key moderating factor influencing emotional responses. This research provides theoretical support for the development of emotion-aware driving intervention systems and offers empirical evidence for the formulation of future strategies for driving emotion regulation.
Zhang, Tingjia, Li, Ruiheng, Zhu, Tong
Application of Phosphogypsum as Filling Materials in Roadbed Engineering2026-99-15069/11/2026
Using modified phosphogypsum (PG) as a filler material may be the most effective approach for large-scale utilization. To verify the feasibility of this method in subgrade engineering, a series of theoretical and experimental investigations were carried out. First, a comparative analysis of the physical properties of raw and modified PG was conducted via direct shear and compaction tests. Subsequently, the modification mechanism was analyzed qualitatively, and the optimal proportion of the modifier was determined. Finally, the impact of compactness on the strength of modified PG was evaluated quantitatively. The research shows that the mechanical properties of raw PG—characterized by an optimal moisture content of 15.3% and a maximum dry density of 1.65 g/cm^3—are significantly influenced by moisture content. Mixing phosphogypsum with Portland cement is an effective modification method. The 7-day compressive strength of compacted modified PG with a 5% cement content reaches 2.5 MPa. Compactness serves as a key control index for determining the engineering performance of PG as a filling material. Once compactness drops below 80%, modified PG fails to develop effective strength. Based on reasonable construction procedures, the application of modified PG as a subgrade filling material is technically feasible.
Zhang, Zeyi, Yang, Qibing, Cheng, Shufan
Research on Heavy-Haul Train Operation Adjustment Considering the Degree of Chaos in Train Timetable2026-99-15229/11/2026
Heavy-haul railway development is as important a strategic direction for China’s railway sector as high-speed railway development. With the continuous expansion of heavy-haul railway operational mileage and the growing transportation demand, the complexity of operational adjustment in heavy-haul railways continues to escalate. The operational adjustment for heavy-haul trains subjected to speed restrictions following maintenance windows, aimed at maximizing the restoration of timetable regularity and guaranteeing freight volume, constitutes a critical and urgent research problem. Grounding on the operational principle of heavy-haul railways that prioritizes freight volume preservation over strict punctuality, this paper proposes a rescheduling model that incorporates the timetable disruption level. By adopting the order entropy theory, the model is formulated to minimize the total system disruption level and freight time cost, thereby framing the rescheduling problem as an order entropy optimization problem. The train disruption level is a metric that quantifies the perturbation intensity of a rescheduled timetable relative to the original operational plan within a given railway section. By initializing the entropy value of the pristine operational order to zero, any subsequent entropy variation directly facilitates a systematic investigation into the evolution of train operational order. Effective timetable adjustment strategies are subsequently derived, contingent upon the available buffer time and freight volume constraints. Guided by actual operational timetables and sectional line characteristics, this research designs a case study. The Gurobi solver is employed to obtain a rescheduled heavy-haul train timetable that successfully restores the original freight volume. The proposed methodology contributes to the enrichment of railway transportation organization theory and provides robust decision-making support for the strategic deployment of heavy-haul train services.
Fu, Lu, Lin, Li, Xu, Shichao, Ji, Guanggang, Li, Zheng
Optimizing Dispatch Frequency of Feeder Buses for Integration2026-99-15749/11/2026
In the context of urban multi-modal transportation systems, the optimization of the integration between urban rail transit and feeder bus services remains a critical challenge for improving service quality and operational efficiency. The present study investigates the frequency optimization of a dedicated feeder bus line during the morning peak period, considering heterogeneous passenger arrival patterns from both random street arrivals and scheduled rail-to-bus transfers. A bi-objective non-linear programming model is proposed to minimize total passenger travel costs and operating costs for the bus system. The model incorporates heterogeneous passenger arrivals at stops, ensuring a realistic representation of feeder line usage. It also distinguishes between transfer and non-transfer passengers, who have different perceived waiting costs derived from queuing and scheduling principles. To evaluate the model, numerical experiments based on simulations are conducted under varying metro transfer intensities. These scenarios are created by applying scaling factors to the original station-level arrival data to approximate different levels of rail-to-bus demand propagation. Results demonstrate that Higher transfer intensity leads to shorter optimal dispatch intervals and a marginal increase in total operating cost, reflecting the additional service pressure from metro-induced demand. The framework provides flexible control through weighting parameters and can guide transit agencies in balancing service quality with cost-efficiency under different demand profiles.
Guo, Xiao, Zhang, Jing
Real-time Vehicle Speed Detection Based on YOLOv11 and DeepSORT2026-99-15959/11/2026
The technology of real-time and effective vehicle speed detection is considered a key technology to improve traffic monitoring efficiency and traffic safety management grade. To address the limitations of traditional speed detection schemes—including reliance on dedicated hardware, poor environmental adaptability, and high construction and maintenance costs—this paper proposes a r10eal-time vehicle speed detection system based on YOLOv11 and the DeepSORT algorithm. The proposed system uses the YOLOv11 target detection algorithm as its primary model. DeepSORT multi-target tracking technology is integrated to enhance tracking performance. Speed measurement is implemented using a virtual detection line. This approach enables accurate vehicle detection, continuous tracking, and real-time speed measurement within video frames. Through the experiments, the result shows that the improved YOLOv11n model reaches mAP@0.5 of 0.982 and a recall rate of 0.956 in the test set, higher than the YOLOv8n and YOLOv5s models. The speed detection error can be restricted to 3 km/h, satisfying the real-time detection need. There is no need for road surface modification, and the detection system has a flexible layout, providing a dynamic basis for traffic law enforcement and traffic data support for road construction and traffic control optimization.
Jin, Guowei, Ma, Wenlong, Jiang, Dali, Li, Nan
Numerical Simulation Study on Borehole Wall Stability of Ultra-Large Diameter Deep Bored Piles in Thick Sand Strata2026-99-15829/11/2026
Taking the newly constructed Maanshan Yangtze River Highway-Railway Dual-Purpose Bridge — a three-tower steel truss cable-stayed bridge with two main spans of 1120 meters — as the research object, this study systematically explores the influencing factors and evolutionary characteristics of hole wall stability for large-diameter bored piles in thick sand layers. The research results reveal the following mechanisms: with the expansion of pile diameter, the hole wall generates greater deflection, the soil’s internal arch effect is gradually attenuated, soil cohesion decreases, and the plastic zone of the soil surrounding the pile shows a tendency of outward extension, collectively increasing the susceptibility to hole collapse. To maintain hole wall stability, the resultant force of the internal circular arch support and mud pressure must exceed or equal the total lateral pressure, including active earth pressure, formation water pressure, and ground surcharge-induced lateral pressure. Notably, soil shear strength and mud relative density are two dominant factors controlling hole wall stability, and a positive correlation exists between these two parameters and stability. Specifically, a mud relative density range of 1.15–1.25 is recommended for practical construction. These findings offer valuable technical references for the design and construction of similar large-diameter bored pile projects in thick sand layers.
Ye, Tao, Wang, Ruyi
Site Selection Method for Solid Waste Processing Plant of Highway Reconstruction and Expansion Project2026-99-15869/11/2026
The highway reconstruction and expansion project is accompanied by the generation of a large amount of construction solid waste. The unreasonable site selection of solid waste processing plants will increase the social, environmental, and economic burden. Taking a highway reconstruction and expansion project in Guangdong Province as an example, this study uses the combination of the analytic hierarchy process and the layer superposition method to extract the influencing factors of site selection, such as geological conditions, natural conditions, hydrological conditions, traffic conditions, and resource conditions, according to relevant specifications, and uses the analytic hierarchy process to quantify each influencing factor. From the relevant research data, official public information, and other channels, we comprehensively collected the data of topography, climate, geology, land use planning, and other aspects of Guangzhou and Dongguan along the project. With the help of buffer analysis tools and overlay analysis tools of GIS software, the optimal decision results were determined. The research results show that using this method to analyze the site selection of the relying project, the factory site selection should be located in Wangniudun Town near the project line, which has comprehensive advantages. The site selection method of a solid waste processing plant for an expressway reconstruction and expansion project proposed in this paper comprehensively considers the influence of 10 sub-factors on the site selection, and has been successfully applied to the site selection decision of an expressway reconstruction and expansion project in Guangdong Province. The final site selection result is more professional and objective than the previous site selection method, which effectively solves the site selection problem of a solid waste processing plant under the influence of economic factors, social factors, municipal factors, and environmental factors.
Zhang, Yuping, Yang, Ming, Zeng, Siqing, Long, Hao, Liu, Yuanqing, Zhao, Qiu
Study on Rapid Formation Generation Method for Multi-UAV Swarms2026-99-14219/11/2026
This paper presents a generalizable geometric framework for rapid on-demand generation of multi-UAV formations with arbitrary 2D geometries and user-specified scalable scales. First, vertices, edge intersections and edges are extracted from a user-defined formation template to enable parametric description of both simple and composite formation geometries. Second, boundary interpolation, edge expansion and recursive internal expansion are integrated to synthesize hierarchical multi-layer UAV deployment point sets under a controllable expansion ratio. Third, a geometric distortion metric is proposed to optimize UAV node indexing and formation reconstruction while preserving inter-node topological consistency. Algorithmic derivations, complexity analysis and simulation assumptions are further elaborated. Simulation results verify that the proposed method preserves geometric fidelity of target formations while delivering superior scalability and spatial coverage, rendering it well-suited for emergency transport, aerial surveying and low-altitude cooperative missions in dense urban environments.
Fu, Mingyi, Zeng, Guoqi, Gu, XinZhu, Wang, Jia
2025 International Conference on Intelligent Equipment, Vehicle Engineering and Automation Control2026-99-11009/11/2026
TOC
Tobolski, Sue
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