Browse Topic: Transportation Systems

Items (5,447)

SAE TOMORROW TODAY UNPLUGGED - No Manual Controls: A Firsthand Look at Autonomous Mobility

1359411/6/2026

No pedals. No steering wheel. No manual controls. In this Unplugged episode of SAE Tomorrow Today, host Grayson Brulte takes the show on the road from inside a Tesla Cybercab in Austin, Texas, to get a firsthand look at what it's like to ride in an autonomous vehicle designed without manual controls. From watching movies and making phone calls to simply sitting back and enjoying the ride, Grayson explores how autonomous vehicles could change the passenger experience and how people use their time on the road. But is this the future of mobility or a glimpse of what could be? The bigger question is how the technology, public perception, and regulations will evolve from here. Have your own thoughts on this topic? We'd love to hear from you! Share your comments, questions, or ideas for future topics with Grayson on Twitter or send them to podcast@sae.org. Follow SAE on LinkedIn, Instagram, Facebook, X, and YouTube. Follow host Grayson Brulte on LinkedIn, X, and Instagram.

Patterson, Lori

Investigation of Time-varying Limitations in Intelligent Ship Automatic Berthing Control

2026-99-0626

11/6/2026

A backstepping control method combining a time-varying tangent barrier Lyapunov function (BLF) and dynamic surface control (DSC) technology is proposed to address the issue of automatic berthing control of underactuated intelligent ships with unknown time-varying environmental interference and limited position and speed. This approach aims to improve the control accuracy and response speed of the system. First, in order to handle the challenging challenge of controller design, the mathematical model is modified using differential homeomorphism transformation with an eye toward the underactuated properties of ships. Second, the tangent BLF is developed to realize the constraint of the ship’s location and speed error and guarantee the system’s safety by building the time-varying constraint border with exponential decay. When combined with DSC technology, the 'differential explosion' problem, which is common in the backstepping design process, is solved. On this premise, the extended state observer (ESO) is used to estimate and correct for the unknown time-varying disturbance. Lyapunov stability theory proves that the closed-loop system is stable, and the closed-loop signals are bounded. The simulation results show that the suggested control approach has a faster response time than the classic backstepping method and can provide safe and stable autonomous berthing of ships while meeting the limitations, indicating good engineering practicality.

Xu, Donghao, Xu, Yirong

An Intelligent Scheduling Optimization Method for High-Speed Railway Beam Yards Integrating Dijkstra Algorithm and Linear Programming

2026-99-0636

11/6/2026

As the core facilities for prefabricated box girder production, highspeed railway beam yards are confronted with multiple practical challenges, including large-scale operation, intricate production processes, and frequent dynamic interferences in construction. Traditional manual scheduling methods are unable to achieve optimal allocation of production resources and efficient coordination of the entire production chain. In view of this problem, this paper proposes an intelligent scheduling optimization method that combines the Dijkstra algorithm with linear programming, and constructs a coordinated scheduling system that covers the whole process of “girder erection-girder fabrication-girder storage”. Supported by BIM+GIS digital twin technology, this system integrates multisource data from the Internet of Things (IoT) and production management platforms. In the system, the Dijkstra algorithm is used to dynamically plan the optimal path for girder erection, while a linear programming model is adopted to realize precise scheduling of production resources. Taking the production task of 1,672 box girders at the Baohui Beam Yard as an engineering application case, the results show that this method can improve the girder erection efficiency by 20%, raise the utilization rate of production resources by 15%, and reduce the process waiting time by 30%. It effectively solves the prominent problems of traditional scheduling, such as resource idleness and construction schedule delays, and thus provides theoretical support and practical reference for the development of intelligent construction 2.0 in high-speed railway beam yards.

Yi, Dongbo, Ma, Tengyue, Li, Yang, Yu, Ziqi, Li, Linsen

Cooperative Adaptive Cruise Control for Connected Vehicle Platoons with Unknown Control Directions Under Output Constraints

2026-99-0624

11/6/2026

In this paper, a distributed cooperative adaptive cruise control (CACC) strategy is designed for connected vehicle platoons under unknown control directions and time-varying speed constraints. To address vehicle control directions unknown problem arising from uncertain actuator and vehicle parameters, a Nussbaum-type gain is incorporated into the controller design processes, enabling stable operation without prior knowledge of the vehicle direction. Furthermore, the barrier Lyapunov function is employed to enforce speed constraints, ensuring all vehicles remain within safe and admissible velocity bounds. The designed leaderless scheme allows all vehicles to participate equally in coordination, enhancing robustness and scalability under a bidirectional communication topology. Finally, a simulation result is proposed to validate the effectiveness of the CACC strategy.

Li, Xin, Wei, Xiaozong, Chen, Si, Yang, Shaopeng, Liu, Mingyang, Zhu, Liangkuan

Run Time Assurance Filter Framework for Collision Avoidance of Unmanned Aerial Vehicles Using Reinforcement Learning

2026-99-0620

11/6/2026

In recent years, Reinforcement Learning (RL) has been increasingly applied to the collision avoidance systems of Unmanned Aerial Vehicles (UAVs) due to its high performance in complex tasks and relatively low online computational cost. Despite these advantages, the lack of interpretability in RL and decision-making processes poses significant challenges to safety verification, which severely limits the practical deployment of RL-based autonomous flight systems in safety-critical scenarios. Ensuring safety during both training and testing remains the key for real-world applications. To address this issue, a Run Time Assurance (RTA) filter framework for a UAV collision avoidance system based on RL is proposed. The framework continuously monitors the avoidance actions generated by RL and ensures that unsafe actions can be identified and corrected in real time. The framework provides security while retaining the performance advantages of RL. First, a discrete kinematics model of the UAV and a collision avoidance environment for a three-dimensional multi-intruder UAV are established. The Proximal Policy Optimization (PPO) algorithm is used to train the UAV avoidance policy. Secondly, the RTA filter with safe constraints is designed based on this model. To reduce the position error between the discrete kinematics model and the continuous dynamics model of the UAV, optimization is performed using the Sequential Least Squares Programming Method (SLSQP). The RTA is applied to the training and testing phases of UAV collision avoidance systems to monitor and correct unsafe actions online. Finally, three training and testing methods are set: no RTA, RTA without punishment, and RTA with punishment. Comparing different relaxation coefficients allows for analyzing their impact on filter performance. Simulation results demonstrate that the RTA effectively enhances safety throughout training and testing. Compared with the no RTA method, the collision rate is reduced by 7.04%, and the success rate is increased by 2.68%. In extreme collision avoidance scenarios, the average collision rate obtained by different reinforcement learning algorithms is reduced by 21.46%, and the average success rate is increased by 15.54%.

Ma, Zan, Yan, Liqin, Bai, Jie, Liu, Yubin, Sun, Shuguang

Vehicle Trajectory Prediction Strategy Based on Spatio-Temporal Graph Attention for Complex Intersection Scenarios

2026-99-2215

11/6/2026

The development of the low-altitude economy presents abundant opportunities for data acquisition in Intelligent Transportation Systems (ITS). High-density interactions among heterogeneous traffic participants at complex urban intersections pose significant challenges for autonomous vehicle trajectory prediction. Existing Graph Neural Network (GNN) models often struggle to adequately capture interaction variances and global spatial dependencies among these heterogeneous agents. To address this, we propose STGANet, a Spatial-Temporal Graph Attention Network integrating Transformer-based multi-head attention with graph convolutions. STGANet employs a local-global feature extraction strategy: a dynamic multi-group GCN first extracts multi-semantic local spatial information, while a temporal attention mechanism captures long-term sequential dependencies. A feature fusion gate then adaptively integrates these spatio-temporal features. Subsequently, a global spatial multi-head attention module is applied to thoroughly mine the overarching heterogeneous interaction dynamics. Evaluated on the real-world ApolloScape trajectory dataset, STGANet demonstrates superior predictive performance in heterogeneous traffic flows. Compared to the baseline GRIP++ model, it reduces the Weighted Sum Average Displacement Error (WSADE) and Weighted Sum Final Displacement Error (WSFDE) by approximately 9% and 19%. Furthermore, with an average inference time of 12.8 ms, STGANet achieves high precision while strictly satisfying the real-time latency constraint (< 20 ms) required for practical autonomous driving applications.

Ou, Jingyi, Ou, Sijia, Zhang, Zhili, Zhu, Wenbo, Yu, Wei, Xie, Kan

Dynamic SFC Deployment in Low-Altitude Communication Network with A3C and GAT

2026-99-2206

11/6/2026

Low-altitude Communication Network (LCN) refers to network systems that employ drones and other low-altitude aerial platforms as carriers. Leveraging advanced communication technologies and data processing methodologies, these networks enable high-efficiency data transmission in low-altitude airspace, thus emerging as a pivotal driver for the advancement of the low-altitude economy. With the continuous advancement of Unmanned Aerial Vehicle (UAV), artificial intelligence, and communication technologies, LCN have been increasingly integrated into smart city construction, Internet of Things expansion, emergency management, and other fields. As a core component of these sectors, LCN have effectively driven the robust development of the low-altitude economy. Within the context of LCN, the efficient deployment of Service Function Chain (SFC) emerges as a critical factor in optimizing network service capabilities and enhancing resource utilization efficiency. In the dynamic and complex operating environment of LCN, reasonable and efficient SFC deployment can effectively coordinate the allocation of communication, computing, and storage resources, laying a solid foundation for the stable and high-quality operation of various network services. However, existing deployment algorithms either fail to fully consider the dynamic changes in the LCN or lack sufficient exploratory strategies, making them difficult to adapt to the diverse business scenarios within the LCN. To address the issue, our study proposes a dynamic SFC deployment method based on the Asynchronous Advantage Actor-Critic (A3C) and Graph Attention Network (GAT) algorithms. The experimental findings indicate that our proposed algorithm achieves a notable reduction in orchestration expenses, while simultaneously enhancing resource utilization, thus exhibiting excellent performance and robust adaptability in dynamic LCN environments.

Yang, Zihan, Yin, Jianhui, Yu, Chengxiao, Hu, Jinju, Liu, Ying

Integrating Dual-Stream Coordinate and Cross-Spatial Attention for Drone-View Traffic Detection

2026-99-2205

11/6/2026

Unmanned Aerial Vehicles (UAVs) are essential for traffic monitoring in Intelligent Transportation Systems (ITS). However, the detection of traffic objects in drone-view imagery still faces serious challenges due to drastic scale variations, dense small objects, and complex background clutter. Existing detectors often struggle to effectively separate targets from background noise and lack efficient cross-scale feature interaction mechanisms. This paper introduces ED-DETR, a refined real-time Detection Transformer specifically designed to optimize performance in UAV scenarios. Specifically, a Dual-Stream Coordinate Attention (DCA) module is designed, which can effectively extract significant texture features while preserving context information through parallel maximum pooling and average pooling operations. In addition, this paper introduces an efficient multi-scale attention structure in the feature fusion neck, which combines grouping convolution and cross-spatial learning to significantly improve the positioning ability of small targets. A large number of experiments on the VisDrone2019 dataset show that ED-DETR achieves an mAP of 40.4%, which is significantly higher than that achieved by RT-DETR and other state-of-the-art detectors. By harmonizing high detection accuracy with low computational overhead, the proposed framework enables effective real-time monitoring of aerial traffic scenarios.

Jiang, Haiming, Zhu, Liang, Liu, Jianhua

SAE Micromobility Harmonization and Regulation Recommendations

J3385_202611 (Current)

11/4/2026

This SAE Information Report establishes best practices and key recommendations for the regulation of micromobility devices. The scope is focused on improving consumer safety and clarifying the distinction between electric bicycles and other motor vehicles. Specifically, this report recommends: (a) defining the 750-W motor limit for low-speed electric bicycles as a measure of peak power, not continuous power; (b) mandating electrical system and battery certification to established safety standards such as UL 2849 and UL 2271; and (c) excluding electrical systems and batteries of micromobility devices and electric bicycles from “Right to Repair” mandates to mitigate the risks of fire and injury from improper servicing.

Micromobility Battery Standards Committee

Optimization of Airport Surface Operations for Multiple Flight-Test Aircraft Based on a Wolf Pack Algorithm

2026-99-2357

10/30/2026

To improve the efficiency of airport surface operations involving multiple aircraft types and multiple flight-test aircraft at the same airport, this study investigates the taxi-route optimization problem for flight-test aircraft. First, a runway-exit-time optimization model is established by modeling the landing rollout process, with minimum runway-occupancy time as the objective, so as to determine the optimal rapid-exit taxiway. Second, a multi-aircraft taxi-route optimization model is formulated by incorporating taxi-conflict constraints and is solved using an improved wolf pack algorithm. The case study shows that the proposed method can effectively reduce the total taxi time of multiple flight-test aircraft and shorten the runway-occupancy time of arriving aircraft, thereby demonstrating good feasibility and practical engineering value.

Wang, Tong

Pressure-Type Anchors in Weathered Rock for Transportation Infrastructure

2026-99-2366

10/30/2026

In transportation infrastructure constructed in mountainous and rocky regions, such as highway slopes, railway cuttings, bridge abutments, and tunnel portal slopes, uplift-resistant anchorage systems are widely required to ensure structural stability and service safety. To support anchorage design in such conditions, this study investigates the uplift bearing behavior, load-transfer mechanism, and key design parameters of pressure-type rock anchors in weathered rock strata through a combined field-and-numerical approach. A rock anchorage project in mountainous terrain in Shaoxing, Zhejiang Province, China, was adopted as the prototype case, and two representative anchors installed in strongly weathered and moderately weathered tuffaceous sandstone were selected for field pullout testing and three- dimensional finite element simulation. The failure characteristics, uplift load–displacement response, axial strain distribution of the grout body, and the effects of anchorage length and rock-socketed length were systematically examined. The results show that pressure- type rock anchors exhibit favorable uplift resistance in weathered rock strata. No overall pullout failure occurred during the tests, and no obvious cracking or significant ground deformation was observed. The uplift load–displacement curves exhibited a pronounced steep- transition pattern, and the axial strain of the grout body was mainly concentrated near the bearing plate and attenuated upward along the anchorage section. When the anchorage section extended into the moderately weathered rock stratum, strain attenuation became faster and interfacial load transfer became more efficient. Parametric analysis further indicates that the uplift bearing capacity increases approximately linearly with anchorage length before a critical anchorage length is reached, whereas the increase becomes much less significant beyond about 8 m. In addition, a proper increase in rock- socketed length can significantly improve the uplift bearing capacity. The findings provide useful reference for the design and optimization of uplift-resistant anchorage systems in transportation infrastructure founded in layered weathered rock.

Feng, Bing, Li, Panfeng, Zhou, Ji’an, Lv, Qing

Microstructure and Properties of CoCrFeNi/WC Cemented Carbides

2026-99-2308

10/30/2026

Traditional cemented carbides struggle to simultaneously improve hardness and toughness, and cobalt scarcity further limits their industrial production. To address these limitations, we utilize CoCrFeNi (with good ductility) as the binder phase to fabricate CoCrFeNi/WC cemented carbides, and regulate sintering temperature (1100-1200 °C) and holding time (3-10 min) to tailor the microstructure and mechanical properties, focusing on the occurrence of residual binder phase. The results indicate that sintering parameters significantly affect the morphology and content of residual binder phases: elliptical phases form at 1100 °C, while strip-like phases dominate at 1150-1200 °C. Specifically, the MEA3 sample sintered at 1200 °C for 10 min achieves the best mechanical balance (Vickers hardness: 2281 HV; fracture toughness: 12.2 MPa·m^1/2), attributed to reduced residual binder phase fraction and enhanced densification, which improve interfacial bonding. In contrast, a relatively high content of residual binder phases induced by lower temperatures (e.g., 1100 °C) or inappropriate holding times degrades mechanical properties. Microstructure analysis confirms that rational sintering optimization is key to controlling residual binder phase evolution and realizing high-performance cemented carbides. This study provides an experimental basis for the industrial production of high-performance WC-based carbides.

Sun, Yifeng, Li, Pengyan, Ma, Zhaolong

Suppression of Traffic Oscillations by Vehicular Platoons with Periodic Control Configuration

12-10-01-0003

10/21/2026

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 Systems

2026-99-2990

10/19/2026

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 Logistics

2026-01-7549

9/22/2026

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 Autonomy

2026-01-7503

9/22/2026

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 Trip

135859/22/2026

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 AI

135869/22/2026

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 Applications

2026-24-0010

9/21/2026

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 Review

2026-24-0025

9/21/2026

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 Crowdshipping

2026-24-0029

9/21/2026

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 Vehicles

J3016_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 Stability

09-15-01-0003

9/17/2026

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 Conditions

2026-99-1136

9/11/2026

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 Forecasting

2026-99-1583

9/11/2026

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 Systems

2026-99-1141

9/11/2026

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 Rail

2026-99-1516

9/11/2026

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 Model

2026-99-1564

9/11/2026

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 Bridges

2026-99-1513

9/11/2026

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 CenterTrack

2026-99-1102

9/11/2026

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 YOLOv11s

2026-99-1129

9/11/2026

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 Terrain

2026-99-1130

9/11/2026

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 Rules

2026-99-1140

9/11/2026

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 Characteristics

2026-99-1541

9/11/2026

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 Extension

2026-99-1548

9/11/2026

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 Technology

2026-99-1536

9/11/2026

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 Delay

2026-99-1521

9/11/2026

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 City

2026-99-1551

9/11/2026

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 Technology

2026-99-1518

9/11/2026

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 Model

2026-99-1555

9/11/2026

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 Extension

2026-99-1559

9/11/2026

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 Method

2026-99-1120

9/11/2026

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 Vehicle

2026-99-1111

9/11/2026

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 Method

2026-99-1560

9/11/2026

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 Tunnels

2026-99-1584

9/11/2026

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 Engineering

2026-99-1580

9/11/2026

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)

2026-99-1500

9/11/2026

TOC

Tobolski, Sue

Nc5-PCS Based Heterogeneous Point Cloud Matching for Roads

2026-99-1533

9/11/2026

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 Conditions

2026-99-1535

9/11/2026

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

Items per page:

1 – 50 of 5447