Browse Topic: Roads and highways

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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
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
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.
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
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
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
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
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
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
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
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
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
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
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
Experimental Analysis of Tube Temperature and Heat Transfer Performance of L-Shaped Gravity Heat Pipes2026-99-15119/11/2026
Gravity heat pipes achieve efficient energy transfer through the evaporation and condensation of their internal working fluid, which steadily conducts underground heat to the surface and thereby provides a continuous and stable heat source for road pavements in winter. Considering the snow and ice melting demand of road surfaces in winter, this paper establishes an indoor environmental simulation experimental platform to systematically investigate the influence laws of different working fluids on the start-up temperature, start-up pressure, heat transfer power, and other key performance indicators of L-shaped gravity heat pipes. Through experimental research and analysis, it is revealed that heat pipes with R-134a and R245fa working fluids can operate stably at a shallow geothermal temperature of about 25 °C, while the acetone working fluid heat pipe operates unstably under this condition. The heat pipe filled with R-134a working fluid achieves the maximum heat transfer power under shallow geothermal conditions, followed by the heat pipe filled with R245fa. Although the heat transfer power of the acetone-filled heat pipe is generally relatively low, its heat transfer power increases most significantly with the rise of the evaporation section temperature. Under low-temperature conditions, the thermal conductivity of the evaporation section increases with the rise in the heating temperature of the evaporation section, while that of the condensation section decreases with the increase in the heating temperature of the evaporation section. Through experimental research and comparative analysis, this paper deeply explores the application potential of gravity heat pipe technology in green highway construction, and evaluates the feasibility and economic benefits of its engineering implementation, which provides a scientific basis and engineering guidance for the selection of green energy in future infrastructure construction.
Wang, Zhen-kun, Yuan, Zhi-ming, Wang, Kang, Zhang, Wen-jun, Wu, Xiang-song, Liu, Guang-bo
Spatial Sight Distance Value for Curved Tunnel of Mountainous Highway Based on Driving Behaviour2026-99-15539/11/2026
In order to conduct more in-depth research on the driving sight distance of curved tunnels in mountainous highways, a systematic theoretical calculation model of spatial sight distance of curved tunnels based on three-dimensional characteristics is established, and the spatial sight distance value of curved tunnels in mountainous highways is recommended in combination with the changes of driving behaviour under different spatial sight distances. Firstly, the concept of spatial sight distance of curved tunnels is proposed, the theoretical calculation model of spatial sight distance of curved tunnels is established, and the model is verified by a multi-scale neural network; Secondly, five UC-win/road simulation models of curved tunnel with different spatial sight distances are established, and the simulation experiments are carried out in combination with mp160 multi-channel physiological recorder and SMI etgtm eye tracker; Finally, the mathematical statistics method and SPSS software are used to analyse the operation behaviour, psychological behaviour and eye movement behaviour of drivers in curved tunnels with different spatial sight distances, and to verify the different effects of the critical value of spatial sight distance on driving behaviour in the theoretical calculation. Furthermore, by taking the spatial sight distance as the independent variable, the regression model is established with the average speed, trajectory offset, heart rate change rate, and pupil diameter change rate as the dependent variables. Based on the driver’s behaviour threshold, the recommended spatial sight distance of a curved tunnel is proposed. The results show that the recommended range of spatial sight distance of the curved tunnel of mountainous highway with a design speed of 80 km/h is 125 m to 140 m, the limit value is 110 m, and the appropriate value is 155 m. There is a critical value between two-dimensional sight distance and spatial sight distance, which has a significant impact on the change of driving behaviour in a curved tunnel.
Tang, Xie, Zheng, LiWen, Lin, GuoJin, Gao, YanYang, Lan, FuAn
DisReID: Single Domain Generalizable Person Re-ID Method for Highway Construction & Operation2026-99-15309/11/2026
With the advancement of computer vision technologies and the widespread deployment of video surveillance systems, traffic safety and the development of intelligent highways have been significantly enhanced. As a key component of the intelligent video analysis module in smart highways, person re-identification (re-ID) addresses critical challenges, including cross-segment tracking of pedestrians illegally using emergency lanes, multi-camera joint searches for lost persons in service areas, and trajectory tracing of individuals involved in traffic accidents. These functions directly support the core goals of "safety assurance and efficient service" for smart highways. However, due to the complexity of the application scene, its generalization to unseen environments remains a core challenge. This problem is formally studied under the setting of Single-Domain Generalizable Person Re-identification (SDG re-ID), which aims to train a model on a single source domain that can perform well on arbitrary unseen target domains. To handle this issue, this paper proposes a novel Disentangled Augmentation re-ID Framework (DisReID) that disentangles and augments both structure and style. Specifically, DisReID consists of two modules: Structure-aware Viewpoint Simulation (SVS), a novel pre-processing technique that simulates cross-camera perspective changes by perspective transformation, diversifying geometric structure without harming identity semantics; and Style-Dominant Frequency Perturbation (SFP), which selectively focuses on the style-dominant frequencies and applies perturbation to enable controllable style augmentation while preserving structure cues. Furthermore, to alleviate the BN-induced domain bias, we introduce a simple yet effective test-time adaptation strategy, termed Cluster Fine-tuning (CF), that performs unsupervised clustering on target-domain features to assign pseudo-labels and subsequently fine-tunes the model, enhancing adaptability to unseen domains. Extensive experimental results on four public datasets demonstrate that our DisReID achieves superior generalization performance compared to the state-of-the-art methods. This work provides key technical support for the large-scale application of re-ID in smart highways, advancing the goal of "full-domain perception and intelligent collaboration".
Pan, Hong, Yu, Fangying
Assessment Model for Fitness for Work of Construction Personnel in Expressway Bridge Engineering Projects2026-99-15099/11/2026
To mitigate safety risks inherent in highway bridge construction, this research establishes a practical framework for assessing workers’ fitness for work. Using grounded theory, we analyzed interview records and documented accident cases through systematic coding, identifying critical indicators spanning physiological states, safety training effectiveness, and atypical behavioral markers. Rather than relying on single-method approaches, we combined Delphi expert consultation with entropy weighting to capture both professional judgment and data-driven variance, thereby reducing bias while preserving information richness. The resulting assessment protocol enables quantifiable classification of workers into distinct risk tiers. Implementation at the Zhangjinggao Yangtze River Bridge demonstrated the system's discriminatory power through field data collection and direct behavioral monitoring, successfully segmenting the workforce into low-, medium-, and high-risk categories. Results suggest the tool functions effectively as a pre-employment screening mechanism, allowing project managers to intercept potentially unfit workers before they enter hazardous work zones, consequently lowering the incidence of human-factor accidents.
Wu, Zhongguang, Dai, Junping, Ruan, Jing, Shi, Yonglong, Yuan, Zhenzhong, Hao, Jiatian
Synergistic Effect of Matrix Porosity and Grouting Material Type on the Performance of Grouted Composite Pavement2026-99-04058/28/2026
The grouted composite pavement combines the advantages of flexibility and rigidity through the composite structure of organic-inorganic materials, but the optimisation of its performance is affected by the complexity of the matrix asphalt mixture void ratio and grouting material type. This study has revealed the influence of matrix asphalt mixture porosity and grouting material type on the grouting effect and road performance of grouted composite asphalt pavement. The results showed that the increase of matrix porosity could significantly improve the grouting rate and resistance to high-temperature rutting of the mortar, but the high porosity led to a decrease of low temperature cracking resistance of the materials. CA mortar enhanced the flexible deformation capacity by optimising the interfacial bond, and its low-temperature cracking resistance was better than that of ordinary cement mortar, but the grouting efficiency and high-temperature performance were slightly lower. In addition, ordinary cement mortar demonstrated better performance regarding high-temperature stability and resistance to water damage.
He, Mu, Wang, Yan, Ye, Ming, Yu, Chao, Ye, Xiao
SAE TOMORROW TODAY UNPLUGGED - The Power Struggle Shaping Autonomous Trucking135818/14/2026
With too many cooks in the kitchen, can innovation ever reach the road? In this Unplugged episode of SAE Tomorrow Today, host Grayson Brulte uses the culinary world as a powerful metaphor to explore one of the autonomous trucking industry's most pressing issues: who gets "veto power"? As startups challenge established OEMs and suppliers, questions around control, competition, and liability are shaping the future of commercial autonomy. Are legacy players protecting safety or their market position? And when disruptive newcomers refuse to back down, who ultimately determines the recipe for success? Tune in for a fresh perspective on the power struggles, partnerships, and industry dynamics that could define the next chapter of autonomous trucking. Have your own thoughts on this topic? 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
Spider-Man-Inspired Technology Comes to FruitionTBMG-555408/1/2026
Every kid who has read a comic book or watched a Spider-Man movie has tried to imagine what it would be like to shoot a web from their wrist, fly over streets, and pin down villains. Researchers at Tufts University took those imaginary scenes seriously and created the first web-slinging technology in which a fluid material can shoot from a needle, immediately solidify as a string, and adhere to and lift objects.
Aging and Performance Restoration Mechanisms of Gussasphalt under Thermo-Oxidative Aging and Remelting Conditions2026-99-01817/31/2026
To address the performance degradation of Gussasphalt during thermo-oxidative aging and remelting processes, this study investigates the restoration mechanisms of different additives on the aged and remelted Gussasphalt. Additives including RSS, CAS modifiers, and polymer-modified asphalt were incorporated into aged asphalt to evaluate their effects on performance recovery. The improvement in high- and low-temperature properties, viscosity, and viscoelasticity under remelting conditions was systematically analyzed. Results indicate that the additives significantly increased penetration and ductility, while reducing softening point and viscosity. Among them, a 10% dosage of CAS additive combined with new asphalt exhibited the optimal performance restoration. RSS additive enhanced the plastic deformation capacity of remelted asphalt, whereas CAS and new asphalt improved ductility and softening point, though CAS showed insufficient thermal stability. Viscosity tests demonstrated that 10% CAS addition yielded the most significant reduction in rotational viscosity. Dynamic shear rheometer (DSR) and bending beam rheometer (BBR) tests revealed that CAS notably improved phase angle and decreased rutting factor, while RSS showed superior enhancement in low-temperature crack resistance. Comprehensive analysis confirms that the incorporation of appropriate amounts of RSS, CAS, and new asphalt during remelting effectively enhances the properties of Gussasphalt. In particular, CAS additive and new asphalt exhibit outstanding overall performance, contributing to the improved durability and service performance of Gussasphalt.
Li, Jinmi, Wu, Guorong, Chen, Yunjin, Chen, Huayan, Ying, Hong
Dynamic Assessment and Optimization of Bridge Resilience under Multi-Hazard Coupling2026-99-08297/30/2026
Traditional methods for assessing bridge resilience often focus on single hazards or static conditions. Yet bridges today face more complex multi-hazard threats. To address this, this research develops a dynamic model to evaluate bridge resilience under multi-hazard conditions, which is intended to provide scientific support for decision-making to improve resilience. The study first establishes an index system that measures a bridge’s ability to absorb impacts, adapt during an event, and recover afterward. We also propose a method to calculate the coupling degree, which quantifies the amplification effect of multiple hazards, such as an earthquake followed by a flood, on each other’s impacts. Next, we clarify the interrelationships among key resilience factors. Using this understanding, we construct a system dynamics model that simulates the variation of bridge resilience over a full disaster cycle. Finally, a numerical simulation is carried out for a concrete continuous girder bridge in China’s coastal areas as a case study. The results confirm the model is valid and clearly show the differences in bridge resilience between single-hazard and multi-hazard events. More importantly, they prove that combined hazards make the bridge system much more vulnerable. The model also identifies the best strategies for intervention: a strategy that coordinates actions across all disaster phases performs best, as it most effectively reduces the impact of compound hazards and keeps the resilience curve smoother. In short, this study presents a new method for assessing bridge resilience and provides engineers and managers with a practical tool to identify structural weaknesses and optimize resource allocation for resilience improvement.
Lin, Jiachen, Chai, Liang
Hybrid Particle Swarm Optimization and Machine Learning Framework for Enhanced Prediction of Ground Settlement during Rectangular Pipe Jacking2026-99-16477/24/2026
Accurate prediction of ground settlement induced by rectangular pipe jacking, a prevalent trenchless technology in urban infrastructure development, remains a significant challenge. This study addresses this by developing and evaluating a robust machine learning (ML) framework. Leveraging 104 sets of field monitoring data from the Liuye Avenue West Extension rectangular pipe jacking project in Hunan, China, key construction parameters including jacking force, advance rate, and grouting pressure were utilized as inputs to predict ground settlement. A Particle Swarm Optimization (PSO) algorithm was integrated for automated hyperparameter tuning of six distinct ML models: standalone Least Squares Support Vector Machine (LSSVM), Backpropagation Neural Network (BPNN), Random Forest (RF), and their respective PSO-optimized counterparts. Comprehensive performance evaluation using Mean Squared Error (MSE), Mean Absolute Error (MAE), and Coefficient of Determination (R^2) revealed that the PSO-LSSVM hybrid model achieved superior predictive accuracy and generalization capability. Specifically, on the test dataset, the PSO-LSSVM model yielded an MSE of 0.367, MAE of 0.424, and an R^2 of 0.941. These findings demonstrate that the proposed PSO-enhanced LSSVM model significantly outperforms baseline models, offering a highly effective and reliable tool for predicting ground deformation in similar complex pipe jacking projects.
Hu, Shiwei, Hu, Rong, Zhang, Hong, Chen, Yi, Hu, Da
Evaluation of Structural Service Performance of Low-temperature Modified Asphalt Pavement based on Peavy-Duty traffic Engineering2026-99-16457/24/2026
Relying on the reconstruction project, the low-temperature modified asphalt pavement significantly reduces the construction temperature of the asphalt mixture by 40 °C compared with the traditional asphalt pavement, and improves the road performance of the material. By comparing the two mixture rolling schemes, the compaction effect of scheme 2 is better. For AC-13 mixture, the flexural tensile strength of USP-SBS composite modified asphalt mixture is 0.67 MPa higher than that of SBS modified asphalt mixture, and compared with SBS modified asphalt mixture, the final rut depth of USP-SBS composite modified asphalt mixture is 2.68 mm shallower than that of SBS modified asphalt mixture, and the total deformation rate is 43.8% lower than that of the latter. The post-construction quality evaluation shows that the stability of the low-temperature modified asphalt pavement test section under the bearing capacity and high-temperature-water coupling is better than that of the conventional road section, and the low-temperature stability is comparable to that of the two. This innovative application not only achieves energy saving and emission reduction but also provides a new solution for road construction under heavy traffic conditions.
Liu, Chuanfeng, Xu, Ke, Shi, Zheng, Hao, Jidong, Zhao, Liandi, Xianwei, Wang
Construction and Empirical Analysis of Coal Road Freight Price Index Using Big Data2026-99-05607/10/2026
Coal is an important component of China's energy structure, mainly transported by three modes: railway, waterway, and highway. In regional coal transportation, highway transport undertakes numerous collection-distribution tasks and medium-short distance transport, playing a vital and indispensable role. Considering the characteristics of the coal highway transportation market and the demand for price indices, a three-tiered coal highway freight price index system has been established, including individual indices, classified indices, and an overall index. Using order data from the logistics platform of the Coal Big Data Center, the coal highway freight price index is compiled by adopting the internationally Laspeyres chain method. The methodological selection has passed the ADF stationarity test. Economically, the coal highway freight price index is closely correlated with coal prices, with the correlation coefficient reaching over 0.7, which can reflect about the coal highway freight market and fill the gap in market highway freight price monitoring.
Zhao, Nanxi, Wang, Xinzi, Rong, Haoyu
Path Planning Algorithm for Self-Driving Cars Based on High-Precision Maps and Improved A*2026-99-05887/10/2026
To address the limitations of the traditional A* algorithm in lane-level navigation, we propose an autonomous vehicle path planning algorithm based on high-precision maps and an improved A* algorithm to ensure effective application in complex traffic environments. We construct a hierarchical high-precision map based on the Lanelet2 framework to achieve structured modeling of complex road environments. To address the adaptability issues of the A* algorithm in lane-level navigation, we propose optimization schemes, including heuristic function improvements, path segment division, and target point validity verification, to ensure that vehicles can autonomously change lanes on multi-lane roads. By combining dynamic programming (DP) and quadratic programming (QP), we ensure the safety and smoothness of the path. Simulation results demonstrate that the optimized algorithm enables smooth stopping and starting at traffic lights in structured road environments and autonomous lane changes on multi-lane roads. Compared to using DP alone, QP provides smoother and safer driving paths and exhibits superior obstacle avoidance performance in speed planning. This method effectively ensures the rationality of path planning in complex road environments while strictly adhering to traffic rules, thereby enhancing the safety and reliability of path planning.
Wang, Siyu, Zhou, Rong, Shi, Tian, Xu, Zhen, Zhao, Zhiguo
Multi-sensor Data Fusion Based on Big Data Modelling2026-99-05687/10/2026
The collection of road high-frequency data often involves inputs from multiple sensors, such as stress and strain, and sampling of these data features a high sampling rate of up to 2,000 Hz. High-frequency sampling enables capturing of the internal stress and strain of the pavements when vehicles are passing and facilitates the analysis of the pavement structure and prediction of its long-term service performance. However, while the sensors are continuously collecting data, the time the vehicles pass is discrete and unpredictable, resulting in a large number of low information density or irrelevant data. Even when the massive high-frequency data are collected, challenges remain in data transmission, storage, and analysis—the challenges are attributable not only to the massive quantity and complexity of data from multiple sensors, but also to the inconsistent data formats, misaligned timestamps, and multi-sensor data fusion difficulties. In response to the challenges specified above, a new approach combining traditional road observation data with deep learning models is proposed here to efficiently process and analyze massive sensor data. This method not only improves the data processing efficiency but also provides new insights into innovation of road engineering technologies.
Gang, Jian, Zhang, Yue, Chen, Yinghao, Zheng, Xiaoyan, Wang, Taojie, Liu, Yilin, Guan, Wei, Wu, Jiangfeng
Research on the Site Selection of Emergency Rescue Stations on Expressways Based on Non-dominated Sorting Particle Swarm Optimization Algorithm2026-99-05397/10/2026
To enhance the rescue efficiency of expressway emergencies and reduce the impact on network operation, this study developed an optimization model for the strategic placement of emergency rescue stations. Firstly, a node importance assessment method is designed to measure the importance of each node in the expressway network by considering both local and global impacts; secondly, an emergency rescue station selection model is constructed based on the node importance to achieve the highest coverage satisfaction, the highest rescue efficiency and the lowest construction cost. Taking the expressway network in Shaanxi Province as an example, a particle swarm algorithm based on non-dominated sorting (NSPSO) is designed to solve the problem. The results demonstrate that, with the same number of rescue stations, the model of Site Selection of Emergency Rescue Stations considering node importance achieves shorter average rescue time and higher coverage satisfaction under comparable conditions.
Chen, Jingli, Lin, Shan, Xu, Hongke, Cao, Jiabao, Yang, Fei, Luo, Mi
Optimization Method for Emergency Rescue Resource Allocation in Two-Way Ten-Lane Expressway Based on Risk Assessment2026-99-05677/10/2026
The two-way ten-lane expressway has the significant characteristics of “large traffic volume, mixed vehicle types, and heavy loads”, which makes the impact of traffic flow status on accident risk present nonlinear characteristics. Traffic flow fluctuations not only directly affect the probability of accidents, but also amplify the spatiotemporal differences in rescue needs through mechanisms such as lane occupancy time and accident chain reactions. Therefore, the essence of resource allocation on a two-way ten-lane expressway is the “spatiotemporal matching problem between dynamic risks and limited resources”, which requires both quantifying the spatiotemporal evolution of risks and coping with the high uncertainty of the traffic system. Aiming at the problem of inefficiency of traditional empirical resource allocation under complex traffic conditions, this study proposes a dynamic optimization framework based on multidimensional risk assessment for emergency rescue resource allocation. In this framework, firstly, the entropy weight method and fuzzy comprehensive evaluation are combined to construct a risk quantification model using historical accident data and real-time traffic characteristics to achieve fine risk classification of road sections. Secondly, a multi-objective optimization model is established with the goal of minimizing risk-weighted costs and maximizing risk-weighted resource demand satisfaction, and considering constraints such as mandatory requirements for key equipment in high-risk areas and minimum site configuration. At the same time, the improved NSGA-II algorithm is used to effectively solve the contradiction between cost and utilization efficiency in emergency rescue resource allocation through adaptive non-dominated sorting, hybrid genetic operators and dynamic penalty mechanism. Experimental results show that the improved NSGA-II algorithm is superior to the traditional method in terms of Pareto front distribution, convergence speed and actual resource allocation effect. Compared with the traditional scheme, the method proposed in this study reduces the resource allocation cost by 35.5%, increases the risk-weighted resource demand satisfaction rate by 1.9%, and expands the resource coverage of high-risk areas by 13.8%. This study provides scientific decision-making support for emergency response in complex road networks and offers a practical optimization approach for highly dynamic traffic emergencies.
Kan, Youjun, Cao, Yang, Shi, Xiaomin, Gao, Shangjie
Advances in Research on Emergency Lane Activation Model for Highways2026-99-05427/10/2026
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Qin, Fengcai, Chen, Jianqiu, Che, Guoyan, Lou, Benxiao, Wang, Xiang, Ning, Longtang, Zhou, Shixuan, Zhang, Xiyuan, Bao, Chun, Gu, Guobin
The Influence of Spatial and Aspatial Factors on the Safety Driving Behavior of Motorcycle Couriers in the Gig-Economy Era: A Case Study of East Jakarta, Indonesia09-14-02-00057/3/2026
This study aims to analyze the impact of spatial and aspatial factors on the safety driving behavior of motorcycle couriers in East Jakarta within the context of the gig economy. Both factors are integrated to clarify how spatial conditions and individual characteristics jointly shape couriers’ safety driving behavior. The Partial Least Squares Structural Equation Modeling (PLS-SEM) method was employed to examine the relationship between spatial and aspatial factors on safety driving behavior. Data were collected through questionnaires from 253 motorcycle couriers operating in three subdistricts in East Jakarta, namely Cakung, Pasar Rebo, and Pulo Gadung. The results show that safety driving behavior is significantly influenced by aspatial factors, particularly socioeconomic characteristics and personality traits. In contrast, spatial factors such as road conditions and daily activity patterns do not directly influence safety driving behavior, but exert indirect effects through the couriers’ personality traits.
Wahyuddin, Yasser, Sitorus, Paldibo Alfriramson, Putri, Kharunia, Maharani, Garnierita
Simulation and Analysis of Flow and Acoustic Induced Structural Vibration2026-01-06966/20/2026
For analysing flow and acoustic induced structural vibration, a fully run time coupled framework combining a hybrid CFD-CAA approach with a modal response simulation was validated and presented at the ISVNH 2022 (SAE Technical Paper 2022-01-0938). In this paper i We apply this CFD–CAA–modal coupling method to a series-representative bonnet geometry and demonstrate its capability to capture flow and aeroacoustically driven vibration with two-way coupling. ii We analyse the modal properties of the bonnet and show that confined air volumes beneath the bonnet can introduce significant fluid loading effects, which are already embedded in experimentally validated FE modal models and must therefore be treated carefully in two-way coupled simulations. iii We validate the fully coupled aeroelastic simulation against wind-tunnel measurements with undisturbed inflow, show close agreement with the measured vibration response and analyse that the dominant excitation is in this case from below the bonnet due to acoustic pressure fluctuations.
Schwertfirm, Florian, Ocker, Joerg, Hartmann, Michael
Prediction of CO 2 Emissions from Light-Duty Vehicles Based on Highway Alignment2026-99-17135/22/2026
In order to allow for the precise prediction of the CO2 emissions of light-duty vehicles during the road design phase and to methodically examine the effect of road alignment on CO2 emissions, this paper classifies the operating conditions of light-duty vehicles according to Vehicle Specific Power (VSP) and the design speed of different road levels. The test vehicle’s environmental data and operational parameters under various road conditions were gathered using a Portable Emission Measurement System (PEMS). The CO2 emissions of the test vehicle under different operating conditions were statistically analyzed. Based on the road’s horizontal and vertical alignment, the road was separated into analytical units, including straight sections, longitudinal slope sections, horizontal curve sections, and curve-slope combination sections. The indicators of each analysis unit were used to anticipate the speed and acceleration of light-duty vehicles in each unit, and a model for forecasting light-duty vehicle CO2 emissions based on road alignment was developed. The results show that the predicted CO2 emissions based on road alignment have a relatively small error compared to actual emissions, indicating high model accuracy. This model enables relatively accurate predictions of CO2 emissions for light-duty vehicles on target road sections during the road design phase. Among the various road alignment indicators, slope has a greater effect on the test vehicle’s CO2 emissions.
Liang, Yao, Wang, Yixuan, Zhao, Xiaoyan, Cheng, Shenzhen, Wu, Bing, Zeng, Weiyi
The Spatial-Temporal Evolution of Coupling Coordination Degree Development of Carbon Emission-Passenger-Freight in Five Northwest Provinces2026-99-17165/22/2026
Taking China’s five northwestern provinces as the study area, this paper investigates the spatial-temporal interactions among carbon emissions, passenger transport, and freight transport from 2010 to 2020. An entropy-weighted composite index is constructed for each system and integrated into a coupling coordination degree model to quantify interaction. It is found that (1) the average annual growth of provincial coupling coordination degree is 4.7%, but the gradient difference between regions is significant, and the extreme difference of coupling coordination degree between east and west reaches 4.5 times in 2020; (2) Spatially, it shows a unipolar leading pattern, with Shaanxi achieving a significant decrease in carbon emission intensity and Qinghai achieving a lesser coupling coordination degree of 23% in Shaanxi due to the high proportion of highway freight transport and single energy structure; (3) the driving mechanism analysis shows that the improvement of transport network density and clean energy substitution rate contributes significantly to coupling coordination degree. These findings suggest substantial room to enhance coordinated low-carbon transport development in the region. Policy efforts should prioritize interprovincial cooperation, integrated optimization of transport infrastructure and energy structure, and differentiated pathways tailored to local conditions.
Qian, Yongsheng, Li, Shaoyuan, Zeng, Junwei, He, Qingling
Multi-Mode Control Strategy for Controllable Vehicle Suspension Systems2026-99-07125/15/2026
The suspension system with variable damping and variable stiffness actuators can realize four-quadrant mechanical output, effectively combining the energy efficiency of the semi-active suspension with the performance levels approaching those of active suspensions. However, the practical effectiveness of this system depends heavily on the ability of the control strategy to adapt to different driving conditions. In order to meet this challenge, this research has developed a multi-mode suspension collaborative control strategy to optimize energy efficiency and ride comfort in various operating scenarios. Based on the four-quadrant characteristics of the actuator, a suspension mode switching framework has been established, and the suspension work is divided into passive, semi-active, pseudo-active and active modes. In order to determine the appropriate switching boundary, first calculate the root mean square (RMS) value of the sprung mass acceleration and suspension dynamic deflection under passive conditions. With the existing human comfort sensitivity as a reference, the switching threshold of sprung mass acceleration is 0.527 m/s2, and the switching threshold of suspension dynamic deflection is 8.31×10−3m, and the corresponding conversion rules are formulated. Then, the LQR controller optimized by the genetic algorithm is used to allocate the control force adaptively according to the suspension mode to realize cooperative multi-mode operation. The simulation results on B-D composite road surfaces show that compared with traditional passive suspension, this method can reduce the sprung mass acceleration, suspension dynamic deflection and tire dynamic load by 10.59%, 16.65% and 32.9% respectively. These results confirm that the collaborative control strategy significantly improves the ride comfort, vehicle adaptability and overall performance in complex road conditions.
Li, Zhiying, Li, Jei, Zhu, Anding, Bai, Xianxu, Li, Weihan, Li, Rui
Machine Learning–Driven Safety Analysis of Automated Vehicles in Simulated Mixed Traffic Environments09-14-01-00215/4/2026
Automated Vehicles (AV) pose new challenges in road safety, multimodal interaction, and urban planning, requiring a holistic approach that prioritizes sustainability and protects all road users. The KASSA.AST project addresses this by deploying and evaluating an automated shuttle in southern Austria on three routes. The study area is a Park & Ride zone near a train station, enabling seamless transfers and higher transit use. To assess the safety impacts of the automated shuttle, four Mobility Observation Boxes (MOBs) were deployed. These AI-based systems detect and classify road users, track their trajectories and geospatial coordinates, and identify safety-critical events via Surrogate Safety Measures (SSMs). Over 10 days, a trajectory dataset captured interactions among vehicles and the shuttle. The resulting real-world dataset is a core contribution. This dataset underpins microscopic behavior modeling. Trajectory pairs yield car-following and interaction metrics (relative distance, relative speed, acceleration) to calibrate custom models for realistic mixed traffic. Simulations generate a structured interaction database with time spans, trajectories, conflict points, and SSMs (such as Time-to Collision—TTC, Post-Encroachment Time—PET, and Deceleration-rate-to-avoid-crash—DRAC). These outputs support detailed analysis of shuttle interactions, including near misses. To reveal patterns, clustering identified three interpretable safety-relevant regimes: (i) a low-demand background regime (n = 96) with low speeds and near-zero deceleration demand, (ii) a fast-and-tight regime (n = 33) with reduced TTC, elevated critical-event speeds, and high DRAC/Modified (M)DRAC demand, and (iii) an AV-regulated regime (n = 10) dominated by the shuttle as adversary, showing short TTC but stable moderate speeds (~4 m/s) and conservative headway policies. Ensemble-tree supervised learning reproduced these regimes with high accuracy and revealed that critical-event speeds and counterpart headway are the strongest discriminators, while AV role metadata contributes marginally. This integrated approach—linking field data, behavior modeling, simulation, and machine learning—provides a robust framework for assessing AV safety in urban contexts.
Losada Arias, Ángel, Rosenkranz, Paul, Hula, Andreas, Aleksa, Michael, Saleh, Peter, Erdelean, Isabela
Real Turbulent Flow in Vehicle Aerodynamics: Overview of On-Road Measurements and Turbulence Generation in Wind Tunnels2026-01-50294/22/2026
Flow conditions on the road are quite different from the conditions used to develop vehicle aerodynamics. However, a significant amount of statistical data now exists that describes realistic road conditions. Some of these on-road flow characteristics can be replicated in wind tunnels. This paper reviews technical facilities designed to simulate on-road flow characteristics, such as turbulence intensity, turbulent length scales, and flow angle distribution. Reconstruction of a flow field that matches real road conditions is made possible by using active or passive turbulence generators within the wind tunnel. This review provides a comprehensive overview of these facilities, offering readers key insights into the challenges involved in replicating real-world flow conditions in wind tunnels.
Vondruš, Jan, Vančura, Jan
SAE TOMORROW TODAY - SAE Standards: Building Consensus for Moving Mobility Forward135634/16/2026
Standards aren't flashy ... but they make modern mobility possible by enabling emerging technologies to scale safely. Listen in as we sit down with SAE International experts Christian Thiele, Senior Director of Global Vehicle Ground Standards, and David Franks, Standards Specialist Engineer for Aerospace, for a wide‑ranging conversation on how SAE standards quietly enable trust, interoperability, and scale across automotive and aerospace. This discussion spans EV charging, wireless roads, automated driving, advanced air mobility, hydrogen propulsion, and the growing role of artificial intelligence. Go behind the scenes to learn how these standards are developed, the importance of industry consensus, and why they often exceed regulatory safety requirements. Are you interested in shaping the standards behind next-gen mobility technology? Get involved at sae.org/standards/development. 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
Adaptive Eco-Driving Feedback for Battery Electric Vehicles: A Reinforcement Learning Approach Using Context-Aware Policy Optimization2026-01-01654/7/2026
Energy efficiency and range optimization remain critical challenges to the widespread adoption of battery electric vehicles (BEVs). As a result, there is a growing demand for intelligent driver assistance systems that can extend the operating range and reduce range anxiety. This paper presents an adaptive eco-feedback and driver rating system based on proximal policy optimization (PPO) reinforcement learning, designed to support drivers with the target to reduce energy consumption and maximize driving range. The system processes real-time driving data, such as velocity, acceleration and powertrain status. Map data of high quality is used to anticipate traffic events, including but not limited to speed limits, curves, gradients, preceding vehicles and traffic lights. This contextual awareness allows the system to continuously assess driving behavior and provide personalized, context-aware visual feedback alongside a dynamic driving behavior rating. A PPO agent learns optimal feedback strategies through continuous interaction and evaluates the impact of specific guidance actions, such as but not limited to “release accelerator pedal”, “brake” and “recuperate”, on immediate energy efficiency and long-term driver adaptation patterns. Feedback intensity and modality are dynamically tailored to individual driver profiles based on observed reaction patterns and feedback adherence. This approach encourages drivers to prioritize energy efficiency while aiming to minimize cognitive distraction and discomfort. The algorithm is implemented and validated within a driving simulation environment that replicates diverse and realistic conditions. Virtual driving tests conducted in various scenarios, such as congested urban areas, suburban routes, mountain roads and highways demonstrate that the proposed PPO-based eco-driving assistance system can reduce energy losses by about 28% compared to conventional driving behavior.
Stocker, Christoph, Hirz, Mario, Martin, Michael, Kreis, Alexander, Stadler, Severin
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