《中国公路学报》：公路交通领域前沿双语文章推荐

公路交通作为国家基础设施的重要组成部分，其安全、低碳与智能化发展一直是行业关注的核心议题。随着“双碳”目标的推进及交通强国战略的深化，高速公路光伏设施布局优化、大跨桥梁荷载监测、驾驶行为安全等领域的创新研究，正为行业可持续发展注入新动力。本期精选文章聚焦公路交通领域五大前沿方向：从高速公路分布式光伏设施的布局优化模型与算法创新，到大跨桥梁车辆荷载时空分布的智能识别系统；从驾驶路怒情绪的低侵入度分级辨识方法，到强震区桥梁抗震挡块的强度退化模型；再到极限工况下汽车队列的非线性动力学特性研究，全面展现了公路交通在绿色能源、结构安全、智能监测及应急管理等领域的最新突破。

这些研究不仅揭示了复杂交通场景下的关键科学问题，更通过跨学科技术融合（如深度学习、数值模拟、智能算法等）提供了切实可行的工程解决方案，为公路交通的低碳化建设、结构安全运维及智能驾驶发展提供了重要理论支撑与技术参考。让我们一同深入这些前沿成果，探索公路交通领域的创新奥秘与应用前景。

精选文章·Selected Articles

01

基于改进DEMO算法的高速公路分布式光伏设施布局优化

Layout Optimization of Distributed Photovoltaic Facilities on Expressway Based on Improved Differential Evolution for Multi-objective Optimization Algorithm

【摘要】合理的光伏能源利用及设施布局优化对于高速公路的低碳化建设和“净零”排放目标的趋近具有重要意义。从能源自洽角度，以经济成本最低为布局优化目标，构建考虑选型建设成本、位置距离成本、运营维护成本及额外能源增益的光伏设施布局优化模型(Photovoltaic Layout Optimization Model, PLOM),对光伏设施的布局面积、密度设置、布局数量及倾角方位等约束进行条件限制。为避免解空间分布不均匀及漏解现象，引入控制参数调整策略、精英选择双变异策略与动态拥挤距离排序策略，提出改进多目标差分进化算法(Improved Differential Evolution for Multi-objective Optimization, IDEMO)进行布局方案求解。依托G40沪陕(上海—陕西)高速(陕西段)及其周围区域的地理信息及路网数据，探讨服务区屋面区域及道路边坡区域光伏设施的布局方案及发电效果。研究结果表明：建筑物屋面面积、太阳辐射强度、边坡位置及设施倾角方位是高速公路光伏设施选址布局的关键要素，当倾角设置为18°～21°、边坡朝南时能量转换和发电效果最佳；IDEMO算法与标准DEMO算法、非支配解排序遗传算法(Non-dominated Sorting Genetic Algorithm, NSGA-II)、粒子群算法(Particle Swarm Optimization, PSO)、混沌猫群算法(Chaos Cat Swarm Optimization, CCSO)及禁忌搜索算法(Tabu Search, TS)的性能对比分析结果显示，IDEMO算法在各基准函数下具有更好的搜索能力和更高的收敛精度，更容易获得全局最优解，其算法寻优效率和寻优可信性较高，整体具有更好的寻优性能。所提出的研究方法可为高速公路的低碳化建设和零碳目标的趋近提供理论基础及思路参考。

【Abstract】Reasonable photovoltaic-energy utilization and facility-layout optimization are crucial for the low-carbon construction of expressways and the approach of “net-zero” emission targets. From the perspective of energy self-consistency and based on the lowest economic cost as the objective of layout optimization, a photovoltaic layout optimization model was constructed by considering the selection and construction costs, location-distance cost, operation and maintenance costs, and additional energy gain. The layout area, density setting, layout number, and inclination azimuth of photovoltaic facilities were restricted. To avoid uneven spatial distribution and missing solutions, a control-parameter adjustment strategy, an elite-selection double-variation strategy, and a dynamic crowding-distance ranking strategy were introduced, and improved differential evolution for multi-objective optimization (IDEMO) was proposed to solve the layout scheme. Based on the geographic information and road network data of the G40 Shanghai-Shaanxi Expressway (Shaanxi section) and its surrounding areas, the layout scheme and power-generation effect of photovoltaic facilities on the roof of the service area and road slope area are discussed. The results show that roof area, solar-radiation intensity, slope location, and facility-inclination orientation are key factors that determine the location layout of expressway photovoltaic facilities. When the inclination was set to 18°-21° and the slope was oriented south, the energy conversion and power-generation effects were the best. Moreover, the performance of the IDEMO algorithm was compared with that of the standard differential evolution for multi-objective optimization algorithm, non-dominated sorting genetic algorithm, particle swarm optimization algorithm, chaos cat swarm optimization algorithm, and tabu search algorithm. Results of comparative analysis show that the IDEMO algorithm offers better searching ability and convergence accuracy under each benchmark function, as well as obtains the global optimal solution more easily than the other algorithms. Moreover, it offers better optimization efficiency, optimization credibility, and overall optimization performance. The proposed method can provide a theoretical basis and reference for the low-carbon construction of expressways and the approach of zero-carbon targets.

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02

大跨桥梁车辆追踪与荷载时空分布智能识别

Intelligent Identification of Vehicle Tracking and Load Spatio-temporal Distribution in Long-span Bridge

【摘要】车辆荷载是大跨桥梁最重要的作用荷载之一，也是大部分桥梁疲劳劣化的最主要原因。但桥梁动态称重系统造价昂贵，无法在桥上分布式布置，桥梁车辆荷载分布信息的动态识别仍是挑战性难题。面向大跨桥梁结构健康监测需求，引入计算机视觉与深度学习技术，建立了一套集成化的桥梁车辆荷载时空分布智能识别系统。首先，研究基于交通监控数据和深度目标检测网络的车辆识别方法，开展车辆目标检测任务的YOLOv7深度网络训练，并通过训练后模型获取单摄像头数据中包含车辆类型与时间等信息的车辆图像；其次，引入HardNet深度特征描述符，建立图像点特征匹配方法，通过分布布置的监控视频数据设计搜索匹配策略，实现车流方向多个监控对应车辆图像数据的匹配，并对监控盲区采用线性插值估计车辆位置，得到车辆在桥梁上的时空分布信息；然后，将各方法集成，建立车辆荷载时空分布识别系统，该系统可结合动态称重数据自动输出车辆荷载时空分布信息与可视化结果，实现从监控数据到车辆荷载时空分布的一体化流程；最后，采用九江长江大桥监控数据进行应用验证。研究结果表明：该系统基于视频数据实现车辆目标识别与匹配追踪，运算耗时小于输入视频时长，对大型车辆匹配准确率达97.62%,可以快速、准确地识别车辆荷载分布信息，该系统对保障桥梁服役安全具有重要的意义，应用前景广阔。

【Abstract】Vehicle load is one of the most important loads of long-span bridges, and it is also the main cause of fatigue deterioration of most bridges. However, the bridge weigh-in-motion system is expensive and cannot be distributed across the bridge, which means the dynamic identification of bridge vehicle load distribution information is still a challenging problem. This paper introduced computer vision and deep learning technologies to meet the needs of long-span bridge structural health monitoring, and established an integrated intelligent identification system for bridge vehicle load spatio-temporal distribution. Firstly, we studied the vehicle identification method based on traffic monitoring data and deep target detection network, trained the YOLOv7 deep network for vehicle target detection tasks, and obtained vehicle images containing information such as vehicle type and time in single camera through the trained model. Then, we introduced the HardNet depth feature descriptor to establish an image point feature matching method, designed a searching and matching strategy through distributed surveillance video data to achieve the matches of vehicle image data corresponding to multiple monitors in the traffic flow direction, and the vehicle position was estimated by linear interpolation of the monitoring blind area to obtain the spatio-temporal distribution of vehicles on the bridge. Finally, the methods were integrated to establish the vehicle load spatio-temporal distribution identification system. This system can automatically output the spatio-temporal distribution of vehicle load and visualization results combining with dynamic weighing data, realizing an integrated process from monitoring data to vehicle load spatio-temporal distribution. In this paper, the monitoring data of Jiujiang Yangtze River Bridge was used for verification. The results show that the system can achieve vehicle identification and tracking based on video data, with computational time less than the duration of the input video and an accuracy rate of 97.62% for large vehicle matching, allowing for rapid and accurate identification of vehicle load distribution. The system is of great significance to ensure the safety of bridge service and has broad application prospect.

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03

基于半监督学习的驾驶路怒情绪低侵入度分级辨识方法

Low-intrusive Driving Anger Classification Method Based on Semi-supervised Learning

【摘要】为实时监控驾驶过程中的路怒情绪，及时进行有效的干预和调整，提出一种准确高效的驾驶路怒情绪分级辨识方法。基于侵入度较低的驾驶行为及语音特征展开，并采用半监督学习方法建立模型，以减少对数据标签的依赖，提高小样本低标注条件下路怒辨识的准确性。通过开展由30人参与的高仿真驾驶模拟试验采集驾驶数据，利用滑动时间窗截取路怒事件后，提取特征形成路怒驾驶数据集。在此基础上，将半监督学习(Semi-supervised Learning, SSL)的伪标签融合于梯度提升机算法(Gradient Boosting Machine, GBM)建立SSL-GBM模型，充分发掘数据内部信息以降低对人工标注的依赖，并在自动机器学习框架中自动化完成数据处理、特征工程、模型搜索、参数优化等流程，从而实现驾驶路怒水平的分类判别。研究结果表明：路怒驾驶情绪辨识模型在预测路怒5级评分中，准确率能够达到90.3%,相较于已有模型中表现最好者提高了3.7%;特别对于2～5级路怒的识别准确度均有2.5%以上的提升，检测失效的比例大幅降低。在驾驶全程路怒水平的预测中，模型表现出应用于实时路怒检测的优秀表征能力和泛化性能，由此验证了方法的有效性和合理性。研究结果可为驾驶辅助系统提升危险驾驶监测能力提供技术支撑，在路怒驾驶状态判别方面具有重要的实际应用价值。

【Abstract】To monitor anger while driving in real time and provide timely and effective intervention and adjustment, an accurate and efficient method for classifying anger while driving is proposed. Based on low-intrusive driving behavior and voice features, this study adopted semi-supervised learning methods to build a model to reduce the dependence on labels and improve classification accuracy. The driving data were obtained from a high-fidelity driving simulation experiment involving 30 participants. A sliding time window was set to intercept anger events, and a driving anger dataset was formed through feature extraction and computation. On this basis, a model called SSL-GBM was developed by combining a pseudo-labeling algorithm in semi-supervised learning (SSL) with a gradient boosting machine (GBM), thus fully exploring the internal information of the data to reduce the dependence on manual labels. Data processing, feature engineering, model searching, and parameter optimization were automated within an automated machine framework, enabling the classification of driving anger levels. The results indicate that the driving anger emotion classification model has an accuracy of 90.3% in predicting five-level driving anger scores, which is an improvement of 3.7% compared to the best-performing model among the existing models. In particular, the recognition accuracy for levels 2-5 improves by more than 2.5%, significantly reducing the detection failure to misjudge the angry state as normal. As shown by the prediction of anger levels throughout the driving duration, the algorithm is fully equipped with the characterization ability and generalization performance applied to real-time driving anger state recognition, thereby verifying the effectiveness and rationality of the proposed approach. This study has significant application value in discriminating driving anger states and enhancing the capacity of driving assistance systems to monitor dangerous driving behaviors.

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04

强震区桥梁抗震挡块强度退化模型及其应用

Strength Degradation Model for Seismic Retaining Blocks on Bridges in High-intensity Earthquake Regions

【摘要】钢筋混凝土抗震挡块作为强震区桥梁的重要受力构件，强震下往往率先发生严重破坏，而现行规范中尚未明确给出挡块的抗震设计方法及其分析模型。为此，在揭示钢筋混凝土抗震挡块斜截面破坏机理的基础上，基于刚体转动平衡方程推导了考虑混凝土残余抗拉强度和钢筋变形协调性的3类挡块强度计算公式，并通过能量等效原理建立了挡块强度双折线退化模型。以九度区一座近断层的中小跨径梁桥为例，通过剪切铰模型模拟挡块强度双折线退化，进而探讨挡块承载力下降对桥梁下部结构地震需求的影响。研究结果表明：所提抗震挡块强度计算公式及其强度退化模型能够较为精确地预测挡块的力学特征(计算平均误差小于5%),采用剪切铰模型能够合理地模拟挡块在强震下的损伤行为；强震作用下，不考虑抗震挡块碰撞效应的影响将低估桥梁下部结构的地震需求，会导致不安全的设计结果；而仅考虑挡块刚性碰撞(不考虑挡块承载力下降)则会高估桥梁下部结构的地震需求，容易造成不必要的浪费；抗震挡块不仅起到限制主梁横向位移的作用，而且挡块的损伤一定程度上起到消耗上部结构地震力的作用；考虑所提挡块强度退化后，能准确反映主梁与挡块之间的碰撞力对桥梁下部结构地震需求的影响。所提的挡块强度退化模型及其模拟方法可为九度区中小跨径梁桥的抗震设计提出借鉴。

【Abstract】As an important load-bearing member of bridges in intensive earthquake regions, reinforced concrete anti-seismic retaining blocks are often the first to be severely damaged under intensive earthquakes, and the seismic design method and its analysis model of block have not been given in the current code. To this end, on the basis of revealing the damage mechanism of the diagonal section of reinforced concrete anti-seismic retaining block, the strength formulas of three types of blocks that considering the residual tensile strength of concrete and the coordination of steel deformation are derived based on the rigid body rotation equation of equilibrium, and a double-line degradation model of block strength is established by the energy equivalence principle. Taking an example of a medium-span girder bridge near-fault in the ninth-degree intensity region, the double-line degradation of block strength was simulated by using a shear hinge model, and the impact of the decrease in block bearing capacity on the seismic demand of piers ware explored. The results show that the proposed strength formula of block and its strength degradation model can predict the mechanical characteristics of the block more accurately (the average error of calculation is less than 5%), and the shear hinge model can reasonably simulate the damage behavior of the block. Under intensive earthquake, not considering the impact of block collision effect will underestimate the seismic demand of piers, which will lead to unsafe design. Considering the rigid block collision (without considering the decrease of block bearing capacity) will overestimate the seismic demand of piers, which will cause unnecessary waste. The block not only plays the role of limiting the lateral displacement of the beam, but also the damage of the block plays the role in consuming the seismic force of the superstructure to a certain extent. When the proposed strength degradation of block is considered, it can accurately reflect the impact of the collision force between the beam and the block on the seismic demand of piers. The proposed block strength degradation model and its simulation method can be used for the seismic design of medium-span girder bridges in the ninth-degree intensity regions.

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05

极限操纵工况下CACC汽车队列的非线性动力学特性

Nonlinear Dynamic Characteristics of the CACC Vehicular Platoon Under Critical Maneuvering Conditions

【摘要】目前汽车队列控制研究中对车辆轮胎力附着极限操纵工况考虑较少，相应的队列控制策略可能无法满足低附着、高速近距跟驰等极限工况下队列的安全稳定行驶。因此，针对探讨较多且应用前景较好的协同自适应巡航控制(Cooperative Adaptive Cruise Control, CACC)汽车队列，研究轮胎力附着极限操纵工况下的CACC队列系统的非线性动力学特性，旨在为极限操纵工况下CACC汽车队列的控制策略设计提供理论依据。考虑轮胎力的非线性饱和特性，建立了队列-个体车辆一体化非线性动力学系统，基于控制增益参数空间分析研究了极限工况下队列的平衡点稳定性和头-尾弦稳定性特性。结果表明：极限工况下队列稳定性增益参数设计范围非常有限，在自适应巡航控制(Adaptive Cruise Control, ACC)队列的基础上增加对领航车的跟驰控制后变为CACC队列，会导致平衡点稳定性增益参数设计范围变小，但是可以大大增加头-尾弦稳定性的增益参数设计范围；极限工况下弦稳定性比平衡点稳定性的要求更为苛刻，弦稳定性的增益参数空间要显著小于平衡点稳定性的参数空间；与ACC队列相比，CACC队列对极限工况下车速、路面附着等变化在保持队列稳定性方面体现出了更强的适应能力和抗扰能力，具有显著优势。

【Abstract】In vehicular platoon control research, there is currently little consideration of maneuvering conditions under which the tire force approaches the adhesion limit. Thus, the corresponding platoon control strategy may not be able to meet the safety and stability requirements of the platoon under extreme conditions, such as low adhesion and high-speed close-range following. Therefore, this study aims to explore the nonlinear dynamic characteristics of the cooperative adaptive cruise control (CACC) platoon system, which has good application prospects and is widely discussed in the literature, under tire force adhesion limit maneuvering conditions to provide a theoretical basis for the design of control strategies of the CACC platoon under critical maneuvering conditions. Considering the nonlinear saturation characteristics of the tire force, an integrated platoon-vehicle nonlinear dynamic system is established. Based on the parameter space analysis of control gains, the equilibrium stability and head-to-tail string stability characteristics of the platoon under extreme conditions are studied. The results show that the stability design range of control gains for a platoon under extreme conditions is limited. Based on the adaptive cruise control (ACC) platoon, adding the following control of the leading vehicle to become a CACC platoon results in a smaller stability design range of control gains for equilibrium stability, but it can greatly increase the design range for head-to-tail string stability. The string stability requirement is more stringent than is the equilibrium stability requirement under extreme conditions, and the parameter space for string stability is significantly smaller than that for equilibrium stability. Compared with the ACC platoon, the CACC platoon has strong adaptability and disturbance resistance to the variations of vehicle speed and road adhesion under extreme conditions. Hence, it presents obvious advantages.

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《中国公路学报》是由中国科学技术协会主管，中国公路学会主办，长安大学承办的公路交通行业最权威的学术性刊物，自1988年创刊以来，一直走在公路交通科技发展的最前沿。办刊宗旨：提升公路交通领域学术交流质效，促进中国公路交通科技创新，推动中国公路交通事业发展。

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