Journal of Intelligent Transportation Systems最新文献_第5页

Evaluating the impacts of vehicle-mounted Variable Message Signs on passing vehicles: implications for protecting roadside incident and service personnel 评估车载可变讯息标志对过往车辆的影响：对保护路边事故及服务人员的影响

IF 2.8 3区工程技术 Q3 TRANSPORTATION

Journal of Intelligent Transportation Systems

Pub Date : 2024-11-01 DOI: 10.1080/15472450.2023.2227968

Jun Liu , Xing Fu , Alexander Hainen , Chenxuan Yang , Leon Villavicencio , William J. Horrey

This study aims to evaluate the Variable Message Signs (VMS) mounted over the cab of emergency vehicles as a safety countermeasure to protect roadside incident and service personnel. The research team collaborated with the Alabama Department of Transportation’s Safety Service Patrol (SSP) program, specifically the Alabama Service Assistance Patrol (ASAP) in the West Central Alabama region, to collect video data from their service vehicles. Deep learning techniques were employed to detect vehicles in the recorded videos. A total of 11,338 passing vehicles were detected in 135,946 frames of video footage, and their trajectories were extracted for analysis. The study focused on examining the behaviors and movements of passing vehicles, including their speed and lane change behaviors, and developed statistical models to systematically investigate the impact of VMS on these behaviors. Random intercept models were utilized to account for unobserved factors associated with different stop locations. The modeling results revealed significant relationships between the use of VMS and the behaviors of passing motorists. When the VMS was active, drivers were more likely to change lanes and reduce their speed compared to situations where the VMS was not active. The odds of a vehicle changing lanes were found to be 95% higher when the VMS was in use. These findings suggest that the utilization of VMS can have a positive impact on traffic, particularly for passenger vehicles. The study outcomes imply that the use of VMS could be an effective countermeasure in protecting roadside incidents and ensuring the safety of service personnel.

本研究旨在评估在应急车辆驾驶室上安装可变信息标志（VMS）作为保护路边事故和服务人员的安全对策。研究小组与阿拉巴马州交通部的安全服务巡逻队（SSP）项目合作，特别是阿拉巴马州中西部地区的阿拉巴马州服务援助巡逻队（ASAP），从他们的服务车辆中收集视频数据。采用深度学习技术检测录制视频中的车辆。在135,946帧的视频片段中，共检测到11,338辆过往车辆，并提取其轨迹进行分析。本研究重点考察了过往车辆的行为和运动，包括它们的速度和变道行为，并建立了统计模型来系统地研究VMS对这些行为的影响。随机截距模型用于解释与不同停车位置相关的未观察到的因素。建模结果揭示了VMS的使用与过路驾驶者行为之间的显著关系。当VMS处于活动状态时，驾驶员更有可能改变车道并降低速度，而VMS处于不活动状态。当使用自动驾驶系统时，车辆变道的几率要高出95%。这些发现表明，VMS的利用可以对交通产生积极影响，特别是对乘用车。研究结果表明，使用自动驾驶系统可以有效地保护路边事故，确保服务人员的安全。

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引用次数: 0

Traffic-sensitive speed advisory system based on Lagrangian traffic indicators 基于拉格朗日交通指标的交通敏感速度咨询系统

IF 2.8 3区工程技术 Q3 TRANSPORTATION

Journal of Intelligent Transportation Systems

Pub Date : 2024-11-01 DOI: 10.1080/15472450.2023.2236549

Pierre-Antoine Laharotte , Kinjal Bhattacharyya , Jonathan Perun , Nour-Eddin El Faouzi

Can we elaborate a traffic-sensitive eco-driving or GLOSA (Green Light Optimal Speed Advice) strategy with a frugal amount of data when approaching an intersection? Here is the purpose of this work, which aims to adapt a traffic-theory-based estimation of the expected queue-length within mixed traffic (Connected and non-Connected Vehicles) in the vicinity of a signalized intersection. While the expected queue-length methodology was developed recently and fits natively with Eulerian traffic indicators resulting from loop sensors or cameras, this paper adapts such a methodology to Lagrangian indicators as the traces produced by any Connected Vehicle, including Floating Car or Probe Data. The main interest of the methodology lies in the frugal amount of data and expenses required to perform the traffic-sensitive speed-advisory at any connected road intersection. The full methodology is developed to extend the SPAT messages broadcast to end-users and take advantage of the Cooperative Awareness Messages (CAM) acting as GPS traces for Connected Vehicles. Contrary to Eulerian-based indicators, no supplementary and costly investment is required to collect the input data and compute the queue-length estimation. However, applying strategies based on Lagrangian indicators will affect the direct traffic observation through these indicators. Therefore, it requires to develop an assessment and predictive framework to estimate the traffic conditions. The performance of the introduced methodology is compared to alternative methods, among other Eulerian-based methods. It results from the analysis that the introduced approach performs almost as well as the ones based on exhaustive, but costly data collections.

在接近十字路口时，我们能否设计一种对交通敏感的生态驾驶或GLOSA（绿灯最佳速度建议）策略？这是本研究的目的，其目的是在信号交叉口附近的混合交通（联网和非联网车辆）中采用基于交通理论的预期排队长度估计。虽然期望队列长度方法是最近发展起来的，并且适合于由环路传感器或摄像头产生的欧拉交通指标，但本文将这种方法应用于拉格朗日指标，即任何联网车辆（包括浮动汽车或探针数据）产生的轨迹。该方法的主要兴趣在于，在任何相连的十字路口执行交通敏感的速度咨询所需的数据和费用很少。开发了完整的方法，将spv消息广播扩展到最终用户，并利用协同感知消息（CAM）作为联网车辆的GPS跟踪。与基于欧拉的指标相反，不需要额外和昂贵的投资来收集输入数据并计算队列长度估计。然而，采用基于拉格朗日指标的策略会影响通过这些指标直接观察交通。因此，需要开发一个评估和预测框架来估计交通状况。介绍的方法的性能比较替代方法，在其他欧拉为基础的方法。分析结果表明，所引入的方法的性能几乎与基于详尽但昂贵的数据收集的方法一样好。

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引用次数: 0

A data-driven traffic shockwave speed detection approach based on vehicle trajectories data 基于车辆轨迹数据的数据驱动交通冲击波速度检测方法

IF 2.8 3区工程技术 Q3 TRANSPORTATION

Journal of Intelligent Transportation Systems

Pub Date : 2024-11-01 DOI: 10.1080/15472450.2023.2270415

Kaitai Yang , Hanyi Yang , Lili Du

Traffic shockwaves demonstrate the formation and spreading of traffic fluctuation on roads. Existing methods mainly detect the shockwaves and their propagation by estimating traffic density and flow, which presents weaknesses in applications when traffic data is only partially or locally collected. This paper proposed a four-step data-driven approach that integrates machine learning with the traffic features to detect shockwaves and estimate their propagation speeds only using partial vehicle trajectory data. Specifically, we first denoise the speed data derived from trajectory data by the Fast Fourier Transform (FFT) to mitigate the effect of spontaneous random speed fluctuation. Next, we identify trajectory curves’ turning points where a vehicle runs into a shockwave and its speed presents a high standard deviation within a short interval. Furthermore, the Density-based Spatial Clustering of Applications with Noise algorithm (DBSCAN) combined with traffic flow features is adopted to split the turning points into different clusters, each corresponding to a shockwave with constant speed. Last, the one-norm distance regression method is used to estimate the propagation speed of detected shockwaves. The proposed framework was applied to the field data collected from the I-80 and US-101 freeway by the Next Generation Simulation (NGSIM) program. The results show that this four-step data-driven method could efficiently detect the shockwaves and their propagation speeds without estimating the traffic densities and flows nearby. It performs well for both homogenous and nonhomogeneous road segments with trajectory data collected from total or partial traffic flow.

交通冲击波表现了道路上交通波动的形成和传播。现有的方法主要是通过估计交通密度和流量来检测冲击波及其传播，这在仅部分或局部收集交通数据的情况下存在弱点。本文提出了一种四步数据驱动方法，该方法将机器学习与交通特征相结合，仅使用部分车辆轨迹数据来检测冲击波并估计其传播速度。具体来说，我们首先通过快速傅里叶变换（FFT）对从轨迹数据中得到的速度数据进行去噪，以减轻自发随机速度波动的影响。其次，我们确定了轨迹曲线的拐点，在这些拐点中，车辆进入冲击波，其速度在短间隔内呈现高标准偏差。结合交通流特征，采用基于密度的噪声应用空间聚类算法（DBSCAN）将拐点划分为不同的聚类，每个聚类对应一个恒定速度的冲击波。最后，利用一范数距离回归方法对探测冲击波的传播速度进行估计。提出的框架应用于下一代模拟（NGSIM）程序从I-80和US-101高速公路收集的现场数据。结果表明，这种四步数据驱动方法可以在不估计附近交通密度和流量的情况下有效地检测出冲击波及其传播速度。该算法对于从全部或部分交通流中收集轨迹数据的同质和非同质路段都表现良好。

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引用次数: 0

Advisory versus automated dynamic eco-driving at signalized intersections: lessons learnt from empirical evidence and simulation experiments 信号交叉口的咨询与自动动态生态驾驶:从经验证据和模拟实验中吸取的教训

IF 2.8 3区工程技术 Q3 TRANSPORTATION

Journal of Intelligent Transportation Systems

Pub Date : 2024-11-01 DOI: 10.1080/15472450.2023.2289118

Evangelos Mintsis , Eleni I. Vlahogianni , Evangelos Mitsakis , Georgia Aifadopoulou

Research in the field of dynamic eco-driving has been primarily coupled with connected and automated vehicles which are equipped with automation functions that can accurately execute energy-efficient speed advice. Advisory dynamic eco-driving that entails driver adaptation to energy-efficient speed advice has received lesser attention although mixed traffic is expected to prevail in the forthcoming decades. This study developed a decision tree model based on real-world data collected during the pilot deployment of an advisory speed advice service along an urban arterial corridor to emulate driver adaptation to speed advice. The decision tree model was integrated into the control logic of an enhanced velocity planning algorithm to replicate the behavior of manually driven connected vehicles along dynamic eco-driving service zones in a microscopic traffic simulation environment. The conducted simulation analysis encompassed scenarios with varying penetration rates of advisory dynamic eco-driving technology, automated dynamic eco-driving technology and manually driven unequipped vehicles. Evaluation of simulation scenarios was based on the estimation of several environmental, traffic efficiency and surrogate safety measures. Simulation results indicated that performance of advisory dynamic eco-driving depends on driver adaptation to speed advice and ranges between that of manually driven unequipped vehicles and its automated counterpart. Moreover, geometrical and operational characteristics of intersection approaches comprising dynamic eco-driving service zones can influence driver adaptation to speed advice. Environmental, safety and traffic efficiency benefits are maximized in the case of vehicle fleets fully equipped with automated dynamic eco-driving systems.

动态生态驾驶领域的研究主要与联网和自动化车辆相结合，这些车辆配备了自动化功能，可以准确地执行节能…

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引用次数: 0

Accurate detection of vehicle, pedestrian, cyclist and wheelchair from roadside light detection and ranging sensors 准确检测车辆，行人，自行车和轮椅从路边的光检测和测距传感器

IF 2.8 3区工程技术 Q3 TRANSPORTATION

Journal of Intelligent Transportation Systems

Pub Date : 2024-11-01 DOI: 10.1080/15472450.2023.2243816

Junxuan Zhao , Hao Xu , Zhihui Chen , Hongchao Liu

Accurate detection plays a critical role in improving the safety situation of vulnerable road users. This study extends infrastructure-based LiDAR application to all three major vulnerable road user groups including pedestrians, cyclists, and wheelchair users. Two critical problems for accurate detection of small-sized road users are scanning angle variability and feature fluctuation. To address these issues, a feature-based classification method combined with prior LiDAR trajectory information is developed. Effective dimension-related features are proposed and five classifiers including artificial neural network (ANN), random forest (RF), adaptive boosting (AdaBoost), random under-sampling boosting (RUSBoost), and long short-term memory (LSTM) are tested with a novel feature engineering process. A total of seven features are selected from the point cloud of clusters for vehicle/pedestrian/cyclist/wheelchair classification. By updating these significant features based on prior information of the entire trajectory, the performance of road user classification (imbalanced datasets) has been significantly improved. Experimental study is conducted to examine the recall rate, F1-score, and AUC of vehicles, pedestrians, cyclists, and wheelchairs before and after integration with prior trajectory information. The result shows the trained AdaBoost, RUSBoost, and LSTM classifiers with prior trajectory information can achieve recall/F1-score/AUC: (1) Low traffic volumes – vehicles (100%/99.96%/99.96%), pedestrians (99.96%/99.96%/99.97%), cyclists (99.74%/99.45%/99.67%), and wheelchairs (99.22%/99.68%/99.01%) and (2) Moderate traffic volumes – vehicles (99.39%/99.44%/99.69%), pedestrians (98.33%/97.99%/98.64%), and cyclists (95.41%/94.29%/94.40%), using 32-laser LiDAR sensors (10 Hz).

准确的检测对于改善弱势道路使用者的安全状况起着至关重要的作用。本研究将基于基础设施的激光雷达应用扩展到所有三个主要的弱势道路使用者群体，包括行人、骑自行车的人和轮椅使用者。精确检测小型道路使用者的两个关键问题是扫描角度的变化和特征的波动。为了解决这些问题，提出了一种结合LiDAR轨迹信息的基于特征的分类方法。提出了有效的维度相关特征，并采用一种新的特征工程过程对人工神经网络（ANN）、随机森林（RF）、自适应增强（AdaBoost）、随机欠采样增强（RUSBoost）和长短期记忆（LSTM）五种分类器进行了测试。从聚类的点云中共选择7个特征进行车辆/行人/骑自行车/轮椅分类。通过基于整个轨迹的先验信息更新这些重要特征，显著提高了道路使用者分类（不平衡数据集）的性能。实验研究了整合先验轨迹信息前后车辆、行人、自行车和轮椅的召回率、f1得分和AUC。结果显示了训练有素的演算法,RUSBoost LSTM分类器与以前的轨迹信息可以实现召回/ F1-score / AUC:(1)低流量——车辆(100% / 99.96% / 99.96%),行人(99.96% / 99.96% / 99.97%),骑自行车的人(99.74% / 99.45% / 99.67%),和轮椅(99.22% / 99.68% / 99.01%)和(2)温和的流量-车辆(99.39% / 99.44% / 99.69%),行人(98.33% / 97.99% / 98.64%),和骑自行车的人(95.41% / 94.29% / 94.40%),使用32-laser激光雷达传感器(10 Hz)。

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引用次数: 0

Infrastructure sensor-based cooperative perception for early stage connected and automated vehicle deployment 基于基础设施传感器的早期互联和自动驾驶车辆协同感知

IF 2.8 3区工程技术 Q3 TRANSPORTATION

Journal of Intelligent Transportation Systems

Pub Date : 2024-11-01 DOI: 10.1080/15472450.2023.2257596

Chenxi Chen , Qing Tang , Xianbiao Hu , Zhitong Huang

Infrastructure-based sensors provide a potentially promising solution to support the wide adoption of connected and automated vehicles (CAVs) technologies at an early stage. For connected vehicles with lower level of automation that do not have perception sensors, infrastructure sensors will significantly boost its capability to understand the driving context. Even if a full suite of sensors is available on a vehicle with higher level of automation, infrastructure sensors can support overcome the issues of occlusion and limited sensor range. To this end, a cooperative perception modeling framework is proposed in this manuscript. In particular, the modeling focus is placed on a key technical challenge, time delay in the cooperative perception process, which is of vital importance to the synchronization, perception, and localization modules. A constant turn-rate velocity (CTRV) model is firstly developed to estimate the future motion states of a vehicle. A delay compensation and fusion module is presented next, to compensate for the time delay due to the computing time and communication latency. Last but not the least, as the behavior of moving objects (i.e., vehicles, cyclists, and pedestrians) is nonlinear in both position and speed aspects, an unscented Kalman filter (UKF) algorithm is developed to improve object tracking accuracy considering communication time delay between the ego vehicle and infrastructure-based LiDAR sensors. Simulation experiments are performed to test the feasibility and evaluate the performance of the proposed algorithm, which shows satisfactory results.

基于基础设施的传感器提供了一种潜在的解决方案，可以在早期阶段支持联网和自动驾驶汽车（cav）技术的广泛采用。对于自动化程度较低、没有感知传感器的联网汽车，基础设施传感器将显著提高其理解驾驶环境的能力。即使在自动化程度较高的车辆上配备了全套传感器，基础设施传感器也可以支持克服遮挡和传感器范围有限的问题。为此，本文提出了一种协作感知建模框架。特别地，建模重点放在了一个关键的技术挑战，即协同感知过程中的时间延迟，这对同步、感知和定位模块至关重要。首先建立了恒转弯速度（CTRV）模型来估计车辆未来的运动状态。然后提出了延迟补偿和融合模块，以补偿由于计算时间和通信延迟造成的时间延迟。最后但并非最不重要的是，由于移动物体（即车辆，骑自行车的人和行人）的行为在位置和速度方面都是非线性的，因此开发了一种无气味卡尔曼滤波（UKF）算法，以提高目标跟踪精度，考虑到自我车辆与基于基础设施的激光雷达传感器之间的通信时间延迟。仿真实验验证了该算法的可行性，并对其性能进行了评价，取得了满意的结果。

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引用次数: 0

Eliminating the impacts of traffic volume variation on before and after studies: a causal inference approach 消除交通量变化对研究前后的影响：一种因果推理方法

IF 2.8 3区工程技术 Q3 TRANSPORTATION

Journal of Intelligent Transportation Systems

Pub Date : 2024-11-01 DOI: 10.1080/15472450.2023.2245327

Xiaobo Ma , Abolfazl Karimpour , Yao-Jan Wu

A before and after study framework measures the outcomes in a group of participants before introducing an intervention, and then again afterward. In this study, a before and after study framework is adopted to evaluate the effectiveness of transportation policies and emerging technologies. Generally, the outcome of every before and after study will help decision-makers to monitor and understand the effects of interventions and to make sound decisions. However, many factors such as seasonal factors, holidays, and lane closures might interfere with the evaluation process by inducing variation in traffic volume during the before and after periods. In practice, limited effort has been made to eliminate the effects of these factors. In this study, an extreme gradient boosting (XGBoost)-based propensity score matching (PSM) method is proposed to reduce the biases caused by traffic volume variation during the before and after periods. In order to evaluate the effectiveness of the proposed method, a corridor in the City of Chandler, Arizona where an advanced traffic signal control system has been recently implemented was selected. The results indicated that the proposed method can effectively eliminate the variation in traffic volume caused by the COVID-19 during the evaluation process. In addition, the results of the t-test and Kolmogorov-Smirnov (KS) test demonstrated that the proposed method outperforms other state-of-the-art PSM methods. The application of the proposed method is also transferrable to other before and after evaluation studies and can significantly assist transportation engineers to eliminate the impacts of traffic volume variation on the evaluation process.

在引入干预措施之前和之后的研究框架测量了一组参与者的结果。在本研究中，采用前后研究框架来评估交通政策和新兴技术的有效性。通常，每次前后研究的结果将有助于决策者监测和了解干预措施的效果，并做出合理的决策。然而，许多因素，如季节因素、节假日和车道关闭，可能会通过诱导前后交通量的变化来干扰评估过程。在实践中，为消除这些因素的影响所作的努力有限。本文提出了一种基于极限梯度提升（XGBoost）的倾向得分匹配（PSM）方法，以减少交通流量前后变化所造成的偏差。为了评估所提出的方法的有效性，选择了亚利桑那州钱德勒市的一条走廊，该走廊最近实施了先进的交通信号控制系统。结果表明，该方法能有效消除评价过程中因新冠肺炎引起的交通量变化。此外，t检验和Kolmogorov-Smirnov （KS）检验的结果表明，所提出的方法优于其他最先进的PSM方法。该方法的应用也可推广到其他前后评价研究中，并可显著帮助交通工程师消除交通量变化对评价过程的影响。

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引用次数: 0

A hierarchical control framework for alleviating network traffic bottleneck congestion using vehicle trajectory data 基于车辆轨迹数据的分层控制框架缓解网络交通瓶颈拥塞

IF 2.8 3区工程技术 Q3 TRANSPORTATION

Journal of Intelligent Transportation Systems

Pub Date : 2024-11-01 DOI: 10.1080/15472450.2023.2270428

Lei Wei , Peng Chen , Yu Mei , Jian Sun , Yunpeng Wang

Traffic bottlenecks significantly influence the operation efficiency of large-scale road networks. Developing advanced control strategies for bottleneck optimization is a cost-efficient and critical way to deal with network congestion. However, the state-of-the-art studies on network congestion control focus on the topology level, which may fail to relieve congestion by addressing the root cause of bottleneck. This study proposed a hierarchical control framework for alleviating network traffic bottleneck congestion using vehicle trajectory data. First, the bottleneck-related sub-network (BRS) was identified by tracing vehicle trajectories upstream and downstream of the bottleneck based on the traffic flow propagation. Then, a hierarchical control framework was proposed for BRS optimization. Specifically, in the outer layer, i.e., the gating control layer, the multigated intersections in BRS were controlled via a multimemory deep Q-network approach to optimize the network traffic distribution. In the inner layer, i.e., the coordinated control layer, local intersection controllers were coordinated by adjusting the dynamic input and output streams of the bottleneck under the guidance of the outer layer controller, which helps balance the traffic pressure within BRS and avoids congestion transferring in the network. Both simulation and field experiments were conducted to verify the performance of the proposed hierarchical framework. Results reveal that the framework can effectively relieve network traffic congestion with decreased queue length and travel time.

交通瓶颈对大型路网的运行效率影响很大。开发先进的瓶颈优化控制策略是解决网络拥塞的一种经济有效的关键方法。然而，目前对网络拥塞控制的研究主要集中在拓扑层面，可能无法从瓶颈的根源上解决拥塞问题。本文提出了一种基于车辆轨迹数据的分层控制框架来缓解网络交通瓶颈拥塞。首先，基于交通流传播，通过跟踪瓶颈上下游的车辆轨迹，识别瓶颈相关子网络（BRS）；然后，提出了BRS优化的层次控制框架。具体而言，在外部层，即门控层，BRS中的多门交叉口通过多内存深度Q-network方法进行控制，以优化网络流量分布。在内层即协调控制层，在外层控制器的引导下，通过调整瓶颈的动态输入和输出流来协调局部交叉口控制器，从而平衡BRS内部的交通压力，避免网络中的拥塞转移。通过仿真和现场实验验证了所提出的分层框架的性能。结果表明，该框架能够有效缓解网络流量拥塞，减少队列长度和行程时间。

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引用次数: 0

Eco-friendly platooning operation algorithm of the electric vehicles 电动汽车的环保队列运行算法

IF 2.8 3区工程技术 Q3 TRANSPORTATION

Journal of Intelligent Transportation Systems

Pub Date : 2024-11-01 DOI: 10.1080/15472450.2023.2209911

Joonwon Jang , Sung Il Kwag , Young Dae Ko

Platooning is one of the promising technologies that maximizes the power efficiency of electric vehicles by decreasing the distances between the vehicles. Along with the development of autonomous driving technology, platooning is expected to be commercialized. Recent studies on the operation of platooning focused on power-efficient maintenance of platooning. However, power-efficient operation strategy is also needed for practical applications. Therefore, this study deals with platooning operations that can maximize the power efficiency of electric vehicles in various operational situations. In order to derive the operation method, a mathematical model structured with an objective function that minimizes power consumption is developed. To derive the solution of the mathematical model, a hybrid genetic algorithm is applied. The numerical experiments on four different operational situations are performed to verify the validity of the model and the solution procedure. The four situations consider overall situation that can happen during the platooning stage. The stages are formation, disassembly, join and breakaway of vehicles of platoon. Those four situations are decided upon since they can represent the general situation that can happen during platooning. As a result, the power-efficient driving patterns of electric vehicles are identified. After the development of electric and systematic technology, operational technology for platooning will collaborate for the further improvement. Therefore, throughout consideration of the formation of platooning, technology will expand the sustainability of technological development.

通过缩短车辆之间的距离，使电动汽车的功率效率最大化，是一种很有前途的技术之一。随着自动驾驶技术的发展，队列驾驶有望实现商业化。近年来对车队运行的研究主要集中在车队的节能维护方面。然而，在实际应用中也需要高效节能的操作策略。因此，本研究涉及在各种运行情况下，使电动汽车的功率效率最大化的队列操作。为了推导出操作方法，建立了以功耗最小为目标函数的数学模型。为了得到数学模型的解，采用了混合遗传算法。通过四种不同工况下的数值实验，验证了模型和求解过程的有效性。这四种情况考虑了排队阶段可能发生的总体情况。车队的组建、拆卸、连接和分离是车队的组成阶段。这四种情况是确定的，因为它们可以代表在队列中可能发生的一般情况。从而确定了电动汽车的节能驾驶模式。在电力技术和系统技术发展之后，车队的操作技术将协同进一步完善。因此，全程考虑编队的形成，将扩大技术发展的可持续性。

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引用次数: 0

Handling inevitable collision states by Advanced Driver Assistance Systems functions: software-in-the-loop performance assessment of an injury risk-based logic in a “lane departure” scenario 通过高级驾驶辅助系统功能处理不可避免的碰撞状态：在“车道偏离”场景下，基于伤害风险逻辑的软件在环性能评估

IF 2.8 3区工程技术 Q3 TRANSPORTATION

Journal of Intelligent Transportation Systems

Pub Date : 2024-11-01 DOI: 10.1080/15472450.2023.2277713

Michelangelo-Santo Gulino , Krzysztof Damaziak , Anita Fiorentino , Dario Vangi

The downward trend in the number of fatalities and serious injuries related to road accidents depends on the implementation of increasingly performing Advanced Driver Assistance Systems (ADAS) in the circulating fleet. The greatest benefit of the adoption of ADASs like Autonomous Emergency Braking (AEB) consists in limiting the frequency of impacts. However, in Inevitable Collision States (ICSs), the decrease in impact closing speed guaranteed by the AEB may not reduce the Injury Risk (IR) for the occupants: IR is a function of the vehicle’s velocity change in the collision (

Δ V

) – a combination of impact closing speed and impact eccentricity. The work virtually analyses, in lane departure ICS scenarios, the performance of an adaptive steering and braking intervention logic based on instantaneous IR minimization. The adaptive logic reduces IR compared to the absence of intervention (down to 80 times lower) and to the AEB (down to 40 times lower) by leading the ego vehicle toward eccentric impact configurations. It is highlighted that full activation of the steer-by-wire system in 0.3 s allows the adaptive logic to also reduce the frequency of impacts; it is further evidenced that employing a function capable of modulating the braking level to minimize IR entails disadvantages from the IR perspective compared to the AEB: efficient intervention strategies on the steering are the only alternative for increasing the safety provided by high-performance ADASs. Finally, compared to previous literature, the study highlights high efficiencies of the adaptive logic in a wide range of ICS scenarios.

与道路交通事故有关的死亡和重伤人数的下降趋势取决于在循环车队中越来越多地实施高级驾驶辅助系统（ADAS）。采用自动紧急制动（AEB）等自动驾驶辅助系统的最大好处在于限制了碰撞的频率。然而，在不可避免的碰撞状态（ics）中，AEB保证的碰撞关闭速度的降低可能不会降低乘员的伤害风险（IR）： IR是车辆在碰撞中速度变化的函数（ΔV） -碰撞关闭速度和碰撞偏心的组合。该工作虚拟分析了车道偏离ICS场景下基于瞬时红外最小化的自适应转向和制动干预逻辑的性能。与没有干预（降低了80倍）和AEB（降低了40倍）相比，自适应逻辑通过引导自我车辆进入偏心撞击配置，降低了IR。值得强调的是，在0.3秒内完全激活线控转向系统，使自适应逻辑也可以减少碰撞的频率；进一步证明，从红外角度来看，与AEB相比，采用能够调节制动水平以最小化红外的功能会带来缺点：高效的转向干预策略是提高高性能ADASs安全性的唯一选择。最后，与之前的文献相比，本研究强调了自适应逻辑在广泛的ICS场景中的高效率。

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引用次数: 0