Journal of Intelligent Transportation Systems最新文献

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A reinforcement learning based autonomous vehicle control in diverse daytime and weather scenarios 基于强化学习的自主车辆控制,适用于不同的白天和天气情况
IF 3.6 3区 工程技术
Journal of Intelligent Transportation Systems Pub Date : 2024-06-26 DOI: 10.1080/15472450.2024.2370010
Badr Ben Elallid, Miloud Bagaa, Nabil Benamar, Nabil Mrani
{"title":"A reinforcement learning based autonomous vehicle control in diverse daytime and weather scenarios","authors":"Badr Ben Elallid, Miloud Bagaa, Nabil Benamar, Nabil Mrani","doi":"10.1080/15472450.2024.2370010","DOIUrl":"https://doi.org/10.1080/15472450.2024.2370010","url":null,"abstract":"Autonomous driving holds significant promise for substantially reducing road fatalities. Unlike traditional machine learning methods that have conventionally been applied to enhance the motion cont...","PeriodicalId":54792,"journal":{"name":"Journal of Intelligent Transportation Systems","volume":"16 1","pages":""},"PeriodicalIF":3.6,"publicationDate":"2024-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141737117","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Integrating vehicle trajectory planning and arterial traffic management to facilitate eco-approach and departure deployment 整合车辆轨迹规划和干道交通管理,促进生态进场和离场部署
IF 3.6 3区 工程技术
Journal of Intelligent Transportation Systems Pub Date : 2024-06-24 DOI: 10.1080/15472450.2024.2369988
Hao Liu, Alex A. Kurzhanskiy, Wanshi Hong, Xiao-Yun Lu
{"title":"Integrating vehicle trajectory planning and arterial traffic management to facilitate eco-approach and departure deployment","authors":"Hao Liu, Alex A. Kurzhanskiy, Wanshi Hong, Xiao-Yun Lu","doi":"10.1080/15472450.2024.2369988","DOIUrl":"https://doi.org/10.1080/15472450.2024.2369988","url":null,"abstract":"Eco-approach and departure (EAD) enable continuous vehicle motion in urban signalized corridors. Since such a motion can extend to the EAD vehicles’ followers, it makes EAD a promising technology t...","PeriodicalId":54792,"journal":{"name":"Journal of Intelligent Transportation Systems","volume":"207 1","pages":""},"PeriodicalIF":3.6,"publicationDate":"2024-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141511945","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Identifying critical transfer zones to coordinate transit with on-demand services using crowdsourced trajectory data 利用众包轨迹数据确定关键换乘区,以协调公交与按需服务的关系
IF 3.6 3区 工程技术
Journal of Intelligent Transportation Systems Pub Date : 2024-05-03 DOI: 10.1080/15472450.2022.2132389
Jiahua Qiu , Yue Jing , Wang Peng , Lili Du , Yujie Hu
{"title":"Identifying critical transfer zones to coordinate transit with on-demand services using crowdsourced trajectory data","authors":"Jiahua Qiu ,&nbsp;Yue Jing ,&nbsp;Wang Peng ,&nbsp;Lili Du ,&nbsp;Yujie Hu","doi":"10.1080/15472450.2022.2132389","DOIUrl":"10.1080/15472450.2022.2132389","url":null,"abstract":"<div><p>This study develops a data-driven approach for identifying critical transfer zones in the city to facilitate the coordination of transit and emerging on-demand services. First, the methods convert the trajectories into a 3 D grid with an optimal cube size. Built upon that, we zoom in and study the trajectory density of each mode in a cube and present the results by heatmaps. After that, we zoom out and aggregate those cube information fragments through the clustering algorithms to explore two critical patterns: the ridesharing swarm (RS) zones where many ridesharing trips go through, and the “sandwich pattern” zones where a transit trajectory dominant zone is sandwiched by two ridesharing trajectory dominant zones. Our numerical analysis confirms that these RS zones are well correlated to the promising areas/corridors for integrating transit and on-demand services; the “sandwich patterns” help discover first/last mile (FLM) zones. Last, we further develop a two-channel deep learning network to predict the variation of the FLM gaps so that adaptive services can be planned. A case study based on the field data of the second ring region of Chengdu, China confirms the effectiveness and capability of our analysis approach.</p></div>","PeriodicalId":54792,"journal":{"name":"Journal of Intelligent Transportation Systems","volume":"28 3","pages":"Pages 386-408"},"PeriodicalIF":3.6,"publicationDate":"2024-05-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82839157","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Price incentive strategy for the E-scooter sharing service using deep reinforcement learning 使用深度强化学习的电动滑板车共享服务价格激励策略
IF 3.6 3区 工程技术
Journal of Intelligent Transportation Systems Pub Date : 2024-05-03 DOI: 10.1080/15472450.2022.2135437
Hyunsoo Yun , Eui-Jin Kim , Seung Woo Ham , Dong-Kyu Kim
{"title":"Price incentive strategy for the E-scooter sharing service using deep reinforcement learning","authors":"Hyunsoo Yun ,&nbsp;Eui-Jin Kim ,&nbsp;Seung Woo Ham ,&nbsp;Dong-Kyu Kim","doi":"10.1080/15472450.2022.2135437","DOIUrl":"10.1080/15472450.2022.2135437","url":null,"abstract":"<div><p>The electric-scooter (e-scooter) has become a popular mode of transportation with the proliferation of shared mobility services. As with other shared mobility services, the operation of the e-scooter sharing service has a recurring problem of imbalance in supply and demand. Various strategies have been studied to resolve the imbalance problems, including demand prediction and relocation strategies. However, the difficulty of accurately predicting the fluctuating demand and the excessive cost-labor consumption of relocation are major limitations of these strategies. As a remedy, we propose a deep reinforcement learning algorithm that suggests price incentives and an alternative rental location for users who find it difficult to acquire e-scooters at their desired boarding locations. A proximal policy optimization algorithm considering temporal dependencies is applied to develop a reinforcement learning agent that allocates the given initial budget to provide price incentives in a cost-efficient manner. We allow the proposed algorithm to re-use a portion of the operating profit as price incentives, which brings higher efficiency compared to the same initial budget. Our proposed algorithm is capable of reducing as much as 56% of the unmet demands by efficiently distributing price incentives. The result of the geographical analysis shows that the proposed algorithm can provide benefits to both users and service providers by promoting the use of idle e-scooters with a price incentive. Through experimental analysis, optimal budget, i.e., the most efficient initial budget, is suggested, which can contribute to e-scooter operators developing efficient e-scooter sharing services.</p></div>","PeriodicalId":54792,"journal":{"name":"Journal of Intelligent Transportation Systems","volume":"28 3","pages":"Pages 409-423"},"PeriodicalIF":3.6,"publicationDate":"2024-05-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77477285","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
A novel context-aware system to improve driver’s field of view in urban traffic networks 改善城市交通网络中驾驶员视野的新型情境感知系统
IF 3.6 3区 工程技术
Journal of Intelligent Transportation Systems Pub Date : 2024-05-03 DOI: 10.1080/15472450.2022.2130290
A. Nourbakhshrezaei , M. Jadidi , M. R. Delavar , B. Moshiri
{"title":"A novel context-aware system to improve driver’s field of view in urban traffic networks","authors":"A. Nourbakhshrezaei ,&nbsp;M. Jadidi ,&nbsp;M. R. Delavar ,&nbsp;B. Moshiri","doi":"10.1080/15472450.2022.2130290","DOIUrl":"10.1080/15472450.2022.2130290","url":null,"abstract":"<div><p>Principal objectives of the Intelligent Transportation Systems (ITS) are to improve traffic safety, facilitate informed traffic decision making, and enhance quality of life and services in a smart traffic environment. Vehicle crashes at urban traffic intersections are among the rudimentary sources of injuries and fatalities in the cities. According to the report of the World Health Organization (WHO), in every 25 seconds, one vulnerable road-user is being killed by a vehicle crash. Therefore, it is necessary to take a novel and smart approach for improving the safety and reducing vehicle crashes. This leads to a contextual perception and spatial awareness of driver to increase security and safety for the driver, vehicle, and road users. Autonomous vehicles collects the information from the environment through equipped sensors on the vehicle such as camera, laser, radar, and Global Navigation Satellite Systems (GNSS). The main challenge arises when the person or objects are located beyond the driver’s Field of View (FOV) and cannot be detected by embedded sensors on the vehicles. This paper proposes an Advanced Driver Assistance System (ADAS) to increase the safety on road intersections by taking advantage of existing infrastructures (e.g road camera) being used for traffic control. The aim of this research is improving the driver’s FOV using a computer vision approach (e.g background subtraction algorithm) and Location Based Service (LBS). The case study results at Tehran metropolitan demonstrate the reduction in traffic collision risk and improvement of pedestrian safety using the proposed system.</p></div>","PeriodicalId":54792,"journal":{"name":"Journal of Intelligent Transportation Systems","volume":"28 3","pages":"Pages 297-312"},"PeriodicalIF":3.6,"publicationDate":"2024-05-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85306183","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
A data-driven method for flight time estimation based on air traffic pattern identification and prediction 基于空中交通模式识别和预测的数据驱动飞行时间估算方法
IF 3.6 3区 工程技术
Journal of Intelligent Transportation Systems Pub Date : 2024-05-03 DOI: 10.1080/15472450.2022.2130693
Chunwei Yang , Junfeng Zhang , Xuhao Gui , Zihan Peng , Bin Wang
{"title":"A data-driven method for flight time estimation based on air traffic pattern identification and prediction","authors":"Chunwei Yang ,&nbsp;Junfeng Zhang ,&nbsp;Xuhao Gui ,&nbsp;Zihan Peng ,&nbsp;Bin Wang","doi":"10.1080/15472450.2022.2130693","DOIUrl":"10.1080/15472450.2022.2130693","url":null,"abstract":"<div><p>Flight time estimation is expected to play a crucial role in predicting the Estimated Time of Arrival, which could help detect conflicts and manage arrivals. This paper proposes a novel data-driven method for flight time estimation based on arrival pattern identification and prediction. Firstly, a trajectory clustering algorithm is employed to group the arrival trajectories into different arrival patterns. A new trajectory representation technique is presented during the clustering process for better-describing arrival patterns. Secondly, we extract features from radar tracks for data-driven flight time estimation. These features consist of current states related, historical information related, traffic situation related, and environmental conditions related features. Furthermore, the permutation feature importance and recursive feature elimination method are adopted to reduce feature dimensions. Then, we develop three widely used tree-based models to estimate the flight time for each arrival pattern. We also propose an image-based flight patterns prediction method to classify each new arrival aircraft into the corresponding arrival pattern for actual operation. Finally, we take the Guangzhou arrival operation as a case to validate our proposed method. The results indicate that our proposed method could improve flight time estimating accuracy. Besides, through the data-driven strategy, we could also find several significant factors affecting the flight time within the Terminal Maneuvering Area.</p></div>","PeriodicalId":54792,"journal":{"name":"Journal of Intelligent Transportation Systems","volume":"28 3","pages":"Pages 352-371"},"PeriodicalIF":3.6,"publicationDate":"2024-05-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85178366","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Including network level safety measures in eco-routing 在生态路由中纳入网络层面的安全措施
IF 3.6 3区 工程技术
Journal of Intelligent Transportation Systems Pub Date : 2024-05-03 DOI: 10.1080/15472450.2022.2129022
Sepehr G. Dehkordi , Grégoire S. Larue , Michael E. Cholette , Andry Rakotonirainy , Sébastien Glaser
{"title":"Including network level safety measures in eco-routing","authors":"Sepehr G. Dehkordi ,&nbsp;Grégoire S. Larue ,&nbsp;Michael E. Cholette ,&nbsp;Andry Rakotonirainy ,&nbsp;Sébastien Glaser","doi":"10.1080/15472450.2022.2129022","DOIUrl":"10.1080/15472450.2022.2129022","url":null,"abstract":"<div><p>Following the most energy-efficient route can have a significant impact on reducing energy consumption. While most eco-routing research has focused on reducing energy consumption and travel time, the safety aspect of route choice is currently neglected. In this paper, a multi-objective optimization methodology is formulated to concurrently minimize fuel consumption, travel time and safety risk, which is quantified using a novel methodology based on network-level safety measures. The proposed optimization framework provides a transparent way to intuitively include driver preferences via “budgets” for time, fuel consumption and safety – which represent the driver’s willingness to sacrifice these factors for fuel consumption improvements. The performance of the proposed method was tested on urban road networks in Brisbane-Australia, with a rear-end collision risk model as the safety measure. The results demonstrate that eco-routing with safety considerations has the potential to improve fuel efficiency while simultaneously reducing safety risks.</p></div>","PeriodicalId":54792,"journal":{"name":"Journal of Intelligent Transportation Systems","volume":"28 3","pages":"Pages 283-296"},"PeriodicalIF":3.6,"publicationDate":"2024-05-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78027022","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
A multi-state merging based analytical model for an operation design domain of autonomous vehicles in work zones on two-lane highways 基于多状态合并的分析模型,适用于双车道高速公路工作区自动驾驶车辆的运行设计域
IF 3.6 3区 工程技术
Journal of Intelligent Transportation Systems Pub Date : 2024-05-03 DOI: 10.1080/15472450.2022.2130697
Qing Tang , Xianbiao Hu
{"title":"A multi-state merging based analytical model for an operation design domain of autonomous vehicles in work zones on two-lane highways","authors":"Qing Tang ,&nbsp;Xianbiao Hu","doi":"10.1080/15472450.2022.2130697","DOIUrl":"10.1080/15472450.2022.2130697","url":null,"abstract":"<div><p>As a special application of connected and automated vehicles (CAVs), the Autonomous Truck Mounted Attenuator (ATMA) vehicle system is promoted to reduce fatalities in work zone locations. In this manuscript, we focus on the Operational Design Domain (ODD) problem of two-lane highways, i.e., under what traffic conditions should an ATMA be deployed. Due to the dramatic speed difference between ATMA vehicles and general vehicles, a queue will be formed, leading to a percent-time-spent-following (PTSF) increase during maintenance. General vehicles in the queue will assess a gap on the opposite lane to perform a passing maneuver, which is broken down into multi-stage merging behavior. As such, an analytical model is first made, based on queuing theory in which the arrival rate and service rate are analyzed to estimate the PTSF. In this way, the linkage between annual average daily traffic (AADT) and level of service (LOS) is analytically established. Then, the proposed model is validated by comparing the estimated PTSF with that of the Highway Capacity Manual (HCM) values. The comparison results show that the mean error is 9.58%, and the mean absolute error is 12.36%, which demonstrate that the developed model is able to generate satisfactory results when compared with the HCM model. Numeric analysis also shows that roadway performance is sensitive to the K factor and D factor, as well as the operating speed of an ATMA. If LOS = C is a desirable design objective, a good AADT threshold to use would be around 11,000 vehicles per day.</p></div>","PeriodicalId":54792,"journal":{"name":"Journal of Intelligent Transportation Systems","volume":"28 3","pages":"Pages 372-385"},"PeriodicalIF":3.6,"publicationDate":"2024-05-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78862430","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
A stochastic microscopic based freeway traffic state and spatial-temporal pattern prediction in a connected vehicle environment 互联车辆环境中基于随机微观的高速公路交通状态和时空模式预测
IF 3.6 3区 工程技术
Journal of Intelligent Transportation Systems Pub Date : 2024-05-03 DOI: 10.1080/15472450.2022.2130291
Seiran Heshami , Lina Kattan
{"title":"A stochastic microscopic based freeway traffic state and spatial-temporal pattern prediction in a connected vehicle environment","authors":"Seiran Heshami ,&nbsp;Lina Kattan","doi":"10.1080/15472450.2022.2130291","DOIUrl":"10.1080/15472450.2022.2130291","url":null,"abstract":"<div><p>Traffic state prediction forms the basis for effective and efficient traffic control and management strategies. A model-based traffic state prediction approach based on a stochastic microscopic three-phase model is developed to predict traffic flow, speed, and travel time in short prediction horizons consisting of multiple time steps ahead. The proposed model utilizes connected vehicles’ trajectory data including location and speed information and fuses this information with detector measurements using an Adaptive Kalman filter. Stochastic driver behaviors in merging, lane-changing, and over-acceleration are considered in the three-phase microscopic model, which allows for a precise prediction of macroscopic parameters for a relatively long stretch of freeway. Traffic flow and speed predictions are conducted for each lane individually and, for a whole segment. Per-lane predictions provide valuable information regarding different speed fluctuations in each lane for identifying congestion and applying proactive freeway controls. Predicted traffic parameters are used for tracking and predicting the spatial-temporal traffic patterns in real-time. The accuracy of the proposed model is examined and validated for various penetration rates of connected vehicles and prediction horizons and outperforms the baseline prediction methods.</p></div>","PeriodicalId":54792,"journal":{"name":"Journal of Intelligent Transportation Systems","volume":"28 3","pages":"Pages 313-339"},"PeriodicalIF":3.6,"publicationDate":"2024-05-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74454901","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Comparative analysis of drowsiness and performance in conditionally automated driving and manual driving considering the effect of circadian rhythm 考虑到昼夜节律的影响,对有条件自动驾驶和手动驾驶中的嗜睡和表现进行比较分析
IF 3.6 3区 工程技术
Journal of Intelligent Transportation Systems Pub Date : 2024-05-03 DOI: 10.1080/15472450.2022.2130292
Qi Zhang , Chaozhong Wu , Hui Zhang , Sara Ferreira
{"title":"Comparative analysis of drowsiness and performance in conditionally automated driving and manual driving considering the effect of circadian rhythm","authors":"Qi Zhang ,&nbsp;Chaozhong Wu ,&nbsp;Hui Zhang ,&nbsp;Sara Ferreira","doi":"10.1080/15472450.2022.2130292","DOIUrl":"10.1080/15472450.2022.2130292","url":null,"abstract":"<div><p>Drowsiness in manual driving (MD) is influenced by circadian rhythms. Conditionally automated driving (CAD) affects drivers’ drowsiness. We conducted a simulator study with 30 participants (every ten subjects in morning group, afternoon group, and evening group) to investigate the effect of circadian rhythm on the changes in drivers’ drowsiness and performance in different driving modes. Each subject was required to complete CAD experiment first and MD experiment later, and experienced 8 risk scenarios in each experiment. The self-reported Karolinska Sleepiness Scale (KSS) was recorded by an investigator every time when the subject drove past the scenario as the drowsiness measurement. The speed, acceleration, time-related metrics, and vehicle lane position were collected as the performance measurements. KSS data were statistically analyzed, and the Spearman’s Rho test was used to confirm the correlation among performance measurements, KSS, and scenarios. The result of the KSS statistical analysis showed that the effect of circadian rhythm on fatigue in MD groups is consistent with the previous studies, but the existence of CAD changes the effect of the circadian rhythm. Compared with the MD, CAD slowed down the drowsiness growth rate in the morning group and promoted the drowsiness growth rate in the evening group. The brake input rate, mean longitude acceleration, max Standard Deviation of Lane Position (SDLP), and the time to pass (TTP) were significantly related to the driver´s drowsiness in both driving modes.</p></div>","PeriodicalId":54792,"journal":{"name":"Journal of Intelligent Transportation Systems","volume":"28 3","pages":"Pages 340-351"},"PeriodicalIF":3.6,"publicationDate":"2024-05-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85896125","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
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