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学者姓名：荣建
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Abstract ：
To provide a better understanding of individual driver's driving style classification in a traditional and a CV environment, spatiotemporal characteristics of vehicle trajectories on a road tunnel were extracted through a driving simulator-based experiment. Speed, acceleration, and rate of acceleration changes are selected as clustering indexes. The dynamic time warping and k-means clustering were adopted to classify participants into different risk level groups. To assess the driver behavior benefits in a CV environment, an indicator BI (behavior indicator, BI) was defined based on the standard deviation of speed, the standard deviation of acceleration, and the standard deviation of the rate of acceleration change. Then, the index BI of each driver was calculated. Furthermore, this paper explored driving style classification, not in terms of traditional driving environment, but rather the transition patterns from a traditional driving environment to a CV environment. The results revealed that inside a long tunnel, 80 % of drivers benefited from a CV environment. Moreover, drivers might need training before using a CV system, especially female drivers who have low driving mileage. In addition, the results showed that the driving style of 69 % of the drivers' transferred from a high risk-level to a low risk-level when driving in a CV environment. The study results can be expected to improve driving training education programs and also to provide a valuable reference for developing individual in-vehicle human-machine interface projects and other proactive safety countermeasures.
Keyword ：
Driving simulator Driving simulator Driving behavior classification Driving behavior classification Vehicle trajectory Vehicle trajectory Driving style Driving style Connected vehicle Connected vehicle Road tunnel Road tunnel
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| GB/T 7714 | Chang, Xin , Li, Haijian , Zhang, Xingjian et al. Transition patterns of driving style from a traditional driving environment to a connected vehicle environment: A case of an extra-long tunnel road [J]. | TRANSPORTATION RESEARCH PART F-TRAFFIC PSYCHOLOGY AND BEHAVIOUR , 2022 , 90 : 181-195 . |
| MLA | Chang, Xin et al. "Transition patterns of driving style from a traditional driving environment to a connected vehicle environment: A case of an extra-long tunnel road" . | TRANSPORTATION RESEARCH PART F-TRAFFIC PSYCHOLOGY AND BEHAVIOUR 90 (2022) : 181-195 . |
| APA | Chang, Xin , Li, Haijian , Zhang, Xingjian , Rong, Jian , Zhao, Xiaohua . Transition patterns of driving style from a traditional driving environment to a connected vehicle environment: A case of an extra-long tunnel road . | TRANSPORTATION RESEARCH PART F-TRAFFIC PSYCHOLOGY AND BEHAVIOUR , 2022 , 90 , 181-195 . |
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Abstract ：
为探讨雾天高速公路车路协同系统信息介入对驾驶人视觉信息加工模式的影响,首先,依托驾驶模拟平台设计了车路协同环境下的雾天高速公路驾驶模拟实验,获取驾驶人的视觉行为参数;其次,将前方道路定义为关键兴趣区域,分别提取驾驶人在全局水平及兴趣区域的注视、扫视等显性视觉特性指标,并分析其分布规律;最后,采用因子分析方法获取信息提取因子、感知密度因子及信息搜索因子共3个公因子,以表征雾天高速公路车路协同系统作用下驾驶人的视觉信息加工模式。结果表明,车路协同系统的应用会显著影响驾驶人的扫视行为及对前方道路的视觉资源分配,多元信息的介入改变了原有的信息分布,使驾驶员的信息提取效率提高,信息感知密度降低,信息搜索...
Keyword ：
视觉信息加工 视觉信息加工 雾天预警 雾天预警 车路协同 车路协同 模拟驾驶 模拟驾驶
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| GB/T 7714 | 李雪玮 , 赵晓华 , 李振龙 et al. 基于雾天高速车路协同模拟驾驶的驾驶人视觉信息加工模式 [J]. | 华南理工大学学报(自然科学版) , 2021 , 49 (03) : 131-138,148 . |
| MLA | 李雪玮 et al. "基于雾天高速车路协同模拟驾驶的驾驶人视觉信息加工模式" . | 华南理工大学学报(自然科学版) 49 . 03 (2021) : 131-138,148 . |
| APA | 李雪玮 , 赵晓华 , 李振龙 , 杨家夏 , 荣建 . 基于雾天高速车路协同模拟驾驶的驾驶人视觉信息加工模式 . | 华南理工大学学报(自然科学版) , 2021 , 49 (03) , 131-138,148 . |
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Abstract ：
基于行程时间累积分布曲线的微观交通仿真模型参数标定
Keyword ：
微观交通仿真 微观交通仿真 信号交叉口 信号交叉口 仿真参数标定 仿真参数标定 DTW算法 DTW算法 智能交通 智能交通 行程时间 行程时间
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| GB/T 7714 | 高亚聪 , 周晨静 , 荣建 et al. 基于行程时间累积分布曲线的微观交通仿真模型参数标定 [J]. | 高亚聪 , 2021 , 38 (4) : 121-130 . |
| MLA | 高亚聪 et al. "基于行程时间累积分布曲线的微观交通仿真模型参数标定" . | 高亚聪 38 . 4 (2021) : 121-130 . |
| APA | 高亚聪 , 周晨静 , 荣建 , 公路交通科技 . 基于行程时间累积分布曲线的微观交通仿真模型参数标定 . | 高亚聪 , 2021 , 38 (4) , 121-130 . |
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Abstract ：
基于雾天高速车路协同模拟驾驶的驾驶人视觉信息加工模式
Keyword ：
模拟驾驶 模拟驾驶 视觉信息加工 视觉信息加工 车路协同 车路协同 雾天预警 雾天预警
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| GB/T 7714 | 李雪玮 , 赵晓华 , 李振龙 et al. 基于雾天高速车路协同模拟驾驶的驾驶人视觉信息加工模式 [J]. | 李雪玮 , 2021 , 49 (3) : 131-138,148 . |
| MLA | 李雪玮 et al. "基于雾天高速车路协同模拟驾驶的驾驶人视觉信息加工模式" . | 李雪玮 49 . 3 (2021) : 131-138,148 . |
| APA | 李雪玮 , 赵晓华 , 李振龙 , 杨家夏 , 荣建 , 华南理工大学学报:自然科学版 . 基于雾天高速车路协同模拟驾驶的驾驶人视觉信息加工模式 . | 李雪玮 , 2021 , 49 (3) , 131-138,148 . |
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Abstract ：
为了实时掌握信号交叉口饱和流率动态变化规律和提升估算精度,构建了以神经网络为基础的饱和流率动态估计模型.通过对北京市典型信号交叉口3种场景(直行进口道、直行左转进口道、直行右转进口道)实测数据为研究对象,分析每种场景下交通流运行特征,确定影响饱和流率的关键因素,确定神经网络模型的输入输出参数,并对模型进行标定.最后与经典HCM方法进行对比.结果表明:不同场景下,神经网络模型估计精度均优于HCM方法;其估算误差分别为11.23％,7.02％,4.70％.提出的方法能够准确地动态估计饱和流率,成果可用于信号控制方案的实时调整与精细化的运行管理.
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| GB/T 7714 | 王益 , 荣建 , 周晨静 et al. 应用神经网络动态估计信号交叉口饱和流率 [J]. | 广西大学学报（自然科学版） , 2021 , 46 (3) : 714-723 . |
| MLA | 王益 et al. "应用神经网络动态估计信号交叉口饱和流率" . | 广西大学学报（自然科学版） 46 . 3 (2021) : 714-723 . |
| APA | 王益 , 荣建 , 周晨静 , 高亚聪 , 罗薇 . 应用神经网络动态估计信号交叉口饱和流率 . | 广西大学学报（自然科学版） , 2021 , 46 (3) , 714-723 . |
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Abstract ：
桥形标设计应用缺乏规范性,复杂桥形标影响驾驶人认读,进而影响通行效率及交通安全.?为明确桥形标复杂度对驾驶人认知加工的影响规律,借助Oddball范式针对不同复杂度桥形标开展脑电认知实验;综合考虑驾驶人的认读行为及脑电特性,提取认读时间、目的地寻找正确比例、脑电事件相关电位(event-related?potential,ERP)中早期注意电位N100及认知电位P3004个主要分析指标;采用重复测量方差分析量化桥形标复杂度对驾驶人认知过程及脑电特性的影响.?结果表明:随着桥形标复杂度的增加,驾驶人认读时间增长,目的地寻找正确比例降低;同时,诱发N100平均振幅、峰值更多地呈现负向偏移,P300平均振幅正向偏移增大,即驾驶人早期注意分配增加,早期注意时间滞后,认知难度增加;靶刺激与标准刺激的相对差异性越大,P300潜伏期越短,越容易与标准刺激低等复杂度桥形标辨别.
Keyword ：
N100 N100 事件相关电位 事件相关电位 桥形标 桥形标 认知过程 认知过程 脑电特性 脑电特性 P300 P300
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| GB/T 7714 | 李雪玮 , 赵晓华 , 黄利华 et al. 桥形标复杂度对驾驶人脑电认知特性的影响机理 [J]. | 西南交通大学学报 , 2021 , 56 (5) : 913-920 . |
| MLA | 李雪玮 et al. "桥形标复杂度对驾驶人脑电认知特性的影响机理" . | 西南交通大学学报 56 . 5 (2021) : 913-920 . |
| APA | 李雪玮 , 赵晓华 , 黄利华 , 荣建 . 桥形标复杂度对驾驶人脑电认知特性的影响机理 . | 西南交通大学学报 , 2021 , 56 (5) , 913-920 . |
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Abstract ：
一种基于驾驶模式转移特征的驾驶员风险评估方法属于交通安全技术领域。本发明包括：基于驾驶模拟技术，获取实验过程驾驶行为数据；根据所述驾驶行为数据进行模式辨识，得到驾驶模式数据；计算驾驶模式之间相互转移概率，作为驾驶风险评估指标；通过最大信息系数得到驾驶模式转移方式与驾驶风险的相关性排序；最后训练随机森林模型用于驾驶风险等级的辨识。本发明在对驾驶员的风险情况进行划分的同时，能够获取驾驶过程中的风险行为偏好，为驾驶员的风险等级评估提供方法，便于运输企业针对高风险驾驶员，采取个性化的培训措施，改善驾驶员的不良驾驶习惯，降低交通安全隐患。
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| GB/T 7714 | 荣建 , 孙宫昊 , 常鑫 . 一种基于驾驶模式转移特征的驾驶员风险评估方法 : CN202110058366.4[P]. | 2021-01-16 . |
| MLA | 荣建 et al. "一种基于驾驶模式转移特征的驾驶员风险评估方法" : CN202110058366.4. | 2021-01-16 . |
| APA | 荣建 , 孙宫昊 , 常鑫 . 一种基于驾驶模式转移特征的驾驶员风险评估方法 : CN202110058366.4. | 2021-01-16 . |
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Abstract ：
Driving fatigue is one of the main causes of traffic accidents in monotonous environments such as grassland highways. However, the process of generation of driving fatigue on grassland highways is still not clear. A driving simulation experiment with 23 participants was performed to collect data on driving behavior, reaction time and electrocardiogram (ECG) results when driving on a grassland highway. The effective feature indicators of driving fatigue based on driving behavior data were calculated by Pearson correlation coefficient and principal component analysis method. The matter-element model based on entropy weight method was used to quantify the generation process of driving fatigue (GPDF). GPDF was classified as different patterns by the eigenvalue of GPDF curves. Reaction time and ECG data were utilized to verify the rationality of GPDF. Results show that there were 13 feature indicators of driving behavior suitable for driving fatigue description. GPDF was not completely consistent among different participants and was classified into three patterns (i.e., mild, moderate and severe fatigue). The mean similarity for GPDF in each pattern was 0.87, 0.61 and 0.50. Validation test demonstrated that driving fatigue detection accuracy by GPDF was 72%. The mean similarity of the GPDF between driving behavior and ECG was 0.72. Driving fatigue tended to occur with driving time of 19 min or 33 min. This study is helpful to understand GPDF on grassland highways from the perspective of individual driving behavior, which would provide suggestions for the reasonable setting of anti-fatigue devices.
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| GB/T 7714 | Peng, Zhibiao , Rong, Jian , Wu, Yiping et al. Exploring the Different Patterns for Generation Process of Driving Fatigue Based on Individual Driving Behavior Parameters [J]. | TRANSPORTATION RESEARCH RECORD , 2021 , 2675 (8) : 408-421 . |
| MLA | Peng, Zhibiao et al. "Exploring the Different Patterns for Generation Process of Driving Fatigue Based on Individual Driving Behavior Parameters" . | TRANSPORTATION RESEARCH RECORD 2675 . 8 (2021) : 408-421 . |
| APA | Peng, Zhibiao , Rong, Jian , Wu, Yiping , Zhou, Chenjing , Yuan, Yuan , Shao, Xiansheng . Exploring the Different Patterns for Generation Process of Driving Fatigue Based on Individual Driving Behavior Parameters . | TRANSPORTATION RESEARCH RECORD , 2021 , 2675 (8) , 408-421 . |
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Abstract ：
Urban rail transit has been commonly regarded as an efficient transportation mode for alleviating the negative impacts of rapid urbanization. However, the complex and comprehensive built environment caused by rapid urbanization prevents policymakers and planners from understanding the performance of urban rail transit, particularly around transit stations. Developing station area typologies plays an important role in describing the characteristics of station areas. Numerous studies have developed typologies of station areas over the past decades; however, few have attempted to estimate the distribution of station types per station. To fill this gap, this paper first proposed the importance of a land use type (ILUT) index based on the term frequency-inverse document frequency method. This method avoids mutual concealment among land use types, to extract key built environment features based on built area datasets of the buffer areas of 337 selected urban rail stations in Beijing. Subsequently, the ILUT index was used to estimate the distribution of the station types per station using the latent Dirichlet allocation model. The 12 identified types of urban rail station areas in Beijing demonstrated that land use types consist of station types and presented the distribution of the station types with their probabilities, revealing the current performance of station areas. This paper proposes a description approach that will help policymakers and planners to effectively and efficiently identify and analyze built environment features.
Keyword ：
Urban planning Urban planning TF-IDF TF-IDF Morphology Morphology Land use type Land use type Urban rail station Urban rail station LDA LDA
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| GB/T 7714 | Liu, Siyang , Rong, Jian , Zhou, Chenjing et al. Probability -based typology for description of built environments around urban rail stations [J]. | BUILDING AND ENVIRONMENT , 2021 , 205 . |
| MLA | Liu, Siyang et al. "Probability -based typology for description of built environments around urban rail stations" . | BUILDING AND ENVIRONMENT 205 (2021) . |
| APA | Liu, Siyang , Rong, Jian , Zhou, Chenjing , Bian, Yang . Probability -based typology for description of built environments around urban rail stations . | BUILDING AND ENVIRONMENT , 2021 , 205 . |
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Abstract ：
To provide a better understanding of spatiotemporal characteristics of vehicle trajectories in connected vehicle environment, a driving simulation study was designed and conducted with an extra-long tunnel scenario. 35 drivers were recruited to participate in the driving experiment. To evaluate the spatiotemporal characteristics of vehicles with and without a warning system, objective measures were analyzed, including a spatiotemporal diagram of the curvature of obtained data and speed adjustment behaviors. This article also evaluated the impacts of connected vehicles on the traffic capacity based on the converging pattern mining method. The results indicated that the in-vehicle human-machine interface (HMI) improved driving behavior and traffic capacity. Notably, the in-vehicle HMI helped drivers better prepare for speed adjustments when approaching the tunnel and when the vehicle in front of the study vehicle made a sudden operational change. Moreover, the system contributed to a more stable operation speed, especially near the tunnel entrance, than that without the system. The findings suggest that connected vehicle environments enable drivers to change from traditional visual stimuli response behaviors to proactive response behaviors based on psychological expectations. Besides, based on the best-converging patterns from the spatiotemporal trajectories of 35 drivers, the results revealed that the traffic capacity could be improved by 22.19% under the experimental traffic flow conditions. Moreover, the differences in the benefits of the in-vehicle HMI among individuals were found to be statistically significant.
Keyword ：
Roads Roads driving simulator driving simulator Layout Layout Trajectory Trajectory Spatiotemporal phenomena Spatiotemporal phenomena Safety Safety Vehicles Vehicles human-machine interface (HMI) human-machine interface (HMI) spatiotemporal characteristics spatiotemporal characteristics Accidents Accidents Driving performance Driving performance extra-long tunnel extra-long tunnel traffic capacity traffic capacity
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| GB/T 7714 | Chang, Xin , Li, Haijian , Rong, Jian et al. Spatiotemporal Characteristics of Vehicle Trajectories in a Connected Vehicle Environment-A Case of an Extra-Long Tunnel Scenario [J]. | IEEE SYSTEMS JOURNAL , 2021 , 15 (2) : 2293-2304 . |
| MLA | Chang, Xin et al. "Spatiotemporal Characteristics of Vehicle Trajectories in a Connected Vehicle Environment-A Case of an Extra-Long Tunnel Scenario" . | IEEE SYSTEMS JOURNAL 15 . 2 (2021) : 2293-2304 . |
| APA | Chang, Xin , Li, Haijian , Rong, Jian , Qin, Lingqiao , Zhao, Xiaohua . Spatiotemporal Characteristics of Vehicle Trajectories in a Connected Vehicle Environment-A Case of an Extra-Long Tunnel Scenario . | IEEE SYSTEMS JOURNAL , 2021 , 15 (2) , 2293-2304 . |
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