Transportation Research Record最新文献_第6页

Improving Pedestrian Progression at Multistage Crossings Using Pedestrian–Left Turn Overlaps 利用行人-左转弯重叠改善多级交叉路口的行人通行

4区工程技术

Transportation Research Record Pub Date : 2023-10-03 DOI: 10.1177/03611981231198848

Felix Yik Kin Lao, Peter G. Furth

{"title":"Improving Pedestrian Progression at Multistage Crossings Using Pedestrian–Left Turn Overlaps","authors":"Felix Yik Kin Lao, Peter G. Furth","doi":"10.1177/03611981231198848","DOIUrl":"https://doi.org/10.1177/03611981231198848","url":null,"abstract":"At signalized intersections where pedestrian crossings are divided into two stages by using a median island, pedestrian delay can be very long if the partial-crossing phases have poor progression. One technique for reducing pedestrian delay is pedestrian–left turn overlaps, in which half-crossings that are not in conflict with a left turn are allowed to run during the left turn phase as well as during the parallel vehicle through phase. Such an overlap can enable some pedestrians to cross in a single pass, or to have a far shorter wait at the median. Because this technique requires surrendering some of the flexibility with which left turn phases normally operate—in phases with a pedestrian call, the left turn phase cannot be skipped and may require a longer minimum green—there can also be an impact on vehicle delay. A case study of two intersections in Brookline, MA found that, compared with the current timing plan, using pedestrian–left turn overlaps could reduce pedestrian delay from about 100 to 35 s, with a negligible impact on vehicle delay. A methodological innovation introduced in this study was that average pedestrian delay was calculated for three pedestrian speeds and averaged together, thus accounting for how pedestrian delay at multistage crossings can be far lower for faster pedestrians who may be able to cross in a single pass than for slower pedestrians who have to wait at the crossing island.","PeriodicalId":23279,"journal":{"name":"Transportation Research Record","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135740543","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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

Using Wi-Fi Connection Data to Analyze Performance of the Subway System in Toronto, Canada 使用Wi-Fi连接数据分析加拿大多伦多地铁系统的性能

4区工程技术

Transportation Research Record Pub Date : 2023-09-30 DOI: 10.1177/03611981231198845

Aidan Grenville, Willem Klumpenhouwer, Amer Shalaby

{"title":"Using Wi-Fi Connection Data to Analyze Performance of the Subway System in Toronto, Canada","authors":"Aidan Grenville, Willem Klumpenhouwer, Amer Shalaby","doi":"10.1177/03611981231198845","DOIUrl":"https://doi.org/10.1177/03611981231198845","url":null,"abstract":"Typical performance measurements of public transit operations make use of vehicle-based data such as automated vehicle location data or passenger-based data at specific fare collection points. Ideally, the performance of a transit system from a reliability perspective and according to passenger experience should be measured through individual passenger journeys. The growing prevalence of smartphones provides one potential source for this analysis, because passive data collection methods such as obtaining Wi-Fi, cellular, and Bluetooth connection data allow us to observe devices as they move throughout the system. In this study we present a collection of methods and performance measures for using Wi-Fi connection data to measure various aspects of customer experience and reliability, including methods for detecting train arrivals at platforms, estimating wait times, measuring origin–destination travel time variation, and developing profiles of various journey types for comparison. In contrast with many other advances toward passenger-based measures, these methods do not require the combination of diverse data sets to generate useful results. These methods are applied to data from the Wi-Fi service in the subway system in Toronto, Canada.","PeriodicalId":23279,"journal":{"name":"Transportation Research Record","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136279832","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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

Flight Conflict Resolution and Trajectory Recovery Through Mixed Integer Nonlinear Programming Based on Speed and Heading Angle Change 基于速度和航向角变化的混合整数非线性规划飞行冲突解决与轨迹恢复

4区工程技术

Transportation Research Record Pub Date : 2023-09-30 DOI: 10.1177/03611981231186602

Xiaoqin Liu, Gang Xiao

引用次数: 0

Resilience Enhancement of an Urban Rail Transit Network by Setting Turn-Back Tracks: A Scenario Model Approach 通过设置返程轨道增强城市轨道交通网络弹性:一个情景模型方法

4区工程技术

Transportation Research Record Pub Date : 2023-09-30 DOI: 10.1177/03611981231203157

Jinqu Chen, Chengzhen Jiang, Xiaowei Liu, Bo Du, Qiyuan Peng, Yong Yin, Baowen Li

{"title":"Resilience Enhancement of an Urban Rail Transit Network by Setting Turn-Back Tracks: A Scenario Model Approach","authors":"Jinqu Chen, Chengzhen Jiang, Xiaowei Liu, Bo Du, Qiyuan Peng, Yong Yin, Baowen Li","doi":"10.1177/03611981231203157","DOIUrl":"https://doi.org/10.1177/03611981231203157","url":null,"abstract":"The resilience of an urban rail transit (URT) network when faced with disruptions is affected by the locations of stations equipped with turn-back (TB) tracks. However, limited studies have enhanced the resilience of a URT network by setting new TB tracks. The present work addresses this gap by proposing and solving a scenario model for improving the operation of a URT network under normal conditions and disruptions by considering uncertain disruptions. A solution algorithm combined with the non-dominated sorting genetic algorithm-II is proposed to solve the model. Numerical experiments conducted on the Chengdu subway system indicate that the resilience of a URT network is significantly affected by TB operations provided at stations equipped with TB tracks. Compared with a network without new TB tracks, the matching degree between passenger flow spatial distribution and TB convenience, and the network’s overall resilience metric (NORM) are improved by 12.05% and 0.58%, respectively, when five new TB tracks are installed. The solution effectiveness of the model is related to the number of new TB tracks, and the NORM decreases by an average of [Formula: see text] after adding new TB tracks to a station.","PeriodicalId":23279,"journal":{"name":"Transportation Research Record","volume":"68 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136280442","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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

Spatio-Temporal Graph Neural Network for Traffic Prediction Based on Adaptive Neighborhood Selection 基于自适应邻域选择的时空图神经网络交通预测

4区工程技术

Transportation Research Record Pub Date : 2023-09-30 DOI: 10.1177/03611981231198851

HuanZhong Sun, XiangHong Tang, JianGuang Lu, FangJie Liu

{"title":"Spatio-Temporal Graph Neural Network for Traffic Prediction Based on Adaptive Neighborhood Selection","authors":"HuanZhong Sun, XiangHong Tang, JianGuang Lu, FangJie Liu","doi":"10.1177/03611981231198851","DOIUrl":"https://doi.org/10.1177/03611981231198851","url":null,"abstract":"Traffic prediction is critical to intelligent transportation and smart cities. The prediction performance of many existing traffic prediction models is limited by the fixed original graph structure and inappropriate spatio-temporal dependency extraction. For this situation, this paper proposes a spatio-temporal graph neural network based on adaptive neighborhood selection (STGNN-ANS). To obtain more flexible graph structures, STGNN-ANS designs a neighbor selection mechanism to generate a new graph structure by filtering inappropriate neighbors. To further capture the spatio-temporal dependence of traffic data, a spatio-temporal serial module of STGNN-ANS adopts the bidirectional learning manner of bidirectional long short-term memory (BiLSTM) and the graph convolution network (GCN) enhanced by self-attention mechanism to reach excellent prediction accuracy in both short-range and long-range scenarios. In this paper, a new baseline comprehensive comparison metric (BCCM) is invented to cope with the complexity in the comparative analysis of large numbers of experimental results. Many experiments have been performed on four real-world traffic datasets, and the results show that the comprehensive prediction performance of STGNN-ANS is better than previous models.","PeriodicalId":23279,"journal":{"name":"Transportation Research Record","volume":"160 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136280587","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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

Hierarchical Automated Machine Learning Approach for Self-Optimizable Driving Distraction Recognition Based on Driver’s Lane-Keeping Performance 基于车道保持性能的自优化驾驶分心识别的分层自动机器学习方法

4区工程技术

Transportation Research Record Pub Date : 2023-09-30 DOI: 10.1177/03611981231196152

Chen Chai, Jiaxin Li, Md Mohaiminul Islam, Rui Feng, Miaojia Lu

{"title":"Hierarchical Automated Machine Learning Approach for Self-Optimizable Driving Distraction Recognition Based on Driver’s Lane-Keeping Performance","authors":"Chen Chai, Jiaxin Li, Md Mohaiminul Islam, Rui Feng, Miaojia Lu","doi":"10.1177/03611981231196152","DOIUrl":"https://doi.org/10.1177/03611981231196152","url":null,"abstract":"With the enrichment of smartphone uses, phone-related driving distractions have become a threat to driving safety. One way to mitigate driving distractions is to detect them and provide real-time warnings. However, most existing driving distraction recognition algorithms are pretrained models composed of structures, hyperparameters, and parameters that may not be able to account for drivers’ individual differences and, thus, might result in low model accuracy. This study proposes a domain-specific hierarchical automated machine learning (HAT-ML) model that self-learns personalized optimal models to detect driving distractions from vehicle movement data. The HAT-ML model integrates key modeling steps into auto-optimizable layers, including knowledge-based feature extraction, feature selection by recursive feature elimination, automated algorithm selection, and hyperparameter autotuning by Bayesian optimization. In our eight-degrees-of-freedom driving simulator experiment, we demonstrated the effectiveness of the proposed model using three driving distraction tasks: browsing a short message, browsing a long message, and answering a phone call. The HAT-ML model was found to be reliable and robust for predicting phone-related driving distraction, achieving satisfactory results with a predictive accuracy of 80% at the group level and 90% at the individual level. Moreover, the results revealed that each distraction and driver type required different optimized hyperparameter values, which demonstrated the value of utilizing HAT-ML to detect driving distractions. The key elements that dominated the performance of the model have several theoretical and practical implications. The proposed method not only enhanced performance, but also provided data-driven insights about model development.","PeriodicalId":23279,"journal":{"name":"Transportation Research Record","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136280277","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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

Impact of Ball Bank Indicator on Predicting Rural Curve Crashes 球库指标对预测农村曲线崩溃的影响

4区工程技术

Transportation Research Record Pub Date : 2023-09-30 DOI: 10.1177/03611981231196148

Ronald Knezevich, Zhongyu Yang, Pingzhou (Lucas) Yu, Yi-Chang (James) Tsai

{"title":"Impact of Ball Bank Indicator on Predicting Rural Curve Crashes","authors":"Ronald Knezevich, Zhongyu Yang, Pingzhou (Lucas) Yu, Yi-Chang (James) Tsai","doi":"10.1177/03611981231196148","DOIUrl":"https://doi.org/10.1177/03611981231196148","url":null,"abstract":"The ball bank indicator (BBI) measures the lateral forces on a vehicle. It is used to establish the advisory speed limit as outlined in the American Association of State Highway and Transportation Officials (AASHTO)’s Green Book. BBI values respond to roadway geometry and driver behavior. Currently, BBI data are available from various curves across the U.S. However, the relationship between BBI and curve lane departures is unknown. Therefore, the objective of this paper is to assess the impact of BBI as an explanatory variable for curve lane departures within a safety performance function (SPF) (i.e., a crash prediction model). To accomplish this objective, a study is conducted on rural curves in Districts 1, 2, and 6 of Georgia Department of Transportation in the U.S. BBI is integrated into a negative binomial model alongside other common explanatory variables used in the Highway Safety Manual. This SPF, with BBI incorporated, is compared with a baseline SPF without the BBI. The results show BBI is a statistically significant variable under a 99.9% threshold. Additionally, it was found that the model with BBI has 2.78% and 2.83% less mean absolute error and route mean squared error, respectively. Though the improvement in the model is minor, this finding is notable because BBI data may already be available for a transportation agency to leverage to assess risk on curves. Furthermore, this data could be even more beneficial if it were crowdsourced to gauge real-world behaviors.","PeriodicalId":23279,"journal":{"name":"Transportation Research Record","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136280445","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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

Traffic Safety Assessment with Integrated Communication System of Connected and Automated Vehicles at Signalized Intersections 信号交叉口网联自动车辆综合通信系统的交通安全评价

4区工程技术

Transportation Research Record Pub Date : 2023-09-30 DOI: 10.1177/03611981231201107

Xu Wang, Xinguo Jiang, Haibo Li, Xinyu Zhao, Zuoan Hu, Chuan Xu

{"title":"Traffic Safety Assessment with Integrated Communication System of Connected and Automated Vehicles at Signalized Intersections","authors":"Xu Wang, Xinguo Jiang, Haibo Li, Xinyu Zhao, Zuoan Hu, Chuan Xu","doi":"10.1177/03611981231201107","DOIUrl":"https://doi.org/10.1177/03611981231201107","url":null,"abstract":"Connected and automated vehicles (CAVs) are expected to improve traffic safety effectively at signalized intersections. Considerable studies have been conducted to investigate the benefits of CAVs in improving traffic mobility and efficiency. However, in most previous research, vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) communication have been considered separately rather than concurrently, to study the characteristics of CAVs, resulting in the potential of CAVs not being fully exploited and inconsistency with reality. In this paper, an integrated communication system of CAVs (ICSC), which incorporates V2V and V2I communication, is proposed, to assess traffic safety at signalized intersections. In this study, the intelligent driver model (IDM) is used to approximate V2V communication between a subject CAV and preceding CAVs. A reinforcement learning algorithm is adopted to model V2I communication between a CAV and a traffic light. The traffic safety effect of ICSC, V2V-only, and V2I-only scenarios is evaluated for different market penetration rates (MPRs). The results show that the ICSC scenario significantly reduces traffic conflicts and outperforms V2V-only, V2I-only, and benchmark scenarios when the MPR is equal to or higher than 50% with different surrogate safety measures (SSMs), such as time-exposed deceleration (TED) to avoid crashing, time exposed time-to-collision (TET), and use of a spacing gap (SGAP). Moreover, the mobility effect of the ICSC scenario is studied, and appears to increase average speed and reduce delay time. Finally, the results suggest that the ICSC can improve traffic safety and mobility concurrently and exploit the potentials of CAVs at signalized intersections.","PeriodicalId":23279,"journal":{"name":"Transportation Research Record","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136341749","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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

BECO (Business, Engineering, Construction, and Other) Framework for Providing Effective and Comprehensive Supportive Services to Disadvantaged Business Enterprises in the United States 为美国的弱势商业企业提供有效和全面的支持服务的BECO(商业、工程、建筑和其他)框架

4区工程技术

Transportation Research Record Pub Date : 2023-09-29 DOI: 10.1177/03611981231198478

Hongtao Dang, Jennifer Shane

{"title":"BECO (Business, Engineering, Construction, and Other) Framework for Providing Effective and Comprehensive Supportive Services to Disadvantaged Business Enterprises in the United States","authors":"Hongtao Dang, Jennifer Shane","doi":"10.1177/03611981231198478","DOIUrl":"https://doi.org/10.1177/03611981231198478","url":null,"abstract":"The Disadvantaged Business Enterprise program, established by the United States Department of Transportation, aims to remove barriers to participation of Disadvantaged Business Enterprises (DBEs) in highway projects, to promote the use of DBEs in federally assisted contracts, and to assist the development of DBEs. A DBE is a small, for-profit business owned by socially and economically disadvantaged individuals such as women or minorities. DBEs need various supportive services, depending on many factors, such as business area, size, and strategy. State Departments of Transportation often provide or hire third parties to provide supportive services to DBEs that are relatively expensive and inefficient. These services may also support only some and unintentionally exclude other DBEs. Under many challenges, one ultimate goal is to find a framework that covers all valuable DBE supportive services. This study proposes, tests, and validates a framework for providing effective and comprehensive DBE supportive services in the transportation sector. Based on discussions with DBE liaison officers and service providers, we propose the business, engineering, construction, and other (BECO) framework to provide DBE supportive services. We then use a sequential explanatory design in mixed methods, collecting quantitative and qualitative data to evaluate and validate the BECO framework. We analyze quantitative data using confirmatory factor analysis and qualitative data using pattern coding techniques. The results provide insights and reveal useful DBE supportive services using the BECO framework. The framework is useful for assessing DBE needs, informing DBE liaison officers and service providers, and offering the most useful supportive services to DBEs.","PeriodicalId":23279,"journal":{"name":"Transportation Research Record","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135199340","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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

Obstacle Detection Method of Underground Electric Locomotive Rail Based on Instance Segmentation 基于实例分割的地下电机车轨道障碍物检测方法

4区工程技术

Transportation Research Record Pub Date : 2023-09-29 DOI: 10.1177/03611981231198842

Jiale Tong, Shuang Wang, Yongcun Guo, Wenshan Wang, Tun Yang, Shuqi Zong

{"title":"Obstacle Detection Method of Underground Electric Locomotive Rail Based on Instance Segmentation","authors":"Jiale Tong, Shuang Wang, Yongcun Guo, Wenshan Wang, Tun Yang, Shuqi Zong","doi":"10.1177/03611981231198842","DOIUrl":"https://doi.org/10.1177/03611981231198842","url":null,"abstract":"Real-time and accurate obstacle detection is a vital technology for electric locomotives, especially as driverless vehicles are introduced. A method of obstacle detection for underground electric locomotive rail based on instance segmentation is developed to solve the problems of misdetection and missing detection, low detection accuracy, and slow detection speed of rail obstacles. The method of locating the track mask, demarcating the effective driving boundary, expanding the track mask, and forming the effective driving area is adopted to verify whether the target is an obstacle based on whether the target is located in the effective driving area, to avoid the problem of misdetection and missing detection of the target obstacle. The YOLACT++ (You Only Look At CoefficienTs) model is improved, and path augmentation and target classification loss function replacement strategies are adopted to enhance the model’s ability to detect target details and increase the accuracy of target segmentation. Compared with traditional image processing, this method can detect both straight rail and turnout. The mean average precision of boundary box mAP 0.5 (box) and mask mAP 0.5 (mask) of the improved YOLACT++ model reaches 98.52% and 98.55%, which is higher than that of the YOLACT++ model, and the detection frame rate reaches 21.9 frames per second.","PeriodicalId":23279,"journal":{"name":"Transportation Research Record","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135246187","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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