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International Conference on Transportation and Development 2022最新文献

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Prioritizing Locations for Safety Improvement: An Integrated Disutility-Based Approach 安全改进的优先位置:基于非效用的综合方法
Pub Date : 2022-08-31 DOI: 10.1061/9780784484333.026
M. R. Bhuiyan, M. A. Raihan, Moinul Hossain
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引用次数: 1
Shifts in Public Transit Equity during the COVID-19 Pandemic: A Case Study in Riverside, California 2019冠状病毒病大流行期间公共交通公平的变化:以加利福尼亚州里弗赛德为例
Pub Date : 2022-08-31 DOI: 10.1061/9780784484371.012
Preston Reed, Holly Chea, Sheng Tan, Raffi Der Wartanian, Yongping Zhang, Yunfei Hou, K. Collins
A prime component of any effective public transportation system is equitable access for all riders within the community. Building transportation networks with equity in mind can boost ridership and transit network coverage. The problem of social equity in transportation is further exacerbated by historically auto-dependent cities and the pandemic restrictions from COVID-19. This paper aims to quantify transit equity using a disadvantage index. These results are then applied to different periods of a transit system throughout the COVID-19 pandemic to see how it affected social equity in public transportation as part of a case study in Riverside, California. Heat maps are overlaid on the transit network's lines and stops using geographic information systems (GIS) software to visualize the variables associated with transit equity calculations. Publicly released General Transit Feed Specification (GTFS) data is used to plot the state of the transit network at different points in time. The results show that route changes during the COVID-19 pandemic had a noticeable but minimal effect on social equity in transportation. © ASCE. All rights reserved.
任何有效的公共交通系统的一个主要组成部分是社区内所有乘客的公平准入。建立公平的交通网络可以提高乘客数量和交通网络的覆盖率。历史上依赖汽车的城市和COVID-19的大流行限制进一步加剧了交通方面的社会公平问题。本文旨在利用劣势指数来量化交通公平。然后将这些结果应用于2019冠状病毒病大流行期间交通系统的不同时期,以了解它如何影响公共交通中的社会公平,这是加利福尼亚州里弗赛德的案例研究的一部分。热图覆盖在公交网络的线路和站点上,使用地理信息系统(GIS)软件将与公交权益计算相关的变量可视化。公开发布的通用交通馈电规范(GTFS)数据用于绘制交通网络在不同时间点的状态。结果表明,2019冠状病毒病大流行期间路线变化对交通运输社会公平的影响明显但很小。©第3期。版权所有。
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引用次数: 0
Research on Expressway Congestion Control Strategy Based on Dynamic Speed Limit 基于动态限速的高速公路拥塞控制策略研究
Pub Date : 2022-08-31 DOI: 10.1061/9780784484326.007
Haoying Sun, Qunlong Huang, Yunping Wei
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引用次数: 0
Concept of Operations of Next-Generation Traffic Control Utilizing Infrastructure-Based Cooperative Perception 基于基础设施协同感知的下一代交通控制操作概念
Pub Date : 2022-08-31 DOI: 10.1061/9780784484326.010
S. Young, Erik A. Bensen, Lei Zhu, C. Day, J. Lott, R. Sandhu, Charles Tripp, Peter Graf
This paper provides a system architecture for an infrastructure-based cooperative perception fusion engine for next-generation traffic control. This engine will provide a complete state-space digital representation with measurable accuracy to support a wide-range of applications. The architecture includes inputs, functional flow, data standardization recommendations, outputs, and supported applications. The cooperative perception engine addresses critical needs with respect to accelerating the benefits of automation through intelligent roadway infrastructure, which complements and accelerates connected and automated vehicle (CAV) technology. The cooperative perception acquires and fuses information from sensors (radar, LiDAR, and cameras) and CAVs to perceive roadway traffic states of moving objects, creates a complete 3D digital representation of that state-space, and communicates it to downstream application such as intelligent signal control, safety and energy applications, and cooperate driving applications. The intelligent roadway infrastructure approach, as opposed to a vehicle-centric approach, is more scalable because it can be deployed to the roughly 300,000 signalized intersections more readily than the over 300 million vehicles in the United States, and accrues early-stage benefits equitable to all roadway users addressing safety, equity, fuel efficiency, and greenhouse gas reduction.
本文提出了一种基于基础设施的下一代交通控制协同感知融合引擎的系统架构。该引擎将提供具有可测量精度的完整状态空间数字表示,以支持广泛的应用。该体系结构包括输入、功能流、数据标准化建议、输出和支持的应用程序。协作感知引擎解决了通过智能道路基础设施加速自动化效益的关键需求,这补充并加速了连接和自动车辆(CAV)技术。协同感知从传感器(雷达、激光雷达和摄像头)和自动驾驶汽车获取并融合信息,感知移动物体的道路交通状态,创建该状态空间的完整3D数字表示,并将其传达给下游应用,如智能信号控制、安全和能源应用以及协同驾驶应用。与以车辆为中心的方法相反,智能道路基础设施方法更具可扩展性,因为它可以比美国超过3亿辆汽车更容易部署到大约30万个有信号的十字路口,并为所有道路用户带来公平的早期利益,解决安全、公平、燃油效率和温室气体减排问题。
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引用次数: 1
Evaluating the Impact of COVID-19 on Transportation Infrastructure Funding in the United States 评估COVID-19对美国交通基础设施资金的影响
Pub Date : 2022-08-31 DOI: 10.1061/9780784484364.012
Lu Gao, Pan Lu, F. Qiao, J. Li, Yunpeng Zhang, Yihao Ren
The coronavirus disease 2019 (COVID-19) pandemic has caused a reduction in business and routine activity and resulted in less motor fuel consumption. Thus, the gas tax revenue is reduced, which is the major funding resource supporting the rehabilitation and maintenance of transportation infrastructure systems. The focus of this study is to evaluate the impact of the COVID-19 pandemic on transportation infrastructure funds in the United States through analyzing the motor fuel consumption data. Machine learning models were developed by integrating COVID-19 scenarios, fuel consumptions, and demographic data. The best model achieves an R2-score of more than 95% and captures the fluctuations of fuel consumption during the pandemic. Using the developed model, we project future motor gas consumption for each state. For some states, the gas tax revenues are going to be 10%-15% lower than the pre-pandemic level for at least one or two years. © 2022 International Conference on Transportation and Development
2019年冠状病毒病(COVID-19)大流行导致商业和日常活动减少,并导致汽车燃料消耗减少。因此,减少了汽油税收入,这是支持恢复和维护运输基础设施系统的主要资金来源。本研究的重点是通过分析汽车燃油消耗数据来评估COVID-19大流行对美国交通基础设施资金的影响。通过整合COVID-19情景、燃料消耗和人口统计数据,开发了机器学习模型。最佳模型的r2得分达到95%以上,并能捕捉大流行期间燃料消耗的波动。利用开发的模型,我们预测了每个州未来的汽车气体消耗。对于一些州来说,至少在一到两年内,汽油税收入将比大流行前的水平低10%-15%。©2022年国际交通与发展会议
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引用次数: 0
Body Feature Filter for Occluded Person Re-Identification 身体特征滤波在闭塞人群再识别中的应用
Pub Date : 2022-08-31 DOI: 10.1061/9780784484319.011
Tianyun Fu, Jianming Hu, Xin Pei
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引用次数: 0
Evaluation of 3D Reconstruction Methods from Terrestrial LiDAR Point Cloud Data to Create Digital Twins of Civil Infrastructure Projects 基于地面激光雷达点云数据的民用基础设施项目三维重建方法评估
Pub Date : 2022-08-31 DOI: 10.1061/9780784484319.008
Jose Luis Lugo, Julio Cesar Gallegos Reyes, J. Weidner, A. Raheem, R. Cheu
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引用次数: 1
Exploration of Ergonomic Injuries and Risky Activities among Transportation Maintenance Workers 交通维修工人工效伤害与危险活动的探讨
Pub Date : 2022-08-31 DOI: 10.1061/9780784484333.012
Xingzhou Guo, Yunfeng Chen, Jiansong Zhang
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引用次数: 0
The Benefits of Expanding the Incident Management Program in Utah 在犹他州扩大事故管理计划的好处
Pub Date : 2022-08-31 DOI: 10.1061/9780784484333.024
Logan S. Bennett, J. Hyer, G. G. Schultz, M. Saito, D. Eggett
A 2018 study of performance measures for the Utah Department of Transportation's (UDOT) Incident Management Team (IMT) program concluded that the program was cost effective and benefited Utah motorists. During the 2018 legislative session, UDOT received funding to expand its IMT program. To determine the benefits of expanding the IMT program, a comparison of performance measures for 2018 and 2020 incident data was conducted. In addition, data regarding the affected volume, the excess travel time, and the excess user cost associated with incident congestion were gathered. The effects of the COVID-19 pandemic affected traffic volumes during this study, and statistical analyses were utilized to account for volume differences between the two years. Results indicated that the expansion of the IMT program has allowed UDOT to respond more consistently to incidents and respond to a larger quantity of incidents over a larger coverage area and in extended operating hours. © ASCE.
2018年对犹他州交通部(UDOT)事故管理小组(IMT)计划的绩效指标进行的一项研究得出结论,该计划具有成本效益,并使犹他州的驾车者受益。在2018年立法会议期间,UDOT获得了扩大其IMT计划的资金。为了确定扩大IMT计划的好处,对2018年和2020年事件数据的绩效指标进行了比较。此外,还收集了与受影响的流量、额外的旅行时间和与事故拥塞相关的额外用户成本相关的数据。在本研究期间,COVID-19大流行的影响影响了交通量,并利用统计分析来解释两年间的交通量差异。结果表明,IMT计划的扩展使UDOT能够更一致地对事件做出反应,并在更大的覆盖范围和更长的运营时间内对更多数量的事件做出反应。©第3期。
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引用次数: 0
Evaluation of Stiffness and Fatigue Cracking Resistance of Post-Consumer Recycled (PCR) Plastic-Modified Asphalt Mixes 消费后再生(PCR)塑料改性沥青混合料的刚度和抗疲劳开裂性评价
Pub Date : 2022-08-31 DOI: 10.1061/9780784484357.018
S. Ghos, S. A. Ali, M. Zaman, P. C. Arevalo, K. Hobson
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引用次数: 0
期刊
International Conference on Transportation and Development 2022
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