BECS Collaborative Research: Modeling the Dynamics of Traffic User Equilibria Using Differential Variational Inequalities
BECS 协作研究:使用微分变分不等式对交通用户均衡动态进行建模
基本信息
- 批准号:1024647
- 负责人:
- 金额:$ 10万
- 依托单位:
- 依托单位国家:美国
- 项目类别:Standard Grant
- 财政年份:2010
- 资助国家:美国
- 起止时间:2010-09-01 至 2014-08-31
- 项目状态:已结题
- 来源:
- 关键词:
项目摘要
The goal of this project is to employ a novel mathematical paradigm, known as a differential variational inequality (DVI), to study two fundamental problems in transportation analysis, namely, the continue-time dynamic user equilibrium with flow propagation and delays, and the problem of traffic disequilibrium in the face of network disruption. Our aim is to develop a nonlinear dynamical system theory that combines classical ordinary differential equation (ODE) methods with contemporary mathematical programming advances to study the equilibrium of short-time (e.g. within-day dynamics) and the equilibration process of longer-time (e.g. transient dynamics) traffic flows, answering questions such as: how to compute dynamic user equilibria, how traffic evolves from a disequilibrium state, due to network disruptions, toward an equilibrium, and how close the current traffic state is to an equilibrium. Results from this study will lead to a new paradigm integrating traffic network analysis methods with recent advances in mathematical science, and bridge the gaps between current practice of traffic analysis and the needs to consider short-term and long-term traffic dynamics in a holistic manner. The research will be the first step to develop a mathematical framework for traffic dynamic analysis that, in a long term, has the potential to revolutionize the traditional way of conducting transportation analyses such as network signal optimization, dynamic congestion pricing, emergency management after disruptions, among others. Since equilibrium analysis and system dynamics are widely used in other science and engineering fields, the concepts and methodologies developed in this research can also provide new perspectives for equilibrium based analysis in these fields. The research team plans to integrate research findings to undergraduate and graduate courses, and involve undergraduate and graduate students with multidisciplinary backgrounds in this research. The team also plans to reach out to policy makers and practitioners at various transportation management agencies for whom findings from the proposed research will enable them to better manage transportation systems.
本计画的目标是采用一种新的数学范式,称为微分变分不等式(DVI),研究交通分析中的两个基本问题,即:具有流量传播和延迟的连续时间动态用户平衡,以及面对网络中断时的交通不平衡问题。我们的目标是发展一个非线性动力系统理论,结合经典的常微分方程(ODE)方法和当代数学规划的进展,以研究短时间的平衡(例如,日内动态)和较长时间的平衡过程(例如瞬时动态)交通流量,回答以下问题:如何计算动态用户平衡,交通如何从不平衡状态演变,由于网络中断,走向平衡,以及当前交通状态如何接近平衡。从这项研究的结果将导致一个新的范式整合交通网络分析方法与数学科学的最新进展,并弥合目前的交通分析实践和需要考虑短期和长期的交通动态整体的方式之间的差距。 该研究将是开发交通动态分析数学框架的第一步,从长远来看,该框架有可能彻底改变传统的交通分析方式,如网络信号优化,动态拥堵定价,中断后的应急管理等。由于平衡分析和系统动力学在其他科学和工程领域中有着广泛的应用,本研究中提出的概念和方法也可以为这些领域中基于平衡的分析提供新的视角。研究团队计划将研究结果整合到本科和研究生课程中,并让具有多学科背景的本科生和研究生参与这项研究。该团队还计划与各交通管理机构的决策者和从业人员进行接触,拟议研究的结果将使他们能够更好地管理交通系统。
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
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Xuegang Ban其他文献
Analysis of Differences in ECG Characteristics for Different Types of Drivers under Anxiety
不同类型驾驶员焦虑状态心电图特征差异分析
- DOI:
10.1155/2021/6640527 - 发表时间:
2021-08 - 期刊:
- 影响因子:1.8
- 作者:
Yongqing Guo;Xiaoyuan Wang;Qing Xu;Quan Yuan;Chenglin Bai;Xuegang Ban - 通讯作者:
Xuegang Ban
Real-time route diversion control in a model predictive control framework with multiple objectives: Traffic efficiency, emission reduction and fuel economy
模型预测控制框架中的实时路线改道控制具有多个目标:交通效率、减排和燃油经济性
- DOI:
10.1016/j.trd.2016.08.013 - 发表时间:
2016-10 - 期刊:
- 影响因子:0
- 作者:
Lihua Luo;Ying-En Ge;Fangwei Zhang;Xuegang Ban - 通讯作者:
Xuegang Ban
Simulation of Carbon Emission for Heavy-Duty Vehicle Queuing Systems
重型车辆排队系统碳排放仿真
- DOI:
- 发表时间:
2017 - 期刊:
- 影响因子:0
- 作者:
Yao Yu;Jialin Zhai;Xuegang Ban;Jinxian Weng - 通讯作者:
Jinxian Weng
The Emergence Characteristics of Driver’s Intentions Influenced by Different Emotions
不同情绪影响驾驶员意图的显现特征
- DOI:
10.3390/su132313292 - 发表时间:
2021-12 - 期刊:
- 影响因子:0
- 作者:
Xiaoyuan Wang;Yongqing Guo;Chenglin Bai;Quan Yuan;Shanliang Liu;Xuegang Ban - 通讯作者:
Xuegang Ban
Correcting the Market Failure in Work Trips with Work Rescheduling: An Analysis Using Bi-level Models for the Firm-workers Interplay
通过工作重新安排来纠正工作旅行中的市场失灵:使用双层模型进行企业-工人相互作用的分析
- DOI:
10.1007/s11067-013-9213-7 - 发表时间:
2013 - 期刊:
- 影响因子:2.4
- 作者:
Wilfredo F. Yushimito;Xuegang Ban;J. Holguín - 通讯作者:
J. Holguín
Xuegang Ban的其他文献
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{{ truncateString('Xuegang Ban', 18)}}的其他基金
Collaborative Research: Data Poisoning Attacks and Infrastructure-Enabled Solutions for Traffic State Estimation and Prediction
合作研究:数据中毒攻击和基于基础设施的交通状态估计和预测解决方案
- 批准号:
2326340 - 财政年份:2023
- 资助金额:
$ 10万 - 项目类别:
Standard Grant
Collaborative Research: SaTC: CORE: Small: Privately Collecting and Analyzing V2X Data for Urban Traffic Modeling
合作研究:SaTC:核心:小型:私下收集和分析用于城市交通建模的 V2X 数据
- 批准号:
2034615 - 财政年份:2021
- 资助金额:
$ 10万 - 项目类别:
Standard Grant
Collaborative Research: Bias Modeling and Estimation of Networked Transportation Data
合作研究:网络交通数据的偏差建模和估计
- 批准号:
1825053 - 财政年份:2018
- 资助金额:
$ 10万 - 项目类别:
Standard Grant
CAREER: Using Mobile Sensors for Traffic Knowledge Extraction and Dynamic Network Management
职业:使用移动传感器进行交通知识提取和动态网络管理
- 批准号:
1719551 - 财政年份:2016
- 资助金额:
$ 10万 - 项目类别:
Continuing Grant
Collaborative Research: Transportation Network Identification: Information Fusion via Stochastic Optimization
合作研究:交通网络识别:通过随机优化进行信息融合
- 批准号:
1719548 - 财政年份:2016
- 资助金额:
$ 10万 - 项目类别:
Standard Grant
Collaborative Research: Transportation Network Identification: Information Fusion via Stochastic Optimization
合作研究:交通网络识别:通过随机优化进行信息融合
- 批准号:
1537700 - 财政年份:2015
- 资助金额:
$ 10万 - 项目类别:
Standard Grant
CAREER: Using Mobile Sensors for Traffic Knowledge Extraction and Dynamic Network Management
职业:使用移动传感器进行交通知识提取和动态网络管理
- 批准号:
1055555 - 财政年份:2011
- 资助金额:
$ 10万 - 项目类别:
Continuing Grant
Collaborative Research: Mobile Sensors as Traffic Probes - Addressing Transportation Modeling and Privacy Protection in an Integrated Framework
协作研究:移动传感器作为交通探针 - 在集成框架中解决交通建模和隐私保护问题
- 批准号:
1031452 - 财政年份:2010
- 资助金额:
$ 10万 - 项目类别:
Standard Grant
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