Cellpath: Fusion of cellular and traffic sensor data for route flow estimation via convex optimization

A new convex optimization framework is developed for the route flow estimation problem from the fusion of vehicle count and cellular network data. The issue of highly underdetermined link flow based methods in transportation networks is investigated, then solved using the proposed concept of cellpaths for cellular network data. With this data-driven approach, our proposed approach is versatile: it is compatible with other data sources, and it is model agnostic and thus compatible with user equilibrium, system-optimum, Stackelberg concepts, and other models. Using a dimensionality reduction scheme, we design a projected gradient algorithm suitable for the proposed route flow estimation problem. The algorithm solves a block isotonic regression problem in the projection step in linear time. The accuracy, computational efficiency, and versatility of the proposed approach are validated on the I-210 corridor near Los Angeles, where we achieve 90% route flow accuracy with 1033 traffic sensors and 1000 cellular towers covering a large network of highways and arterials with more than 20,000 links. In contrast to long-term land use planning applications, we demonstrate the first system to our knowledge that can produce route-level flow estimates suitable for short time horizon prediction and control applications in traffic management. Our system is open source and available for validation and extension.     

基于灰色二次指数平滑的QAR参数关联度预测

由于QAR参数波动的后果具有潜在性和滞后性,因此分析人员容易忽视其危险性而使其发展为不利事件。针对该问题,提出运用QAR参数关联度分析的方法,建立QAR参数波动与事件之间的对应关系;并构建基于二次指数平滑-灰色关联法的关联度预测模型,进一步明确QAR参数波动与事件之间关系的动态变化趋势。运用实际数据对该模型进行验证,表明结论符合实际,该模型科学合理,可以用于QAR参数分析过程。     

The Gothenburg congestion charge. Effects,design and politics

This paper summarizes the traffic effects of the Gothenburg congestion charges introduced in 2013. The system is similar to the system introduced in Stockholm in 2006; both are designed as time-of-day dependent cordon pricing systems. We find that many effects and adaptation strategies are similar to those found in Stockholm, indicating a high transferability between smaller and larger cities with substantial differences in public transport use. However, there are also important differences regarding some of the effects, the accuracy of the model forecasts and public support arising from different topologies, public transport use, congestion levels and main objectives communicated to the public. Finally, the Gothenburg case suggests that whether congestion charges are introduced or not depends on the support among the political parties, and that this is determined primarily by the prevailing institutional setting and power over revenues, and to a lower extent by the public support, and benefits from congestion reduction.     

Compromising system and user interests in shelter location and evacuation planning

Traffic management during an evacuation and the decision of where to locate the shelters are of critical importance to the performance of an evacuation plan. From the evacuation management authority’s point of view, the desirable goal is to minimize the total evacuation time by computing a system optimum (SO). However, evacuees may not be willing to take long routes enforced on them by a SO solution; but they may consent to taking routes with lengths not longer than the shortest path to the nearest shelter site by more than a tolerable factor. We develop a model that optimally locates shelters and assigns evacuees to the nearest shelter sites by assigning them to shortest paths, shortest and nearest with a given degree of tolerance, so that the total evacuation time is minimized. As the travel time on a road segment is often modeled as a nonlinear function of the flow on the segment, the resulting model is a nonlinear mixed integer programming model. We develop a solution method that can handle practical size problems using second order cone programming techniques. Using our model, we investigate the importance of the number and locations of shelter sites and the trade-off between efficiency and fairness.     

基于Fisk运量随机配流的交通信息最优发布水平确定研究

本文借助Fisk运量随机配流模型建立一个简单二层规划模型来研究交通信息的最优发布水平，通过模型分析得出一些重要结论。在非拥挤交通网络中，信息发布不产生外部效果，信息系统应发布全部信息；在严重拥挤的交通网络中，产生正的外部效果，信息系统应发布全部信息；在一般拥挤网络中，可能产生正的外部效果，也可能产生负的外部效果，应根据具体情况选择合适的信息发布水平。     

浅析普通公路道路交通标志的设置

通过分析交通标志设置基础、设置功能、设置方式和设置场所选定,为正确设置道路交通标志提供参考与借鉴。     

基于混沌蚁群算法的最短路径选择研究

如何解决最短路径选择问题一直是城市交通流诱导系统的关键之一.基于群体仿生理论的蚁群算法是解决此问题的一种方法,针对采用蚁群算法进行最短路径选择时易出现的陷入局部最优解问题,引入混沌理论,采用混沌蚁群算法利用混沌初始化进行改善个体质量和利用混沌扰动避免在蚁群算法搜索过程中陷入局部极值,同时降低了蚁群算法的时间复杂度,从而更好的解决了最短路径选择问题.     

生成模型在中心城市的应用实践

本文从城市的区域交通节点考虑,把城市分为中心城市、资源型城市和一般城市.以中心城市土地利用特性和现状人口为基础,采用曲线估计的方法建立了交通生成预测模型.利用辽宁省锦州市、盘锦市和辽阳市的交通数据,对模型进行了验证,结果表明模型能够较好反映规划年城市土地利用特征变化所带来的各种交通需求特性的差异.     

融合边缘检测与区域生长的交通图像分割方法

在交通监控中,如何从复杂的背景中分割运动物体是至关重要的一步,针对车辆的运动阴影对图像分割产生的不利影响,提出了一种新的融合边缘检测与区域生长的彩色图像分割算法,算法同时考虑了图像的彩色信息和空间信息.该算法首先对彩色图像边缘检测,并根据检测结果设置种子像素;再基于颜色相似性生长准则,结合边缘检测结果,对每个种子点进行区域生长;最后,利用区域合并算法对剩余的像素进行合并.实验结果表明该算法很大程度上克服了阴影给图像分割带来的不利影响.     

基于还贷的收费公路合理费率研究

由于经济发展相对滞后、公路建设资金短缺等客观因素制约,目前我国的收费公路很大一部分为收费还贷公路。从公路还贷的角度,在考虑公路建设方和用户双方利益的前提下,以交逋均衡理论及最优化理论为基础,建立均衡状态下的基于还贷的公路收费费率——流量关系的双层规划模型,提出了模型的算法并加以应用,由此确定合理费率。