Estimation of the Impact of Traveler Information Apps on Urban Air Quality Improvement

With the rapid growth of vehicle population and vehicle miles traveled, automobile emission has become a severe issue in the metropolitan cities of China. There are policies that concentrate on the management of emission sources. However, improving the operation of the transportation system through apps on mobile devices, especially navigation apps, may have a unique role in promoting urban air quality. Real-time traveler information can not only help travelers avoid traffic congestion, but also advise them to adjust their departure time, mode, or route, or even to cancel trips. Will such changes in personal travel patterns have a significant impact in decreasing emissions? If so, to what extent will they impact urban air quality? The aim of this study is to determine how urban traffic emission is affected by the use of navigation apps. With this work, we attempt to answer the question of whether the real-time traffic information provided by navigation apps can help to improve urban air quality. Some of these findings may provide references for the formulation of urban traffic and environmental policies.     

有砟轨道动力性能分析的频域方法

建立有砟轨道的三层连续弹性支承模型,推导了钢轨、轨枕和道床的运动方程,并在频域内求得简谐激励下的稳态响应。再引入轮轨相互作用频域模型,并借助动柔度法计算轮轨力。在此基础上,采用MATLAB平台自编程序,实现轨道不平顺激励下的频域分析。在案例分析中,综合考虑轮轨力、力传递率、轨道各部件的振动等指标,对弹性扣件、枕下弹性垫板、复合轨枕、道砟垫以及它们的组合等多种减振措施进行对比。结果表明：减振措施使得系统的固有频率发生改变,进而导致各指标在不同频率范围出现复杂的变化规律;相比于弹性扣件,枕下弹性垫板和道砟垫表现出更好的综合效果,而复合轨枕的减振效果有限。     

城市交通系统管理与优化研究综述

根据城市路网交通需求与供给平衡关系,对城市交通问题产生的机理进行分析。通过对比分析国内外城市交通需求管理、交通运行管理及交通应急管理研究现状,指出多技术协同集成研究、交通参与者行为研究、交通政策评估与仿真研究、交通大数据应用研究,将成为未来研究的重要趋势。     

基于汽车的多主体多通道交互模型研究

目的借助物联网相关技术改变城市与交通系统内"人—汽车—环境"之间的交互模式,提高驾乘过程中的用户体验,提升城市交通运行效率。方法在移动互联网的背景下,利用物联网与汽车智能化技术,把人机交互的概念从人与汽车之间的双向互动,放大到整个城市交通体系的多主体多通道互动之中,重新审视智能交通体系下的人机交互概念。分析不同移动场景中用户的需求,阐述"基于汽车的多主体多通道交互模型"给城市出行效率与驾乘体验带来的本质改变。结论提出面对未来的智能化交通体系中人与汽车、汽车与汽车、汽车与城市公共设施之间的复杂互动关系,即"基于汽车的多主体多通道交互模型"。该模型的运用对未来城市交通与信息化建设,具有一定的理论指导与实用价值。     

GACNet: A Generative Adversarial Capsule Network for Regional Epitaxial Traffic Flow Prediction

With continuous urbanization, cities are undergoing a sharp expansion within the regional space. Due to the high cost, the prediction of regional traffic flow is more difficult to extend to entire urban areas. To address this challenging problem, we present a new deep learning architecture for regional epitaxial traffic flow prediction called GACNet, which predicts traffic flow of surrounding areas based on inflow and outflow information in central area. The method is data-driven, and the spatial relationship of traffic flow is characterized by dynamically transforming traffic information into images through a two-dimensional matrix. We introduce adversarial training to improve performance of prediction and enhance the robustness. The generator mainly consists of two parts: abstract traffic feature extraction in the central region and traffic prediction in the extended region. In particular, the feature extraction part captures nonlinear spatial dependence using gated convolution, and replaces the maximum pooling operation with dynamic routing, finally aggregates multidimensional information in capsule form. The effectiveness of the method is evaluated using traffic flow datasets for two real traffic networks: Beijing and New York. Experiments on highly challenging datasets show that our method performs well for this task.     

Metaheuristic Optimization of Time Series Models for Predicting NetworksTraffic

Traffic prediction of wireless networks attracted many researchers and practitioners during the past decades. However, wireless traffic frequently exhibits strong nonlinearities and complicated patterns, which makes it challenging to be predicted accurately. Many of the existing approaches for predicting wireless network traffic are unable to produce accurate predictions because they lack the ability to describe the dynamic spatial-temporal correlations of wireless network traffic data. In this paper, we proposed a novel meta-heuristic optimization approach based on fitness grey wolf and dipper throated optimization algorithms for boosting the prediction accuracy of traffic volume. The proposed algorithm is employed to optimize the hyper-parameters of long short-term memory (LSTM) network as an efficient time series modeling approach which is widely used in sequence prediction tasks. To prove the superiority of the proposed algorithm, four other optimization algorithms were employed to optimize LSTM, and the results were compared. The evaluation results confirmed the effectiveness of the proposed approach in predicting the traffic of wireless networks accurately. On the other hand, a statistical analysis is performed to emphasize the stability of the proposed approach.     

基于灰色模糊数的公交线网优化研究

在考虑信息不完全的情况下,用灰色模糊数对公交线网优化问题进行了研究。在给出了公交线网优化的约束条件与优化目标的基础上,利用灰色模糊数建立了公交线网优化的决策模型。灰色模糊数是用三参数区间参与优化过程,在允许参数在一定范围内变化的情况下,计算后得到的结果是一个区间向量,其中向量值最大的为所求结果,适用于城市公交线网的优化问题。实例应用分析表明,优化后的公交线网效率提高,可达性良好,可满足城市公交可持续发展的要求。     

Image tracking of motorcycles and vehicles on urban roads and its application to traffic monitoring and enforcement

Abstract

Image tracking has increasingly gained attention for use in vision‐based traffic monitoring and surveillance applications. For many cities in Asia countries, it is desirable to detect multiple motorcycles as well as cars for urban traffic monitoring and enforcement. In this paper, a novel contour initialization and tracking algorithm is presented to track multiple motorcycles and vehicles at any position on the roadway. This method has the capability to detect moving vehicles of various sizes and to generate their initial contours for image tracking. The proposed method is not constrained by lane boundaries or vehicle size. To track vehicles on roadways, dynamic models are designed to predict the horizontal and vertical positions of vehicle contours. A Kalman filter is designed to update the prediction based on real‐time image measurement. Practical experimental studies using video clips are presented to evaluate the performance of the proposed method. Traffic parameters such as traffic flow, vehicle speeds and traffic density are obtained with satisfactory accuracy.     

控制城市交通声对住区影响的设计实践

城市交通在带来生活、工作便捷的同时却给住区形成难以容忍的声音干扰，在充分研究降低交通工具，市政道路而造成噪声的工作同时，通过城市建筑设计方法来控制交通声对住区的影响是一项可行的，科学的实践。     

转子有碰摩和支承松动故障时的混沌特性研究

以具有支承松动的Jeffcott转子为研究对象，并考虑到转子系统转子和定子间的碰摩现象，分析了支承松动和碰摩对转子系统刚度的影响，建立了转子系统振动的微分方程，并用数值方法分析系统的分叉与混沌等非线性动力学特性，数值分析表明，转子在碰摩和支承松动这两种非线性因素的作用下，具有复杂的拟周期运动和混沌运动。     

基于车流密度的道路噪声源动态辐射模型

相较于车流相对稳定的高速公路而言,城市交通流因上下班高峰、红绿灯、交叉路口等影响,具有明显的波动性。现有噪声预测模式中,声源辐射模型采用小时流量及设计速度作为独立变量,车速与车流量没有关联,仅适用于测量常年平均声级,不能正确反映城市道路噪声的动态变化特征。文章对交通流模型进行了调查,以行车速度与车流密度制约关系为基础,结合道路车辆的物理模型及声源辐射模型,建立以车流密度为变量的噪声源动态声源辐射计算模型,描述城市道路交通噪声辐射声级随车流密度的动态变化特征,与已有模型进行对比并通过实测,验证了新模型能更好地反映城市道路车辆声源辐射声级的变化情况。     

Travel time prediction under heterogeneous traffic conditions using global positioning system data from buses

Travel time information is a vital component of many intelligent transportation systems (ITS) applications. In recent years, the number of vehicles in India has increased tremendously, leading to severe traffic congestion and pollution in urban areas, particularly during peak periods. A desirable strategy to deal with such issues is to shift more people from personal vehicles to public transport by providing better service (comfort, convenience and so on). In this context, advanced public transportation systems (APTS) are one of the most important ITS applications, which can significantly improve the traffic situation in India. One such application will be to provide accurate information about bus arrivals to passengers, leading to reduced waiting times at bus stops. This needs a real-time data collection technique, a quick and reliable prediction technique to calculate the expected travel time based on real-time data and informing the passengers regarding the same. The scope of this study is to use global positioning system data collected from public transportation buses plying on urban roadways in the city of Chennai, India, to predict travel times under heterogeneous traffic conditions using an algorithm based on the Kalman filtering technique. The performance of the proposed algorithm is found to be promising and expected to be valuable in the development of APTS in India. The work presented here is one of the first attempts at real-time short-term prediction of travel time for ITS applications in Indian traffic conditions.     

Finite element solution for the continuum traffic equilibrium problems

In this paper, we consider a city with a highly compact Central Business District (CBD), and the commuters’ destinations from the CBD are dispersed over the whole city. The street network is approximated as a continuum and commuters’ movements in the city are measured by the flow intensity, and the local travel cost depends on the location and the traffic flow intensity. We extend the continuum user equilibrium problem to deal with the case of variable demand, in which the traffic demand from any destination in the city to the CBD is assumed to be a function of both the destination location and the total travel cost to the CBD. An equivalent mathematical model is formulated and proved to satisfy the user equilibrium conditions, which is then solved by a finite element solution algorithm. Numerical examples are given to illustrate the effectiveness of the proposed method. © 1998 John Wiley & Sons, Ltd.     

道路交通噪声源强快速建模方法

道路交通噪声源强的预测是道路交通噪声预测的关键。由于车辆状况、道路状况等在我国具有不同的特点;因而在采用国外道路交通噪声源强模型时将导致准确性降低。建立源强模型通常采用的实验方法对场地要求严格,样本数量需求巨大,不易获得本地模型。基于标准实验情况建立的模型不一定适用于复杂的城市交通流。为此,提出一种简单快速建立符合本地城市交通特点模型的方法,该方法以实测交通流数据计算观测点噪声,通过优化算法求解最优参数,确定本地化源强模型。该方法利用多辆车共同作用得到的等效声级,反演得到单车模型,既包含了丰富的样本,又节省测量时间。以北京选取道路的实践为例,建立模型并验证,结果表明本方法快速易行,准确性高。     

Area-wide urban traffic calming schemes: a meta-analysis of safety effects

This paper presents a meta-analysis of 33 studies that have evaluated the effects on road safety of area-wide urban traffic calming schemes. Area-wide urban traffic calming schemes are typically implemented in residential areas in towns in order to reduce the environmental and safety problems caused by road traffic. A hierarchical road system is established and through traffic is removed from residential streets by means of, for example, street closures or one-way systems. Speed reducing devices are often installed in residential streets. Main roads are improved in order to carry a larger traffic volume without additional delays or more accidents. The meta-analysis shows that area-wide urban traffic calming schemes on the average reduce the number of injury accidents by about 15%. The largest reduction in the number of accidents is found for residential streets (about 25%), a somewhat smaller reduction is found for main roads (about 10%). Similar reductions are found in the number of property damage only accidents. The results of evaluation studies are robust with respect to study design. There is no evidence of publication bias in evaluation studies. Study findings are found to have high external validity.     

Universal predictability of mobility patterns in cities

Despite the long history of modelling human mobility, we continue to lack a highly accurate approach with low data requirements for predicting mobility patterns in cities. Here, we present a population-weighted opportunities model without any adjustable parameters to capture the underlying driving force accounting for human mobility patterns at the city scale. We use various mobility data collected from a number of cities with different characteristics to demonstrate the predictive power of our model. We find that insofar as the spatial distribution of population is available, our model offers universal prediction of mobility patterns in good agreement with real observations, including distance distribution, destination travel constraints and flux. By contrast, the models that succeed in modelling mobility patterns in countries are not applicable in cities, which suggests that there is a diversity of human mobility at different spatial scales. Our model has potential applications in many fields relevant to mobility behaviour in cities, without relying on previous mobility measurements.     

Reasons underlying behaviour of motorcyclists disregarding traffic regulations in urban areas of Indonesia

Over the last decade, motorcycle use has been rapidly increasing in Indonesia as have violations of traffic rules committed by motorcyclists. This study aims to explore the impacts of motorcyclists’ attitudes, habits, preferences, and travel patterns on their behaviour in disregarding traffic regulations in three cities in Indonesia. The theory of planned behaviour and structural equation modelling are employed to explore these relationships. Consistent with results from previous studies in developed countries, an individual’s beliefs and attitudes, social norms and perceived behaviour control significantly influence behaviour in disregarding traffic rules. Young adults and students are found to be more likely to frequently violate traffic regulations. However, unlike previous findings from developed countries, in Indonesia, males are less likely to disregard traffic rules than females. Overall, pushing the motorcycle through a (very) narrow gap, speeding, driving recklessly, and overtaking on the wrong side are the most frequent traffic violations that make up repetitive violation behaviour among urban motorcyclists in Indonesia. The results highlight the need to revisit Indonesian National Traffic Law traffic violation classification and penalties and separate violations that are likely to cause fatal results, thus requiring tougher law enforcement, from violations that are unlikely to have fatal consequences.     

香港交通噪声问题及其控制政策综述

不同于世界其他大城市,香港因其特有的噪声问题,有时会被冠以世界最嘈杂的城市的称号。对此,香港政府为改善噪声环境付出了极大的努力,并且取得了一定的成效。然而,主要的噪声问题仍然存在,部分缘于其拥挤的城市结构以及八十年代之前城市规划时对噪声污染问题的忽视,这些都不是一朝一夕之间能解决的问题。香港的噪声问题中,又以交通噪声最为严重,80%的香港人在不同程度上受到道路交通噪声的影响。该文介绍了香港交通噪声问题及其现行的交通噪声政策,并讨论了现行政策所遇到的问题,最后介绍了由香港声学学会提议的进一步的交通噪声控制策略。     

KSUTraffic: A Microscopic Traffic Simulator for Traffic Planning in Smart Cities

Simulation is a powerful tool for improving, evaluating and analyzing the performance of new and existing systems. Traffic simulators provide tools for studying transportation systems in smart cities as they describe the evolution of traffic to the highest level of detail. There are many types of traffic simulators that allow simulating traffic in modern cities. The most popular traffic simulation approach is the microscopic traffic simulation because of its ability to model traffic in a realistic manner. In many cities of Saudi Arabia, traffic management represents a major challenge as a result of expansion in traffic demands and increasing number of incidents. Unfortunately, employing simulation to provide effective traffic management for local scenarios in Saudi Arabia is limited to a number of commercial products in both public and private sectors. Commercial simulators are usually expensive, closed source and inflexible as they allow limited functionalities. In this project, we developed a local traffic simulator “KSUtraffic” for traffic modeling, planning and analysis with respect to different traffic control strategies and considerations. We modeled information specified by GIS and real traffic data. Furthermore, we designed experiments that manipulate simulation parameters and the underlying area. KSUTraffic visualizes traffic and provides statistical results on the simulated traffic which would help to improve traffic management and efficiency.     

Traffic planning for non-homogeneous traffic

Traffic on Indian roads (both urban and inter-urban) consists of a variety of vehicles. These vehicles have widely different static and dynamic characteristics. The traffic is also very different from homogeneous traffic which primarily consists of motorized vehicles. Homogeneous traffic follows strict lane discipline as compared to non-homogeneous traffic. Western traffic planning methodologies mostly address the concerns of homogeneous traffic and therefore often prove inadequate in solving problems involving non-homogeneous traffic conditions as found in Indian cities. This paper presents studies conducted on non-homogeneous traffic. Section 1 presents a methodology to verify the continuity equation, the basic block of any traffic planning analysis. In § 2, the methodology developed is applied to modify the Highway Capacity Manual (HCM) 2000 density method to derive passengercar equivalencies (PCEs) or units (PCUs) for heavy vehicles and recreational vehicles. These PCUs appear as ‘ET’ and ‘ER’ in HCM tables. The density method assumes motorized, four-wheeler traffic, i.e., homogeneous traffic, and does not include motorized three-wheelers, motorized two-wheelers, and non-motorized traffic often present on Indian highways. By modifying the density method to represent non-homogeneous traffic, which includes significant percentages of motorized, three-wheelers, motorized two-wheelers, and non-motorized traffic entities, one can derive more accurate passenger car units for Indian conditions. Transport professionals can use these PCU values for accurate capacity, safety, and operational analysis of highways carrying non-homogeneous traffic.