基于METANET模型的车道级可变限速控制研究

可变限速控制是一种应用广泛的主动管理方式，能够提高车辆的通行效率和安全性。现有研究集中在对多车道路段不区分车道进行限速控制。事实上，不同车道的交通状态有所不同，且换道行为本身也会对交通流造成影响，进而影响限速控制的效果。本文基于METANET模型，提出一个新的高速公路多车道交通流模型。以总行程时间最小和总周转量最大作为目标函数，建立了车道级可变限速控制模型。利用MATLAB数值仿真的方法，基于真实交通数据对所提出的模型进行了评价。研究结果显示，相较于整体可变限速控制，车道级可变限速控制使车辆总行程时间减少了5.9%，总周转量提高了6.8%，证明本文提出的模型能够更进一步提升高速公路通行能力、缓解交通拥堵。     

高速公路改扩建工程车速限制方案研究

基于高速公路限速标准、限速方法以及改扩建高速公路的特征,围绕道路线形、特殊道路设施与事故率等方面着重分析了改扩建高速公路限速方案制定的依据及考虑因素,在符合相关法律法规的范围内提出适合我国改扩建高速公路限速研究及方案制定的思路及流程,并通过广东某改扩建高速公路的限速方案制定以详细介绍制定流程。     

雾天高速公路交通事故成因分析及管理措施

文章分析了雾天高速公路交通事故的成因与特征,提出了相应的交通管制方式和处置措施,为雾天高速公路的交通管理工作提供思路。     

基于VB的高速公路动态限速仿真软件平台

文章利用VB语言及VISSIM交通仿真软件自主开发了高速公路动态限速仿真软件平台,对高速公路网进行微观仿真,并结合宏观交通流模型及成本函数制定高速公路动态限速方案。通过广西柳州(鹿寨)至南宁高速公路改扩建项目动态限速仿真软件平台的应用实践表明,该平台可以有效帮助高速公路交通规划管理部门制定科学合理的动态限速方案,并产生容量可观的数据库,有利于相关研究人员进行进一步的分析与评价。     

高速公路分段限速值设计方法研究

总结了欧美等发达国家高速公路所使用的限速值设计方法,分析了影响高速公路限速的因素.在此基础上提出并构建了适合我国交通特性的高速公路分段限速值设计方法及具体实施流程.该方法综合考虑了运行速度、高速公路线形、设计速度和交通安全等因素,可合理、科学的确定高速公路限速值.     

基于能见度检测的高速公路雾天智能诱导系统

为了车辆安全通过高速公路雨雾路段,文章基于能见度检测和低能见度的安全行车间距,设计出一套适应广西雨雾特殊天气条件的高速公路雾天智能诱导系统。该系统具有能见度检测、智能诱导、多元化控制、无人值守等功能,提升了高速公路运营管理水平,增加高速公路行车安全性和舒适性,降低事故发生概率。     

高速公路扩建交通转换期中分带开口设置技术研究

分析了我国高速公路扩建中的交通组织方式的基础上,结合半封闭半通车的交通组织方案特点,建立了中分带开口车辆换道模型,提出了扩建路段中分带开口位置合理长度的计算模型,并提出了在不同限速、不同中间带宽度状态下的中分带开口位置合理长度建议值。     

高速公路出口匝道影响区分级限速方案适用性研究

本文针对所研究的出口匝道类型,划分其影响区并制定相应的分级限速方案。选取速度偏差的变化系数、交通冲突率、车均延误时间和平均排队长度这四个评估指标,构建高速公路出口匝道影响区分级限速方案适用性的评估指标体系,采用加权加法平均法对方案适用性进行综合评估。最后基于VISSIM仿真结果,对比分析得到分级限速方案在不同交通组织环境下的适用性结论。     

基于视觉负荷的高速公路隧道限速值的研究

本文为了确定高速公路隧道内提速方案具体的限速值,通过选取多条有提速需求的典型高速公路隧道进行试验,通过瞳孔面积变化率表征驾驶人在隧道内的视觉负荷程度。根据瞳孔面积变化率与机动车临界速度之间的关系,得到满足明、暗适应的视觉负荷程度对应的机动车临界速度值,取机动车临界速度分析车辆进出高速公路隧道时由于明、暗适应引起的速度变化规律;提出了以机动车临界速度值和全线提速方案对应的隧道限速值,取两者最小值作为隧道最终提速方案的限速值,然后对隧道限速原则进行修正,最后确定了原隧道路段限速60km/h、80km/h时的提速方案的具体限速值。研究结果表明:对于满足提速要求的隧道路段,原限速60km/h时,提速后的限速值取80km/h较合适;原隧道路段限速80km/h时,提速后的限速值取90km/h较合适。本文的研究具有安全性、可靠性,为日后隧道限速提供了相应参考。     

高速公路桥梁施工技术及管理体系研究

文章分析了高速公路桥梁施工中常见的技术及管理问题,从成孔灌注桩施工、混凝土施工以及钢筋预制件施工等方面,介绍了高速公路桥梁主要施工技术,并提出了基于多目标架构的施工质量及进度管理系统,设计了施工安全管理模型,可为同类工程施工提供理论依据。     

冰雪、大雾天气下交通安全保障设施应用研究

文章分析了冰雪、大雾天气的特点及其对道路行车安全的影响,探讨了冰雪、大雾天气下的交通安全保障措施,并对各种交通安全保障设施的设置进行了优化研究,为不良气候条件下的道路交通安全设计、评价提供技术依据。     

Investigating the impacts of weather variability on individual’s daily activity–travel patterns: A comparison between commuters and non-commuters in Sweden

Understanding travel behaviour change under various weather conditions can help analysts and policy makers incorporate the uniqueness of local weather and climate within their policy design, especially given the fact that future climate and weather will become more unpredictable and adverse. Using datasets from the Swedish National Travel Survey and the Swedish Meteorological and Hydrological Institute that spans a period of thirteen years, this study explores the impacts of weather variability on individual activity–travel patterns. In doing so, this study uses an alternative representation of weather from that of directly applying observed weather parameters. Furthermore, this study employs a holistic model structure. The model structure is able to analyse the simultaneous effects of weather on a wide range of interrelated travel behavioural aspects, which has not been investigated in previous weather studies. Structural equation models (SEM) are applied for this purpose. The models for commuters and non-commuters are constructed separately. The analysis results show that the effects of weather can be even more extreme when considering indirect effects from other travel behaviour indicators involved in the decision-making processes. Commuters are shown to be much less sensitive to weather changes than non-commuters. Variation of monthly average temperature is shown to play a more important role in influencing individual travel behaviour than variation of daily temperature relative to its monthly mean, whilst in the short term, individual activity–travel choices are shown to be more sensitive to the daily variation of the relative humidity and wind speed relative to the month mean. Poor visibility and heavy rain are shown to strongly discourage the intention to travel, leading to a reduction in non-work activity duration, travel time and the number of trips on the given day. These findings depict a more comprehensive picture of weather impact compared to previous studies and highlight the importance of considering interdependencies of activity travel indicators when evaluating weather impacts.     

Utilizing naturalistic driving data for in-depth analysis of driver lane-keeping behavior in rain: Non-parametric MARS and parametric logistic regression modeling approaches

It is known that adverse weather conditions can affect driver performance due to reduction in visibility and slippery surface conditions. Lane keeping is one of the main factors that might be affected by weather conditions. Most of the previous studies on lane keeping have investigated driver lane-keeping performance from driver inattention perspective. In addition, the majority of previous lane-keeping studies have been conducted in controlled environments such as driving simulators. Therefore, there is a lack of studies that investigate driver lane-keeping ability considering adverse weather conditions in naturalistic settings. In this study, the relationship between weather conditions and driver lane-keeping performance was investigated using the SHRP2 naturalistic driving data for 141 drivers between 19 and 89 years of age. Moreover, a threshold was introduced to differentiate lane keeping and lane changing in naturalistic driving data. Two lane-keeping models were developed using the logistic regression and multivariate adaptive regression splines (MARS) to better understand factors affecting driver lane-keeping ability considering adverse weather conditions. The results revealed that heavy rain can significantly increase the standard deviation of lane position (SDLP), which is a very widely used method for analyzing lane-keeping ability. It was also found that traffic conditions, driver age and experience, and posted speed limits have significant effects on driver lane-keeping ability. An interesting finding of this study is that drivers have a better lane-keeping ability in roadways with higher posted speed limits. The results from this study might provide better insights into understanding the complex effect of adverse weather conditions on driver behavior.     

Modeling traffic's flow-density relation: Accommodation of multiple flow regimes and traveler types

This research investigates freeway-flow impacts of different traveler types by specifying and applying a latent-segmentation model of congested and uncongested driving behaviors. Drivers in uncongested conditions are assumed to drive at self-chosen speeds, while drivers in congested conditions are assumed to take speed as given and choose a spacing (between their vehicle and the previous vehicle). Several classes of driver-vehicle combinations are distinguished in a data set based on double-loop-detector pulses and a household travel survey. These classifications are made on the basis of vehicle type and gender, leading to class estimates of speeds and spacings. The segmentation model is specified as a logit function of density, weather, and vehicle type, leading to estimates of congested-condition probabilities. Unobserved heterogeneity is incorporated in all models via common error assumptions.Results indicate that segmentation models are promising tools for traffic data analysis and that information on travelers, their vehicles, and weather conditions explains significant variation in flow data. By clarifying a greater understanding of traffic conditions and traveler behavior explains much scatter in the fundamental relation between flow, speed, and density, can assist regions in their traffic-management efforts and engineers in their design of roadway facilities. Ultimately, such improvements to travel networks should enhance quality of life.     

Impact of weather on urban transit ridership

Utilizing daily ridership data, literature has shown that adverse weather conditions have a negative impact on transit ridership and in turn, result in revenue loss for the transit agencies. This paper extends this discussion by using more detailed hourly ridership data to model the weather effects. For this purpose, the daily and hourly subway ridership from New York City Transit for the years 2010–2011 is utilized. The paper compares the weather impacts on ridership based on day of week and time of day combinations and further demonstrates that the weather’s impact on transit ridership varies based on the time period and location. The separation of ridership models based on time of day provides a deeper understanding of the relationship between trip purpose and weather for transit riders. The paper investigates the role of station characteristics such as weather protection, accessibility, proximity and the connecting bus services by developing models based on station types. The findings indicate substantial differences in the extent to which the daily and hourly models and the individual weather elements are able to explain the ridership variability and travel behavior of transit riders. By utilizing the time of day and station based models, the paper demonstrates the potential sources of weather impact on transit infrastructure, transit service and trip characteristics. The results suggest the development of specific policy measures which can help the transit agencies to mitigate the ridership differences due to adverse weather conditions.     

西部地区公路速度限制标准与控制技术研究

《西部地区公路速度限制标准与速度控制技术研究》项目通过对大量调查资料的统计分析,确定了公路限速设置标准及方法体系,提出了适用于我国西部地区不同技术等级公路的速度控制技术的设置条件及方法,形成了我国公路速度限制与控制技术指南。本篇阐述了该项目的主要研究成果,指出了项目的创新点,并对项目的应用及推广情况进行了介绍,为我国相关公路管理部门设置限速标准及进行速度管理与控制提供科学依据。     

A utility-theory analysis of automobile speed under uncertainty of enforcement

Highway automobile speed and uncertain enforcement of the speed limit are introduced into a standard household utility model having time and income constraints. Due to uncertainty, expected utility is maximized to obtain the optimal speed (in excess of the speed limit). The optimal amounts of all other commodities and travel are also obtained. The key feature of the model is the risk attitude of the driver and the effect on optimal speed of such attitude. A related feature is the effect of risk attitude on the amount of speed self-insurance. An important finding is that the risk avert (seeking, neutral) driver charges himself an insurance premium that is larger than (smaller than, equal to) what is actuarially sufficient. The relationship between speed, risk attitude, and efficient cost of automobile travel is developed and implications are explored. A parametric analysis is conducted to establish the effect on optimal speed (and other variables) of changes in such policy instruments as the price of gasoline, the probability of being caught exceeding the speed limit, the unit speed fine, and the speed limit. Policy implications of the theoretical results are part of the conclusions.     

Winter problems on mountain passes – Implications for cost-benefit analysis

Cost-benefit analysis is a tool in government decision-making for determining the consequences of alternative uses of society’s scarce resources. Such a systematic process of comparing benefits and costs was adopted in early years for transportation projects and it has been the subject of much refining over the years. There are still some flaws, however, in the application of the method. In this article we have studied the impact of weather conditions on traffic speed on low traffic roads often exposed to adverse weather. This is an issue not currently considered in the cost-benefit analysis of road projects. By using two analytical approaches—structural equation modelling and classification and regression tree analysis—the impact of the weather indicators temperature, wind speed, and precipitation on traffic speed has been quantified. The data relates to three winter months on the European Route 6 road over the mountain pass Saltfjellet in Norway. Increase in wind speed, increase in precipitation and temperatures around freezing point all caused significant decrease in traffic speed in the case studied. If actions were taken to reduce the impact of adverse weather on traffic (e.g. by building a tunnel through the mountain) this study indicates that the road users would gain a total benefit of approximately 2,348,000 NOK (282,000 EUR) each winter at Saltfjellet if all the weather related benefits were included. We argue that this is a significant number that is highly relevant to include in CBAs. This applies both to the CBAs of new transportation projects as well as when resources are allocated for operation, maintenance, and monitoring of the existing transport systems. Including the weather related benefits would improve the application of CBA as a decision-making tool for policy makers.     

Does winter road maintenance help reduce air emissions and fuel consumption?

Winter road maintenance (WRM) has been shown to have significant benefits of improving road safety and reducing traffic delay caused by adverse weather conditions. It has also been suggested that WRM is also beneficial in terms of reducing vehicular air emissions and fuel consumptions because snow and ice on road surface often cause the drivers to reduce their vehicle speeds or to switch to high gears, thus decreasing fuel combustion efficiency. However, there has been very limited information about the underlying relationship, which is important for quantifying this particular benefit of a winter road maintenance program. This research is focused on establishing a quantitative relationship between winter road surface conditions and vehicular air emissions. Speed distribution models are developed for the selected Ontario highways using data from 22 road sites across the province of Ontario, Canada. The vehicular air emissions under different road surface conditions are calculated by coupling the speed models with the engine emission models integrated in the emission estimation model - MOVES. It was found that, on the average, a 10% improvement in road surface conditions could result in approximately 0.6–2% reduction in air emissions. Application of the proposed methodology is demonstrated through a case study to analyse the air emission and energy consumption effects under specific weather events.     

Benefit of speed reduction for ships in different weather conditions

Currently, the shipping industry is facing a great challenge of reducing emissions. Reducing ship speeds will reduce the emissions in the immediate future with no additional infrastructure. However, a detailed investigation is required to verify the claim that a 10% speed reduction would lead to 19% fuel savings (Faber et al., 2012).This paper investigates fuel savings due to speed reduction using detailed modeling of ship performance. Three container ships, two bulk carriers, and one tanker, representative of the shipping fleet, have been designed. Voyages have been simulated by modeling calm water resistance, wave resistance, propulsion efficiency, and engine limits. Six ships have been simulated in various weather conditions at different speeds. Potential fuel savings have been estimated for a range of speed reductions in realistic weather.It is concluded that the common assumption of cubic speed-power relation can cause a significant error in the estimation of bunker consumption. Simulations in different seasons have revealed that fuel savings due to speed reduction are highly weather dependent. Therefore, a simple way to include the effect of weather in shipping transport models has been proposed.Speed reduction can lead to an increase in the number of ships to fulfill the transport demand. Therefore, the emission reduction potential of speed reduction strategy, after accounting for the additional ships, has been studied. Surprisingly, when the speed is reduced by 30%, fuel savings vary from 2% to 45% depending on ship type, size and weather conditions. Fuel savings further reduce when the auxiliary engines are considered.