海外传真

瑞典：自行车也有高速公路 据悉,厄勒布鲁有望在近期完成3条自行车高速公路建设,并计划在2020年完成15条,以实现全民自行车出行的目标。与平时看到的自行车道不同,自行车高速公路以橙色标记划出,严格与人行道及机动车道分开,并设有专门的交通信号灯、指示牌和停靠站等设施。     

公交停靠站通行能力研究

为提高现有公交停靠站的通行能力,文章分析了公交停靠站通行能力的影响因素,从公交停靠时间、清空时间、停靠波动性、交通信号控制四个方面研究公交停靠站的通行能力,并以重庆市公交车作为研究对象,计算了重庆南坪协信城停靠站车辆通过能力。提出为降低停靠时间,需要从减少乘客服务时间出发,对现有站厅的设施配置及功能分区进行完善,既能提高公交运行效率,又能改善站厅的舒适性,一定程度上降低了乘客候车心理时间。研究结果表明改善后的公交停靠站的通行能力有显著提升,车位利用率得到提高,候车环境的舒适性有所改善。     

“阿尔法巴”来了!“无人驾驶”智能公交系统深圳试运行

正方向盘可以自己动,遇到交通灯和行人会自动刹车,到了十字路口自动转弯,到了公交站自动变道停靠……这样酷炫的无人驾驶汽车,真的在深圳试运行了!12月2日,阿尔法巴智能驾驶公交系统在深圳福田保税区首发试运行。4辆全电动公交车在全程1.2公里的线路运行,车速10-30公里/小时,途中设三个停靠站。     

佳通GT867中标银川公交

日前,银川市公共交通有限公司轮胎招标活动顺利结束。此次竞标吸引到国内外多家知名品牌参与,最终佳通推介的公交专用轮胎GT867崭露头角一举中标。佳通轮胎此次成功中标不仅源于GT867自身的卓越性能,更得益于佳通轮胎与全国逾百家公交公司长期合作的成功经验。据保守估计,目前全国已有60%的省会城市公交系统选用了佳通GT867。据了解,银川市的公交车在停靠站时需要从机动车道转     

"我的胃口非常大"--浙江省交通厅运输管理局局长张平平农村客运

<运输经理世界>:贵局采取哪些方法推进城乡客一体化进程? 张平平:一是确定农村客动城乡一体化"八个统一"(统一管理体制、统一经营体制、统一硬件设施、统一市场监管、统一市场配置、统一车型载客政策、统一服务标准、统一政策待遇)的发展方向,从"税、费价、险"四方面入手,对农材短途客动班车规费实行减免;二是根据到2020年我省提前基本实现现代化的目标要求,我厅提出并实施了"乡村康庄工程"建设,努力提高全省农村公路通达深度和质量,要求在全省范围内加快按部颁四级公路工程技术标准或地方标准改造通村公路的速度,同时提高农村公路的路面质量,对通行政村公路进行路面硬化,从根本上改善农村交通条件,从而为农村客运的发展打下坚实基础;三是为改善农民群众的出行条件,我厅对28个农村客运站和港湾式停靠站的设计方案组织专家进行了评选,推选出了5个农村客运站和2个港湾式停靠站设计方案.     

风雨十年铸辉煌 争创一流拓新路——广西南宁高速公路管理处

1998年7月18日,随着桂海高速公路南宁至南间段的开通,广西南宁高速公路管理处诞生了.随后,南宁高速公路管理处先后接管了柳南高速公路南段、南宁环城高速公路和都南高速公路.     

关于高速公路施工安全与文明施工的探讨

高速公路施工作业区是为高速公路新建、维修、养护作业而设置的区域,存在各种各样的施工风险.文章以高速公路施工作业区为主要阵地,以某高速公路施工项目为例,简要阐述了高速公路施工安全管理措施,并对高速公路文明施工的相关策略进行了进一步探究,希望为高速公路施工安全与文明施工的实现提供一些参考.     

论宣传报道在高速公路建设管理中的重要作用

文章结合广西高速公路项目建设发展实际,阐述了宣传报道与高速公路项目建设的关系,分析了宣传报道在高速公路建设发展中的重要导向作用,并提出了做好高速公路建设行业宣传报道工作的具体思路。     

高速公路工程试验检测技术研究

文章介绍了高速公路工程试验检测技术的发展趋势,分析了常规的高速公路工程试验检测方案,研究了高速公路工程试验的主要检测项目及要求,包括综合甲级检测项目、高速公路隧道项目和高速公路桥梁项目等,可为高速公路的工程试验工作提供相关参考依据。     

对重庆高速公路融资方式的思考

高速公路建设资金不足日益严重,融资方式的单一又局限了资金的来源渠道。目前高速公路建设主要的融资渠道是银行贷款,但高负债危机已经引起广泛关注。本文立足重庆市高速公路建设融资的现状,深入分析了高速公路建设项目的多种融资方式,提出了高速公路融资的有效方式。     

Exploring the impact of connected and autonomous vehicles on freeway capacity using a revised Intelligent Driver Model

ABSTRACT

Connected and autonomous vehicle (CAV) technologies are expected to change driving/vehicle behavior on freeways. This study investigates the impact of CAVs on freeway capacity using a microsimulation tool. A four-lane basic freeway segment is selected as the case study through the Caltrans Performance Measurement System (PeMS). To obtain valid results, various driving behavior parameters are calibrated to the real traffic conditions for human-driven vehicles. In particular, the calibration is conducted using genetic algorithm. A revised Intelligent Driver Model (IDM) is developed and used as the car-following model for CAVs. The simulation is conducted on the basic freeway segment under different penetration rates of CAVs and different freeway speed limits. The results show that with an increase in the market penetration rate, freeway capacity increases, and will increase significantly as the speed limit increases.     

Stochasticity of freeway operational capacity and chance-constrained ramp metering

The notion of capacity is essential to the planning, design, and operations of freeway systems. However, in the practice freeway capacity is commonly referred as a theoretical/design value without consideration of operational characteristics of freeways. This is evident from the Highway Capacity Manual (HCM) 2000 in that no influence from downstream traffic is considered in the definition of freeway capacity. In contrast to this definition, in this paper, we consider the impact of downstream traffic and define freeway operational capacity as the maximum hourly rate at which vehicles can be expected to traverse a point or a uniform section of a roadway under prevailing traffic flow conditions. Therefore freeway operational capacity is not a single value with theoretical notion. Rather, it changes under different traffic flow conditions. Specifically, this concept addresses the capacity loss during congested traffic conditions. We further study the stochasticity of freeway operational capacity by examining loop detector data at three specifically selected detector stations in the Twin Cities’ area. It is found that values of freeway operational capacity under different traffic flow conditions generally fit normal distributions. In recognition of the stochastic nature of freeway capacity, we propose a new chance-constrained ramp metering strategy, in which, constant capacity value is replaced by a probabilistic one that changes dynamically depending on real-time traffic conditions and acceptable probability of risk determined by traffic engineers. We then improve the Minnesota ZONE metering algorithm by applying the stochastic chance constraints and test the improved algorithm through microscopic traffic simulation. The evaluation results demonstrate varying degrees of system improvement depending on the acceptable level of risk defined.     

A decentralized control strategy for freeway regulation

A multilevel decentralized control scheme, the cascading technique, with application to the regulation of traffic on an urban freeway is presented. Performance of the decentralized system is compared to the performance of a centralized and a fixed time control structure. It is shown that the decentralized structure performs better than the centralized structure when incidents (lane closures) occur on the freeway. The freeway is modeled in terms of the aggregate variables section density and section speed, and is considered as a system of interconnected subsystems.     

Methods of dropping auxiliary lanes at freeway weaving segments

Auxiliary lanes connecting freeway entrance and exit ramps provide additional space for entering and exiting vehicles to change lanes. The method of dropping auxiliary lanes is critical in the design of freeway auxiliary lanes. This study investigates the performance of different methods of dropping auxiliary lanes. Case studies were conducted at two selected freeway segments with successive entrance or exit ramps in the City of Houston. Traffic simulation analysis results of these two case studies show that additional operational benefits can be achieved by extending an auxiliary lane beyond the freeway weaving segment. The study also found that if the weaving segment is followed by an entrance/exit ramp and this ramp has high traffic volume, it can be less operationally favorable to extend and terminate the auxiliary lane at this entrance/exit ramp location. Instead, dropping the auxiliary lane before this entrance/exit ramp represents a more operationally effective option.     

Considering various ALINEA ramp metering strategies for crash risk mitigation on freeways under congested regime

This study evaluates the expected benefits of using the ALINEA ramp metering algorithm as a method for real-time safety improvement on an urban freeway. The objective of this research is to use ramp metering to produce a significant decrease in the risk of crashes on the freeway while avoiding any significant adverse effects on operation. This is achieved by simulating the freeway during the congested period in micro-simulation and testing various ramp metering configurations to determine which provides the best results. Statistical measures developed for the same stretch of freeway using loop detector data are used to quantify the risk of crashes as well as the benefits in each of the alternative strategies. The study concludes that there are significant benefits in metering multiple ramps when the feedback ramp metering algorithm is implemented at multiple locations. It was found that increasing the number of metered on-ramps produces increasing safety benefits. Also, a shorter cycle length for each of the meters and a higher critical occupancy value leads to better results.     

On the macroscopic stability of freeway traffic

A simple model of traffic flow is used to analyze the spatio-temporal distribution of flow and density on closed-loop homogeneous freeways with many ramps, which produce inflows and allow outflows. As we would expect, if the on-ramp demand is space-independent then this distribution tends toward uniformity in space if the freeway is either: (i) uncongested; or (ii) congested with queues on its on-ramps and enough inflow to cause the average freeway density to increase with time. In all other cases, however, including any recovery phase of a rush hour where the freeway’s average density declines, the distribution of flow and density quickly becomes uneven. This happens even under conditions of perfect symmetry, where the percentage of vehicles exiting at every off ramp is the same. The flow-density deviations from the average are shown to grow exponentially in time and propagate backwards in space with a fixed wave speed. A consequence of this type of instability is that, during recovery, gaps of uncongested traffic will quickly appear in the unevenly congested stream, reducing average flow. This extends the duration of recovery and invariably creates clockwise hysteresis loops on scatter-plots of average system flow vs. density during any rush hour that oversaturates the freeway. All these effects are quantified with formulas and verified with simulations. Some have been observed in real networks. In a more practical vein, it is also shown that the negative effects of instability diminish (i.e., freeway flows increase) if (a) some drivers choose to exit the freeway prematurely when it is too congested and/or (b) freeway access is regulated in a certain traffic-responsive way. These two findings could be used to improve the algorithms behind VMS displays for driver guidance (finding a), and on-ramp metering rates (finding b).     

Patterns and projections of technical development in freeway surveillance and control in the U.S.A.

This paper explores the historical trends in freeway traffic management technology in the U.S., and the most likely projections for the coming two decades. First, existing computer‐supervised freeway surveillance and control techniques are reviewed with particular emphasis on the scientific and technological landmarks which has led to the evolution of these techniques. Next, the major underlying trends which bear on the future of automated freeway surveillance and control are identified. Finally, extrapolative projections are made to determine the most likely future of this technology. The paper concludes with implications for the issues of meeting short‐term transportation needs of urban areas through more efficient use of existing transportation facilities.     

Will a higher free-flow speed lead us to a less congested freeway?

An approach based on cell transmission model (CTM) is proposed to estimate the impact of variable free-flow speeds (FFS) on the performance of a freeway system. Based on the basic CTM, four typical freeway control strategies consisting of non control, local ramp metering, coordinated ramp metering and global control are first formulated. Then the method of adjusting model parameters to the changed free-flow speeds is presented. Among the adjustments, an experimental function based on Fan and Seibold (2014) is proposed to change the jam density. Several useful measures are defined to estimate and compare the performances of different freeways. The following three main observations are obtained from numerical experiments. (a) With the gradually increasing FFS, the throughput of freeway will increase at the beginning and then change to decrease. (b) With the increasing FFS, the average delay of vehicles will decrease at the beginning and then change to increase. (c) A series of free-flow speeds associate with the best performance of freeway. These observations are theoretically analyzed through investigating the location and capacity of bottleneck. Study shows that in general the actual bottleneck capacity will increase at the beginning and then change to decrease with the continually increasing FFS. In view of the positive correlation between traffic delay and bottleneck capacity, the theoretical analysis confirms the numerical observations. The findings of this study can deepen the understanding of freeway systems and help management agents adopt proper measures to improve the performance of the whole system.     

Understanding the variability of speed distributions under mixed traffic conditions caused by holiday traffic

Understanding the variability of speed patterns and congestion characteristics of interstate freeway systems caused by holiday traffic is beneficial because appropriate countermeasures for safety improvement and congestion mitigation can be prepared and drivers can avoid traffic congestion and change their holiday travel schedules. This study evaluated the traffic congestion patterns during the Thanksgiving holiday period in 2006 using a Gaussian mixture speed distribution estimated by the Expectation–Maximization (EM) algorithm. This mathematical approach showed the potential of improving freeway operational performance evaluation schemes for holiday periods (even non-holiday periods). This study suggested that a Gaussian mixture model using the EM algorithm could be used to properly characterize the severity and the variability of congestion on certain interstate roadway systems. However, this study also pointed out that the fundamental limitations of the mixture model and the statistical significance test about the mixture components should be well understood and need to be further investigated. In addition, because this study investigated the changing patterns of speed distributions with only one interstate freeway system, I-95 northbound, other freeway systems with both directions need to be evaluated so that a more broad and confident analysis on holiday traffic can be achieved.     

Stochastic cell transmission model (SCTM): A stochastic dynamic traffic model for traffic state surveillance and assignment

The paper proposes a first-order macroscopic stochastic dynamic traffic model, namely the stochastic cell transmission model (SCTM), to model traffic flow density on freeway segments with stochastic demand and supply. The SCTM consists of five operational modes corresponding to different congestion levels of the freeway segment. Each mode is formulated as a discrete time bilinear stochastic system. A set of probabilistic conditions is proposed to characterize the probability of occurrence of each mode. The overall effect of the five modes is estimated by the joint traffic density which is derived from the theory of finite mixture distribution. The SCTM captures not only the mean and standard deviation (SD) of density of the traffic flow, but also the propagation of SD over time and space. The SCTM is tested with a hypothetical freeway corridor simulation and an empirical study. The simulation results are compared against the means and SDs of traffic densities obtained from the Monte Carlo Simulation (MCS) of the modified cell transmission model (MCTM). An approximately two-miles freeway segment of Interstate 210 West (I-210W) in Los Ageles, Southern California, is chosen for the empirical study. Traffic data is obtained from the Performance Measurement System (PeMS). The stochastic parameters of the SCTM are calibrated against the flow-density empirical data of I-210W. Both the SCTM and the MCS of the MCTM are tested. A discussion of the computational efficiency and the accuracy issues of the two methods is provided based on the empirical results. Both the numerical simulation results and the empirical results confirm that the SCTM is capable of accurately estimating the means and SDs of the freeway densities as compared to the MCS.