Y型交叉口绿灯释放初期电动自行车对机动车的影响

Y型道路交叉口属异形交叉口,趋于行驶车流角度,从而使灵活多变的电动自行车对机动车的影响较为突出.为研究Y型交叉口绿灯周期电动自行车对机动车的影响程度,统计了307组绿灯期电动自行车流量分布,确定了绿灯期0-10s为电动自行车释放初期,建立了基于Logistic逐步回归的电动自行车对机动车影响模型,通过实例验证了模型的有效性.结果表明,释放初期电动自行车的流量、占道间隙停车行为、自进口机动车第1车道驶入出口第2车道及自进口非机动车道驶入出口机动车第1车道的入侵行为对机动车影响显著,其中占道间隙停车行为对机动车影响最大.研究成果可为提高异形交叉口混合交通流通行效率、交叉口渠化设计及交通组织管理提供理论参考.     

基于延误模型的定时信号交叉口配时方案研究

信号交叉口配时方案的最优策略是平衡关键车道组的v/c比和所有车辆延误最小化.本文在研究已有控制延误模型的基础上,提出一种新的随机控制延误计算模型.根据不同地区各城市信号交叉口的交通流运行特性,在信号优化策略基础上兼顾考虑其通行能力,给出实时实地的信号配时方案策略.实例说明该定时信号交叉口配时方案.     

车流高峰期交通信号的模糊控制及仿真

用较少的模糊规则控制车流高峰期的交通信号,建立仿真系统模拟单交叉口二相位交通流,利用遗传算法对模糊规则进行优化并找出绿灯时间模糊集隶属函数的最优边界.实验结果表明,优化后的模糊规则对高峰期的车流变化具有更强的适应性.     

一种确定信号交叉口拥堵的概率统计预警模型

研究信号交叉口的运行效率及车辆服务水平对于城市交通建设与发展具有重要的意义。本文针对信号交叉口各入口方向上车流的运行特性,从概率统计的角度研究各入口方向上通过信号交叉口车流的统计模型,并在此基础上得到了一种用于定时信号交叉口拥堵的概率统计实时交通状况预警判断模型。     

基于元胞自动机的交叉口混合交通模型研究

在我国很多中小城市普遍存在着摩托车与小汽车混行的现象,摩托车既有类似自行车横向移动灵活、启动速度快的特点,又有类似小汽车纵向移动速度快的特点,特别是在城市交叉口附近范围内,摩托车与小汽车几乎速度相当.根据交叉口红灯起亮时,摩托车会灵活穿插,充分利用车道空间,绿灯起亮时,由于摩托车的启动速度比小汽车快,产生侧向膨胀效应,挤压小汽车行驶空间,从而使其速度减慢等现象,结合我国中小城市交叉口小汽车及摩托车的行驶特性,利用元胞自动机模型,建立信号交叉口小汽车与摩托车的混合交通模型.     

一种确定加速车道长度的概率统计模型

加速车道有利于次要道路上的车流平顺地汇入高速公路的车流 ,加速车道长度的确定是加速车道设计的核心内容。本文针对加速车道车流的运行特性 ,从概率统计角度研究了加速车道上车辆汇入高速公路车流的概率 ,并在此基础上得到了一种用于确定加速车道长度的实用模型     

优化交通信号配时 缓解城市交通拥堵

为了缓解城市交通拥堵,建立以延误时间最短、停车次数最少为目标函数的非线性优化模型,用遗传算法进行计算求解.计算结果表明,所得的优化信号配时,降低了平均延误时间,减少了平均停车次数,提高了交叉口通行能力.     

自动驾驶汽车在交通网络中的效能分析

研究了对于三车道的高速公路,自动驾驶汽车对混合交通流的通行能力及安全性的影响。引入变道欲望值、连续刹车率、空间速度方差和时间速度方差的概念,基于交通流元胞自动机模型,针对手动和自动驾驶2种汽车,建立了单向三车道的加减速和换道规则。选取6个评价参数,针对三车道模型,研究了随着自动驾驶汽车比例的增加,车道平均速度、平均速度的方差、交通密度、连续刹车率以及变道次数的变化情况。实验结果表明:在通行能力方面,当自动驾驶汽车的比例持续增加时,整个车道的平均速度、交通密度显著增加,从而大大提高了此交通网路中的通行能力;同时空间速度方差和时间速度方差会显著减少,说明整个交通流的平稳性增加了。在安全表现方面,当自动驾驶汽车的比例持续增加时,整个交通网路中的连续刹车率、变道次数先逐渐增加,然后逐渐减少,从而很好地刻画了安全性。最后分析了模型的优缺点,并指出了改进的方向。     

基于实际路网情境的配送车辆调度优化

在实际路网情境下结合车道数、车道宽度、路口信号灯设置等路网物理特性,构建了考虑综合交通阻抗的多车型车辆调度模型,提出了两阶段求解策略:第1阶段设计了改进A-star精确解算法用于计算客户时间距离矩阵;第2阶段针对实际路网的特征设计了混合模拟退火算法求解调度方案。以大连市某配送中心运营实例进行路网情境仿真试验,结果表明:改进A-star算法较改进Dijkstra算法具有更短的路径搜索时间;混合模拟退火算法求解结果较实际调度方案优化了13.1% 的综合成本;路网增流、区域拥堵和路段禁行三类路网情境均能对配送方案的车辆配置、路径选择、客户服务次序、作业时间和违约费用等5方面内容产生干扰,调度计划的制定需要详细考虑这些因素的变化。     

考虑禁左条件的用户均衡交通配流模型与算法

交叉口处左转车流是对车流量影响较大的一个流向,也是造成城市交通拥挤和交通事故的关键因素之一,所以越来越多的城市路网选择在交叉口禁止左转来保障主干路车流通畅.在禁左的情况下,出行者究竟如何选择出行路径,究竟应该在哪些交叉口采取禁左管理可以使网络总旅行时间最小?针对以上两个问题,将根据用户均衡(UE)原理,建立考虑交叉口禁左条件的交通配流双层规划模型.利用Frank-Wolfe算法,对下层模型中的出行车辆进行配流,并返回到上层模型计算网络总旅行时间,通过遗传算法确定设置禁左交叉口位置,使得网络总旅行时间达到最小.根据数值算例,展现合理设置禁左交叉口的位置,可以使得交通网络总费用减小.     

主路多车道无信号交叉口混合交通流的通行能力

Highway capacity is defined as maximum volume of traffic flow through the particular highway section under given traffic conditions,road conditions and so on.Highway construction and management is judged by capacity standard.The reasonable scale and time of highway construction,rational network structure and optimal management mode of highway network can be determined by analyzing the fitness between capacity and traffic volume.All over the world,highway capacity is studied to different extent in different country. Based on the gap acceptance theory,the mixed traffic flow composed of two representative vehicle types heavy and light vehicles is analyzed with probability theory.Capacity model of the minor mixed traffic flows crossing m major lanes,on which the traffic flows fix in with M3 distributed headway,on the unsignalized intersection is set up,and it is an extension of minor lane capacity theory for one vehicle-type and one major-lane traffic flow.     

A dynamical systems approach based on averaging to model the macroscopic flow of freeway traffic

The flow of traffic exhibits distinct characteristics under different conditions, reflecting the congestion during peak hours and relatively free motion during off-peak hours. This requires one to use different mathematical equations to describe the diverse traffic characteristics. Thus, the flow of traffic is best described by a hybrid system, namely different governing equations for the different regimes of response, and it is such a hybrid approach that is investigated in this paper. Existing models for the flow of traffic treat traffic as a continuum or employ techniques similar to those used in the kinetic theory of gases, neither of these approaches gainfully exploit the hybrid nature of the problem. Spurious two-way propagation of disturbances that are physically unacceptable are predicted by continuum models for the flow of traffic. The number of vehicles in a typical section of the highway does not justify its being modeled as a continuum. It is also important to recognize that the basic premises of kinetic theory are not appropriate for the flow of traffic (see [S. Darbha, K.R. Rajagopal, Limit of a collection of dynamical systems: an application to modeling the flow of traffic, Mathematical Models and Methods in Applied Sciences 12 (10) (2002) 1381–1399] for a rationale for the same). A model for the flow of traffic that does not treat traffic as a continuum or use notions from kinetic theory is developed here and corroborated with real-time data collected on US 183 in Austin, Texas. Predictions based on the hybrid system model seem to agree reasonably well with the data collected on US 183.     

Motorway traffic parameter estimation from mobile phone counts

In this paper a new method for real time estimation of vehicular flows and densities on motorways is proposed. This method is based on fusing traffic counts with mobile phone counts. The procedure used for the estimation of traffic flow parameters is based on the hypothesis that “instrumented” vehicles can be counted on specific motorway sections and traffic flow can be measured on entrance and exit ramps. The motorway is subdivided into cells, assuming that mobile phones entering and exiting every cell can be counted during the observation period. An estimate of “instrumented” vehicle concentration is obtained and propagated on the network in time and space. This allows one to estimate traffic flow parameters by sampling “instrumented” traffic flow parameters using a “concentration” (the ratio of the densities of instrumented vehicles to the density of overall traffic) propagation mechanism.     

Distributions for Gaps in Road Traffic

The importance of both counting and gap distributions in roadtraffic flow has been recognized for some years. One reasonfor their importance is that they are linked to three importantaspects of road traffic viz. flow, concentration and capacity.The flow-rate is the reciprocal of the mean time-gap betweenvehicles and concentration is the reciprocal of the mean distance-gapbetween vehicles. Capacity is, in one sense or another, themaximum flow, and is thus related to the minimum time-gap betweenvehicles. Another reason for the importance of these distributionsis that the distribution of vehicles on a road can be consideredas a succession of moving gaps and dealt with on that basis. The displaced exponential distribution has been known for sometime to be a reasonably good model for low-medium flow-ratesof up to about 800 vehicles per hour (v/h) in one lane, butit breaks down for higher flows. A number of alternatives tothe displaced exponential are considered in this paper. A substantial amount of data, collected in New Zealand, hasbeen used in fitting the distributions. There is no real evidenceto show that the displaced exponential can be improved uponmuch as a model, although overall the use of a mixed exponentialimproves the fit somewhat. However, all the alternative distributionsare easy to sample from, and can be used in simulation studies.     

Instability of cooperative adaptive cruise control traffic flow: A macroscopic approach

This paper proposes a macroscopic model to describe the operations of cooperative adaptive cruise control (CACC) traffic flow, which is an extension of adaptive cruise control (ACC) traffic flow. In CACC traffic flow a vehicle can exchange information with many preceding vehicles through wireless communication. Due to such communication the CACC vehicle can follow its leader at a closer distance than the ACC vehicle. The stability diagrams are constructed from the developed model based on the linear and nonlinear stability method for a certain model parameter set. It is found analytically that CACC vehicles enhance the stabilization of traffic flow with respect to both small and large perturbations compared to ACC vehicles. Numerical simulation is carried out to support our analytical findings. Based on the nonlinear stability analysis, we will show analytically and numerically that the CACC system better improves the dynamic equilibrium capacity over the ACC system. We have argued that in parallel to microscopic models for CACC traffic flow, the newly developed macroscopic will provide a complete insight into the dynamics of intelligent traffic flow.     

Analytical studies on the instabilities of heterogeneous intelligent traffic flow

It has been widely reported in literature that a small perturbation in traffic flow such as a sudden deceleration of a vehicle could lead to the formation of traffic jams without a clear bottleneck. These traffic jams are usually related to instabilities in traffic flow. The applications of intelligent traffic systems are a potential solution to reduce the amplitude or to eliminate the formation of such traffic instabilities. A lot of research has been conducted to theoretically study the effect of intelligent vehicles, for example adaptive cruise control vehicles, using either computer simulation or analytical method. However, most current analytical research has only applied to single class traffic flow. To this end, the main topic of this paper is to perform a linear stability analysis to find the stability threshold of heterogeneous traffic flow using microscopic models, particularly the effect of intelligent vehicles on heterogeneous (or multi-class) traffic flow instabilities. The analytical results will show how intelligent vehicle percentages affect the stability of multi-class traffic flow.     

Simulating vehicular traffic in a network using dynamic routing

We present a new numerical code which solves the Lighthill – Whitham model, the classic macroscopic model for vehicular traffic flow, in a network with multi-destinations. We use a high-resolution shock-capturing scheme with approximate Riemann solver to solve the partial differential equations of the Lighthill – Whitham theory. These schemes are very efficient, robust and moreover well adapted to simulations of traffic flows. We develop a theory of dynamic routing including a procedure for traffic flow assignment at junctions which reproduces the correct propagation of irregularities and ensures at the same time conservation of the number of vehicles.     

Dynamic system optimal performances of shared autonomous and human vehicle system for heterogeneous travellers

ABSTRACT

Autonomous vehicles (AV) can solve vehicle relocation problems faced by traditional one-way vehicle-sharing systems. This paper explores the deterministic time-dependent system optimum of mixed shared AVs (SAV) and human vehicles (SHV) system to provide the benchmark for the situation of mixed vehicle flows. In such a system, the system planner determines vehicle-traveller assignment and optimal vehicle routing in transportation networks to serve predetermined travel demand of heterogeneous travellers. Due to large number of vehicles involved, travel time is considered endogenous with congestion. Using link transmission model (LTM) as a traffic flow model, the deterministic time-dependent system optimum is formulated as linear programming (LP) model to minimize the comprehensive cost including travellers’ travel time cost, waiting time cost and empty vehicle repositioning time cost. Numerical examples are conducted to show system performances and model effectiveness.     

An optimization based approach for deployment of roadway incident response vehicles with reliability constraints

In recent years transportation agencies have introduced patrol based response programs to remove roadway incidents rapidly. With the evolution of technology incident detection and notification from remote traffic operation centers is possible and patrols to detect incidents are not necessary. Instead, the response units can be placed at various depots in urban areas and dispatched to incident sites upon notification. In this paper, we propose a reliability based mixed integer programming model to find best locations of incidence response depots and assign response vehicles to these depots so that incidents can be cleared efficiently at a minimum cost. The approach is unique as it considers fixed and variable costs of vehicles and depots, occurrences of major and minor incidents, and reliability of response service in the same model. Numerical results are generated for an example problem and sensitivity analysis is conducted to explore the relationships between parameters of the problem.     

Discrete time dynamic traffic assignment models and solution algorithm for managed lanes

“Managed” lanes of highways usually refer to lanes that are not open to all types of vehicles, such as “High Occupancy Vehicles” (HOV) lanes and “High Occupancy Toll” (HOT) lanes, etc. The HOV lanes of highways are reserved only for vehicles with a driver and one or more passengers. Whereas, HOT lanes allow all vehicles but require tolls from the vehicles with no passenger except the driver. In this paper, we present a discrete-time traffic assignment system optimum model to predict the optimal traffic flows on managed lanes at various times in the entire planning horizon. This model minimizes the overall delay (travel time) and belongs to the class of dynamic traffic assignment (DTA) problems. When applied to general networks, DTA problems can be large and difficult to solve, but the problem is manageable when it is applied to a network with managed lanes. In particular, the DTA model in this paper for managed lanes is reduced to a mixed integer program for which several efficient heuristic algorithms exist. This paper also discusses the special properties of the discrete-time DTA model, based upon which a heuristic algorithm is proposed. Numerical results show that this algorithm is efficient for many cases of the managed lane problems.