基于模糊控制的双交叉口相序可变信号配时方法

为优化交叉口信号配时,降低车辆平均延误,提出了一种相序可变的干线双交叉口模糊协调控制方法。提出的模糊协调控制方法包括候选相位选择控制器、绿灯相位观测控制器、相位切换控制器和两个交叉口协调控制模块共五个控制模块。相序可变的干线双交叉口模糊协调控制方法基于对当前上下游交叉口交通紧迫程度的判断,以及对未来交通状态演变的估计,采用相序可变的模糊控制方法实时、动态调整交叉口信号配时方案。利用MATLAB对VISSIM二次开发搭建仿真平台,对所提出的模糊控制方法进行了验证。结果表明,所提出的模糊控制方法在单交叉口和双交叉口两个控制层面均优于传统定时控制方法,可以显著降低车辆平均延误,提高交叉口通行效率。     

多目标优化的公交被动优先信号配时模型

从公交信号优先的原则出发,考虑公交到达率的不确定性对周期长度、绿灯时间等合理调整,针对多路公交车共用同一公交专用道情况,提出以人均总延误最小为目标,分别以绿灯时间差模型和Webster最佳周期模型为信号配时计算模型计算交叉口信号配时参数,选取两者中造成人均延误最小的结果作为最终信号配时方案的计算方法。另外,除采用原有Webster最佳周期计算模型进行信号配时计算,还结合随机机会约束规划方法提出了以各相位绿灯时间与所需绿灯时间差绝对值之和最小为目标的绿灯时间差模型,通过随机模拟与微粒群算法的结合,给出了求解随机机会约束规划的新算法。以设有公交专用道的两相位信号交叉口为例设计算例,结果证明,公交车到达率的随机变化特性对于其所在交叉口信号配时参数的设置有明显影响,验证了公交被动优先对交叉口信号配时参数动态调整的有效性。本文模型根据被动优先中调整了周期时长及绿信比策略确定更优信号配时方案,相较仅以Webster最佳周期模型为依据计算人均延误的传统模型,最小人均延误模型平均降低了8. 12%的人均延误,证明了最小人均延误模型的有效性。说明最小人均延误模型可更好描述公交车到达率的波动性,降低对社会车辆负面影响,达到减少人均延误,提高交叉口通行效率的目的。     

基于信号配时的路网交通流分析及优化研究

文章以南宁市四条主干道上七个交叉口组成的闭合路网为优化对象,通过交叉口交通流量分析,利用R.Kimber饱和流量计算法和F.Webster交叉口信号配时理论,初步拟定车辆延误最小的信号配时方案,然后使用遗传算法优化配时方案,最后利用VISSIM进行交通仿真,验算服务水平指标的变化,验证该优化方案。     

韦伯斯特算法在不同流量下的排队延误优化效果

韦伯斯特算法是一种优化信号交叉口配时的算法,该算法可以降低交叉口的车辆延误,从而达到缓解交通压力和交通拥堵的目的。若某交叉口车流量较低,利用韦伯斯特算法进行信号配时优化后,该交叉口排队延误改变不大,考虑行政成本,应用价值不高。因此,基于VISSIM仿真软件,以拉萨市江苏路与藏大西路交叉口为例,在该交叉口原信号配时的基础上,利用韦伯斯特算法优化信号配时,通过对比,研究在不同交通流量的情况下,韦伯斯特算法降低排队延误的效果。     

基于VISSIM仿真的交叉口信号配时优化分析

随着我国城市化发展和车辆保有量的增加,城市交通负荷也随之急剧增长,现有交通信号配时方案与交通需求不能很好地匹配。为了缓解交通延误、提高道路通行效率,文章以石河子市北五路—东二路交叉口为例,利用交通仿真软件VISSIM对该交叉口建立微观道路交通流模型并进行仿真优化分析。结果表明,优化后交叉口排队长度、车辆延误等指标明显降低,能够有效缓解交通拥堵、提高安全性。     

基于公交专用进口道的交叉口信号配时优化设计研究

本文研究设置公交专用进口道的城市交叉口信号配时,综合考虑社会车辆的运行,实现信号配时的公交优先与人均延误最小化。本文运用延误三角形及其相关理论建立延误模型,推导出人均延误函数,为公交优先单点定时控制提供了优化算法。同时本文利用VisualC仿真模型与改进算法对城市具体交叉口信号最佳周期及有效绿灯时间进行优化设计。     

左转过饱和考虑相位均衡的信号配时优化研究

提出在保障交叉口总体效益最优和考虑驾驶员对红灯时长容忍度的前提下，设置逆向可变车道达到降低交叉口延误和提升通行能力。以各相位有效绿灯时长为优化变量，建立交叉口信号配时优化模型，并采取MOEA/D算法进行求解，结合设计案例，利用VISSIM7.0仿真软件在单位时长下对比优化前后各相位车均延误、车均排队长度和通行能力。求解的有效绿灯时长为19s、16s、15s、16s，有效验证了均衡相位绿灯时长的假设；仿真结果表明，车均延误平均下降26.15%；车均排队长度平均下降76.84%；通行能力平均提升约11.39%。提出的方法在降低交叉口延误，提升通行能力同时，能够均衡分配各相位有效绿灯时长，进而降低驾驶员等待红灯的焦虑感。     

预信号在次右侧型公交专用道中的应用研究

为了减少次右侧型公交专用道的公交延误和乘客人均延误,针对不饱和进口道建立了一种基于公交候驶区的公交预信号控制方法。分析了公交预信号的工作原理,研究了车辆到达率、信号配时参数、候驶区长度之间的关系,提出了预信号配置的方法。通过车辆到达-离开曲线来研究车辆延误与信号配时的关系,分析公交预信号设置前后公交车辆与社会车辆的延误变化。并对给定条件的交叉口进口道设置预信号,结果表明公交车的平均延误减少57.2%,社会车辆平均延误增加35.6%,所有乘客平均延误减少25.7%。     

城市道路交叉口信号配时质量管理研究

为了提高城市交通管理水平,通过对国内外学者的研究成果进行梳理和分析,并借鉴相关技术和方法,结合对影响信号配时质量相关因素的分析,采用模糊综合评判法对城市道路交叉口信号配时质量管理进行研究,提出以最小化交通延误为目标的、评判指标体系和层次分析法（AHP）相结合的道路交叉口信号配时质量评判方法,利用MATLAB/Simulink工具箱建立相应模型并利用其求解出不同时段及相邻两个道路交叉口间的信号配时质量值,最后将其与模糊综合评判法得到结果和计算结果进行比较,验证该方法所得到结果。     

黄岛区长江中路与庐山路信号交叉口优化设计

文章针对黄岛区长江中路和庐山路交叉口处交通流运行特性,采用多渠化多相位优化方法制定了三个不同的交叉口优化设计方案,比选出了平均信控延误时间最小的优化方案,并运用Vissim软件对优化设计结果进行评测,增加了优化结果的可行性及科学性,为类似平面信号交叉口的优化设计提供思路。     

Signalized intersections with variable flow rates: I analysis and simulation

One of the most common measures of signalized intersection operation is the amount of delay a vehicle incurs while passing through the intersection. Traditional models for estimating vehicle delay at intersections generally assume fixed signal timing and uniform arrival rates for vehicles approaching the intersection. One would expect that highly variable arrival rates would result in much longer delays than uniform arrival rates of the same average magnitude. Furthermore, one might expect that signal timing that is adjusted according to traffic volume would result in lower delay signal when variations in flow warrant such adjustable timing. This paper attempts to test several hypotheses concerning the effects of variable traffic arrival rates and adjusted signal timing through the use of simulation. The simulation results corroborate the hypothesis concerning the effect of varying arrival rates. As the variance of the arrival rate over time increases, the average delay per vehicle also increases. Signal timing adjustments based on traffic appear to decrease delay when flow rates vary greatly. As flow variations stabilize, the benefits of signal adjustments tend to diminish.     

Multi-modal traffic signal control with priority,signal actuation and coordination

Both coordinated-actuated signal control systems and signal priority control systems have been widely deployed for the last few decades. However, these two control systems are often conflicting with each due to different control objectives. This paper aims to address the conflicting issues between actuated-coordination and multi-modal priority control. Enabled by vehicle-to-infrastructure (v2i) communication in Connected Vehicle Systems, priority eligible vehicles, such as emergency vehicles, transit buses, commercial trucks, and pedestrians are able to send request for priority messages to a traffic signal controller when approaching a signalized intersection. It is likely that multiple vehicles and pedestrians will send requests such that there may be multiple active requests at the same time. A request-based mixed-integer linear program (MILP) is formulated that explicitly accommodate multiple priority requests from different modes of vehicles and pedestrians while simultaneously considering coordination and vehicle actuation. Signal coordination is achieved by integrating virtual coordination requests for priority in the formulation. A penalty is added to the objective function when the signal coordination is not fulfilled. This “soft” signal coordination allows the signal plan to adjust itself to serve multiple priority requests that may be from different modes. The priority-optimal signal timing is responsive to real-time actuations of non-priority demand by allowing phases to extend and gap out using traditional vehicle actuation logic. The proposed control method is compared with state-of-practice transit signal priority (TSP) both under the optimized signal timing plans using microscopic traffic simulation. The simulation experiments show that the proposed control model is able to reduce average bus delay, average pedestrian delay, and average passenger car delay, especially for highly congested condition with a high frequency of transit vehicle priority requests.     

Model based urban traffic control,part II: Coordinated model predictive controllers

The present paper describes how to use coordination between neighbouring intersections in order to improve the performance of urban traffic controllers. Both the local MPC (LMPC) introduced in the companion paper (Hao et al., 2018) and the coordinated MPC (CMPC) introduced in this paper use the urban cell transmission model (UCTM) (Hao et al., 2018) in order to predict the average delay of vehicles in the upstream links of each intersection, for different scenarios of switching times of the traffic lights at that intersection. The feedback controller selects the next switching times of the traffic light corresponding to the shortest predicted average delay. While the local MPC (Hao et al., 2018) only uses local measurements of traffic in the links connected to the intersection in comparing the performance of different scenarios, the CMPC approach improves the accuracy of the performance predictions by allowing a control agent to exchange information about planned switching times with control agents at all neighbouring intersections. Compared to local MPC the offline information on average flow rates from neighbouring intersections is replaced in coordinated MPC by additional online information on when the neighbouring intersections plan to send vehicles to the intersection under control. To achieve good coordination planned switching times should not change too often, hence a cost for changing planned schedules from one decision time to the next decision time is added to the cost function. In order to improve the stability properties of CMPC a prediction of the sum of squared queue sizes is used whenever some downstream queues of an intersection become too long. Only scenarios that decrease this sum of squares of local queues are considered for possible implementation. This stabilization criterion is shown experimentally to further improve the performance of our controller. In particular it leads to a significant reduction of the queues that build up at the edges of the traffic region under control. We compare via simulation the average delay of vehicles travelling on a simple 4 by 4 Manhattan grid, for traffic lights with pre-timed control, traffic lights using the local MPC controller (Hao et al., 2018), and coordinated MPC (with and without the stabilizing condition). These simulations show that the proposed CMPC achieves a significant reduction in delay for different traffic conditions in comparison to these other strategies.     

The optimization of lane assignment and signal timing at the tandem intersection with pre‐signal

This paper presents an integrated model for optimizing lane assignment and signal timing at tandem intersection, which is introduced recently. The pre‐signal is utilized in the tandem intersection to reorganize the traffic flow; hence, the vehicles, regardless of whether left‐turns or through vehicles, can be discharged in all the lanes. However, the previous work does not consider the extra traffic disruption and the associated delay caused by the additional pre‐signal. In the paper, the extra delay aroused by the coordination is incorporated in a lane assignment and signal timing optimization model, and the problem is converted into a mixed‐integer non‐linear programming. A feasible directions method is hence introduced to solve the mixed‐integer non‐linear programming. The result of the optimization shows that the performance of the tandem intersection is improved and the average delay is minimized. The comparison between the tandem and the conventional configuration is presented, and the results verify that the former shows better performance than the latter. In addition, the optimal sequence corresponding to the turning proportion and the optimal lane assignment at the upstream approach of the pre‐signal are presented. Furthermore, if the number of lanes is equal in all arms, the paper proves that the average delay will be reduced if lane assignment is proportional to the turning proportion and the vehicles with low proportion are discharged in advance. Copyright © 2013 John Wiley & Sons, Ltd.     

Multi-stage stochastic program to optimize signal timings under coordinated adaptive control

In the wake of traffic congestion at intersections, it is imperative to shorten delays in corridors with stochastic arrivals. Coordinated adaptive control can adjust green time flexibly to deal with a stochastic demand, while maintaining a minimum through-band for coordinated intersections. In this paper, a multi-stage stochastic program based on phase clearance reliability (PCR) is proposed to optimize base timing plans and green split adjustments of coordinated intersections under adaptive control. The objective is to minimize the expected intersection delay and overflow of the coordinated approach. The overflow or oversaturated effect is explicitly addressed in the delay calculation, which greatly increases the modeling complexity due to the interaction of overflow delays across cycles. The notion of PCR separates the otherwise related green time settings of consecutive cycles into a number of stages, in which the base timing plan and actual timing plan in different cycles are handled sequentially. We then develop a PCR based solution algorithm to solve the problem, and apply the model and the solution algorithm to actual intersections in Shanghai to investigate its performance as compared with Allsop’s method and Webster’s method. Preliminary results show the PCR-based method can significantly shorten delays and almost eliminates overflow for the coordinated approaches, with acceptable delay increases of the non-coordinated approaches. A comparison between the proposed coordinated adaptive logic and a coordinated actuated logic is also conducted in the case study to show the advantages and disadvantages.     

Methods to reduce dimensionality and identify candidate solutions in multi-objective signal timing problems

Adjusting traffic signal timings is a practical way for agencies to manage urban traffic without the need for significant infrastructure investments. Signal timings are generally selected to minimize the total control delay vehicles experience at an intersection, particularly when the intersection is isolated or undersaturated. However, in practice, there are many other potential objectives that might be considered in signal timing design, including: total passenger delay, pedestrian delays, delay inequity among competing movements, total number of stopping maneuvers, among others. These objectives do not tend to share the same relationships with signal timing plans and some of these objectives may be in direct conflict. The research proposes the use of a new multi-objective optimization (MOO) visualization technique—the mosaic plot—to easily quantify and identify significant tradeoffs between competing objectives using the set of Pareto optimal solutions that are normally provided by MOO algorithms. Using this tool, methods are also proposed to identify and remove potentially redundant or unnecessary objectives that do not have any significant tradeoffs with others in an effort to reduce problem dimensionality. Since MOO procedures will still be needed if more than one objective remains and MOO algorithms generally provide a set of candidate solutions instead of a single final solution, two methods are proposed to rank the set of Pareto optimal solutions based on how well they balance between the competing objectives to provide a final recommendation. These methods rely on converting the objectives to dimensionless values based on the optimal value for each specific objectives, which allows for direct comparison between and weighting of each. The proposed methods are demonstrated using a simple numerical example of an undersaturated intersection where all objectives can be analytically obtained. However, they can be readily applied to other signal timing problems where objectives can be obtained using simulation outputs to help identify the signal timing plan that provides the most reasonable tradeoff between competing objectives.     

Interactions between driver information,route choice,and optimal signal timing on a simple network

The interaction between driver information, route choice, and optimal traffic signal settings was investigated using a simple two-route system with a single “T” intersection and a fixed O-D demand. The logit model and the method of successive averages (MSA) were used to calculate the route choice probabilities and the stochastic equilibrium assignment. Given an assignment, signal settings which minimized average intersection delay were calculated; flow reassignment and new optimal signal settings were then obtained and this iterative process continued until convergence. The calculations were performed either directly in a combined assignment/signal optimization model or in stages using the output flows of an assignment model as inputs to TRANSYT-7F and iterating between the two models. Results show that a unique joint signal timing/assignment equilibrium is reached in all cases provided that a certain precision in drivers' perceptions is not reached. If driver information increases to this precision (bifurcation point) and beyond, results show clearly that the unique joint signal timing/assignment equilibrium no longer exists. In fact, three joint equilibria points exist after the bifurcation point. Two of these points are stable and one is not. It was found that the system yields the lowest total intersection delay when the joint equilibrium is such that all traffic and hence the major part of green time is assigned to only one of the two routes. Although this may not be feasible to implement in practice, the results indicate clearly for this simple example that there is a trade-off between a system with minimum total delay but no unique joint signal-settings/assignment equilibrium (achieved when drivers have nearly perfect information about the system) and a system with a unique joint equilibrium but with higher total delay (achieved when drivers have reasonably good but somewhat limited information). In most cases the second system seems appropriate for a number of practical reasons.     

Dynamic network traffic control

This study developed a dynamic traffic control formulation designated as dynamic intersection signal control optimization (DISCO). Traffic in DISCO is modeled after the cell-transmission model (CTM), which is a convergent numerical approximation to the hydrodynamic model of traffic flow. It considers the entire fundamental diagram and captures traffic phenomena such as shockwaves and queue dynamics. As a dynamic approach, the formulation derives dynamic timing plans for time-variant traffic patterns. We solved DISCO based on a genetic algorithm (GA) approach and applied it to a traffic black spot in Hong Kong that is notorious for severe congestion. For performance comparisons, we also applied TRANSYT to the same scenarios. The Results showed that DISCO outperformed TRANSYT for all the scenarios tested especially in congested traffic. For the congested scenarios, DISCO could reduce delay by as much as 33% when compared with TRANSYT. Even for the uncongested scenarios, DISCO’s delays could be smaller by as much as 23%.     

Development of a delay model for unsignalized intersections applicable to traffic assignment

Abstract

This paper develops a model for estimating unsignalized intersection delays which can be applied to traffic assignment (TA) models. Current unsignalized intersection delay models have been developed mostly for operational purposes, and demand detailed geometric data and complicated procedures to estimate delay. These difficulties result in unsignalized intersection delays being ignored or assumed as a constant in TA models.

Video and vehicle license plate number recognition methods are used to collect traffic volume data and to measure delays during peak and off-peak traffic periods at four unsignalized intersections in the city of Tehran, Iran. Data on geometric design elements are measured through field surveys. An empirical approach is used to develop a delay model as a function of influencing factors based on 5- and 15-min time intervals. The proposed model estimates delays on each approach based on total traffic volumes, rights-of-way of the subject approach and the intersection friction factor. The effect of conflicting traffic flows is considered implicitly by using the intersection friction factor. As a result, the developed delay model guarantees the convergence of TA solution methods.

A comparison between delay models performed using different time intervals shows that the coefficients of determination, R ², increases from 43.2% to 63.1% as the time interval increases from 5- to 15-min. The US Highway Capacity Manual (HCM) delay model (which is widely used in Iran) is validated using the field data and it is found that it overestimates delay, especially in the high delay ranges.     

Using connected vehicle technology to improve the efficiency of intersections

Information from connected vehicles, such as the position and speed of individual vehicles, can be used to optimize traffic operations at an intersection. This paper proposes such an algorithm for two one-way-streets assuming that only a certain percentage of cars are equipped with this technology. The algorithm enumerates different sequences of cars discharging from the intersection to minimize the objective function. Benefits of platooning (multiple cars consecutively discharging from a queue) and signal flexibility (adaptability to demand) are also considered. The goal is to gain insights about the value (in terms of delay savings) of using connected vehicle technology for intersection control.Simulations are conducted for different total demand values and demand ratios to understand the effects of changing the minimum green time at the signal and the penetration rate of connected cars. Using autonomous vehicle control systems, the signal could rapidly change the direction of priority without relying on the reaction of drivers. However, without this technology a minimum green time is necessary. The results of the simulations show that a minimum green time increases the delay only for the low and balanced demand scenarios. Therefore, the value of using cars with autonomous vehicle control can only be seen at intersections with this kind of demand patterns, and could result in up to 7% decrease in delay. On the other hand, using information from connected vehicles to better adapt the traffic signal has proven to be indeed very valuable. Increases in the penetration rate from 0% up to 60% can significantly reduce the average delay (in low demand scenarios a decrease in delay of up to 60% can be observed). That being said, after a penetration rate of 60%, while the delays continue to decrease, the rate of reduction decreases and the marginal value of information from communication technologies diminishes. Overall, it is observed that connected vehicle technology could significantly improve the operation of traffic at signalized intersections, at least under the proposed algorithm.