技术领域technical field
本发明涉及智能交通系统的技术领域，特别涉及一种考虑车道切换影响的交叉口可变车道系统优化方法。The invention relates to the technical field of intelligent traffic systems, in particular to an optimization method for a variable lane system at an intersection considering the influence of lane switching.
背景技术Background technique
近年来,随着城市及经济的快速发展，许多城市都具有职住分离的空间特性，通勤早晚高峰导致交叉口常发性出现交通流向分布不均衡与变化。上述现象加剧了交叉口交通供给与需求的失衡问题，严重影响城市交通运行通畅。为了充分利用交叉口的时间与空间资源提高交叉口的运行效率，近年来我国诸多大城市建设了交叉口可变导向车道系统。可变导向车道可以根据不同转向交通流量的大小改变指示方向的车道。In recent years, with the rapid development of cities and economies, many cities have the spatial characteristics of separation of occupations and residences. The morning and evening rush hours of commuting often lead to unbalanced distribution and changes in traffic flow at intersections. The above phenomena exacerbated the imbalance between supply and demand of traffic at intersections, seriously affecting the smooth operation of urban traffic. In order to make full use of the time and space resources of intersections and improve the operational efficiency of intersections, many large cities in my country have built intersection variable directional lane systems in recent years. The variable guide lane can change the lane indicating the direction according to the size of different steering traffic flows.
虽然目前可变车道技术一定程度上缓解交通压力，但大多仍采用较传统的人工手段来控制可变车道，其效益是有限的。就当前可变车道技术现状而言，具体存在以下不足：Although the current variable lane technology relieves traffic pressure to a certain extent, most of them still use traditional manual means to control the variable lane, and its benefits are limited. As far as the current status of variable lane technology is concerned, there are the following deficiencies:
1、现实中，由于车道清空、驾驶特性等原因，可变车道切换过程会对交通流产生一定负面影响。而在现有可变车道优化控制算法层面，大多忽略了这一点，可能生成非最优方案；1. In reality, due to reasons such as lane clearing and driving characteristics, the variable lane switching process will have a certain negative impact on traffic flow. However, at the level of existing variable lane optimization control algorithms, this point is mostly ignored, and non-optimal solutions may be generated;
2、传统的方案优化方法中，可变车道方案选择和切换时机大多聚焦于相邻子时段，以阈值判断为主，频繁切换车道功能可能带来安全隐患。同时未能针对全时空尺度的全样本条件建立交通系统模型，无法优化得出系统最优的分时段可变车道方案。2. In the traditional scheme optimization method, the selection of variable lane schemes and the timing of switching are mostly focused on adjacent sub-periods, and the judgment is mainly based on thresholds. Frequent lane switching functions may bring safety hazards. At the same time, the traffic system model cannot be established for the full sample conditions of the full time and space scale, and the optimal time-based variable lane scheme for the system cannot be optimized.
发明内容Contents of the invention
针对现有技术中存在的不足之处，本发明的目的是提供一种考虑车道切换影响的交叉口可变车道系统优化方法，克服不考虑切换成本的可变车道频繁切换的弊端，同时在整个优化全时段协同优化切换次数、切换时机和信号配时，减少了频繁切换带来的安全风险，并提高全时段交叉口交通效率。为了实现本发明的上述目的和其他优点，提供了一种考虑车道切换影响的交叉口可变车道系统优化方法，包括：Aiming at the deficiencies in the prior art, the purpose of the present invention is to provide a method for optimizing the variable lane system at intersections considering the impact of lane switching, to overcome the disadvantages of frequent switching of variable lanes without considering the cost of switching, and to Optimizing the number of handovers, handover timing and signal timing through collaborative optimization of the whole time, reducing the safety risks caused by frequent handovers, and improving the traffic efficiency of the full-time intersection. In order to achieve the above-mentioned purpose and other advantages of the present invention, a kind of intersection variable lane system optimization method considering the impact of lane switching is provided, including:
S1、初始化可变车道控制系统各交通参数；S1. Initialize the traffic parameters of the variable lane control system;
S2、根据优化时间步长完成子时段划分；S2. Complete sub-period division according to the optimized time step;
S3、穷举所有车道切换次数、切换时机、车道功能和信号配时组合方案，形成车道切换子时段矩阵与车道功能信号配时矩阵；S3. Exhaustively enumerate all lane switching times, switching timing, lane functions and signal timing combination schemes to form a lane switching sub-period matrix and a lane function signal timing matrix;
S4、针对每个组合方案，将子时段进一步划分为车道切换子时段和信号切换子时段，并分别计算两类子时段延误；S4. For each combination scheme, the sub-period is further divided into a lane switching sub-period and a signal switching sub-period, and the delays of the two sub-periods are calculated respectively;
S5、针对每个组合方案，累加所有子时段延误得到总延误，选择总延误最小值即为全时段最优方案。S5. For each combination plan, add up the delays of all sub-periods to obtain the total delay, and select the minimum value of the total delay as the optimal solution for the whole period.
优选的，步骤S1中的交通参数包括交叉口几何条件、优化时段区间、优化时间步长、交通流量、信号周期、最小绿灯时间、车道基础饱和流率、清空时间、车道利用率、可变车道饱和车头时距。Preferably, the traffic parameters in step S1 include intersection geometry, optimal time interval, optimal time step, traffic flow, signal cycle, minimum green light time, lane base saturation flow rate, clearing time, lane utilization, variable lane Saturated headway.
优选的，设置一个优化区间，所述优化区间大于信号周期，且选择时间步长Δt将优化区间划分为若干子时段，输入子时段交通需求数据，利用模型得到各个子时段最优的时空资源方案。Preferably, an optimization interval is set, the optimization interval is greater than the signal period, and the time step Δt is selected to divide the optimization interval into several sub-periods, input the traffic demand data of the sub-periods, and use the model to obtain the optimal space-time resource scheme for each sub-period .
优选的，车道基础饱和流率为单位时间内某一车道断面所能通过的最大车辆数；车道利用率为某一方向上交通流在不同车道上的分布状况，衡量了车流分布的均衡程度；车道利用率用于修正基于车道基础饱和流率计算出的理论通行能力。Preferably, the lane base saturation flow rate is the maximum number of vehicles that can pass through a certain lane section per unit time; the lane utilization rate is the distribution of traffic flow on different lanes in a certain direction, which measures the balance of traffic flow distribution; Utilization is used to correct the theoretical capacity calculated based on the lane base saturation flow rate.
优选的，将优化全时段[Ts，Te]离散化，Δt为时间步长，共计K个子时段，子时段划分集合T0为：Preferably, the optimized whole period [Ts , Te ] is discretized, Δt is the time step, and there are K sub-periods in total, and the sub-period division set T0 is:
T0＝{Ts，1，2…t，t+Δt…Te}，t∈{1，2，…K}#(1)。T0 ={Ts , 1, 2...t, t+Δt...Te }, t∈{1, 2,...K}#(1).
优选的，步骤S3中切换次数和切换时机：枚举优化时段内车道功能切换次数M和车道切换子时段，形成车道切换子时段矩阵为：T＝[t1，t2…tM]；Preferably, switching times and switching timings in step S3: enumerate lane function switching times M and lane switching sub-periods within the optimization period, and form a lane switching sub-period matrix as: T=[t1 , t2 ...tM ];
车道功能和信号配时：Lane functions and signal timing:
枚举t子时段交叉口i进口道采用的车道功能和信号配时方案矩阵包括使用车道功能p的车辆数/>和不同相位绿信比/>Enumerate the lane function and signal timing scheme matrix adopted by the intersection i entrance road in sub-period t Include the number of vehicles using the lane function p /> and different phase green signal ratio/>
本发明与现有技术相比，其有益效果是：The present invention compares with prior art, and its beneficial effect is:
(1)精细刻画车道切换过程对交通效率的负面影响，利用可变车道饱和车头时距和车道利用率定量计算切换影响，考虑到优化模型中，将优化时段进一步划分为车道切换子时段和信号切换子时段，生成更符合工程实践的可变车道方案。(1) Finely describe the negative impact of the lane switching process on traffic efficiency, use the variable lane saturation headway and lane utilization to quantitatively calculate the switching impact, and consider the optimization model, further divide the optimization period into lane switching sub-periods and signal Switch sub-periods to generate a variable lane scheme that is more in line with engineering practice.
(2)提出方法实现了交通波动情况下可变车道功能、信号配时、切换次数和切换时机的协同优化，在优化全时段进行综合决策，可以提出适用于不同时段的方案，可以适应变化的交通需求。(2) The proposed method realizes the collaborative optimization of variable lane functions, signal timing, switching times, and switching timing under traffic fluctuations. Comprehensive decision-making can be made during the entire period of optimization, and schemes suitable for different periods can be proposed, which can adapt to changes. transportation needs.
(3)通过算法流程的设计，摆脱人工能力的局限性，高效地输出最佳可变车道设置方案。相比以往技术，减少可变车道频繁切换带来的安全隐患，同时提高交叉口通行效率。(3) Through the design of the algorithm process, get rid of the limitations of manual capabilities, and efficiently output the best variable lane setting scheme. Compared with the previous technology, it reduces the potential safety hazards caused by frequent switching of variable lanes, and at the same time improves the efficiency of intersection traffic.
(4)相对同向固定车道(fixed lane，FIX)，可变车道在切换期间平均饱和车头时距和车道利用率存在显著差异。其次，针对差异提出一种车道功能与信号配时协同优化方法，考虑车道切换产生的负效用，切换次数和切换时机在优化区间进行综合决策，以求达到进口道总延误最低。最后，以真实数据为基础设置不同交通需求场景，将考虑切换影响的优化方法和基于阈值判断方法在相同场景下进行试验，对比两种方案的交通效率和交通安全指标，验证了该模型的有效性。(4) Compared with fixed lanes (FIX) in the same direction, there are significant differences in the average saturated headway and lane utilization of variable lanes during switching. Secondly, a collaborative optimization method for lane function and signal timing is proposed in view of the difference, considering the negative effects of lane switching, the number of switching and switching timing are comprehensively decided in the optimization interval, in order to achieve the lowest total delay of the entrance lane. Finally, different traffic demand scenarios are set based on real data, and the optimization method considering the handover effect and the threshold-based judgment method are tested in the same scenario, and the traffic efficiency and traffic safety indicators of the two schemes are compared to verify the effectiveness of the model. sex.
附图说明Description of drawings
图1为根据本发明的考虑车道切换影响的交叉口可变车道系统优化方法的研究示意场景图；Fig. 1 is a research schematic scene diagram of the variable lane system optimization method at an intersection considering the influence of lane switching according to the present invention;
图2为根据本发明的考虑车道切换影响的交叉口可变车道系统优化方法的交叉口场景及系统界面图；Fig. 2 is an intersection scene and a system interface diagram of an intersection variable lane system optimization method considering the impact of lane switching according to the present invention;
图3为根据本发明的考虑车道切换影响的交叉口可变车道系统优化方法的交叉口统计数据图；Fig. 3 is the intersection statistical data diagram of the variable lane system optimization method of the intersection considering the impact of lane switching according to the present invention;
图4为根据本发明的考虑车道切换影响的交叉口可变车道系统优化方法的可变车道切换流程图；Fig. 4 is the variable lane switching flow chart of the intersection variable lane system optimization method considering the influence of lane switching according to the present invention;
图5为根据本发明的考虑车道切换影响的交叉口可变车道系统优化方法的考虑切换影响可变车道系统优化流程图；Fig. 5 is the flow chart of considering the switching influence variable lane system optimization method of the intersection variable lane system optimization method considering the influence of lane switching according to the present invention;
图6为根据本发明的考虑车道切换影响的交叉口可变车道系统优化方法的交叉口几何条件和流量图；Fig. 6 is the intersection geometrical condition and the traffic diagram of the variable lane system optimization method of the intersection considering the impact of lane switching according to the present invention;
图7为根据本发明的考虑车道切换影响的交叉口可变车道系统优化方法的优化结果图；Fig. 7 is the optimization result diagram of the variable lane system optimization method at the intersection considering the impact of lane switching according to the present invention;
图8为根据本发明的考虑车道切换影响的交叉口可变车道系统优化方法的实施例1的数值分析结果图。Fig. 8 is a numerical analysis result diagram of Embodiment 1 of the method for optimizing the variable lane system at an intersection considering the influence of lane switching according to the present invention.
具体实施方式Detailed ways
下面将结合本发明实施例中的附图，对本发明实施例中的技术方案进行清楚、完整地描述，显然，所描述的实施例仅仅是本发明一部分实施例，而不是全部的实施例。基于本发明中的实施例，本领域普通技术人员在没有做出创造性劳动前提下所获得的所有其他实施例，都属于本发明保护的范围。The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only some, not all, embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without making creative efforts belong to the protection scope of the present invention.
参照图1-8，一种考虑车道切换影响的交叉口可变车道系统优化方法，包括：S1、初始化可变车道控制系统各交通参数；Referring to Figures 1-8, a method for optimizing a variable lane system at an intersection considering the influence of lane switching, including: S1, initializing each traffic parameter of the variable lane control system;
S2、根据优化时间步长完成子时段划分；S2. Complete sub-period division according to the optimized time step;
S3、穷举所有车道切换次数、切换时机、车道功能和信号配时组合方案，形成车道切换子时段矩阵与车道功能信号配时矩阵；S3. Exhaustively enumerate all lane switching times, switching timing, lane functions and signal timing combination schemes to form a lane switching sub-period matrix and a lane function signal timing matrix;
S4、针对每个组合方案，将子时段进一步划分为车道切换子时段和信号切换子时段，并分别计算两类子时段延误；S4. For each combination scheme, the sub-period is further divided into a lane switching sub-period and a signal switching sub-period, and the delays of the two sub-periods are calculated respectively;
S5、针对每个组合方案，累加所有子时段延误得到总延误，选择总延误最小值即为全时段最优方案。S5. For each combination plan, add up the delays of all sub-periods to obtain the total delay, and select the minimum value of the total delay as the optimal solution for the whole period.
进一步的，步骤S1中的交通参数包括交叉口几何条件、优化时段区间、优化时间步长、交通流量、信号周期、最小绿灯时间、车道基础饱和流率、清空时间、车道利用率、可变车道饱和车头时距。车道基础饱和流率为单位时间内某一车道断面所能通过的最大车辆数；车道利用率为某一方向上交通流在不同车道上的分布状况，衡量了车流分布的均衡程度；车道利用率用于修正基于车道基础饱和流率计算出的理论通行能力，调查交叉口每次进行方案过渡时，研究小组均统计7个信号周期的数据。车辆车头时距和可变车道及同向相邻车道驶入车辆数统计结果见图2。Further, the traffic parameters in step S1 include intersection geometry, optimal time interval, optimal time step, traffic flow, signal period, minimum green light time, lane base saturated flow rate, clearing time, lane utilization, variable lane Saturated headway. The lane base saturation flow rate is the maximum number of vehicles that can pass through a certain lane section per unit time; the lane utilization rate is the distribution of traffic flow in different lanes in a certain direction, which measures the balance of traffic flow distribution; the lane utilization rate is expressed as In order to revise the theoretical traffic capacity calculated based on the basic saturated flow rate of the lane, the research team counted the data of 7 signal periods every time the transition of the scheme was carried out at the surveyed intersection. The statistical results of vehicle headway, variable lanes and the number of vehicles entering adjacent lanes in the same direction are shown in Figure 2.
1)车头时距1) Headway
图3d中可变车道和固定车道车头时距样本均值分别为3.09s和2.53s，可变车道总体上大于普通车道的车头时距。一种合理的解释在于驾驶员对可变车道标志存在一定反应时间，通常拥有较低的配速，导致更大的车头时距。In Figure 3d, the sample mean values of the headway of variable lanes and fixed lanes are 3.09s and 2.53s, respectively, and the variable lanes are generally greater than the headway of ordinary lanes. A plausible explanation is that drivers have a certain reaction time to variable lane markings and usually have a lower pace, resulting in a greater headway.
饱和车头时距通常从第4辆车开始进行统计分析。由于饱和车头时距数据拒绝正态性检验，表1给出两种车道饱和车头时距的独立样本非参数检验结果。可变与固定车道饱和车头时距均值分别为2.64s和2.23s，增大了18.4％。p<0.001表明饱和车头时距测量值在可变车道与固定车道之间存在显著差异，与图3d观测规律相符。The saturated headway is usually statistically analyzed starting from the fourth car. Since the saturated headway data rejects the normality test, Table 1 shows the independent sample nonparametric test results of the saturated headway of the two lanes. The average saturated headway of variable and fixed lanes is 2.64s and 2.23s respectively, an increase of 18.4%. p < 0.001 indicates that there is a significant difference in the saturated headway measurements between variable lanes and fixed lanes, which is consistent with the observations in Figure 3d.
2)车辆横向分布2) Horizontal distribution of vehicles
图3中e、g为直行切换左转时车辆分布统计，使用可变车道与固定车道的车辆数差异较小。表2给出不同切换顺序下可变和固定车辆数的独立样本非参数检验结果：In Figure 3, e and g are statistics of vehicle distribution when going straight and switching to left. The difference in the number of vehicles using variable lanes and fixed lanes is small. Table 2 shows the independent sample nonparametric test results of variable and fixed vehicle numbers under different switching sequences:
直行切换左转时，p>0.05表明驶入可变车道车辆数与固定车道无明显区别，一种可能解释是交叉口采用先直行后左转的相序，观察直行车流有利于辨认可变车道功能，左转驾驶员更愿意驶入可变车道；When going straight and switching to left, p>0.05 indicates that the number of vehicles entering the variable lane is not significantly different from that of the fixed lane. One possible explanation is that the intersection adopts the phase sequence of going straight first and then turning left. Observing the straight traffic flow is conducive to identifying the variable lane function, left-turn drivers are more willing to drive into variable lanes;
左转切换直行时，驶入两种车道车辆数均值分别为7和10.88，可变车道的车辆仅占总车流的39.1％。p<0.05表明驶入可变车道车辆数与固定车道存在显著差异，可能解释是车道切换功能后，对可变车道不熟悉的驾驶员倾向于选择固定车道，导致可变车道处于较低的车道利用率。When turning left and going straight, the average numbers of vehicles entering the two lanes are 7 and 10.88 respectively, and the vehicles in variable lanes only account for 39.1% of the total traffic flow. p<0.05 indicates that there is a significant difference between the number of vehicles entering the variable lane and the fixed lane, which may explain that after the lane switching function, drivers who are not familiar with the variable lane tend to choose the fixed lane, resulting in the variable lane being in a lower lane utilization rate.
实地数据分析可知，DLG控制切换车道功能时，可变车道的饱和车头时距和驶入车辆数均劣于同向固定车道。其中平均饱和车头时距增大了18.4％，平均驶入车辆数仅占总车流的39.1％且随时间存在动态变化。Field data analysis shows that when DLG controls the lane switching function, the saturated headway and the number of vehicles entering the variable lane are inferior to those of the fixed lane in the same direction. Among them, the average saturated headway has increased by 18.4%, and the average number of entering vehicles only accounts for 39.1% of the total traffic flow, and there are dynamic changes with time.
表1样本非参数检验结果Table 1 Sample nonparametric test results
车道切换过程影响测算，可变车道的设置不仅对交通效率有积极的影响，而且有时也会产生负面的影响。分析切换过程交通流变化对优化方案准确性尤为重要。采集地点为杭州市滨盛路机场城市大道交叉口、杭州滨康路火炬大道和上海天玥桥路与中山南二路交叉口，一个或者多个进口道均设有可变车道设施，相位相序均为先直行后左转的对称四相位控制。数据来源于视频检测器，时间为2020年5月和7月，对可变车道左转变直行和直行变左转分别进行若干信号周期的系统测试。交叉口几何条件及系统界面如图2。The lane switching process affects the calculation, and the setting of variable lanes not only has a positive impact on traffic efficiency, but also sometimes has a negative impact. Analyzing the traffic flow changes during the switching process is particularly important for the accuracy of the optimization scheme. The collection locations are the intersection of Binsheng Road Airport City Avenue, Hangzhou City, Huoju Avenue, Binkang Road, Hangzhou, and the intersection of Tianyueqiao Road and Zhongshan South 2nd Road, Shanghai. One or more entrances are equipped with variable lane facilities, with phase phase The sequence is a symmetrical four-phase control that goes straight first and then turns left. The data comes from the video detector, and the time is May and July 2020. The system tests of several signal cycles were carried out for the variable lane turning left and going straight and going straight and turning left. The geometric conditions and system interface of the intersection are shown in Figure 2.
进一步的，设置一个优化区间，所述优化区间大于信号周期，且选择时间步长Δt将优化区间划分为若干子时段，输入子时段交通需求数据，利用模型得到各个子时段最优的时空资源方案。Further, set an optimization interval, the optimization interval is greater than the signal period, and select the time step Δt to divide the optimization interval into several sub-periods, input the traffic demand data of the sub-periods, and use the model to obtain the optimal space-time resource scheme for each sub-period .
进一步的，将优化全时段[Ts，Te]离散化，Δt为时间步长，共计K个子时段，子时段划分集合T0为：Further, discretize the optimized whole period [Ts , Te ], Δt is the time step, and there are K sub-periods in total, and the sub-period division set T0 is:
T0＝{Ts，1，2…t，t+Δt…Te}，t∈{1，2，…K}#(1)。T0 ={Ts , 1, 2...t, t+Δt...Te }, t∈{1, 2,...K}#(1).
进一步的，步骤S3中切换次数和切换时机：枚举优化时段内车道功能切换次数M和车道切换子时段，形成车道切换子时段矩阵为：T＝[t1，t2…tM]；Further, switching times and switching timings in step S3: enumerate lane function switching times M and lane switching sub-periods within the optimization period, and form a lane switching sub-period matrix as: T=[t1 , t2 ...tM ];
车道功能和信号配时：Lane functions and signal timing:
枚举t子时段交叉口i进口道采用的车道功能和信号配时方案矩阵包括使用车道功能p的车辆数/>和不同相位绿信比/>Enumerate the lane function and signal timing scheme matrix adopted by the intersection i entrance road in sub-period t Include the number of vehicles using the lane function p /> and different phase green signal ratio/>
考虑切换影响的可变车道优化模型，先进行基本假设，暂不考虑饱和或过饱和条件下的两相位信号控制交叉口与设置优化全时段内，交通需求已知。设置可变车道的主要目的是缓解交叉口不同流向供需矛盾，提高运行效率。延误可以充分反映交叉口运行效率，广泛作为衡量DLG性能的标准，可以直接作为优化目标。模型以所有子时段累计延误之和最小为目标函数。The variable lane optimization model considering the effect of switching, firstly makes the basic assumptions, and does not consider the two-phase signal control intersection and setting optimization under saturated or oversaturated conditions for the time being, and the traffic demand is known during the whole period of optimization. The main purpose of setting variable lanes is to alleviate the contradiction between supply and demand in different flow directions at intersections and improve operational efficiency. Delay can fully reflect the operational efficiency of intersections, and it is widely used as a standard to measure DLG performance, and can be directly used as an optimization target. The objective function of the model is to minimize the sum of cumulative delays in all sub-periods.
对于信号切换子时段，假设不存在来自上一周期的初始排队延误，仅需考虑均匀延误和增量延误。进口道子时段延误式:For the signal switching subperiod, assuming that there is no initial queuing delay from the previous period, only the uniform and incremental delays need to be considered. Import road sub-session delay Mode:
对于车道切换子时段，切换过程影响使可变车道通行能力存在波动。本发明为了便于优化建模，将其影响因素分为清空时间影响和驾驶员特性两个方面。For the lane switching sub-period, the impact of the switching process makes the capacity of the variable lane fluctuate. In order to facilitate the optimization modeling, the present invention divides its influencing factors into two aspects: the influence of the emptying time and the characteristics of the driver.
车道清空影响Lane Clearing Effects
车道功能过渡期间，提前关闭可变车道，达到清空原方向车流目的，随后进行车流转向转换。车道清空保证了行车安全，但同时也导致通行能力损失。不同可变车道切换顺序下，可以借助累计车辆曲线图定量分析通行能力损失。During the transition of the lane function, the variable lane is closed in advance to achieve the purpose of clearing the traffic flow in the original direction, and then the traffic flow is turned to change. Lane clearing ensures traffic safety, but at the same time results in a loss of capacity. Under different variable lane switching sequences, the capacity loss can be quantitatively analyzed with the help of cumulative vehicle curves.
本发明考虑两种可变车道切换方式：直行变左转和左转变直行，切换流程如图4a、b所示。以直行变左转为例，直行绿灯亮起前期，可变车道直行车辆保持释放；进入清空阶段，禁止直行车辆驶入可变车道，当左转绿灯亮起时，允许左转车流进入可变车道，完成切换。The present invention considers two variable lane switching modes: going straight to turn left and turning left to go straight. The switching process is shown in Figure 4a and b. Take straight going to turn left as an example. In the early stage when the straight going green light is on, the straight-going vehicles in the variable lane remain released; when entering the clearing stage, straight-going vehicles are prohibited from entering the variable lane. Lane, complete switch.
可变车道由直行变为左转时，图4c、d)分别为直行与左转累计车辆曲线图。清空阶段禁止上游直行车辆进入可变车道，已在车道中直行车辆仍然顺利驶离，切换对直行车通行能力影响可忽略。左转相位开启时，可变车道填充时间导致通行能力存在损失。假设填充时间与清空时间tc相等，图4c多边形面积OAD为直行延误d1，图4d三角形面积AODE为左转延误d2；车道切换子时段延误dt计算如式：When the variable lane changes from going straight to turning left, Figure 4c and d) are the cumulative vehicle curves for going straight and turning left respectively. In the clearing phase, upstream through vehicles are prohibited from entering the variable lane, and vehicles already in the lane still leave smoothly, and the impact of switching on the capacity of through vehicles is negligible. When the left turn phase is on, there is a loss of capacity due to variable lane fill times. Assuming that the filling time is equal to the emptying timetc , the polygon area OAD in Figure 4c is the straight-going delay d1 , and the triangle area AODE in Figure 4d is the left-turn delay d2 ; the lane switching sub-period delay dt is calculated as follows:
式中r1、r2分别为直行、左转红灯时长，g1、g2为有效绿灯时长，λt、λl为车辆到达率，s1、s2为饱和流率，s′1表示切换后饱和流率，tc为清空时间。In the formula, r1 and r2 are the time lengths of red lights for going straight and turning left respectively, g1 and g2 are the effective time lengths for green lights, λt and λl are vehicle arrival rates, s1 and s2 are saturation flow rates, and s′1 Indicates the saturated flow rate after switching, andtc is the emptying time.
可变车道由左转变直行后，另一方向放行，填充时间与红灯时间重合，车道填充负面影响可忽略。清空时间tc的最小时长需满足在原方向绿灯期间可变导向车道上原方向车辆全部驶离交叉口：After the variable lane turns from the left to go straight, it is released in the other direction. The filling time coincides with the red light time, and the negative impact of lane filling can be ignored. The minimum hour length of the clearing time tc needs to satisfy that all vehicles in the original direction on the variable steering lane leave the intersection during the green light period of the original direction:
驾驶特性影响，可变车道切换车道功能时，不熟悉可变车道设施的驾驶人，可能感到困惑导致更大的饱和车头时距，并倾向于驶入固定车道。优化区间内，t子时段可变车道饱和车头时距记为h(t)，式11表示优化区间可变车道饱和车头时距矩阵H。t子时段可变车道利用率记为f(t)，式12表示优化区间可变车道利用率矩阵F：Influenced by driving characteristics, when changing lanes with variable lanes, drivers who are not familiar with variable lane facilities may be confused resulting in a larger saturated headway and tend to drive into a fixed lane. In the optimization interval, the saturated headway of the variable lane in the t sub-period is denoted as h(t), and Equation 11 represents the matrix H of the saturated headway of the variable lane in the optimization interval. The variable lane utilization rate in sub-period t is denoted as f(t), and Equation 12 represents the variable lane utilization matrix F in the optimization interval:
H＝[h(1)，h(2)…h(t)]，t∈{1，2，…K}#(11)H=[h(1), h(2)...h(t)], t∈{1, 2,...K}#(11)
F＝[f(1)，f(2)…f(t)]，t∈{1，2，…K}#(12)F=[f(1), f(2)...f(t)], t∈{1, 2,...K}#(12)
t子时段可变车道饱和流率s(t)计算如式13，优化区间可变车道饱和流率记为矩阵S：The saturated flow rate s(t) of the variable lane in sub-period t is calculated as Equation 13, and the saturated flow rate of the variable lane in the optimal interval is recorded as matrix S:
S＝[s(1)，s(2)…s(t)]，t∈{1，2，…K}#(14)S=[s(1), s(2)...s(t)], t∈{1, 2,...K}#(14)
s0为基础饱和流率，车道利用率f(t)是t子时段对饱和车头时距的修正因子，计算如式：s0 is the basic saturated flow rate, and the lane utilization rate f(t) is the correction factor for the saturated headway in sub-period t, calculated as follows:
式中Qt为t子时段可变车道所处车道组总流量，/>为t子时段可变车道所处车道组单车道流量最大值，Nt为t子时段车道组车道数。 In the formula,Qt is the total flow of the lane group where the variable lane is located in the t sub-period, /> is the maximum value of the single-lane traffic of the lane group where the variable lane is located in sub-period t, and Nt is the number of lanes in the lane group in sub-period t.
约束条件为：车道功能作为交通控制中较为稳定的部分，应限制其变化频率保证交叉口安全运行，这里设定最短切换时长为10分钟，Δt≥10#(16)，交叉口每个进口的各种车道功能的车道数符合式，所有车道数之和符合式：The constraints are as follows: lane function is a relatively stable part of traffic control, and its changing frequency should be limited to ensure the safe operation of the intersection. Here, the shortest switching time is set to 10 minutes, Δt≥10#(16), and the number of intersections at each entrance The number of lanes of various lane functions conforms to the formula, and the sum of all lane numbers conforms to the formula:
若某个流向流量大于0，则必须有该流向的车道功能。同理，若某个流向流量等于0，则禁止该流向的车道功能表示为，式(19)表示各相位绿信比应在最小绿灯时长和周期时长之间取得。式(20)表示各相位绿信比之和应该不超过周期：If the flow rate of a flow direction is greater than 0, there must be a lane function for this flow direction. Similarly, if the flow in a certain flow direction is equal to 0, the lane function forbidding the flow direction is expressed as, Equation (19) indicates that the green signal ratio of each phase should be obtained between the minimum green light duration and the cycle duration. Equation (20) indicates that the sum of the green-to-signal ratios of each phase should not exceed the period:
实施例1Example 1
实施例中选取杭州市机场大道与滨盛路交叉口作为案例交叉口，几何布局如图6，西进口两条车道设置为可变车道，分析中仅对交叉口西进口优化分析，原因是高峰期间西进口左转交通流较大，进口道转向比例失衡问题明显。西进口30个周期分转向交通需求见图6b。保护性左转相位，无搭接相位。分析中，信号周期为150s，最小绿灯时长取10s。In the embodiment, the intersection of Hangzhou Airport Avenue and Binsheng Road is selected as the case intersection. The geometric layout is shown in Figure 6. The two lanes at the west entrance are set as variable lanes. In the analysis, only the west entrance of the intersection is optimized for analysis, because the peak During the period, the traffic flow of the left turn at the west entrance was relatively large, and the turning ratio of the entrance road was obviously out of balance. Figure 6b shows the diversion traffic demand of the west entrance for 30 cycles. Protective left turn phase, no overlapping phase. In the analysis, the signal period is 150s, and the minimum green light duration is 10s.
进口道车道功能与信号配时主要受流量和流向比例等因素影响。为分析不同交通需求条件下模型的输出结果，基于案例进口道总流量大小和各转向比例趋势，调整图6中交通需求建立多个场景。主要由两个参数进行调整：The lane function and signal timing of the entrance road are mainly affected by factors such as flow rate and flow direction ratio. In order to analyze the output results of the model under different traffic demand conditions, based on the total flow of the entrance road and the proportion trend of each turn in the case, adjust the traffic demand in Figure 6 to establish multiple scenarios. It is mainly adjusted by two parameters:
流向不平衡系数α：调整进口道不同转向流量之间的比例，α∈[3，5]，间隔为0.2Flow direction unbalance coefficient α: adjust the ratio between the different turning flows of the inlet channel, α∈[3,5], the interval is 0.2
交通流量系数β：扩增进口道总流量，β∈[1.5，2.5]，间隔为0.1。Traffic flow coefficient β: the total flow of the amplified entrance, β∈[1.5, 2.5], the interval is 0.1.
设计方案为：为评估优化模型的效益，后文分析将对比本文提出的优化方案(提出方法)与传统基于规则的切换方案(基于规则方法)。其中，The design scheme is: In order to evaluate the benefits of the optimization model, the following analysis will compare the optimization scheme proposed in this paper (proposed method) with the traditional rule-based switching scheme (rule-based method). in,
提出方法(PM)：考虑切换影响系统优化方案，同时优化切换次数、切换时机、车道功能和信号配时；切换过程影响持续时长θ设为两个周期，根据表，可变车道平均饱和车头时距h(t)固定取值2.64s，将表中带入公式()，可变车道利用率f(t)固定取值0.82，；Proposed method (PM): consider the system optimization scheme of the handover impact, and optimize the number of handovers, handover timing, lane functions, and signal timing at the same time; the handover process influence duration θ is set to two cycles, and according to the table, the average saturated headway time of the variable lane The fixed value of distance h(t) is 2.64s, and the table is brought into the formula (), and the variable lane utilization rate f(t) is fixed at 0.82;
基于规则方法(RM)：不考虑切换影响，优化车道功能和信号配时，方案实施仅考虑交通效率：进口道总延误减少μ时改变车道功能。Rule-Based Method (RM): The lane function and signal timing are optimized without considering the handover effect, and the scheme implementation only considers the traffic efficiency: the lane function is changed when the total delay of the entrance lane is reduced μ.
模型效益分析：α、β分别取3.8、2.1时记作点M1(3.8,2.1)，切换阈值μ＝10％时，对M1和M2(4.6,2.3)两个场景进行详细分析。交通流量如图所示，L、T分别表示左转和直行。图7表示两种方案输出的车道功能与信号配时优化结果。每个方格代表一个周期，L、T方格颜色分别为左转和直行绿信比，车道箭头代表行车方向，红色标志代表可变车道切换点。根据模型优化方案计算总延误如图7所示。Model benefit analysis: when α and β are respectively taken as 3.8 and 2.1, it is recorded as point M1(3.8,2.1), and when the switching threshold μ=10%, the two scenarios of M1 and M2(4.6,2.3) are analyzed in detail. The traffic flow is shown in the figure, L and T represent left turn and straight ahead respectively. Figure 7 shows the optimization results of lane function and signal timing output by the two schemes. Each square represents a cycle, the colors of the L and T squares represent the ratio of green signals for left-turn and straight-going respectively, the lane arrows represent the driving direction, and the red signs represent the changeable lane switching points. The total delay calculated according to the model optimization scheme is shown in Fig. 7.
分析可得：M1场景周期区间[1,10]中，对于直行流量激增，方案RM选择切换2次车道，由于考虑切换的负效益，方案PM不切换车道，仅提高直行绿信比，且PM总延误低于RM；在周期区间(10,30)，两种方案均为两次切换，区别在于切换时机不同。在周期区间[11,12]，虽然PM总延误高于RM，但是在区间[13,14]取得更大的收益。总体而言，与方案RM相比，PM减少50％切换次数，总延误降低量为9.9％。The analysis shows that: in the M1 scene cycle interval [1,10], for the surge of straight traffic, the scheme RM chooses to switch lanes twice. Due to the negative benefits of switching, the scheme PM does not switch lanes, but only improves the green signal ratio of straight traffic, and PM The total delay is lower than RM; in the period interval (10,30), both schemes are switched twice, the difference lies in the timing of switching. In the periodic interval [11,12], although the total delay of PM is higher than that of RM, it achieves greater gains in the interval [13,14]. Overall, PM reduces handoff times by 50% compared to scheme RM, and the total delay reduction is 9.9%.
M2场景中，由于转向需求进一步失衡，两种方案均为4次切换，并且切换时机多集中于交通需求显著变化阶段，而较小的波动由信号配时调节，这与模型最初的构想是一致的。In the M2 scenario, due to the further unbalanced steering demand, both schemes are switched four times, and the switching timing is mostly concentrated in the stage of significant changes in traffic demand, while the smaller fluctuations are adjusted by signal timing, which is consistent with the original concept of the model of.
总体而言，与方案RM相比，PM保持相同切换次数下，通过调整切换时机，对总延误降低量为4.1％。Overall, compared with scheme RM, PM maintains the same number of handovers, and by adjusting the handover timing, the total delay reduction is 4.1%.
综上，相对基于阈值判断切换方法，两种场景下提出的考虑切换影响系统优化方案，通过减少车道切换次数和调整车道切换时机，有助于降低进口道总延误水平，特别在M1场景，车道切换的频率的大幅降低，意味着降低了DLG控制方法的安全风险。In summary, compared with the switching method based on the threshold value judgment, the system optimization scheme considering the switching impact proposed in the two scenarios can help reduce the total delay level of the entrance by reducing the number of lane switching times and adjusting the timing of lane switching, especially in the M1 scenario. The significant reduction in switching frequency means that the safety risk of the DLG control method is reduced.
对α、β进行交叉组合实验作进一步分析。图8(a)、(b)表示两种方案不同场景下切换次数统计，颜色表示不同车道切换次数，蓝色、绿色和红色分别表示不切换、2次和4次。当处于β+0.16α＞2.3区域，两种方案均不切换车道功能；当处于β+0.16α＜2.3区域，提出方法红色面积明显缩小。整体而言，相对基于规则方法，本文提出的方法采取更少的车道功能切换次数策略，降低了频繁切换带来的安全风险。For α, β, the cross-combination experiment was carried out for further analysis. Figure 8(a) and (b) show the statistics of switching times in different scenarios of the two schemes. The colors represent the switching times of different lanes, and blue, green and red represent no switching, 2 times and 4 times, respectively. When it is in the region of β+0.16α>2.3, neither of the two schemes has the function of switching lanes; when it is in the region of β+0.16α<2.3, the red area of the proposed method is significantly reduced. Overall, compared with the rule-based method, the method proposed in this paper adopts fewer lane function switching strategies, which reduces the safety risk caused by frequent switching.
图8(d)为切换阈值μ＝10％时，提出方法和基于规则方法目标函数对比结果，方格颜色深浅代表总延误降低百分比。并且为进一步分析切换阈值对本文提出的考虑切换系统优化模型的影响，图研究不同μ取值下总延误的变化。Figure 8(d) shows the comparison results of the objective function between the proposed method and the rule-based method when the switching threshold μ=10%, and the shade of the grid represents the percentage of total delay reduction. And in order to further analyze the influence of the switching threshold on the optimization model considering the switching system proposed in this paper, the change of the total delay under different μ values is studied in the figure.
由图可得：It can be obtained from the figure:
(1)总体而言，提出方法有助于降低进口道总延误，尤其是进口道交通需求和转向不平衡较大时。算例中，与基于阈值判断优化方法相比，μ＝5％时点(4，2.1)总延误降低量最高达12.89％。(1) Overall, the proposed method is helpful to reduce the total delay of the entrance, especially when the traffic demand and steering imbalance of the entrance are large. In the calculation example, compared with the threshold-based judgment optimization method, the total delay reduction at the time point (4, 2.1) of μ = 5% is up to 12.89%.
(2)减少切换次数会显著降低总延误。提出方法优势区域分为红色与橘黄两种，红色区域类似M1点，主要通过减少非必要切换次数降低总延误；橘黄区域类似M2点，两种方法切换次数相同，总延误差异来源于切换时机不同。(2) Reducing the number of switching times will significantly reduce the total delay. The advantage area of the proposed method is divided into red and orange. The red area is similar to M1 point, which mainly reduces the total delay by reducing the number of unnecessary switching; the orange area is similar to M2 point. The switching times of the two methods are the same, and the difference in total delay comes from the different timing of switching .
(3)随着切换阈值μ增大，提出方法优势区域逐渐缩小。这主要由于切换阈值μ的增大，等价于考虑了车道功能切换带来的负面影响。但当μ＝30％时，基于规则方法不在切换车道，此时等价于固定车道方法。(3) As the switching threshold μ increases, the advantage area of the proposed method gradually shrinks. This is mainly due to the increase of the switching threshold μ, which is equivalent to considering the negative impact of lane function switching. But when μ = 30%, the rule-based method does not switch lanes, which is equivalent to the fixed-lane method.
(4)不同切换阈值μ下，M1点优化效果具有显著差异，表明基于规则方法在不同场景下需要制定相应的切换阈值才能获得最佳效益，缺乏灵活性。而在所有场景下，系统优化方法效益均不劣于规则方法和固定车道方法，并且在区域D2始终表现更好，总延误降低量最高达12.22％。(4) Under different switching threshold μ, the optimization effect of M1 point is significantly different, indicating that the rule-based method needs to formulate corresponding switching thresholds in different scenarios to obtain the best benefits, and lacks flexibility. In all scenarios, the system optimization method is not inferior to the rule method and the fixed lane method, and it always performs better in the area D2, and the total delay reduction is as high as 12.22%.
以α＝4、β＝2为界将图8(f)分为四个区域：D1-D4。取所有切换阈值μ下提出方法相比基于规则方法的延误降低百分比的平均值及两种方案的切换次数，见表2。平均切换次数方面，提出方法平均次数为1.2次，少于基于规则方法的1.6次，随着切换阈值μ的增加，两者的切换次数差距不断缩小。延误降低百分比方面，可以发现，除D2区域以外随着切换阈值μ的增加，两种方案优化延误差异不断缩小，但在D2区域，提出方法始终优于基于规则方法。提出方法与基于规则方法相比，可以在降低平均切换次数34.3％的同时降低交叉口总延误水平6.55％。Figure 8(f) is divided into four regions: D1-D4, with α=4 and β=2 as boundaries. Take the average value of the delay reduction percentage of the proposed method compared with the rule-based method under the switching threshold μ and the switching times of the two schemes, see Table 2. In terms of average switching times, the average switching times of the proposed method is 1.2 times, which is less than 1.6 times of the rule-based method. As the switching threshold μ increases, the gap between the switching times between the two continues to narrow. In terms of the percentage of delay reduction, it can be found that with the increase of the switching threshold μ, the difference in the optimization delay between the two schemes is continuously shrinking except in the D2 area, but in the D2 area, the proposed method is always better than the rule-based method. Compared with the rule-based method, the proposed method can reduce the average handover times by 34.3% and reduce the total delay level at the intersection by 6.55%.
表2总体分析结果Table 2 Overall analysis results
这里说明的设备数量和处理规模是用来简化本发明的说明的，对本发明的应用、修改和变化对本领域的技术人员来说是显而易见的。The number of devices and processing scale described here are used to simplify the description of the present invention, and the application, modification and variation of the present invention will be obvious to those skilled in the art.
尽管本发明的实施方案已公开如上，但其并不仅限于说明书和实施方式中所列运用，它完全可以被适用于各种适合本发明的领域，对于熟悉本领域的人员而言，可容易地实现另外的修改，因此在不背离权利要求及等同范围所限定的一般概念下，本发明并不限于特定的细节和这里示出与描述的图例。Although the embodiment of the present invention has been disclosed as above, it is not limited to the use listed in the specification and implementation, it can be applied to various fields suitable for the present invention, and it can be easily understood by those skilled in the art Further modifications can be effected, so the invention is not limited to the specific details and examples shown and described herein without departing from the general concept defined by the claims and their equivalents.
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| CN105139667A (en)* | 2015-09-28 | 2015-12-09 | 大连理工大学 | Reversible lane control method at intersection under influence of left-turn short lane |
| WO2018072240A1 (en)* | 2016-10-20 | 2018-04-26 | 中国科学院深圳先进技术研究院 | Direction-variable lane control method for tidal traffic flow on road network |
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