CN109712401A - A kind of compound road network bottleneck point recognition methods based on Floating Car track data - Google Patents

A kind of compound road network bottleneck point recognition methods based on Floating Car track data Download PDF

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CN109712401A
CN109712401A CN201910074831.6A CN201910074831A CN109712401A CN 109712401 A CN109712401 A CN 109712401A CN 201910074831 A CN201910074831 A CN 201910074831A CN 109712401 A CN109712401 A CN 109712401A
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bottleneck
point
track
intersection
points
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CN109712401B (en
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马万经
袁见
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Tongji University
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Abstract

本发明涉及一种基于浮动车轨迹数据的复合路网瓶颈点识别方法,包括:步骤S1:对浮动车轨迹数据进行数据清洗;步骤S2:对经过清洗后的浮动车轨迹数据进行轨迹数据与地理信息数据的融合;步骤S3:进行信息挖掘得到瓶颈点;步骤S4:根据瓶颈点的位置变化将瓶颈点分为移动瓶颈或固定瓶颈,以及根据瓶颈点的时间变化将瓶颈点分为常发性瓶颈或偶发性瓶颈;步骤S5:输出瓶颈点成因。与现有技术相比,本发明轨迹数据无须额外安装交通检测传感器,获取成本低廉。

The present invention relates to a method for identifying bottleneck points of a composite road network based on floating vehicle trajectory data, comprising: step S1: performing data cleaning on the floating vehicle trajectory data; step S2: performing the trajectory data and geographic analysis on the cleaned floating vehicle trajectory data Fusion of information data; Step S3: perform information mining to obtain bottleneck points; Step S4: divide the bottleneck points into mobile bottlenecks or fixed bottlenecks according to the location changes of the bottleneck points, and divide the bottleneck points into frequent bottleneck points according to the time changes of the bottleneck points Bottleneck or occasional bottleneck; Step S5: output the cause of the bottleneck point. Compared with the prior art, the trajectory data of the present invention does not need to install additional traffic detection sensors, and the acquisition cost is low.

Description

A kind of compound road network bottleneck point recognition methods based on Floating Car track data
Technical field
The present invention relates to traffic state analysis fields, more particularly, to a kind of compound road network based on Floating Car track data Bottleneck point recognition methods.
Background technique
Bottleneck point in transportation network refers to the certain point throughput in section, and there are a significant declines.Bottleneck Formation will result directly in the formation of traffic congestion and the sprawling of queuing vehicle.Timely detection and the dissipation of bottleneck point are that road is handed over One of the top priority of logical manager.For bottleneck, the position occurred, the queue length of formation and bottleneck it is lasting when Between, occurrence frequency, rule are the most concerned contents of traffic administration person.
Bottleneck is usually made of two parts parameter, first is that bottleneck starting point, refering in particular to downstream, section traffic throughput occur aobvious The case where work increases and traffic shows free flow feature.Second is that being lined up caused by bottleneck, it refers to bottleneck starting point up The slow vehicle of the travel speed of roam all around the would to appearance is formed by queue.
Whether moved in its duration according to the starting point of bottleneck, fixed bottleneck and moving bottleneck can be divided into.It presses According to the time and space idea that bottleneck occurs, often hair property bottleneck and sporadic bottleneck can be divided into.Often hair property bottleneck point refers to that one kind often exists Same or like place, in the bottleneck that the different time period (such as not interior on the same day) repeats.Sporadic bottleneck then shows Weaker regularity.
The largely method and research about bottleneck detection existing at present, wherein most common way is under detection speed is significant The section of drop.But based on detection data source be essentially section fixed detector data, such as loop coil.Its common practice It is to lay loop coil at certain intervals on a plurality of adjacent section and detect velocity information.But this method can not be extended to Road network level is analyzed, and this method precision is limited by detector density.With the appearance of track data, also occur The more method for carrying out bottleneck judgement based on such data.The advantages of this method is that procurement cost is low, without installing on road Entity detection device, and wide coverage.But since floating wheel paths permeability is low, the sampling interval is big and inconsistent, GPS positioning The problems such as precision is different brings certain difficulty to the direct application of data.And the existing bottleneck point spy based on track data Sign calculates identification and description method is abundant not enough.
Summary of the invention
It is an object of the present invention to overcome the above-mentioned drawbacks of the prior art and provide one kind to be based on floating track The compound road network bottleneck point recognition methods of mark data.
The purpose of the present invention can be achieved through the following technical solutions:
A kind of compound road network bottleneck point recognition methods based on Floating Car track data, comprising:
Step S1: data cleansing is carried out to Floating Car track data;
Step S2: merging for track data and geographic information data is carried out to the Floating Car track data after over cleaning;
Step S3: it carries out information excavating and obtains bottleneck point;
Step S4: bottleneck point is divided by moving bottleneck or fixed bottleneck according to the change in location of bottleneck point, and according to bottle Bottleneck point is divided into often hair property bottleneck or sporadic bottleneck by the time change of neck point;
Step S5: the output bottleneck point origin cause of formation.
The step S1 is specifically included:
Step S11: judging whether the vehicle ID of current trace points in Floating Car track data, timestamp lack or abnormal, If it is, S12 is thened follow the steps, conversely, thening follow the steps S13;
Step S12: current trace points are abandoned, next tracing point is read and judges whether track data terminates, if it has not, then Execute step S11;
Step S13: judging whether the instantaneous velocity of current trace points lacks or abnormal, if it is, S14 is thened follow the steps, Conversely, thening follow the steps S15;
Step S14: being attempted smoothly to be repaired using the instantaneous velocity of adjacent track point, and judge whether success, if it has, then Step S15 is executed, conversely, thening follow the steps S12;
Step S15: judge whether the longitude and latitude of current trace points lacks or abnormal, if it is, thening follow the steps S16, instead It, thens follow the steps S17;
Step S16: it attempts smoothly to repair using the longitude and latitude of adjacent track point, and judges whether success, if it has, then holding Row step S17, conversely, thening follow the steps S12;
Step S17: reading next tracing point and judges whether track data terminates, if it has not, thening follow the steps S11.
Judge whether successful process in the step S14 specifically: judging the difference of the instantaneous velocity of adjacent track point is It is no to be less than threshold velocity.
Judge whether successful process in the step S16 specifically:
The distance between two tracing points of calculation of longitude & latitude based on adjacent track point;
First Speed is calculated according to the distance between two tracing points and time difference, and judges the First Speed and wink Whether the difference of Shi Sudu is less than setting ratio, if, then it is assumed that success, it is on the contrary then think failure.
The step S2 is specifically included:
Step S21: by delimiting a rectangular area, tracing point all in target intersection group is obtained;
Step S22: it assigns tracing point intersection number interid, road number roadid, go out row number tripid;
Step S23: direction of travel when whether passing through intersection according to track and passing through intersection assigns tracing point and turns To number moveid;
Step S24: for the section between two intersections, tracing point is being repaired just according to the intersection that vehicle is driven towards Intersection number interid;
Step S25: the distance of vehicle distances stop line is obtained.
The step S22 is specifically included:
Step S221: the second is converted by road time format;
Step S222: for the road between intersection, centre adheres to two intersections separately to half-open, assigns and handing over for each tracing point Prong number interid;
Step S223: delimiting the region of longitude and latitude for different sections of highway, and correspondence invests road number roadid value;
Step S224: row number tripid is assigned out according to the corresponding row order out of each tracing point.
It is specific to wrap for the tracing point that each tripid of each each car of each car is covered in the step S25 It includes:
If only including 1 roadid value, the distance for arriving intersection is directly calculated;
If containing 3 roadid values, an intersection only have passed through, equally directly calculate distance;
If characterization have passed through multiple intersections comprising being greater than 3 roadid values, a pair of cross mouth number is successively screened The corresponding tracing point of interid, calculates separately the distance apart from stop line.
The step S5 includes:
If moving bottleneck, there is the vehicle (may be truck or car of going slowly) of retardance traffic in output;
If fixed bottleneck, the traffic capacity for exporting the existing means of transportation of the bottleneck point of the bottleneck point be can no longer meet Status transport need.
Compared with prior art, the invention has the following advantages:
1) acquisition of track data need not additionally install Vehicle Detection sensor, and procurement cost is cheap.
2) the various topological structure and traffic flow condition for combining compound road network, classify to bottleneck point.The bottleneck of foundation Feature judgement and the opposite more easily execution of classifying method.
Detailed description of the invention
Fig. 1 is the key step flow diagram of the method for the present invention;
Fig. 2 is the space-time trajectory schematic diagram of track data;
Fig. 3 is track data fusion process schematic diagram.
Specific embodiment
The present invention is described in detail with specific embodiment below in conjunction with the accompanying drawings.The present embodiment is with technical solution of the present invention Premised on implemented, the detailed implementation method and specific operation process are given, but protection scope of the present invention is not limited to Following embodiments.
The purpose of the application is in order to overcome the shortcomings of existing bottleneck point identifying and analyzing method, based on the traffic to become increasingly abundant Track big data constructs compound road network bottleneck point recognizer, to promote traffic condition detection accuracy, expand bottleneck point knowledge Other application range.The it is proposed of this method peomotes urban traffic control system construction and upgrading, accurately identifies and deposits city Traffic congestion critical issue, to reach the purpose for more targetedly alleviating urban traffic blocking.
It proposes compound road network bottleneck point recognition methods, is based on Floating Car track data, commented from the quantization of time-domain space angle Estimate the parameter attribute and rule of bottleneck point, thus for network traffic supersaturation control evaluation provide with optimization it is objective, effective Foundation.
A kind of compound road network bottleneck point recognition methods based on Floating Car track data, as shown in Figure 1, comprising:
Step S1: carrying out data cleansing to Floating Car track data, as shown in Fig. 2, specifically including:
Step S11: judging whether the vehicle ID of current trace points in Floating Car track data, timestamp lack or abnormal, If it is, S12 is thened follow the steps, conversely, thening follow the steps S13;
Step S12: current trace points are abandoned, next tracing point is read and judges whether track data terminates, if it has not, then Execute step S11;
Step S13: judging whether the instantaneous velocity of current trace points lacks or abnormal, if it is, S14 is thened follow the steps, Conversely, thening follow the steps S15;
Step S14: being attempted smoothly to be repaired using the instantaneous velocity of adjacent track point, and judge whether success, if it has, then Step S15 is executed, conversely, thening follow the steps S12;
Specifically, should judge whether that successful process was specifically as follows in the process: judging the instantaneous velocity of adjacent track point Difference whether be less than threshold velocity.
Step S15: judge whether the longitude and latitude of current trace points lacks or abnormal, if it is, thening follow the steps S16, instead It, thens follow the steps S17;
Step S16: it attempts smoothly to repair using the longitude and latitude of adjacent track point, and judges whether success, if it has, then holding Row step S17, conversely, thening follow the steps S12;
Specifically, wherein judging whether successful process can include:
The distance between two tracing points of calculation of longitude & latitude based on adjacent track point;Then according between two tracing points Distance and the time difference First Speed is calculated, and judge whether the difference of the First Speed and instantaneous velocity is less than setting ratio Example, if, then it is assumed that success, it is on the contrary then think failure.
Step S17: reading next tracing point and judges whether track data terminates, if it has not, thening follow the steps S11.
Step S2: carrying out merging for track data and geographic information data to the Floating Car track data after over cleaning, It specifically includes:
Step S21:: there is a large amount of unrelated tracing point in screening target area in file, by delimiting a rectangular area, Obtain tracing point all in target intersection group;
Step S22: tracing point intersection number interid, road number roadid are assigned, goes out row number tripid, tool Body includes:
Step S221: the second is converted by road time format, such as be converted into number of seconds in 35 seconds 35 minutes at 17 points;
Step S222: for the road between intersection, centre adheres to two intersections separately to half-open, assigns and handing over for each tracing point Prong number interid;
Step S223: delimiting the region of longitude and latitude for different sections of highway, and correspondence invests road number roadid value, specifically, The region of longitude and latitude delimited to different sections of highway, is corresponded and is assigned roadid value (intersection region can random assignment), then Roadid is tracing point of the empty data line i.e. not on section, is deleted;
Step S224: row number tripid is assigned out according to the corresponding row order out of each tracing point, specifically, for one Vehicle, it may have multiple trip in one day, and not occur continuously in time, and therefore, different trips is drawn It separates.If time interval is greater than 15 seconds (official's explanation, the tracing point sample frequencys of type=11 between upper and lower two tracing points It is 15 seconds/time, remaining is 1 second/time), then judge that the vehicle has started another new trip, tripid is numbered from 1, this is Place mat has been made in the setting of subsequent turn around parameters.
Step S23: direction of travel when whether passing through intersection according to track and passing through intersection assigns tracing point and turns To number moveid, specifically, as follows:
A) for having passed through the track of vehicle of intersection, setting: turning left is 1, and keeping straight on is 2, and turning right is 3;
B) for not passed through the track of vehicle of intersection, 4 are set as.
Step S24: for the section between two intersections, tracing point is being repaired just according to the intersection that vehicle is driven towards Intersection number interid just needs to correct for the section between two intersections: which the intersection that vehicle drives towards is As soon as, its interid is assigned a value of to the number of which intersection;
Step S25: the distance of vehicle distances stop line is obtained, wherein for each of each each car of each car The tracing point that tripid is covered, specifically includes:
If only including 1 roadid value, the distance for arriving intersection is directly calculated;
If containing 3 roadid values, an intersection only have passed through, equally directly calculate distance;
If characterization have passed through multiple intersections comprising being greater than 3 roadid values, a pair of cross mouth number is successively screened The corresponding tracing point of interid, calculates separately the distance apart from stop line.
Next, draw space-time diagram as shown in figure 3, check virtual stop line at a distance from true stop line, to it is existing away from It is modified from data.
Step S3: it carries out information excavating and obtains bottleneck point;
Step S4: bottleneck point is divided by moving bottleneck or fixed bottleneck according to the change in location of bottleneck point, and according to bottle Bottleneck point is divided into often hair property bottleneck or sporadic bottleneck by the time change of neck point;
Bottleneck point analysis specifically includes: bottleneck point Evolution, the analysis of bottleneck range of point influence.
(1) bottleneck point Evolution
Section is drawn and is divided into several sections of separate spaces at certain intervals, it is assumed that each unit road section traffic volume situation is identical, is based on It corrects track data and carries out state matching.It detects that upstream speed is significantly lower than the section in downstream, is then bottleneck point.Record is different When the changing rule of bottleneck point inscribed, can use machine learning algorithm and carry out feature identification and predicted with evolvement trend.
(2) bottleneck range of point influence
For the bottleneck point identified, its upstream traffic behavior is observed based on track data.Generally according to 1km, 5km range The segmentation of carry out state (finds the initial point position of bottleneck upstream congestion), and state segmentation range is flexibly adjusted according to the range in city It is whole.Since track positioning accuracy is not up to lane grade, need to judge by the deflection attribute of track herein.
Bottleneck type includes:
1) normal hair property bottleneck: more day datas repeat to recognize certain section, and at the close moment, there are bottleneck or bottleneck points The coverage of mobile trend and bottleneck point is consistent, then can all be classified as the often property sent out bottleneck;
2) sporadic bottleneck: the bottleneck point and its coverage detected, spatial homing phase of getting along well in the historical data Matching, temporal regularity of also getting along well match;
3) moving bottleneck and fixed bottleneck: being directed to certain bottleneck, if bottleneck point is not moved during being formed with dissipation Dynamic, then otherwise it is moving bottleneck that explanation, which is fixed bottleneck,.
Step S5: the output bottleneck point origin cause of formation, comprising:
If moving bottleneck, there is the vehicle (may be truck or car of going slowly) of retardance traffic in output;
If fixed bottleneck, the traffic capacity for exporting the existing means of transportation of the bottleneck point of the bottleneck point be can no longer meet Status transport need.

Claims (8)

1.一种基于浮动车轨迹数据的复合路网瓶颈点识别方法,其特征在于,包括:1. a composite road network bottleneck point identification method based on floating vehicle trajectory data, is characterized in that, comprises: 步骤S1:对浮动车轨迹数据进行数据清洗;Step S1: perform data cleaning on the trajectory data of the floating car; 步骤S2:对经过清洗后的浮动车轨迹数据进行轨迹数据与地理信息数据的融合;Step S2: Fusion of trajectory data and geographic information data is performed on the cleaned floating vehicle trajectory data; 步骤S3:进行信息挖掘得到瓶颈点;Step S3: perform information mining to obtain bottleneck points; 步骤S4:根据瓶颈点的位置变化将瓶颈点分为移动瓶颈或固定瓶颈,以及根据瓶颈点的时间变化将瓶颈点分为常发性瓶颈或偶发性瓶颈;Step S4: classifying the bottleneck point into a mobile bottleneck or a fixed bottleneck according to the positional change of the bottleneck point, and classifying the bottleneck point into a frequent bottleneck or an occasional bottleneck according to the time change of the bottleneck point; 步骤S5:输出瓶颈点成因。Step S5: output the cause of the bottleneck point. 2.根据权利要求1所述的一种基于浮动车轨迹数据的复合路网瓶颈点识别方法,其特征在于,所述步骤S1具体包括:2. a kind of composite road network bottleneck point identification method based on floating vehicle trajectory data according to claim 1, is characterized in that, described step S1 specifically comprises: 步骤S11:判断浮动车轨迹数据中当前轨迹点的车辆ID、时间戳是否缺失或异常,若为是,则执行步骤S12,反之,则执行步骤S13;Step S11: Determine whether the vehicle ID and time stamp of the current track point in the floating car track data are missing or abnormal, if so, execute step S12, otherwise, execute step S13; 步骤S12:丢弃当前轨迹点、读取下一轨迹点并判断轨迹数据是否结束,若为否,则执行步骤S11;Step S12: discard the current track point, read the next track point, and determine whether the track data is over, if not, execute step S11; 步骤S13:判断当前轨迹点的瞬时速度是否缺失或异常,若为是,则执行步骤S14,反之,则执行步骤S15;Step S13: determine whether the instantaneous speed of the current trajectory point is missing or abnormal, if so, execute step S14, otherwise, execute step S15; 步骤S14:尝试使用相邻轨迹点的瞬时速度平滑修复,并判断是否成功,若为是,则执行步骤S15,反之,则执行步骤S12;Step S14: try to use the instantaneous speed of the adjacent track points to smooth the repair, and determine whether it is successful, if so, go to step S15, otherwise, go to step S12; 步骤S15:判断当前轨迹点的经纬度是否缺失或异常,若为是,则执行步骤S16,反之,则执行步骤S17;Step S15: determine whether the latitude and longitude of the current track point is missing or abnormal, if so, execute step S16; otherwise, execute step S17; 步骤S16:尝试使用相邻轨迹点的经纬度平滑修复,并判断是否成功,若为是,则执行步骤S17,反之,则执行步骤S12;Step S16: try to use the latitude and longitude of the adjacent track points to smooth the repair, and judge whether it is successful, if so, go to step S17, otherwise, go to step S12; 步骤S17:读取下一轨迹点并判断轨迹数据是否结束,若为否,则执行步骤S11。Step S17 : Read the next track point and judge whether the track data is over, if not, go to step S11 . 3.根据权利要求2所述的一种基于浮动车轨迹数据的复合路网瓶颈点识别方法,其特征在于,所述步骤S14中判断是否成功的过程具体为:判断相邻轨迹点的瞬时速度之差是否小于阈值速度。3. a kind of composite road network bottleneck point identification method based on floating vehicle trajectory data according to claim 2, is characterized in that, the process of judging whether successful in described step S14 is specifically: judge the instantaneous speed of adjacent trajectory point Whether the difference is less than the threshold speed. 4.根据权利要求2所述的一种基于浮动车轨迹数据的复合路网瓶颈点识别方法,其特征在于,所述步骤S16中判断是否成功的过程具体为:4. a kind of composite road network bottleneck point identification method based on floating vehicle trajectory data according to claim 2, is characterized in that, the process of judging whether successful in described step S16 is specifically: 基于相邻轨迹点的经纬度计算两个轨迹点之间的距离;Calculate the distance between two track points based on the latitude and longitude of adjacent track points; 根据两个轨迹点之间的距离和时间差计算得到第一速度,并判断该第一速度与瞬时速度的差值是否小于设定比例,若为,则认为成功,反之则认为失败。Calculate the first speed according to the distance and time difference between the two track points, and judge whether the difference between the first speed and the instantaneous speed is less than the set ratio. If so, it is considered successful, otherwise, it is considered failure. 5.根据权利要求1所述的一种基于浮动车轨迹数据的复合路网瓶颈点识别方法,其特征在于,所述步骤S2具体包括:5. a kind of composite road network bottleneck point identification method based on floating vehicle trajectory data according to claim 1, is characterized in that, described step S2 specifically comprises: 步骤S21:通过划定一个矩形区域,获得目标交叉口群内所有的轨迹点;Step S21: by delimiting a rectangular area, obtain all the trajectory points in the target intersection group; 步骤S22:赋予轨迹点交叉口编号interid、道路编号roadid、出行编号tripid;Step S22: assign the intersection number interid, road number roadid, and trip number tripid to the track point; 步骤S23:根据轨迹是否通过交叉口以及通过交叉口时的行进方向赋予轨迹点转向编号moveid;Step S23: according to whether the trajectory passes through the intersection and the direction of travel when passing through the intersection, the trajectory point is given a turn number moveid; 步骤S24:对于处于两个交叉口间的路段,根据车辆所驶向的交叉口修轨迹点的正交叉口编号interid;Step S24: For the road segment between the two intersections, repair the normal intersection number interid of the trajectory point according to the intersection to which the vehicle is heading; 步骤S25:获取车辆距离停车线的距离。Step S25: Obtain the distance of the vehicle from the stop line. 6.根据权利要求5所述的一种基于浮动车轨迹数据的复合路网瓶颈点识别方法,其特征在于,所述步骤S22具体包括:6. a kind of composite road network bottleneck point identification method based on floating vehicle trajectory data according to claim 5, is characterized in that, described step S22 specifically comprises: 步骤S221:将道路时间格式转化为秒;Step S221: Convert the road time format into seconds; 步骤S222:对于交叉口间的道路,中间对半开分属两个交叉口,为各轨迹点赋予交叉口编号interid;Step S222: For the road between the intersections, the middle is divided into two intersections, and the intersection number interid is assigned to each track point; 步骤S223:为不同路段划定经纬度的区域,对应赋与道路编号roadid值;Step S223: Delineate latitude and longitude areas for different road sections, and assign a road number roadid value correspondingly; 步骤S224:根据各连续轨迹点之间时间戳间隔,赋予每一个轨迹点对应的出行次序编号tripid。Step S224: According to the time stamp interval between the consecutive track points, assign a travel sequence number tripid corresponding to each track point. 7.根据权利要求5所述的一种基于浮动车轨迹数据的复合路网瓶颈点识别方法,其特征在于,所述步骤S25中,对于每辆车的每个每辆车的每个tripid所涵盖的轨迹点,具体包括:7. a kind of composite road network bottleneck point identification method based on floating vehicle trajectory data according to claim 5, is characterized in that, in described step S25, for each tripid of each each vehicle of each vehicle. Track points covered, specifically: 若只包含1个roadid值,则直接计算到交叉口的距离;If only one roadid value is included, the distance to the intersection is directly calculated; 若包含了3个roadid值,则只经过了一个交叉口,同样直接计算距离;If 3 roadid values are included, only one intersection has been passed, and the distance is also directly calculated; 若包含大于3个roadid值,则表征经过了多个交叉口,依次筛选一对交叉口编号interid对应的轨迹点,分别计算距离停车线的距离。If it contains more than 3 roadid values, it means that it has passed through multiple intersections, and then screen the trajectory points corresponding to a pair of intersection numbers interid in turn, and calculate the distance from the stop line respectively. 8.根据权利要求1所述的一种基于浮动车轨迹数据的复合路网瓶颈点识别方法,其特征在于,所述步骤S5包括:8. a kind of composite road network bottleneck point identification method based on floating vehicle trajectory data according to claim 1, is characterized in that, described step S5 comprises: 若为移动瓶颈,输出存在阻滞交通的车辆;If it is a mobile bottleneck, output vehicles that block traffic; 若为固定瓶颈,输出该瓶颈点的现有交通设施的通行能力已经无法满足现状交通需求。If it is a fixed bottleneck, the traffic capacity of the existing traffic facilities that output the bottleneck point can no longer meet the current traffic demand.
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