CN105046963A - Elevated-road-section traffic-jam critical value calculating method based on basic traffic diagram - Google Patents
Elevated-road-section traffic-jam critical value calculating method based on basic traffic diagram Download PDFInfo
- Publication number
- CN105046963A CN105046963A CN201510524253.3A CN201510524253A CN105046963A CN 105046963 A CN105046963 A CN 105046963A CN 201510524253 A CN201510524253 A CN 201510524253A CN 105046963 A CN105046963 A CN 105046963A
- Authority
- CN
- China
- Prior art keywords
- traffic
- msub
- mrow
- elevated
- data
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
- 238000010586 diagram Methods 0.000 title claims abstract description 28
- 238000000034 method Methods 0.000 title claims abstract description 19
- 238000004364 calculation method Methods 0.000 claims description 14
- 230000007547 defect Effects 0.000 description 4
- 230000006698 induction Effects 0.000 description 2
- 238000005070 sampling Methods 0.000 description 2
- 206010033799 Paralysis Diseases 0.000 description 1
- 238000013479 data entry Methods 0.000 description 1
- 238000001514 detection method Methods 0.000 description 1
- 239000006185 dispersion Substances 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 238000000611 regression analysis Methods 0.000 description 1
- 230000003068 static effect Effects 0.000 description 1
- 238000006467 substitution reaction Methods 0.000 description 1
Landscapes
- Traffic Control Systems (AREA)
Abstract
The invention belongs to the urban elevated road traffic diversion dredging field and especially relates to an elevated-road-section traffic-jam critical value calculating method based on a basic traffic diagram. The method comprises the following steps of 1) taking an elevated bridge road which connects adjacent exit and entrance ramps as one elevated road section; acquiring traffic flow data and each vehicle running speed data on each elevated road section; 2) calculating a traffic flow and an average speed of vehicles on each road section in each acquisition period; 3) taking a sample set; 4) drawing a scatter diagram of the basic traffic diagram; 5) calculating and acquiring a road average critical vehicle speed Vm at a maximum traffic flow and an unblocked vehicle speed Vf of the elevated road section. The method fits a current elevated-road actual dynamic change road condition of a current city. High accuracy of calculating data is ensured. An accurate basis can be provided for a traffic manager to carry out on-line traffic diversion so that unblocked performance of the traffic on the elevated road is finally guaranteed.
Description
Technical Field
The invention belongs to the field of traffic diversion and dredging of urban elevated roads, and particularly relates to an elevated road section traffic jam critical value calculation method based on a traffic basic map.
Background
The traffic jam is the centralized embodiment of various social contradictions such as uneven population distribution, limited urban traffic supply, unmatched urban layout and economic development and the like caused by unbalanced economic development, and is a worldwide problem. Compared with ground traffic on the ground, the elevated road for three-dimensional traffic has a relatively high closing characteristic, and once the elevated road is congested, long-distance and large-range congestion is easily caused, even regional road network paralysis occurs, and passengers and drivers often face the situation of wrong driving and reversing. Although the national standard of road traffic state information release specification (GA/T994-2012) determines a correspondence table of the overhead road traffic state and the motor vehicle running speed, the correspondence table is used for comparing the current overhead road running data, and provides traffic diversion and guidance reference for a traffic manager. However, practical problems are: due to the fact that the cities are different in development degree and the regional road plans are different, even the elevated roads in the same region are different in road conditions and lanes, the unified specification of only idealization and staticization often has the defects of poor flexibility and lack of adaptability, and therefore the dynamic use requirement of perfectly attaching the elevated roads in all road sections cannot be met far away. How to seek an objective traffic jam calculation mode which is simple and reasonable in operation, can ensure high accuracy and high pertinence of calculation data while fitting actual dynamically-changed road conditions of the current elevated road in the current city, thereby providing an accurate basis for traffic flow distribution on line for a traffic manager, deploying police force before the traffic jam comes and executing traffic flow distribution induction operation, and finally ensuring the traffic smoothness of the elevated road, which is a technical problem to be urgently solved in recent years for technical personnel in the field.
Disclosure of Invention
The invention aims to overcome the defects of the prior art and provide a more efficient and rapid calculation method for the traffic jam critical value of the elevated road section based on the traffic basic diagram. The method can meet the actual dynamically changed road conditions of the current elevated road in the current city, and can ensure the high accuracy and high pertinence requirements of the calculated data, thereby providing accurate basis for traffic managers to carry out online traffic diversion, and further deploying police force and executing traffic diversion induction operation before traffic jam comes, so as to finally ensure the traffic smoothness of the elevated road.
In order to achieve the purpose, the invention adopts the following technical scheme:
a method for calculating a traffic jam critical value of an elevated road section based on a traffic basic map is characterized by comprising the following steps:
1) according to the positions of the exit ramp and the entrance ramp of the elevated road, the elevated road section is defined by the elevated road connecting the adjacent exit ramp and the entrance ramp; acquiring equipment data of a microwave radar detector on each elevated road section, wherein the data at least comprises elevated road section traffic flow data and vehicle running speed data;
2) determining an acquisition cycle, and calculating the traffic flow and the vehicle average speed of each road section in each acquisition cycle according to the traffic flow and the vehicle speed data of the road section of the elevated road;
3) and taking the traffic flow and the average speed of the vehicles corresponding to all the collection periods in one day as a sample set, and recording as follows:
Q={(x,y)|x=x1,x2......xn;y=y1,y2......yn},
wherein,
x represents an elevated road segment traffic flow;
y represents the average vehicle speed of the elevated road section in km/h;
4) drawing a scatter diagram of the traffic basic diagram according to the traffic flow and the vehicle average speed data in the sample set;
5) and returning the equation X to beta by using the basic flow-speed diagram0+β1(Y)2+β2Y +, according to the traffic flow and vehicle average speed data in the sample set, inputting the data into a regression equation calculation model to obtain a regression coefficient beta0、β1、β2And statistical errors;
according to the mathematical meaning of the regression curve, the value corresponding to the curve vertex is the maximum traffic flow and the critical vehicle speed value, and the regression equation of the flow-speed basic diagram is converted into the following formula:
when gettingWhen the value is 0, the value Y is reversely deduced to obtain the average critical vehicle speed V under the condition of the maximum traffic flow corresponding to the curve vertexm(ii) a Substituting the regression coefficients and the statistical errors into a regression equation to calculate and obtain the average critical vehicle speed V of the section when the maximum traffic flow of the section of the elevated road is obtainedmSmooth vehicle speed VfThe calculation formula is as follows:
wherein, VmAnd VfThe units of (A) are km/h.
In the step 1), the device data of the microwave radar detector further includes current device number data, number data of a located position, and name ID data of a current located traffic road section.
In the step 2), one acquisition period is one hour; the traffic flow is the total number of cars passing through the traffic road section in each hour, and the average speed of the vehicles is the average value of the running speeds of all the vehicles in the collection period.
The main advantages of the invention are:
1) and various defects such as low control flexibility and incapability of visually fitting the dynamic traffic demand of the current elevated road caused by a traditional mode of only depending on a national standard correspondence table are abandoned. The invention is calculated by a regression equation model in a traffic basic diagram mode, completely presents a road traffic state dynamic change curve depending on the dynamic relation between traffic flow and average speed, and intuitively and pertinently accurately reflects the traffic dynamic characteristics of the current road. The method utilizes a microwave radar detector on an elevated road section to acquire point-to-point acquisition data, accurately obtains a sample set for drawing a traffic basic diagram scatter diagram, adopts a regression analysis method to fit a flow-speed basic diagram, and further calculates and obtains a critical vehicle speed and a smooth vehicle speed. The invention realizes the actualization and the joint management of the appointed road section of the appointed area through point-to-point data sampling, and the adaptability and the management pertinence are obviously stronger. By using the dynamic traffic data of the elevated road, the defects of experience judgment and traditional standard static judgment of the traffic congestion of the elevated road are effectively overcome, and the method has high refinement degree and extremely reliable and stable operation.
The invention finally obtains the smooth vehicle speed and the average critical vehicle speed of the elevated road section when the maximum traffic flow of the elevated road section is realized by means of the point-to-point calculation process. Once the average running speed of the elevated road section is lower than the average critical vehicle speed after the speed is obtained, the traffic manager can perform traffic evacuation shunting and guidance operation; and judge at what time the police force is arranged to further rationalize and intervene the overhead road traffic management. On the contrary, once the average driving speed of the elevated road section is higher than the speed of the smooth vehicle, the elevated road section has excellent vehicle conditions at present. The traffic manager can consider that when the traffic is shunted, the driver is advised to preferentially select the section of the elevated road to drive so as to improve the utilization rate of elevated road resources. Through the operation head end, a decision support technology is finally provided for a traffic management department to more carefully master the traffic state of the elevated road and early warn traffic jam.
Drawings
FIG. 1 is a schematic flow chart of the present invention;
FIG. 2 is the average critical vehicle speed V under the flow-speed curvemSmooth vehicle speed VfA positional relationship diagram of (1);
FIG. 3 is a 24-hour traffic volume-vehicle speed single-point relationship diagram of sample data in example 1;
fig. 4 is a graph of traffic flow-speed curves of sample data in example 1.
Detailed Description
For ease of understanding, the practice of the present invention is further described herein in connection with FIGS. 1-2 as follows:
a method for calculating a traffic jam critical value of an elevated road section based on a traffic basic map comprises the following steps:
1) dividing the elevated road into an entrance ramp, an exit ramp and an elevated road section according to the entrance ramp and exit ramp positions of the elevated road; the elevated road section where data is to be acquired is also referred to as the elevated road section connecting the adjacent exit ramp and the entrance ramp.
2) And acquiring equipment data of the microwave radar detector of each elevated road section, wherein the data at least comprises elevated road section traffic flow data and vehicle speed data.
3) Calculating the traffic flow and the vehicle average speed of each road section in one acquisition period according to the traffic flow and the vehicle speed data of the road sections of the elevated road; taking the traffic flow and the average speed of vehicles corresponding to all the collection periods within one day as a sample set, and recording as Q { (x, y) | x ═ x { (x, y) |1,x2......xn;y=y1,y2......ynWhere x represents elevated road segment traffic flow and y represents elevated road segment vehicle average speed.
4) Drawing a scatter diagram of the traffic basic diagram according to the traffic flow and the vehicle average speed data in the sample set; fitting a flow-speed curve of a traffic basic diagram by adopting a regression equation, determining a regression coefficient, and calculating the average critical vehicle speed V of the road section when the maximum traffic flow of the elevated road section occursmAnd smooth vehicle speed Vf. In the regression coefficient and curve fitting process, data entry and fitting calculation are performed by using a regression equation model in the conventional mathematical field, which is not repeated here.
The device data of the microwave radar detector further includes a device number, a location number, road section name data, and the like. And a collection period typically ranges from one hour, traffic flow is the total number of all equivalent cars passing through the road segment in the collection period, and vehicle average speed is the average of all vehicle speeds in the collection period.
The method for fitting the traffic basic diagram flow-speed curve by adopting the regression equation means that the regression equation of the flow-speed basic diagram is set to be X ═ beta0+β1(Y)2+β2Y +, calculating regression coefficient beta according to the traffic flow and vehicle average speed data in the sample set0、β1、β2And statistical errors; substituting the regression coefficient and the statistical error into the converted regression equation
As shown in fig. 2, when takingWhen the value is 0, the value Y is reversely deduced to obtain the average critical vehicle speed V under the condition of the maximum traffic flow corresponding to the curve vertexm(ii) a Obtaining the average critical vehicle speed VmSmooth vehicle speed VfThe value, the calculation formula is as follows:
wherein, VmEqual to the average vehicle speed of the road section when the maximum traffic flow is obtained, namely the average critical vehicle speed and the smooth vehicle speed V of the road sectionfAccording to the conventional traffic basic diagram and traffic flow basic theory, the V is 2 times of Vm,VmAnd VfThe units of (A) are km/h.
In the calculation process, the data acquisition and even calculation modes are objectively acquired from the current elevated road section, so the method has strong point-to-point pertinence and adaptability to the specified road section. In actual operation, the traffic manager can perform traffic management arrangement in a targeted manner by summarizing the information data of each road section and the corresponding speed data. In short, a certain elevated road section is below the above-mentioned average critical vehicle speed VmIf so, a congestion point is inevitably existed, and the traffic manager can perform early warning and online police force dredging operation on the road section; not only the rigid management is carried out according to the standard of calculating congestion below 20 km/h. Whereas, once a certain section of elevated road is above the clear vehicle speed VfThe road section is necessarily extremely good in road condition, and when a traffic manager conducts traffic dispersion and diversion of other road sections, the traffic manager should preferably advise a driver to select the road section for driving so as to improve the utilization rate of traffic resources.
On the basis, the national standard threshold value can be further refined and distinguished according to the acquired data so as to improve the adaptability of the system to various different regions and even elevated road sections of road sections. The method comprises the following specific steps:
a. defining an initial threshold value, wherein the initial threshold value is determined according to the standard of the national road traffic status information release specification (GA/T994-2012), and the initial threshold value is shown in Table 1:
TABLE 1
Table 1 is a table of correspondence between the traffic state of the overhead road and the driving speed of the motor vehicle, which is determined by the standard "traffic state information issue specification" (GA/T994-2012).
According to Table 1, the initial threshold values were determined to be 20km/h and 50 km/h.
b. Carry out Vm、VfComparison with initial thresholds, such as:
if Vm<20, then the congestion threshold is VmTaking 20km/h as compared with a congestion threshold;
if Vm>20, the congestion threshold value is 20km/h, and V is taken as the congestion threshold valuem;
If Vf<50, then V is taken as the threshold value of better smoothnessmTaking 50km/h as a smooth threshold value;
if Vf>50, the clear threshold is 50, and the clear threshold is Vf。
If Vm=20,VfThe traffic state is still divided by the initial threshold 50.
According to the corrected traffic jam threshold value of the elevated road, the traffic jam level of the section of the elevated road can be determined, so that a traffic manager can conveniently perform further detailed management. Specifically, as shown in table 2:
TABLE 2
Table 2 is a table of correspondence between traffic congestion correction threshold values and traffic congestion levels on elevated roads.
Example 1
1) Dividing the elevated road into an entrance ramp, an exit ramp and an elevated road section according to the entrance ramp and exit ramp positions of the elevated road, and selecting a section of the elevated road section as a detection object;
acquiring traffic flow and vehicle speed data detected by the microwave radar detector of the selected elevated road section as follows:
(32,71),(24,73),(36,69),…(30,65),…(198,27);
the statistical period was 5 minutes, resulting in 288 pairs of data acquired during the day.
2) And calculating the traffic flow and the vehicle average speed in one acquisition period (namely 1h) of the section according to the traffic flow and the vehicle speed data of the elevated road section:
namely:
the 1h traffic flow is the sum of the traffic flows of each 5 minutes in the hour;
the 1h vehicle average speed is the average of all vehicle speeds in that hour.
For example, the traffic flow between sample 0 and 1 is:
32+24+36+……+30=158pcu/h;
the average vehicle speed between sample 0 and 1 is:
(32 × 71+24 × 73+ … … +30 × 65)/158 ═ 65km/h, and so on.
3) And taking the traffic flow and the average speed of vehicles corresponding to all the acquisition periods in one day as a sample set, wherein the sample set comprises the following steps:
Q={(x,y)|x=158,111,60,35,25,40,......185;y=65,70,75,81,80,81,......70}
4) drawing a scatter diagram of the traffic basic diagram according to the traffic flow and the vehicle average speed data in the sample set, wherein the scatter diagram is shown in FIG. 3; wherein the X-axis of fig. 3 is the average vehicle travel speed in each acquisition period within 24h, and the Y-axis is the traffic flow in each acquisition period corresponding to the X-axis within 24 h.
5) Calculating a regression coefficient beta from the traffic flow and the vehicle average speed data in the sample set by using a mathematical regression equation model as shown in FIG. 40、β1、β2And counting errors, and carrying out numerical value substitution to finally obtain the following formula:
X=387.716-0.399(Y)2+25.743Y+0.0000102
calculating the average critical vehicle speed VmSmooth vehicle speed VfThe following are:
5) and further, according to the national road traffic state information release specification (GA/T994-2012), determining the initial threshold values of the traffic jam levels of the elevated roads to be 20km/h and 50 km/h.
6) Comparison Vm、VfAnd the corrected threshold values are 20km/h, 32.26km/h, 50km/h and 64.5 km/h.
7) And estimating the traffic jam levels of the elevated road sample sections according to the table 3 according to the corrected traffic jam threshold as follows:
TABLE 3 sample road segment traffic congestion level Table
Traffic congestion level | Is very unblocked | Is unblocked | Slow moving | Congestion of the earth | Congestion |
Traffic congestion threshold | ≥64.5 | 50≤v<64.5 | 32.26≤v<50 | 20≤v<32.26 | <20 |
According to the table 3, the traffic jam grade corresponding to each sampling period of the sample road section can be known, and the traffic management department can take corresponding traffic measures according to different grades according to the management requirements.
Claims (3)
1. A method for calculating a traffic jam critical value of an elevated road section based on a traffic basic map is characterized by comprising the following steps:
1) according to the positions of the exit ramp and the entrance ramp of the elevated road, the elevated road section is defined by the elevated road connecting the adjacent exit ramp and the entrance ramp; acquiring equipment data of a microwave radar detector on each elevated road section, wherein the data at least comprises elevated road section traffic flow data and vehicle running speed data;
2) determining an acquisition cycle, and calculating the traffic flow and the vehicle average speed of each road section in each acquisition cycle according to the traffic flow and the vehicle speed data of the road section of the elevated road;
3) and taking the traffic flow and the average speed of the vehicles corresponding to all the collection periods in one day as a sample set, and recording as follows:
Q={(x,y)|x=x1,x2......xn;y=y1,y2......yn},
wherein,
x represents an elevated road segment traffic flow;
y represents the average vehicle speed of the elevated road section in km/h;
4) drawing a scatter diagram of the traffic basic diagram according to the traffic flow and the vehicle average speed data in the sample set;
5) and returning the equation X to beta by using the basic flow-speed diagram0+β1(Y)2+β2Y +, according to the traffic flow and vehicle average speed data in the sample set, inputting the data into a regression equation calculation model to obtain a regression coefficient beta0、β1、β2And statistical errors;
according to the mathematical meaning of the regression curve, the value corresponding to the curve vertex is the maximum traffic flow and the critical vehicle speed value, and the regression equation of the flow-speed basic diagram is converted into the following formula:
when gettingWhen the value is 0, the value Y is reversely deduced to obtain the average critical vehicle speed V under the condition of the maximum traffic flow corresponding to the curve vertexm(ii) a Substituting the regression coefficients and the statistical errors into a regression equation to calculate and obtain the average critical vehicle speed V of the section when the maximum traffic flow of the section of the elevated road is obtainedmSmooth vehicle speed VfThe calculation formula is as follows:
wherein, VmAnd VfThe units of (A) are km/h.
2. The method for calculating the traffic congestion threshold value of the elevated road section based on the traffic basic map as claimed in claim 1, wherein: in the step 1), the device data of the microwave radar detector further includes current device number data, number data of a located position, and name ID data of a current located traffic road section.
3. The method for calculating the traffic congestion threshold value of the elevated road section based on the traffic basic map as claimed in claim 1, wherein: in the step 2), one acquisition period is one hour; the traffic flow is the total number of cars passing through the traffic road section in each hour, and the average speed of the vehicles is the average value of the running speeds of all the vehicles in the collection period.
Priority Applications (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN201510524253.3A CN105046963B (en) | 2015-08-21 | 2015-08-21 | The critical value calculating method of overpass road section traffic volume congestion based on traffic parent map |
Applications Claiming Priority (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN201510524253.3A CN105046963B (en) | 2015-08-21 | 2015-08-21 | The critical value calculating method of overpass road section traffic volume congestion based on traffic parent map |
Publications (2)
Publication Number | Publication Date |
---|---|
CN105046963A true CN105046963A (en) | 2015-11-11 |
CN105046963B CN105046963B (en) | 2017-07-28 |
Family
ID=54453469
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
CN201510524253.3A Active CN105046963B (en) | 2015-08-21 | 2015-08-21 | The critical value calculating method of overpass road section traffic volume congestion based on traffic parent map |
Country Status (1)
Country | Link |
---|---|
CN (1) | CN105046963B (en) |
Cited By (5)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN105702031A (en) * | 2016-03-08 | 2016-06-22 | 北京航空航天大学 | Macroscopic fundamental diagram-based road network key section identification method |
CN107176163A (en) * | 2016-03-11 | 2017-09-19 | 福特全球技术公司 | The method and apparatus that congestion is reduced by cooperating adaptive learning algorithms |
CN107895481A (en) * | 2017-11-21 | 2018-04-10 | 福建工程学院 | Area road wagon flow amount control method based on floating car technology |
CN110232237A (en) * | 2019-06-11 | 2019-09-13 | 北京航空航天大学 | A kind of evacuation vehicle flowrate distribution model based on traffic parent map |
CN112630770A (en) * | 2020-12-02 | 2021-04-09 | 北京首科丰汇科技有限公司 | Method and device for evaluating service quality of expressway |
Citations (3)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
EP1895485A1 (en) * | 2006-08-31 | 2008-03-05 | Hitachi, Ltd. | Road congestion detection by distributed vehicle-to-vehicle communication systems |
CN104464295A (en) * | 2014-12-17 | 2015-03-25 | 合肥革绿信息科技有限公司 | Intelligent traffic control method and device for elevated road entrance ramps based on video |
CN104809869A (en) * | 2015-04-10 | 2015-07-29 | 安徽四创电子股份有限公司 | Viaduct entrance ramp traffic state identifying method based on lifting height limiting rack |
-
2015
- 2015-08-21 CN CN201510524253.3A patent/CN105046963B/en active Active
Patent Citations (3)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
EP1895485A1 (en) * | 2006-08-31 | 2008-03-05 | Hitachi, Ltd. | Road congestion detection by distributed vehicle-to-vehicle communication systems |
CN104464295A (en) * | 2014-12-17 | 2015-03-25 | 合肥革绿信息科技有限公司 | Intelligent traffic control method and device for elevated road entrance ramps based on video |
CN104809869A (en) * | 2015-04-10 | 2015-07-29 | 安徽四创电子股份有限公司 | Viaduct entrance ramp traffic state identifying method based on lifting height limiting rack |
Non-Patent Citations (2)
Title |
---|
卢智军: "高速公路混合车流车速及通行能力的仿真研究", 《中国优秀硕士学位论文全文数据库工程科技Ⅱ辑》 * |
高超等: "城市干道交通流速度-流量关系模型研究", 《山东交通学院学报》 * |
Cited By (7)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN105702031A (en) * | 2016-03-08 | 2016-06-22 | 北京航空航天大学 | Macroscopic fundamental diagram-based road network key section identification method |
CN107176163A (en) * | 2016-03-11 | 2017-09-19 | 福特全球技术公司 | The method and apparatus that congestion is reduced by cooperating adaptive learning algorithms |
CN107176163B (en) * | 2016-03-11 | 2021-11-19 | 福特全球技术公司 | Method and apparatus for reducing congestion through cooperative adaptive cruise control |
CN107895481A (en) * | 2017-11-21 | 2018-04-10 | 福建工程学院 | Area road wagon flow amount control method based on floating car technology |
CN110232237A (en) * | 2019-06-11 | 2019-09-13 | 北京航空航天大学 | A kind of evacuation vehicle flowrate distribution model based on traffic parent map |
CN110232237B (en) * | 2019-06-11 | 2021-04-13 | 北京航空航天大学 | Traffic basic diagram-based evacuation traffic flow distribution method |
CN112630770A (en) * | 2020-12-02 | 2021-04-09 | 北京首科丰汇科技有限公司 | Method and device for evaluating service quality of expressway |
Also Published As
Publication number | Publication date |
---|---|
CN105046963B (en) | 2017-07-28 |
Similar Documents
Publication | Publication Date | Title |
---|---|---|
CN105046963B (en) | The critical value calculating method of overpass road section traffic volume congestion based on traffic parent map | |
CN110491154B (en) | Suggested vehicle speed making method based on safety risk and distance | |
CN105303832B (en) | Overpass road section traffic volume congestion index computational methods based on microwave vehicle detector | |
CN101739824B (en) | Data fusion technology-based traffic condition estimation method | |
CN102737504B (en) | Method for estimating bus arrival time in real time based on drive characteristics | |
CN104792937B (en) | Bridge head bump detection evaluation method based on vehicle-mounted gravitational acceleration sensor | |
DK2619059T3 (en) | Driver profiling system and method | |
CN103761430B (en) | A kind of road network peak period recognition methods based on Floating Car | |
CN104680789B (en) | Rapid road congestion index estimation and prediction method | |
CN103198713B (en) | Based on the vehicle regulate and control method of the minimizing traffic hazard of traffic data and weather data | |
DE102015201383A1 (en) | Driving stabilization for a vehicle | |
CN113870570B (en) | ETC-based road network operation state method, system and storage medium | |
CN105139645A (en) | Urban regional road network operation index assessment method based on floating car technology | |
CN105405294A (en) | Early warning method of traffic congestion roads | |
Konbattulwar et al. | Development of in-vehicle noise prediction models for Mumbai Metropolitan Region, India | |
WO2013136778A1 (en) | Device for determining sensitivity to prediction of unexpected situations | |
CN105513362A (en) | Method for evaluating and verifying running state of bus in area adjacent to bus stop | |
CN103198707B (en) | A kind of vehicle regulate and control method based on traffic flow character dangerous under fine day situation | |
CN110867075B (en) | Method for evaluating influence of road speed meter on reaction behavior of driver under rainy condition | |
CN103198709B (en) | Vehicle regulating and controlling method for reducing traffic accidents under raining conditions | |
CN102956109B (en) | Method for judging requirement for arranging external left turn lane at entrance lane of signal intersection | |
CN105931463B (en) | Road section traffic volume operation index calculation method based on traffic scene radar | |
CN102518054B (en) | Road deceleration marked line setting method based on actual deceleration effect | |
CN116740940A (en) | Severe weather high-impact road section risk prediction and safety management method, device and equipment | |
CN106530700A (en) | Method for judging traffic congestion based on fixed detector |
Legal Events
Date | Code | Title | Description |
---|---|---|---|
C06 | Publication | ||
PB01 | Publication | ||
C10 | Entry into substantive examination | ||
SE01 | Entry into force of request for substantive examination | ||
GR01 | Patent grant | ||
GR01 | Patent grant |