CN105894825A - Flow sensor-based urban road occupancy calculating method - Google Patents

Flow sensor-based urban road occupancy calculating method Download PDF

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Publication number
CN105894825A
CN105894825A CN201510304349.9A CN201510304349A CN105894825A CN 105894825 A CN105894825 A CN 105894825A CN 201510304349 A CN201510304349 A CN 201510304349A CN 105894825 A CN105894825 A CN 105894825A
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vehicle
road
length
calculated
urban road
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夏莹杰
单振宇
吴佳雯
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Hangzhou Yuantiao Technology Co Ltd
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Hangzhou Yuantiao Technology Co Ltd
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Abstract

The invention discloses a flow sensor-based urban road occupancy calculating method and belongs to the field of intelligent traffic research. The method comprises the following steps: (1) vehicle flow quantity data is collected; (2) a vehicle quantity is standardized based on vehicle models; (3) a vehicle traveling length is calculated based on product of a road speed limit and an observation time length, vehicle safety headway is calculated; an effective vehicle traveling length is calculated; according to the effective vehicle traveling length, the vehicle safety headway and a standard vehicle length, a theoretical maximum vehicle flow quantity is calculated; (4) according to the calculated theoretical maximum vehicle flow quantity and a quantity of standardized vehicles that actually pass, urban road occupancy can be obtained in an observation time period via formula calculation based on an urban road occupancy calculating method. Via use of the flow sensor-based urban road occupancy calculating method, the urban road occupancy can be accurately and automatically calculated.

Description

A kind of computational methods of urban road occupation rate based on flow transducer
Technical field
The present invention relates to the computational methods of a kind of urban road occupation rate based on flow transducer, belong to intelligent transportation system research Category.
Background technology
Roadway occupancy represents in specific time period, and road (section) is by the ratio of traffic participant usage amount Yu total amount.Road Occupation rate has reacted the busy situation of road occupation, is conducive to intuitively to traveler, vehicle supervision department and Town Planning Division Door represents urban road service condition, is the important component part of intelligent transportation system.
The computational methods of conventional roadway occupancy are divided into time and two kinds of space.In time-based method, vehicle is used to lead to Cross the aggregate-value of time and the ratio calculation roadway occupancy of observation duration.In this kind of method, cumulative each vehicle is needed to pass through The time of road cross section, but the sensor on current urban road is bigger by time time error at each car of measurement.Based on sky Between occupation rate method in, use the effective area that occupies of vehicle and the ratio calculation roadway occupancy of the road gross area (length). In this kind of method, need to calculate the area that each car occupies, can directly measure what vehicle in section occupied currently without sensor Area.In a word, above two method is used to be difficult to accurately, automatically obtain corresponding sensing data.This patent uses flow to pass The vehicle flowrate data that sensor gathers, by the space roadway occupancy computational methods optimized, automatically calculate urban road occupation rate.
At present, the flow transducer being deployed in urban road can obtain the number of vehicles of road the most automatically.Flow Sensor refers to automatically to detect in certain time period by single track, a certain section or the sensing of whole tracks number of vehicles Device.In current intelligent transportation system, conventional flow transducer includes that microwave detector, ground induction coil and bayonet socket shooting are first-class.
The patent relating to flow transducer includes " a kind of traffic flow detector based on geomagnetic induction coil ", the Shu Xiao that Chen Ting etc. writes " a kind of traffic flow detectors " that " traffic flow detector " write, Qin great Hai write etc., these patents relate generally to flow and pass The design of sensor and organizational composition.This patent is to analyze the vehicle flowrate data that flow transducer gathers, and the model of these patent protections Enclose difference.
Time of driver's reaction refers to when driver finds emergency until the time interval before stepping on braking action claims, at English In " highway code " of state, the response time of driver is set to 0.68 second, is referred to as " thinking time ".
With theory of speeding is to use dynamic method, when probing into convoy on the single track that cannot overtake other vehicles, rear car is followed The transport condition of front truck, and express by mathematic(al) mode and analyzed a kind of theory illustrated, sentencing of train tracing model marginal value Surely it is a key in vehicle follow gallop research, in external research, " HCM " rule of U.S.'s version in 1994 When settled time headway is less than or equal to 5s, vehicle is in train tracing model;Sven Maerivoet and Bart De Moor writes " Traffic Flow Theory " thinks that with speeding on as occurring at two car space headways be in the range of 0~100m or 0~125m; The research of Weidman is then thought when space headway is less than or equal to 150m, and vehicle is in train tracing model.
Accident-free vehicle spacing refers in the string fleet travelled in the same direction on a track, front and back between Adjacent vehicles, and a rear car car Distance between head and previous the car tailstock.
Summary of the invention
In order to overcome in existing road occupation rate computational methods, it is more difficult to obtaining the situation of corresponding sensing data, the present invention proposes one Plant the computational methods of urban road occupation rate based on flow transducer.In the case of accurately obtaining road traffic, the method It it is a kind of effectively approximation of space occupancy result of calculation.
The scheme provided to solve above-mentioned technical problem is:
The computational methods of a kind of urban road occupation rate based on flow transducer, said method comprising the steps of:
(1) collecting vehicle data on flows.Flow transducer is used to collect the vehicle flowrate data (Q) in observation duration (T) interior section. This method can use microwave detector, ground induction coil and bayonet socket to image the first-class flow transducer being deployed in urban road;
(2) standardized vehicle number.The variable lengths of dissimilar vehicle, the most different to the occupied area of road, need standard Change.This method using the Vehicle length of car as full-length.For three kinds of common vehicle types another in urban road: bus and Passenger vehicle is 2.4 times of full-lengths, and lorry is 2 times of full-lengths, and by manually adding up on road, the ratio of bus is a, The ratio of passenger vehicle is b, and the ratio of lorry is c, and the ratio of car is d.The then number of vehicles after normalized, particularly as follows:
Ql=2.4*Q*a+2.4*Q*b+2*Q*c+1*Q*d;Formula (1)
In formula, QlFor the number of vehicles after the standardization in observation duration (T) interior section;Q is the wagon flow in observation duration (T) interior section Amount data;A is the ratio of bus;B is the ratio of passenger vehicle;C is the ratio of lorry;D is the ratio of car;
(3) road theoretical maximum vehicle flowrate is calculated.When all vehicles travel with train tracing model, then after a period of time, from first Car is to the distance of last car, and namely effective road length of vehicle can be equal to the Vehicle length of each car and vehicle Accident-free vehicle spacing sum, can calculate theoretical maximum vehicle flowrate accordingly.Concretely comprise the following steps:
A) according to road speed limit (V) and observation duration (T), the road length (L of vehicle is calculatedt), particularly as follows:
Lt=V*T;Formula (2)
In formula, LtRoad length for vehicle;V is road speed limit, and such as, the designed driving speed of one-level road is 60-80km/h, The designed driving speed of secondary road is 40-60km/h, and the designed driving speed of three grades of roads is 30-40km/h, level Four road Designed driving speed is 30km/h;T is observation duration;
B) the accident-free vehicle spacing (L of vehicle is calculatedd), in the case of all vehicles all travel with road speed limit, the safety of two cars Following distance should be reaction distance, particularly as follows:
Ld=V*t;Formula (3)
In formula, LdAccident-free vehicle spacing for vehicle;V is road speed limit;T is driver's response time in case of emergency;
C) effective road length (L) is calculated, particularly as follows:
L=Lt+Lr;Formula (4)
In formula, L is effective road length of vehicle;LtRoad length for vehicle;LrTotal length for road;
D) according to effective road length (L), the accident-free vehicle spacing (L of vehicled) and standard vehicle length (Lcar), calculate reason Maximum vehicle flowrate (the Q of opinionm), particularly as follows:
Q m = L L car + L d * t 1 T 1 ; Formula (5)
In formula, QmFor in observation time section, the maximum vehicle flowrate that road can pass through in theory;L is effective road length of vehicle;Lcar For standard vehicle length;LdFor accident-free vehicle spacing;T1A cycle for traffic lights;t1For in the cycle of traffic lights, green Time shared by lamp.
If road speed limit changes, theoretical maximum vehicle flowrate need to recalculate, and otherwise this process is without repeating;
(4) roadway occupancy is calculated.Road theoretical maximum vehicle flowrate (Q obtained by calculatingm) and road is actual passes through Standardized vehicle number (Ql) utilize the computational methods of urban road occupation rate to calculate, obtain observing the road, city of period Road occupation rate (U).Particularly as follows:
U = Q l Q m ; Formula (6)
In formula, U is the urban road occupation rate of observation period;QlFor observing in the period, the actual standardized vehicle number passed through of road; QmFor observation the period in, the maximum vehicle flowrate that road can pass through in theory.
The invention have the benefit that the present invention proposes the computational methods of a kind of novel urban road occupation rate, it is only necessary to stream The data that quantity sensor provides are as input, and Data Source is simple, quick;The service condition of road can be represented intuitively, for handing over The decision-making of logical administration section and urban planning authority provides data supporting;Can automatically calculate urban road occupation rate, be space A kind of effectively approximation of occupation rate result of calculation.
Accompanying drawing explanation
Accompanying drawing 1 is the flow chart of the urban road occupation rate computational methods of the embodiment of the present invention;
Detailed description of the invention
Below in conjunction with drawings and Examples, technical scheme is described in further detail.
(1) collecting vehicle data on flows:
With city of Hangzhou Bei Shanlu-Bao Lu-dawn road ,-Feng Qi road, foundation North Road-stadium road, Wen Yilu-Gu Cuilu-Xueyuan Road, 5 sections such as Qiu Taolu-liberation East Road-Qing Jianglu, a civilian-Feng Tanlu-Gu Dun road, West Road are as data acquisition region, by above 5 Bar section is designated as section 1, section 2, section 3, section 4, section 5, using 07:30-07:35 as data acquisition time section. Flow detector is microwave detector, and it collects vehicle flowrate as source data in these 5 minutes.
(2) standardized vehicle number:
The present embodiment using the Vehicle length of car as full-length.For three kinds of common vehicle types another in urban road: bus Being 2.4 times of full-lengths with passenger vehicle, lorry is 2 times of full-lengths, and by manually adding up on road, the ratio of bus is 20%, the ratio of passenger vehicle is 40%, and the ratio of lorry is 20%, and the ratio of car is 20%.The then car after normalized Number, particularly as follows:
Ql=2.4*Q*20%+2.4*Q*40%+2*Q*20%+1*Q*20%;
In formula, QlFor observing the standardized vehicle number in duration (T) interior section;Q is the wagon flow in observation duration (T) interior section Amount data.Then the standardized vehicle number in above 5 sections is as follows:
(3) road theoretical maximum vehicle flowrate is calculated:
A) road length (L of vehicle is calculatedt), because above 5 sections are major urban arterial highway, its speed limit is 60 (km/h), I.e. 60/3.6 (m/s), 5 minutes again=300 (s), therefore the road length (L of the vehicle in above 5 sectionst) it is:
L t = 60 3.6 * 300 = 500 ( m ) ;
B) the accident-free vehicle spacing (L of vehicle is calculatedd), driver takes 0.68 (s) in the response time in case of emergency.With a) class Seemingly, the accident-free vehicle spacing (L of the vehicle in above 5 sectionsd) it is:
L d = 60 3.6 * 0.68 = 11.33 ( m ) ;
C) calculating effective road length (L), the total length in above 5 sections is as follows:
Then obtain according to formula (4):
L=5000+Lr
In formula, L is effective road length of vehicle;Lt(value is 5000) is the road length of vehicle, LrTotal length for road. Effective road length of the vehicle in above 5 sections is can be obtained fom the above equation:
D) theoretical maximum vehicle flowrate (Q is calculatedm), 5 minutes=300 (s), the full-length of vehicle is 5 meters, by artificial at road On add up, during 07:30-07:35, shared by green light and red light, the ratio of time is 4: 6, then can obtain according to formula (5):
Q m = L 5 + 11.33 * 0.4 * 300 300 ( m )
In formula, QmFor in observation time section, the maximum vehicle flowrate that road can pass through in theory;L is effective road length of vehicle. The then theoretical maximum vehicle flowrate (Q in above 5 sectionsm) as follows:
(4) roadway occupancy is calculated:
Road maximum vehicle flowrate (Q obtained by calculatingm) and the actual standardized vehicle number (Q passed through of roadl) utilize The computational methods of urban road occupation rate calculate, and obtain observing the urban road occupation rate (U) of period.Take formula (6), That is:
U = Q l Q m
In formula, U is the urban road occupation rate of observation period;QlFor observing in the period, the actual standardized vehicle number passed through of road; QmFor observation the period in, the maximum vehicle flowrate that road can pass through in theory.By the standardized vehicle number of above 5 roads with And theoretical maximum vehicle flowrate substitutes into above formula, above 5 roads roadway occupancy during 07:30-07:35 can be obtained as follows:
(5) roadway occupancy is compared:
The occupation rate result that manual video observation track obtains, is typically considered exact value.Will be by manually being existed by video observation Roadway occupancy (the U added up on roadr) compare with the roadway occupancy (U) calculating gained by the method for the present invention As follows:
It follows that the computational methods of urban road occupation rate based on flow transducer are compared with manual video observation, error rate It can be controlled in less than 5%, be a kind of effective automatic calculating method.

Claims (6)

1. the computational methods of urban road occupation rate (U) based on flow transducer, it is characterised in that:
(1) collecting vehicle data on flows;
(2) standardized vehicle number;
(3) road theoretical maximum vehicle flowrate (Q is calculatedm);
(4) the maximum vehicle flowrate (Q that the road obtained by calculating can pass through in theorym) and the actual standardized vehicle number (Q passed through of roadl) utilize the computational methods of urban road occupation rate to carry out formula calculating, obtain observing the urban road occupation rate (U) of period.
2., according in claim 1 (3), calculate road theoretical maximum vehicle flowrate and specifically include that
(1) by the product of road speed limit (V) with observation duration (T), the road length (L of vehicle is calculatedt);
(2) the accident-free vehicle spacing (L of vehicle is calculatedd);
(3) effective road length (L) is calculated;
(4) according to effective road length (L), the accident-free vehicle spacing (L of vehicled) and standard vehicle length (Lcar), calculate theoretical maximum vehicle flowrate (Qm)。
3. according to claim 2 (2), calculate the accident-free vehicle spacing (L of vehicled) method, it is characterised in that: all vehicles all with road speed limit travel in the case of, the accident-free vehicle spacing of two cars should be reaction distance, be specially
Ld=V*t
In formula, LdAccident-free vehicle spacing for vehicle;V is road speed limit;T is driver's response time in case of emergency.
4. according to claim 2 (3), the method calculating effective road length (L), it is characterised in that: according to road length and the road total length of vehicle, calculate effective road length (L), be specially
L=Lt+Lr
In formula, L is effective road length of vehicle;LtRoad length for vehicle;LrTotal length for road.
5. according to claims 2 (4), calculate theoretical maximum vehicle flowrate (Qm) method, it is characterized in that: when all vehicles travel with train tracing model, then after a period of time, distance from first car to last car, namely effective road length of vehicle can be equal to the Vehicle length of each car and the accident-free vehicle spacing sum of vehicle, theoretical maximum vehicle flowrate can be calculated accordingly, be specially
In formula, QmFor in observation time section, the maximum vehicle flowrate that road can pass through in theory;L is effective road length of vehicle;LcarFor standard vehicle length;LdFollowing distance for safety;T1A cycle for traffic lights;t1For in the cycle of traffic lights, the time shared by green light.
6. according to claim 1 (4), the computational methods of urban road occupation rate, it is characterised in that: the maximum vehicle flowrate (Q that the road obtained by calculating can pass through in theorym) and the actual same standard vehicle flow (Q) passed through of road utilize the computational methods of urban road occupation rate to calculate, obtain observe the period urban road occupation rate (U).It is specially
In formula, U is the urban road occupation rate of observation period;QlFor observing in the period, the vehicle flowrate after the actual standardization passed through of road;QmFor observation the period in, the maximum vehicle flowrate that road can pass through in theory.
CN201510304349.9A 2015-06-03 2015-06-03 Flow sensor-based urban road occupancy calculating method Pending CN105894825A (en)

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Cited By (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN111311930A (en) * 2018-12-12 2020-06-19 阿里巴巴集团控股有限公司 Method and device for acquiring traffic flow
CN111696369A (en) * 2020-04-10 2020-09-22 北京数城未来科技有限公司 Whole-city road time-division vehicle type traffic flow prediction method based on multi-source geographic space big data
CN113255469A (en) * 2021-05-06 2021-08-13 南京大学 Method and device for measuring road occupancy of traffic monitoring scene
CN115127562A (en) * 2021-03-26 2022-09-30 深圳联友科技有限公司 Road matching method and device
CN115294776A (en) * 2022-06-23 2022-11-04 北京北大千方科技有限公司 Method, device, equipment and medium for counting vehicle traffic based on time slice

Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2009016773A1 (en) * 2007-07-30 2009-02-05 Shouzou Iwamoto Packet traffic control system
JP2009245042A (en) * 2008-03-31 2009-10-22 Hitachi Ltd Traffic flow measurement device and program
CN102867415A (en) * 2012-09-12 2013-01-09 重庆大学 Video detection technology-based road jam judgement method
CN103700251A (en) * 2013-11-27 2014-04-02 东南大学 Variable speed limiting and ramp control coordination and optimization control method on expressway

Patent Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2009016773A1 (en) * 2007-07-30 2009-02-05 Shouzou Iwamoto Packet traffic control system
JP2009245042A (en) * 2008-03-31 2009-10-22 Hitachi Ltd Traffic flow measurement device and program
CN102867415A (en) * 2012-09-12 2013-01-09 重庆大学 Video detection technology-based road jam judgement method
CN103700251A (en) * 2013-11-27 2014-04-02 东南大学 Variable speed limiting and ramp control coordination and optimization control method on expressway

Non-Patent Citations (1)

* Cited by examiner, † Cited by third party
Title
郑淑鉴,杨敬锋: "国内外交通拥堵评价指标计算方法研究", 《公路与汽运》 *

Cited By (8)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN111311930A (en) * 2018-12-12 2020-06-19 阿里巴巴集团控股有限公司 Method and device for acquiring traffic flow
CN111311930B (en) * 2018-12-12 2022-05-31 阿里巴巴集团控股有限公司 Method and device for acquiring traffic flow
CN111696369A (en) * 2020-04-10 2020-09-22 北京数城未来科技有限公司 Whole-city road time-division vehicle type traffic flow prediction method based on multi-source geographic space big data
CN111696369B (en) * 2020-04-10 2023-04-28 北京数城未来科技有限公司 All-market road time-sharing and vehicle-division type traffic flow prediction method based on multi-source geographic space big data
CN115127562A (en) * 2021-03-26 2022-09-30 深圳联友科技有限公司 Road matching method and device
CN113255469A (en) * 2021-05-06 2021-08-13 南京大学 Method and device for measuring road occupancy of traffic monitoring scene
CN115294776A (en) * 2022-06-23 2022-11-04 北京北大千方科技有限公司 Method, device, equipment and medium for counting vehicle traffic based on time slice
CN115294776B (en) * 2022-06-23 2024-04-12 北京北大千方科技有限公司 Method, device, equipment and medium for counting traffic of vehicles based on time slices

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