WO2016192668A1

WO2016192668A1 - Traffic condition and vehicle travelling time prediction

Info

Publication number: WO2016192668A1
Application number: PCT/CN2016/084693
Authority: WO
Inventors: 刘光明
Original assignee: 刘光明
Priority date: 2015-06-05
Filing date: 2016-06-03
Publication date: 2016-12-08
Also published as: CN104882020B; CN104882020A

Abstract

A method for predicting a traffic condition. The method comprises the following steps: dividing a road on a map into sections (101); acquiring a current traffic condition and an average traffic condition of a corresponding historical time period of each road section (103); calculating a relative traffic condition of each road section based on the current traffic condition and the average traffic condition of the corresponding historical time period of each road section (105); acquiring for each road section an average historical traffic condition corresponding to a future time period (107); estimating for each road section a future traffic condition based on the average historical traffic condition corresponding to the future time period and the relative traffic condition of each road section (109); and displaying the estimated future traffic condition of each road section on the map (111). The method is applicable to a vehicle travelling time prediction method, comprising: estimating, based on a traffic condition of each road section at an estimated arrival time, a vehicle travelling time for each road section of each candidate vehicle route (215); and estimating, according to the vehicle travelling time for each road section of each candidate vehicle route, a total vehicle travelling time (217).

Description

Forecast traffic conditions and travel time

Technical field

The present invention relates to maps and navigation, and more particularly to predicting traffic conditions and travel times.

Background technique

Currently, electronic maps are widely used in mobile applications or desktop applications. As long as the network supports it, people can view the electronic map anytime, anywhere and find the destination they want to know. The current traffic conditions can be displayed on the electronic map. For example, green represents a smooth passage segment, yellow represents a slow-moving section, and red represents a congested section. When people are driving, they can refer to the traffic conditions displayed on the map. On the one hand, they can have certain psychological expectations for the trip. On the other hand, they can choose a relatively smooth route to avoid congestion.

However, people often look at the map before they travel to understand or plan the trip. In other words, the traffic situation when looking at a map is not equal to the traffic situation when actually traveling to a certain section.

In some electronic navigation applications, multiple candidate driving routes are provided. For these multiple candidate routes, electronic navigation will estimate the time that may be needed for people to refer to when selecting a route. However, the estimated time for electronic navigation is generally based on current traffic conditions. Since the traffic condition when the route is selected is not equal to the traffic situation when actually traveling to the road section, the estimated time actually differs from the time taken by the route when actually traveling.

Summary of the invention

In view of the above, it is desirable to include elements in the map that predict traffic conditions in the future. Moreover, when people choose a driving route, they can provide predictions of future traffic conditions to more accurately estimate the travel time spent for reference.

According to an aspect of the present invention, there is provided a method of embodying a predicted traffic condition on a map, comprising the steps of: segmenting a road on a map; and obtaining a current intersection of each of the segmented roads Average traffic conditions over the same period of history; historical traffic conditions based on current traffic conditions and historical average traffic conditions; calculation of relative traffic conditions of each segmented road; acquisition of historical average traffic conditions of future time of each segmented road; The history of the future time is the average traffic situation and relative traffic conditions, estimating the traffic conditions of the future time of each segmented road; and presenting the estimated traffic conditions of the future time of each segmented road on the map.

Preferably, the traffic condition is a traffic speed, and the relative traffic conditions of the respective segmented roads are calculated by comparing the current traffic speed with the historical average transit speed.

Preferably, the traffic condition is a congestion index, and the relative traffic condition of each segmented road is calculated by comparing the current congestion index with a historical average average congestion index.

Preferably, the traffic conditions of the future time of each of the segmented roads are estimated by multiplying the historical average traffic conditions of the future time of each of the segmented roads by the relative traffic conditions.

Preferably, the segmented roads on the map with different traffic conditions are presented in different colors.

According to another aspect of the present invention, a method for predicting travel time is provided, comprising the steps of: identifying one or more candidate driving routes on a map according to a departure place and a destination; and classifying each candidate driving route a segment; obtaining current traffic conditions and historical average traffic conditions of each segmented road of each candidate driving route; calculating each candidate based on current traffic conditions of each segmented road of each candidate driving route and historical average traffic conditions during the same period Relative traffic conditions of each segmented road of the driving route; estimating the time of arrival of each segmented road in each route according to the current traffic condition; obtaining the historical average traffic condition of each segmented road at the estimated time of arrival; The historical average traffic condition and relative traffic conditions of the segmented road at the estimated time of arrival, estimating the traffic conditions of the various segmented roads at the estimated time of arrival; based on the traffic conditions of the respective segmented roads at the estimated time of arrival, Estimate the driving of each segmented road for each candidate driving route Room; and the total estimated travel time according to the driving time for each road segment for each of the candidate route.

Preferably, the traffic condition is a traffic speed, by averaging the current traffic speed with history The average traffic speed is compared to calculate the relative traffic conditions of each segmented road.

Preferably, the traffic conditions of the respective segmented roads at the estimated time of arrival are estimated by multiplying the historically averaged traffic conditions of the respective segmented roads at the estimated time of arrival with the relative traffic conditions.

Preferably, the total travel time of each candidate driving route is obtained by adding the travel times of the respective divided roads of each of the candidate driving routes.

DRAWINGS

The invention will now be described in connection with the embodiments with reference to the accompanying drawings. In the drawing:

1 is a flow chart of a method of embodying a predicted traffic condition on a map in accordance with an embodiment of the present invention.

2 is a flow chart of a method of predicting travel time in accordance with an embodiment of the present invention.

detailed description

Specific embodiments of the present invention will be described in detail below.

1 is a flow chart 100 of a method of embodying a predicted traffic condition on a map in accordance with an embodiment of the present invention.

According to FIG. 1, in step 101, the road on the map is first segmented. The current electronic maps basically segment the roads on the map to indicate different traffic conditions. For example, the segmentation of the road may be based on distance, for example, every 1 km or every 500 meters, 100 meters, 50 meters, 10 meters, or any other suitable distance as a segment; the segmentation of the road may also be based on the setting of the traffic light, for example, The road between every two (or more) traffic lights is a segment; the segmentation of the road can also be based on the planning of the block, for example, each block, the road between each intersection as a segment. In theory, the finer the road segment, the more accurate the traffic situation reflected, but At the same time, the requirements for the calculation and storage of electronic maps are higher. In addition, it should be noted that the segmentation criteria for roads may be different on the same road or on the same route. Therefore, some sections are 500 meters and some sections are 1 km.

In step 103, the current traffic condition of each segment road and the historical average traffic condition are obtained.

There are many ways to get traffic on a road. For example, the speed of the car passing through the section in a certain period of time, the number of cars passing through the end of the section in a certain period of time, and the like are examined. According to different ways, the physical quantity reflecting the traffic condition may be the driving speed or the congestion index. For example, taking the speed as the physical quantity reflecting the traffic situation, the speed of 40-60 km per hour can be considered as smooth. The speed of 20-40 km per hour can be considered as slow driving. The speed of 20 km or less can be considered as congestion. The speed of 5 km or less can be considered as serious. Congestion, and so on. In another example, the congestion index is used as the physical quantity reflecting the traffic situation. For example, a congestion index of 0-10 can be used. The larger the congestion index, the more congested the traffic situation; conversely, the smaller the congestion index, the more the traffic condition is. unobstructed. The congestion index may be obtained based on the traveling speed of the car passing through the road section within a certain period of time, or may be obtained based on the number of cars connected to each other through the end of the road section within a certain period of time.

In step 103, the current traffic condition, such as the traffic speed or congestion index of the road section, can be obtained through public real-time data measured by the local traffic jurisdiction. At the same time, according to historical big data, the average traffic condition of the road section in the historical period, such as the average traffic speed or average congestion index of the road section during the period, can be found.

Let's explore the concept of "history of the same period". In general, the historical period can be the same time or the same time period on the same day of the same month on the Gregorian calendar. For example, it is also the time of 18:00-18:15 on June 1. The same period of history can also be in the lunar calendar. For example, the time of 12:00-12:15 on Lunar New Year's Eve, the time of 17:00 or 17:00-17:15 of Mid-Autumn Festival (August 15th). The concept of the week can also be considered in the same period of history. For example, the time of 16:00 or 16:00-16:15 on Friday. Or, consider the period of 16:00 or 16:00-16:15 of the current day of the holiday, 10:00 or 10:00-10:15 of the day of the holiday. In addition, in cities with tail number restrictions, the impact of tail number limits can also be considered. For example, Beijing Municipality implements the regulation of motor vehicle tail number restriction: motor vehicles follow the tail of the license plate No. One day a week, you cannot travel on the road within the specified time. For example, on Thursdays, the vehicles with tail numbers 4 and 9 were restricted. Because there are very few vehicles with a tail number of 4 in Beijing, resulting in fewer vehicles being restricted this day, congestion is more likely to occur. On Wednesdays, the vehicles with tail numbers 3 and 8 were restricted. Since there are more vehicles with a tail number of 8 in Beijing, resulting in more vehicles being restricted this day, it is likely to be smooth all the way. Since the rule of the tail number limit is rotated every once in a while (for example, 3 months), it is not enough to simply consider the concept of the week. It is also necessary to consider the rotation of the tail limit rule (for example, 4, 9 limit and Monday morning peak) Or the collateral combination on Friday night will increase the traffic burden), in order to calculate the so-called historical average traffic situation under the same factor (the tail number is the same and there are no other influencing factors). In addition, you can also consider the school's winter and summer vacation time, due to the lack of parental pick-up traffic, the positive impact on traffic conditions.

In addition, “contemporary” also refers to the concept of “simultaneous” or “simultaneous segment”. In the present invention, time can refer to a specific moment. The time period may refer to a time period of 5 minutes, 10 minutes, 15 minutes, or any other suitable time period. Similar to the theory of road segmentation, the finer the time period, the more accurate the traffic conditions reflected, but at the same time the higher the requirements for the calculation and storage of electronic maps.

Another concept worth exploring is "average." Historical big data can range from 1 year, 2 years, 3 years, 5 years, or any other suitable time. However, as the number of motor vehicles continues to grow, the longer historical range is less practical. A longer historical range is appropriate once the number of vehicles reaches a peak or balance. The average traffic condition can be the average of the traffic conditions values for the same period in the historical range. For example, on a certain road segment, there are 3 more speed records during the last 3 years from June 1st to 18:00-18:15 (1 year ago, 2 years ago, 3 years ago, June). On the 1st, 18:00-18:15 speed of the time), the average of these three speeds is averaged, and the average traffic condition (average traffic speed) of the historical section of the road section is obtained. In addition, the historical average traffic situation during the same period can also be the average congestion index. For example, on a road segment, there are a total of 30 congested index records for each Friday 18:00-18:15 period in the last year (although there are 52 weeks in 1 year, but some special circumstances are screened out). On Friday, for example, on holidays (no congestion), or before holidays (especially congested), about 30 meaningful records are available for reference. By averaging the 30 congestion indices, you get the road score. Average historical traffic conditions (average congestion index) for the same period in the segment.

At step 105, the relative traffic conditions of the various segmented roads are calculated based on the current traffic conditions and the historical average traffic conditions. In one embodiment, the current traffic conditions are compared to historical average traffic conditions to calculate the relative traffic conditions for each of the segmented roads. For example, the relative traffic condition may be a ratio of speeds, that is, the current transit speed is compared with the historical average transit speed, and the obtained ratio is a relative speed index. When the relative speed index is in the range of 1±a (a can take 20%, 10%, 5%, etc. or any other suitable value), it can be considered that the current traffic situation is not much different from the historical period. When the relative speed index is less than 1-a, the road section is more congested than the historical period; when the relative speed index is greater than 1+a, the road section is more smooth than the historical period. Similarly, the relative traffic condition may be the ratio of the congestion index (between 0 and 10, the larger the value indicates the more congested), that is, the current congestion index is compared with the historical average congested index, and the obtained ratio is the relative congestion index. When the relative congestion index is in the range of 1±b (b can take 20%, 10%, 5%, etc. or any other suitable value), it can be considered that the current traffic situation is not much different from the historical period. When the relative congestion index is less than 1-b, the road section is more smooth than the historical period; when the relative speed index is greater than 1+b, the road section is more congested than the historical period.

At step 107, historical average traffic conditions of future time of each segmented road are obtained.

In general, users want to predict traffic conditions in future or future time periods, such as predicting traffic conditions after 30 minutes. If the current time is 16:00, the user wants to predict the traffic conditions after 30 minutes, ie 16:30 or 16:30-16:45, then the time of each segment is 16:30 or 16:30-16:45. The average traffic situation in the same period of history.

At step 109, traffic conditions for future time of each segmented road are estimated based on historical average traffic conditions and relative traffic conditions for future time of each segmented road.

In one embodiment, traffic conditions for future time of each segmented road are estimated by multiplying historical average traffic conditions of future time of each segmented road by relative traffic conditions.

The historical average traffic conditions during the same period here refer to the average traffic conditions over the same period of history in the future. For example, although it is now a time of 16:00 or 16:00-16:15, since the user specifies a traffic condition after 30 minutes of prediction, the step 109 uses 16:30 or 16:30-16:45. The average traffic situation during the same period of history. However, the relative traffic conditions here refer to the relative traffic conditions of the current time period, that is, the ratio of the current traffic conditions of the time period of 16:00 or 16:00-16:15 to the average traffic conditions of the historical period. Therefore, here is actually an assumption that the current relative traffic conditions are roughly the same as the relative traffic conditions of the future time (after 30 minutes).

For example, for a segmented road, a traffic condition of 16:30 is predicted at 16:00, and can be multiplied by a historical average traffic condition of 16:30 (for example, a speed of 30 km/h or a congestion index of 4.0). The relative traffic conditions (eg 1.2 or 0.8) measured at 16:00, thus an estimated traffic situation of 16:30 (eg 36 km/h or 3.2 congestion index).

At step 111, the estimated traffic conditions for the future time of each of the segmented roads are presented on the map. Through the above steps, each segmented road on the map estimates its own traffic conditions in the future. These predicted traffic conditions need to be presented on the map. Among them, for the segmented roads with different traffic conditions, different presentations are made on the map. In one embodiment, the segmented roads on the map with different predicted traffic conditions are presented in different colors. Those skilled in the art will appreciate that the presentation may be in addition to color, grayscale, texture, shading, flicker, or even a audible cue, a voice cue, a pitch change, or a tactile representation.

Through the method of flowchart 100 of Figure 1, it is easier for people to understand the traffic conditions by viewing the map. For example, when users choose to view traffic conditions, they can choose to view the current traffic conditions, or they can choose to view predicted traffic conditions at a certain time or a certain time in the future. In this way, people can have certain psychological expectations for future travel, and can also plan or adjust their time and itinerary according to the forecast.

2 is a flow chart 200 of a method of predicting travel time in accordance with an embodiment of the present invention.

According to FIG. 2, in step 201, one or more candidate driving routes are identified on the map based on the departure place and the destination. At present, many electronic maps have the functions of travel planning or driving navigation. In addition, the car navigation system also has the functions of travel planning or driving navigation. One or several candidate driving routes are identified on the map according to the destination selected by the user and the current location of the user (departure place) or the departure place specified by the user. For example, identify route 1, route 2, route 3 Wait for three driving directions.

At step 203, each candidate driving route is segmented. At step 205, the current traffic condition and the historical average traffic condition of each segment of each candidate driving route are obtained.

Regarding the manner of obtaining the current traffic condition and the historical average traffic condition of each segment of each candidate driving route, reference may be made to the specific discussion of step 103 in the flowchart of FIG.

At step 207, a relative traffic condition of each segment of each candidate driving route is calculated based on the current traffic condition of each segment of each candidate driving route and the historical average traffic condition. In one embodiment, the traffic condition is a traffic speed, and the relative traffic conditions of the respective segmented roads are calculated by comparing the current traffic speed with a historical average average traffic speed. In another embodiment, the traffic condition is a congestion index that is calculated by comparing a current congestion index to a historical average average congestion index. Reference may be made to the specific discussion of step 105 in the flow chart of FIG.

At step 209, the time to reach each of the segmented roads in each route is estimated based on the current traffic conditions. Existing electronic navigation applications have corresponding functions. In fact, it is equivalent to let e-navigation calculate the time required from the starting point to each segmented road according to the current traffic conditions. For example, if there are 10 segmented roads in a candidate route, the required roads from the starting point to the 2nd, 3rd, ..., 10th segment roads are calculated according to the current traffic conditions of each segmented road. time. For example, it takes 10 minutes, 20 minutes, ..., 70 minutes, respectively.

At step 211, historical average traffic conditions for each of the segmented roads at the estimated time of arrival are obtained.

The above example of 10 segmented roads is still used. It is possible to obtain historical average traffic conditions of the second, third, ..., and tenth segment roads after 10 minutes, 20 minutes, ... 70 minutes, respectively. See the discussion of step 107 in the method flow diagram of FIG.

At step 213, based on the historical average period of the estimated time of arrival of each segmented road Through the traffic conditions and the relative traffic conditions, the traffic conditions of the various segmented roads at the estimated time of arrival are estimated.

In one embodiment, the traffic conditions of the respective segmented roads at the estimated time of arrival are estimated by multiplying the historically averaged traffic conditions of the respective segmented roads at the estimated time of arrival with the relative traffic conditions.

The above example of 10 segmented roads is still used. The historical average traffic conditions of the first, second, third, ..., 10th segment roads at the current, 10 minutes, 20 minutes, ..., 70 minutes have been obtained. For example, the average vehicle speed is 40, 40, 30, ..., 50 km/h, respectively, or the average congestion index is 4.0, 4.0, 4.8, ..., 3.0, respectively. The current relative traffic conditions of these segmented roads are 1.0, 1.1, 1.2, ..., 1.2 (relative vehicle speed) or 1.0, 0.9, 0.8, ..., 0.8 (relative congestion). Therefore, the traffic conditions of each segmented road at the estimated time of arrival can be estimated as follows:

The first segmented road: current - speed 40*1.0 = 40 km / h, congestion index 4.0 * 1.0 = 4.0;

The second segmented road: after 10 minutes - estimated speed 40*1.1 = 44 km / h, estimated congestion index 4.0 * 0.9 = 3.6;

The third segment road: after 20 minutes - estimated speed 30*1.2 = 36 km / h, estimated congestion index 4.8 * 0.8 = 3.84;

......

The 10th segmented road: After 70 minutes - estimated speed 50*1.2 = 60 km / h, estimated congestion index 3.0 * 0.8 = 2.4.

Therefore, here is actually an assumption that the current relative traffic conditions are roughly the same as the relative traffic conditions of the future time (10, 20, ..., 70 minutes).

At step 215, the travel time of each of the segmented roads of each of the candidate driving routes is estimated based on the traffic conditions of the respective segmented roads at the estimated time of arrival.

For example, dividing the length of each segmented road by the estimated arrival estimated in step 213, respectively. At the time of the speed of the vehicle, the estimated travel time of each segmented road is obtained. Alternatively, the estimated travel time of each segmented road can also be obtained based on the congestion index of the length of each segmented road and the estimated time of arrival estimated in step 213. For example, the above example of 10 segmented roads is still used, and the driving times of the first, second, third, ..., and 10th roads are 10 minutes, 8 minutes, and 9 minutes, respectively. ,……,5 minutes.

At step 217, the total travel time is estimated based on the travel time of each of the segmented roads of each of the candidate travel routes.

The total travel time of each candidate driving route is obtained by adding the travel times of the respective divided roads of each of the candidate driving routes. For example, the following example of 10 segmented roads is still used, and the travel times of the first, second, third, ..., and 10th segment roads are respectively added to obtain N=10+8+ 9+...+5. The total travel time for each candidate driving route is N minutes.

On some electronic navigation applications, one or more candidate driving directions are provided. For this or more candidate routes, e-navigation estimates the time that may be needed for people to refer to when selecting a route. However, the estimated time for electronic navigation is generally based on current traffic conditions. Since the traffic condition when the route is selected is not equal to the traffic situation when actually traveling to the road section, the estimated time actually differs from the time taken by the route when actually traveling.

In view of the above, the present invention enables a prediction of future traffic conditions to be provided when people select a driving route to more accurately estimate the travel time spent for reference.

The embodiments of the present invention have been described above. However, the spirit and scope of the present invention are not limited thereto. Those skilled in the art will be able to make further applications in accordance with the teachings of the present invention and are within the scope of the present invention.

Claims

A method for predicting traffic conditions on a map includes the following steps:

Segment the road on the map;

Obtain the current traffic conditions and historical average traffic conditions of each segmented road;

Calculating the relative traffic conditions of each segmented road based on the current traffic conditions and historical average traffic conditions;

Obtaining historical average traffic conditions for the future time of each segmented road;

Estimating the traffic conditions of the future time of each segmented road based on historical average traffic conditions and relative traffic conditions of future time of each segmented road;

The estimated traffic conditions of the future time of each segmented road are presented on the map.
The method of claim 1, wherein the traffic condition is a traffic speed, and the relative traffic conditions of the respective segmented roads are calculated by comparing the current traffic speed with a historical average average traffic speed.
The method of claim 1, wherein the traffic condition is a congestion index, and the relative traffic conditions of the respective segmented roads are calculated by comparing the current congestion index with a historical average average congestion index.
The method according to claim 1, wherein the traffic conditions of the future time of each of the segmented roads are estimated based on the historical average traffic conditions and the relative traffic conditions of the future time of each of the segmented roads, including: by The history of the future time is the same as the average traffic situation and the relative traffic conditions to estimate the traffic conditions of the future time of each segmented road.
The method of claim 1, wherein presenting the calculated traffic conditions of the future time of each of the segmented roads on the map comprises presenting the segmented roads on the map having different traffic conditions in different colors.
A method of predicting travel time includes the following steps:

Identify one or more candidate driving routes on the map based on the departure place and destination;

Segment each candidate driving route;

Obtaining the current traffic conditions and historical average traffic conditions of each segmented road of each candidate driving route;

Calculating the relative traffic conditions of each segmented road of each candidate driving route based on the current traffic condition of each segmented road of each candidate driving route and the historical average traffic condition;

Estimating the time of arrival of each segmented road in each route based on current traffic conditions;

Obtaining historical average traffic conditions for each segmented road at the estimated time of arrival;

Estimating traffic conditions of each segmented road at an estimated time of arrival based on historical average traffic conditions and relative traffic conditions of each segmented road at estimated time of arrival;

Estimating the travel time of each segmented road of each candidate driving route based on the traffic conditions of the respective segmented roads at the estimated time of arrival;

The total travel time is estimated based on the travel time of each segmented road of each candidate driving route.
The method of claim 6, wherein the traffic condition is a traffic speed, and the relative traffic conditions of the respective segmented roads are calculated by comparing the current traffic speed with a historical average average traffic speed.
The method of claim 6, wherein the traffic condition is a congestion index, and the relative traffic conditions of the respective segmented roads are calculated by comparing the current congestion index with a historical average average congestion index.
The method according to claim 6, wherein the traffic conditions of the respective segmented roads at the estimated time of arrival are estimated based on historical average traffic conditions and relative traffic conditions of the estimated time of arrival of the respective segmented roads, including: The traffic conditions of the respective segmented roads at the estimated time of arrival are estimated by multiplying the historical average traffic conditions of the respective segmented roads at the estimated time of arrival with the relative traffic conditions.
The method according to claim 6, wherein estimating the total travel time based on the travel time of each of the divided roads of each of the candidate travel routes comprises: adding the travel times of the respective divided roads of each of the candidate travel routes Get the total travel time of each candidate driving route.