WO2016197936A1

WO2016197936A1 - Method for predicting traffic condition and travel time

Info

Publication number: WO2016197936A1
Application number: PCT/CN2016/085202
Authority: WO
Inventors: 刘光明
Original assignee: 刘光明
Priority date: 2015-06-09
Filing date: 2016-06-08
Publication date: 2016-12-15
Also published as: CN104851298A; CN104851298B

Abstract

A method for predicting a traffic condition and travel time, comprising: segmenting roads on a map (101); acquiring a current traffic condition and a previous traffic condition of each of the segmented roads (103); on the basis of the current traffic condition and the previous traffic condition, calculating the traffic condition variation tendency of each of the segmented roads (105); on the basis of the current traffic condition and the traffic condition variation tendency of each of the segmented roads, estimating the traffic condition of a future time of each of the segmented roads (107); and presenting the estimated traffic condition of the future time of each of the segmented roads on the map (109). The method can also be used for predicting travel time, comprising: on the basis of the current traffic condition and the traffic condition variation tendency of each of the segmented roads (211), estimating the traffic condition of each of the segmented roads at an estimated time of arrival, so as to estimate the travel time on each of the segmented roads of each candidate drive route (213); and according to the travel time on each of the segmented roads of each candidate drive route, estimating the total drive time (215).

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 Traffic conditions of the current situation and the previous time; based on the current traffic conditions and the traffic conditions of the previous time, calculate the traffic trend of each segmented road; estimate the segments based on the current traffic conditions and traffic trends of each segmented road The traffic conditions of the road in the future; and the traffic conditions of the estimated future time of each segmented road are presented on the map.

Preferably, the traffic condition is a traffic speed, and the traffic condition change trend of each segment road is calculated by comparing the current traffic speed with the traffic speed of the previous time.

Preferably, the traffic condition is a congestion index, and the traffic condition change trend of each segment road is calculated by comparing the current congestion index with the congestion index of the previous time.

Preferably, in addition to the current traffic conditions and traffic situation trends based on the respective segmented roads, the traffic conditions of the future time of each of the segmented roads are estimated based on events to be occurred on each of the segmented roads in the future.

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 a current traffic condition of each segmented road of each candidate driving route and a traffic condition of a previous time; calculating each candidate based on the current traffic condition of each segmented road of each candidate driving route and the traffic condition of the previous time Traffic trend of each segmented road of the driving route; estimating the time of each segment reaching each segmented road according to the current traffic situation; estimating each segment based on the current traffic conditions and traffic conditions of each segmented road a traffic condition of the road at the estimated time of arrival; estimating the travel time of each of the segmented roads of each of the candidate driving routes based on the traffic conditions of the respective segmented roads at the estimated time of arrival; and each of each of the candidate driving routes The total travel time is estimated by the travel time of the segmented road.

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 segmentation, the more accurate the traffic conditions reflected, but at the same time the higher the requirements for the calculation and storage of electronic maps. Also, it should be noted that in the same On a road or on the same route, the segmentation criteria of the road may be different. Therefore, some sections are 500 meters and some sections are 1 km.

At step 103, the current traffic conditions of the respective segmented roads and the traffic conditions of the previous time 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 traffic condition of the road section at the previous time can be found, for example, the traffic speed or congestion index of the road section at that time.

In the present invention, a period of time may refer to 5 minutes, 10 minutes, 15 minutes, or any other suitable period of time.

At step 105, based on the current traffic situation and the traffic conditions of the previous time, the traffic condition change trend of each segmented road is calculated. In one embodiment, the current traffic condition is compared to the traffic condition of the previous time to calculate a trend of traffic conditions for each of the segmented roads.

For example, the trend of traffic conditions may be a trend of speed, that is, comparing the current traffic speed with the traffic speed of the previous time. Specifically, the current transit speed is communicated with the previous time. The difference between the line speeds is compared with the speed of the previous time, and the ratio obtained is the speed change trend index. For example, if the current traffic speed of a certain section is 50 km/h and the traffic speed before 15 minutes is 40 km/h, the speed change trend index within 15 minutes is: (50-40)/40=+0.25. In another example, the current speed of a road section is 40 km/h, and the speed of traffic before 15 minutes is 50 km/h. The speed change trend index within 15 minutes is: (40-50)/50= -0.20. That is to say, the sign of the speed change trend index (+ or -) indicates whether the speed is increasing or decreasing, and the specific value is the degree of change.

Similarly, the trend of traffic conditions may be a trend of a congestion index (eg, between 0 and 10, the greater the value indicating more congestion), comparing the current congestion index with the congestion index of the previous time. Specifically, the ratio of the current congestion index to the congestion index of the previous time is compared with the congestion index of the previous time, and the obtained ratio is the congestion change trend index. For example, if the current congestion index of a certain road segment is 5.0 and the congestion index before 15 minutes is 4.0, the congestion change trend index within 15 minutes is: (5.0-4.0)/4.0=+0.25. In another example, the current congestion index for a segment is 4.0, and the congestion index for 15 minutes is 5.0, and the congestion trend index for 15 minutes is: (4.0-5.0)/5.0=-0.20. That is to say, the sign (+ or -) of the congestion change trend index indicates whether the congestion is aggravating or mitigating, and the specific value is the degree of change.

The above-mentioned speed change trend index and congestion change trend index are examples of trends in traffic conditions.

In addition, the traffic conditions of the previous time may be a plurality of traffic conditions of the previous time. Therefore, it is possible to obtain a curve of the trend of traffic conditions by traffic conditions at several time points.

In general, users want to predict traffic conditions in the future, such as predicting traffic conditions after 30 minutes. If it is currently 16:00, the user wants to predict traffic conditions after 30 minutes, ie 16:30.

At step 107, the traffic conditions of the future time of each of the segmented roads are estimated based on the current traffic conditions of each of the segmented roads and the trend of the traffic conditions.

For example, for a segmented road, a traffic situation of 16:30 should be predicted at 16:00, and the traffic condition at 16:00 can be multiplied by (1 + traffic trend (eg traffic trend) * time ratio) This is estimated to have a traffic situation of 16:30. The process can be calculated as follows:

Speed: 30 km / h * (1 + 0.25 * 30 / 15) = 45 km / h

Congestion: 4.0*(1-0.20*30/15)=2.4

Here, the example adopted in step 105 is adopted, that is, the current traffic condition is a vehicle speed of 30 km/h or a congestion index of 4.0, and the traffic condition change trend within 15 minutes is a speed change trend index + 0.25 and a congestion change trend index -0.20 .

It should be noted here that the future time should match the time used to calculate the trend of change. For example, to predict traffic conditions after 30 minutes, the trend within 15 minutes can be used instead of the trend within 5 minutes. In particular, for larger time spans, such as half an hour or more, the trend curve (curve fit) should be used to estimate and apply the trend of change.

In addition to the current traffic conditions and traffic conditions based on the various segmented roads, it is also possible to estimate the traffic conditions of the future time of each segmented road based on events that will occur on each of the segmented roads in the future.

For example, it is known that a road section will be traffic controlled (for example, restricted traffic) at 16:30 due to foreign affairs activities. In estimating the traffic conditions of the future time of each segmented road, it is also possible to consider this situation and further modify the traffic conditions estimated in the future based on the current traffic conditions and the trend of the traffic conditions.

At step 109, 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 rendering mode can be grayscale, texture, shadow, and flash in addition to color. Shuo can even be a sound prompt, a voice prompt, a pitch change, or a tactile distinction.

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, three driving routes such as route 1, route 2, and route 3 are identified.

At step 203, each candidate driving route is segmented. At step 205, the current traffic conditions of the respective segments of each of the candidate driving routes are acquired and the traffic conditions of the previous time.

Regarding the manner of obtaining the current traffic conditions of the respective segments of each of the candidate driving routes and the traffic conditions of the previous time, reference may be made to the specific discussion of step 103 in the flowchart of FIG.

At step 207, a traffic condition change trend 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 traffic condition of the previous time. In one embodiment, the traffic condition is a traffic speed, and a traffic condition change trend of each of the segmented roads is calculated by comparing the current traffic speed with the traffic speed of the previous time. In another embodiment, the traffic condition is a congestion index, and the traffic condition change trend of each segment road is calculated by comparing the current congestion index with a congestion index of a previous time. 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, based on the current traffic conditions of each of the segmented roads and the trend of the traffic conditions, the traffic conditions of the respective segmented roads at the estimated time of arrival are estimated.

The above example of 10 segmented roads is still used. The current traffic conditions for the 1st, 2nd, 3rd, ... 10th segmented roads have been obtained. For example, the current vehicle speeds are 40, 40, 30, ..., 50 km/h, respectively, or the current congestion indices are 4.0, 4.0, 4.8, ..., 3.0, respectively. The traffic trends of these segmented roads are 0.0, +0.1 (within 5 minutes), +0.2 (within 10 minutes), ..., +0.2 (within 60 minutes) (speed trend) or 0.0, -0.1 ( Within 5 minutes), -0.2 (within 10 minutes), ..., -0.2 (within 60 minutes) (congestion trend). 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 km / h, congestion index 4.0;

The second segmented road: after 10 minutes - estimated speed 40* (1 + 0.1 * 10 / 5) = 48 km / hour, estimated congestion index 4.0 * (1-0.1 * 10 / 5) = 3.2;

The third segmented road: after 20 minutes - estimated speed 30* (1 + 0.2 * 20/10) = 42 km / h, estimated congestion index 4.8 * (1-0.2 * 10 / 5) = 2.88;

......

10th segment road: After 70 minutes - estimated speed 50*(1+0.2*70/60)=61.7 km/h, estimated congestion index 3.0*(1-0.2*70/60)=2.3

For example, it is known that a road section will be traffic controlled (for example, restricted traffic) after half an hour due to foreign affairs activities. In estimating the traffic conditions of the future time of each segmented road, it is also possible to consider this situation and further modify the traffic conditions estimated in the future based on the current traffic conditions and the trend of the traffic conditions.

At step 213, 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, by dividing the length of each segmented road by the vehicle speed of the estimated time of arrival estimated in step 213, 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 215, 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. By The traffic condition at the time of selecting the route is not equal to the traffic situation when actually traveling to the road section, so the estimated time is actually much different 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;

Obtaining the current traffic conditions of each segmented road and the traffic conditions of the previous time;

Calculating the traffic trend of each segmented road based on the current traffic conditions and the traffic conditions of the previous time;

Estimating the traffic conditions of the future time of each segmented road based on the current traffic conditions and trends of traffic conditions 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 a traffic condition change trend of each of the segmented roads is calculated by comparing the current traffic speed with a traffic speed of the previous time.
The method of claim 1, wherein the traffic condition is a congestion index, and a traffic condition change trend of each of the segmented roads is calculated by comparing a current congestion index with a congestion index of a previous time.
The method according to claim 1, wherein the traffic conditions of the future time of each of the segmented roads are estimated based on current traffic conditions and traffic situation change trends of the respective segmented roads, further comprising: except for current traffic based on the respective segmented roads The trend of status and traffic conditions is also based on the events that will occur on each segmented road in the future, estimating 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 of each of the segmented roads of each candidate driving route and the traffic conditions of the previous time;

Calculating a traffic trend change trend of each segment road of each candidate driving route based on the current traffic condition of each segment road of each candidate driving route and the traffic state of the previous time;

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

Estimating the traffic conditions of each segmented road at the estimated time of arrival based on the current traffic conditions and traffic conditions of each segmented road;

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 according to claim 6, wherein the traffic condition is a traffic speed, and a traffic condition change trend of each of the segment roads is calculated by comparing the current traffic speed with a traffic speed of the previous time.
The method according to claim 6, wherein the traffic condition is a congestion index, and a traffic condition change trend of each segment road is calculated by comparing a current congestion index with a congestion index of a previous time.
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 current traffic conditions and traffic condition changes trends of the respective segmented roads, further comprising: The current traffic conditions and trends in traffic conditions are also based on future events on various segmented roads, estimating the future traffic conditions of each segmented road.
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.