CN104197948A - Navigation system and method based on traffic information prediction - Google Patents

Abstract

The invention discloses a navigation system based on traffic information prediction, which is characterized in that it includes a vehicle navigation terminal and a navigation server, the vehicle navigation terminal includes a GPS positioning module, an electronic map module and a navigation processing module, and the navigation server includes a real-time traffic information collection module , traffic information prediction module, traffic information storage module and navigation path planning module, the GPS positioning module sends vehicle position information and speed information to the real-time traffic information collection module, and the traffic information storage module sends real-time and predicted traffic information to the electronic map module , the navigation path planning module sends the navigation path information to the navigation processing module, and the navigation processing module sends the processed navigation path information back to the navigation path planning module. The present invention considers the influence of future traffic condition changes and the road selection of the vehicle on the traffic, so that the navigation path is closer to the real optimal path.

Description

A navigation system and navigation method based on traffic information prediction

technical field

The invention relates to a navigation system and a navigation method based on traffic information prediction, belonging to the field of vehicle navigation.

Background technique

Vehicle navigation system includes vehicle positioning, electronic map and path planning. The problem to be solved in navigation is to determine the current position of the navigation object on the electronic map according to the relevant traffic information such as roads provided by the electronic map, and to search for the optimal route according to the navigation destination, traffic information and optimization goals set by the user.

The traditional navigation system is mainly a stand-alone offline navigation system, which has GPS positioning function, pre-stored electronic map and navigation path calculation ability, and can navigate according to the road information provided by the fixed electronic map, and can also avoid frequent traffic based on historical information. congested road. This kind of navigation system works well under normal circumstances, but because it cannot obtain real-time online traffic information, it cannot obtain the best navigation route in the urban traffic with congestion from time to time.

Most of the current navigation systems have a wireless connection, and real-time traffic information can be obtained through the wireless network, and the navigation route can be selected through the real-time traffic information. Real-time traffic information can largely solve the problem of real-time information acquisition of stand-alone navigation systems.

However, with the extensive use of navigation systems, a new problem has been brought: the higher the proportion of vehicles using navigation systems during peak traffic hours, the more serious the traffic jams will be. This is because the navigation system uses a unified algorithm, and the optimal routes selected by the vehicles are highly consistent. Since the vehicles all choose the "optimal route" at the current moment, at the next moment, the route will instead become the most congested. path of. In order to solve this problem, some literatures propose to randomly select multiple possible navigation paths. Although the random selection of multi-paths solves the problem of "optimal path" conflicts to a certain extent, due to the random selection of paths, the paths are not necessarily optimal whether it is a single vehicle or the entire road network. This will reduce the user's trust in the navigation system and make the navigation system meaningless to a certain extent.

Contents of the invention

The technical problem to be solved by the present invention is to provide a navigation system and navigation method based on traffic information prediction that obtains the optimal path through traffic information prediction and road selection in the future, and solves the unification of algorithms in traditional navigation systems. , the optimal path chosen by the vehicle is highly consistent, leading to the problem of traffic congestion on this path.

In order to solve the above technical problems, the technical solution of the present invention is to provide a navigation system based on traffic information prediction, which is characterized in that it includes a vehicle-mounted navigation terminal and a navigation server, and the vehicle-mounted navigation terminal includes a GPS positioning module, an electronic map module and a navigation processing module. The navigation server includes a real-time traffic information collection module, a traffic information prediction module, a traffic information storage module and a navigation path planning module. The GPS positioning module sends the vehicle position information and speed information to the real-time traffic information collection module, and the traffic information storage module sends real-time And the predicted traffic information is sent to the electronic map module, the navigation route planning module sends the navigation route information to the navigation processing module, and the navigation processing module sends the processed navigation route information back to the navigation route planning module.

A navigation method for a navigation system based on traffic information prediction, characterized in that it includes the following two situations:

The first is a navigation method for a navigation system based on traffic information prediction under normal traffic conditions, which includes the following steps:

Step 11: Obtain the current real-time traffic condition information; obtain the vehicle navigation route information that has already been route-planned;

Step 12: Use the current real-time traffic condition information and the vehicle navigation path information that has been route-planned to predict the traffic conditions of each route in each period in the future;

Step 13: Locate the current position by GPS, calculate the vehicle navigation route and select the navigation route according to the vehicle navigation request and the predicted traffic and road condition information of each route in each time period in the future;

Step 14: store the vehicle navigation path for subsequent vehicles to select a navigation path;

The second is a navigation method for a navigation system based on traffic information prediction under sudden traffic conditions, which includes the following steps:

Step 21: Send sudden traffic accident information to obtain real-time traffic traffic information, and clear the vehicle navigation path passing through the road section, and set the transit time of the sudden traffic accident road section to infinity;

Step 22: Carry out route planning again for the vehicle closest to the sudden traffic road condition point among the vehicles whose planned route passes through the sudden traffic accident road section;

Step 23: According to the current real-time traffic road condition information and the vehicle navigation route information of the re-planned route, carry out the traffic road condition prediction of each time period of each route in the future;

Step 24: judging whether there is a vehicle without a navigation path;

Step 25: If it exists, skip to step 26; if it does not exist, it ends;

Step 26: Carry out vehicle navigation route calculation and navigation route selection according to the predicted traffic and road condition information of each route in each time period in the future;

Step 27: Store the vehicle navigation route for subsequent vehicle selection of a navigation route, and repeat steps 22-25.

Existing navigation route planning algorithms generally only navigate based on current real-time traffic information, and do not consider the impact of future traffic conditions changes and the vehicle's road choice on traffic. The present invention relates to the method of real-time traffic information collection, vehicle positioning, and navigation terminal and server end traffic information prediction and path planning. Its navigation system and path planning algorithm have the following advantages:

1. Since traffic conditions are time-dependent, traffic information closer to the real situation can be obtained by predicting traffic information in the future, so that the navigation path is closer to the real optimal path.

2. Consider the impact of the vehicle's route selection on future road conditions, and avoid all vehicles choosing the optimal route at the moment, resulting in the most congested optimal route instead.

Description of drawings

Fig. 1 is the workflow of a navigation system based on traffic information prediction under normal traffic conditions;

Fig. 2 is the workflow of a navigation system based on traffic information prediction under sudden traffic conditions;

Fig. 3 is a system structure diagram of a navigation system based on traffic information prediction;

Fig. 4 is the schematic diagram of real-time traffic condition;

Fig. 5 is the schematic diagram of predicting traffic conditions;

Fig. 6 is a schematic diagram of route selection of a large number of vehicles in a common navigation system;

Fig. 7 is a schematic diagram of route selection of a large number of vehicles in the navigation system of the present invention.

Detailed ways

In order to make the present invention more comprehensible, preferred embodiments are described in detail below with accompanying drawings.

The navigation method of the present invention predicts the traffic road conditions of each path in the future according to the current real-time traffic information and the vehicle route information that has already been routed, and selects the route of the current vehicle according to the predicted traffic conditions, and selects the best route at the current moment. optimal path. Since the navigation of each subsequent vehicle is selected based on the currently existing navigation path, there will be no conflict of the "optimal path" of the existing navigation system.

The navigation method under the normal traffic condition of the present invention, as shown in Figure 1, comprises the following steps:

Step 11: Obtain the current real-time traffic condition information; obtain the vehicle navigation route information that has already been route-planned;

Step 12: Use the current real-time traffic condition information and the vehicle navigation path information that has been route-planned to predict the traffic conditions of each route in each period in the future;

Step 13: Position the current position by GPS, calculate the vehicle navigation route and select the navigation route according to the vehicle navigation request (that is, input the destination) and the predicted traffic and road condition information of each route in each time period in the future;

Step 14: Store the vehicle navigation route (that is, store the route selection information of the current vehicle) for future vehicle selection of a navigation route.

The traffic road condition prediction in the present invention is carried out by macro traffic flow model; any other methods such as time series model, neural network and support vector machine can also be used to carry out traffic information prediction.

The vehicle navigation path calculation based on traffic information prediction in the present invention is realized by using the time-dependent network shortest path algorithm; path planning can also be carried out by using other path planning algorithms.

In order to facilitate computer processing and reduce the amount of computation and storage for traffic road condition prediction, the system of the present invention uses time segments to collect and predict real-time traffic data. The choice of time period can be selected according to the complexity of traffic conditions and the speed of change. For example, fast-changing downtown roads can be calculated every 1 minute, while suburban roads can be calculated every 5 minutes.

The present invention also proposes a vehicle navigation route allocation method when sudden traffic conditions (such as traffic accidents, road damage, traffic control, etc. cause road interruptions) occur, as shown in Figure 2, the steps of the allocation method are:

Step 21: Send sudden traffic accident information to obtain real-time traffic traffic information, and clear the vehicle navigation path passing through the road section, and set the transit time of the sudden traffic accident road section to infinity;

Step 22: Carry out route planning again for the vehicle closest to the sudden traffic road condition point among the vehicles whose planned route passes through the sudden traffic accident road section;

Step 23: According to the current real-time traffic road condition information and the vehicle navigation route information of the re-planned route, carry out the traffic road condition prediction of each time period of each route in the future;

Step 24: judging whether there is a vehicle without a navigation path;

Step 25: If it exists, skip to step 26; if it does not exist, it will end, that is, all vehicles whose original navigation path passes through the sudden traffic point will re-plan the navigation path;

Step 26: Carry out vehicle navigation route calculation and navigation route selection according to the predicted traffic and road condition information of each route in each time period in the future;

Step 27: Store the vehicle navigation route for subsequent vehicle selection of a navigation route, and repeat steps 22-25.

In order to improve efficiency, a traffic flow allocation algorithm can also be used to allocate traffic flow according to the distance from the congestion point. For example, first run a traffic flow allocation algorithm for vehicles within a range of 500 meters from a traffic congestion point, and then perform an allocation algorithm for vehicles within a range of 1,000 meters.

A kind of navigation system based on traffic information prediction of the present invention, it comprises two parts of vehicle navigation terminal and navigation server, as shown in Figure 3, vehicle navigation terminal comprises GPS positioning module, electronic map module and navigation processing module, vehicle navigation terminal Send the source and destination information to the navigation server for navigation request, and perform route navigation according to the navigation route information and electronic map information obtained from the navigation server. At the same time, the vehicle navigation terminal regularly reports the real-time vehicle position information and speed information obtained through the GPS positioning module according to the requirements of the navigation server. The navigation server includes a real-time traffic information collection module, a traffic information prediction module, a traffic information storage module and a navigation path planning module. The real-time traffic information collection module of the navigation server collects the vehicle position information and speed information using the navigation system, and obtains them from the traffic department. And real-time traffic information data obtained by other means. The traffic information prediction module uses real-time traffic information, historical traffic information, and vehicle route planning information using the navigation system to obtain traffic road condition prediction information for each time period in the future through a prediction algorithm. The traffic information storage module sends real-time and predicted traffic information to the electronic map module, the navigation route planning module sends the navigation route information to the navigation processing module, and the navigation processing module sends the processed navigation route information back to the navigation route planning module.

The traffic information storage module stores the historical actual traffic information, the current time period traffic information and the predicted traffic information for subsequent traffic information prediction and navigation route planning.

The navigation path planning module accepts the request of the navigation terminal user, and plans the navigation path according to the current and future traffic information of the traffic information storage module in order to obtain the optimal navigation path related to time, and store the navigation path for the next traffic For information forecasting.

As shown in Figures 4-7, the cross symbol indicates a congested road section, and the others indicate a smooth road section. The north-south road 5 and the east-west road C represented by thick and long lines are express roads, and other roads are ordinary roads.

It can be seen from Figure 4 that the road section C2-C3 is from west to east and the road section A3-B3 is from north to south due to the large traffic flow leading to traffic congestion. As shown in Figure 5, it is a schematic diagram of predicting traffic conditions. Vehicles on the C2-C3 road section drive to the C3-C4 road section, causing congestion on the C3-C4 road section from west to east; vehicles on the A3-B3 road section driving to the B3-C3 road section cause B3 - Section C3 is congested from north to south.

Vehicle navigation scenario 1: Assume that a vehicle needs to travel from B2 to D4, as shown in Figure 4-Figure 5.

For the existing route planning using a common navigation system, the route selection will be to avoid the C2-C3 road section and choose B2->B3->C3->C4->D4. However, since the traffic condition changes with time, when the vehicle arrives at B3-C3, the road section starts to be congested, and the road section C3-C4 ahead also starts to be congested, obviously this path is not the optimal path.

And for the vehicle that adopts the navigation system of the present invention, since the navigation route is selected comprehensively in real time and predicted traffic conditions, the system will select B2->C2->D2->D3->D4 to dynamically avoid congested road sections.

Vehicle navigation scenario 2: During rush hours, a large number of vehicles need to drive from A3 and A4 to F5 and F6, and from A5 and A6 to F3 and F4, as shown in Figure 6-7. Different lines represent different traffic navigation paths.

If all vehicles adopt the common navigation system, then all vehicles will choose the north-south expressway 5, and a large number of vehicles will flock to the expressway 5 at the same time, which will cause the north-south road 5 to be congested, and all vehicles will be blocked in what seems to be a smooth road now. on road 5, as shown in Figure 6.

And the vehicle that adopts the navigation system of the present invention will select respectively the north-south direction road 3,5,6 and the east-west direction expressway C (for example, A3->C3->C6 according to the impact of the selected navigation path vehicle on the future traffic road conditions) ->F6, A6->C6->C3->F3), improve the utilization rate of the road network, and at the same time make all users reach the destination quickly, as shown in Figure 7.

Claims (2)

1. a navigation system based on traffic information prediction, it is characterized in that, comprises vehicle-mounted navigation terminal and navigation server, and vehicle-mounted navigation terminal comprises GPS positioning module, electronic map module and navigation processing module, and navigation server comprises real-time traffic information collection module, traffic Information prediction module, traffic information storage module and navigation path planning module, GPS positioning module sends vehicle position information and speed information to real-time traffic information collection module, traffic information storage module sends real-time and predicted traffic information to electronic map module, navigation The route planning module sends the navigation route information to the navigation processing module, and the navigation processing module sends the processed navigation route information back to the navigation route planning module. 2. A navigation method of a navigation system based on traffic information prediction, characterized in that it comprises the following two situations: The first is a navigation method for a navigation system based on traffic information prediction under normal traffic conditions, which includes the following steps: Step 11: Obtain the current real-time traffic condition information; obtain the vehicle navigation route information that has already been route-planned; Step 12: Use the current real-time traffic condition information and the vehicle navigation path information that has been route-planned to predict the traffic conditions of each route in each period in the future; Step 13: Locate the current position by GPS, calculate the vehicle navigation route and select the navigation route according to the vehicle navigation request and the predicted traffic and road condition information of each route in each time period in the future; Step 14: store the vehicle navigation path for subsequent vehicles to select a navigation path; The second is a navigation method for a navigation system based on traffic information prediction under sudden traffic conditions, which includes the following steps: Step 21: Send sudden traffic accident information to obtain real-time traffic traffic information, and clear the vehicle navigation path passing through the road section, and set the transit time of the sudden traffic accident road section to infinity; Step 22: Carry out route planning again for the vehicle closest to the sudden traffic road condition point among the vehicles whose planned route passes through the sudden traffic accident road section; Step 23: According to the current real-time traffic road condition information and the vehicle navigation route information of the re-planned route, carry out the traffic road condition prediction of each time period of each route in the future; Step 24: judging whether there is a vehicle without a navigation path; Step 25: If it exists, skip to step 26; if it does not exist, it ends; Step 26: Carry out vehicle navigation route calculation and navigation route selection according to the predicted traffic and road condition information of each route in each time period in the future; Step 27: Store the vehicle navigation route for subsequent vehicle selection of a navigation route, and repeat steps 22-25.