CN115031749A

CN115031749A - Night walk navigation method, device, equipment, storage medium and program product

Info

Publication number: CN115031749A
Application number: CN202210630382.0A
Authority: CN
Inventors: 翟铭阳; 卢振; 杨建忠; 曹婷婷
Original assignee: Beijing Baidu Netcom Science and Technology Co Ltd
Current assignee: Beijing Baidu Netcom Science and Technology Co Ltd
Priority date: 2022-06-06
Filing date: 2022-06-06
Publication date: 2022-09-09
Anticipated expiration: 2042-06-06
Also published as: CN115031749B; WO2023236522A1

Abstract

The disclosure provides a night walking navigation method, a night walking navigation device, an electronic device, a computer readable storage medium and a computer program product, and relates to the technical fields of image analysis, navigation planning, walking navigation and the like. The method comprises the following steps: determining a walking navigation starting point and a walking navigation end point according to the acquired night walking travel request; determining each candidate walking route according to the walking navigation starting point and the walking navigation end point; determining a night safe walking route according to the night walking safety degree of each candidate walking route; and outputting night walking navigation content corresponding to the night safe walking route. The method determines the safety degree of walking at night of each candidate walking route, namely, determines the candidate walking route which can walk safely at night as the safe walking route at night by considering the safety influence on walking caused by night, so that navigation content with high safety can be provided for a user, and the personal and property safety of the user walking at night is guaranteed.

Description

Night walk navigation method, device, equipment, storage medium and program product

Technical Field

The present disclosure relates to the field of data processing technologies, and in particular, to the technical fields of image analysis, navigation planning, walking navigation, and the like, and in particular, to a method and an apparatus for night walking navigation, an electronic device, a computer-readable storage medium, and a computer program product.

Background

The development of maps enters the electronic map era, and under the impact of the internet, users put higher requirements on the navigation and use experience of the maps.

The walking navigation is a common travel mode navigation which is parallel to the riding navigation, the riding travel navigation and the driving travel navigation. However, the daytime walking navigation is substantially different from the nighttime walking navigation.

Disclosure of Invention

The embodiment of the disclosure provides a night walking navigation method, a night walking navigation device, an electronic device, a computer readable storage medium and a computer program product.

In a first aspect, an embodiment of the present disclosure provides a night walking navigation method, including: determining a walking navigation starting point and a walking navigation end point according to the acquired night walking travel request; determining each candidate walking route according to the walking navigation starting point and the walking navigation end point; determining a night safe walking route according to the night walking safety degree of each candidate walking route; and outputting night walking navigation content corresponding to the night safe walking route.

In a second aspect, an embodiment of the present disclosure provides a navigation device for walking at night, including: a walking navigation start/end point determination unit configured to determine a walking navigation start point and a walking navigation end point according to the acquired night walking travel request; a candidate walking route determination unit configured to determine each candidate walking route based on the walking navigation start point and the walking navigation end point; a nighttime safe walking route determination unit configured to determine a nighttime safe walking route based on the nighttime walking safety degree of each candidate walking route; a night walk guidance content output unit configured to output night walk guidance content corresponding to the night safe walk route.

In a third aspect, an embodiment of the present disclosure provides an electronic device, including: at least one processor; and a memory communicatively coupled to the at least one processor; wherein the memory stores instructions executable by the at least one processor to cause the at least one processor to perform the method of night walk navigation as described in any one of the implementations of the first aspect when executed by the at least one processor.

In a fourth aspect, the disclosed embodiments provide a non-transitory computer-readable storage medium storing computer instructions for enabling a computer to implement the night walk navigation method as described in any one of the implementations of the first aspect when executed.

In a fifth aspect, the embodiments of the present disclosure provide a computer program product including a computer program, which when executed by a processor is capable of implementing the nighttime walking navigation method as described in any one of the implementations of the first aspect.

The night walking navigation scheme provided by the disclosure determines a walking navigation starting point and a walking navigation end point after receiving a night walking travel request, determines a plurality of candidate walking routes based on the walking navigation starting point and the walking navigation end point, and then determines the night walking safety degree of each candidate walking route, namely, determines the candidate walking route which can walk safely at night as a night safe walking route by considering the safety influence on walking caused by night, thereby providing navigation content with high safety for a user and ensuring the personal and property safety of the user walking at night.

It should be understood that the statements in this section do not necessarily identify key or critical features of the embodiments of the present disclosure, nor do they limit the scope of the present disclosure. Other features of the present disclosure will become apparent from the following description.

Drawings

Other features, objects and advantages of the disclosure will become more apparent upon reading of the following detailed description of non-limiting embodiments thereof, made with reference to the accompanying drawings in which:

FIG. 1 is an exemplary system architecture to which the present disclosure may be applied;

fig. 2 is a flowchart of a night walking navigation method according to an embodiment of the present disclosure;

fig. 3 is a flowchart of a method for determining a walking safety level during night in a walking navigation method during night provided by an embodiment of the present disclosure;

FIG. 4 is a flowchart of a method for determining a trajectory characteristic and determining a first safety index according to an embodiment of the disclosure;

FIG. 5 is a flow chart of a method of determining image characteristics and determining a second safety index provided by an embodiment of the present disclosure;

FIG. 6 is a flow chart of a method for determining a road condition characteristic and determining a third safety index provided by an embodiment of the present disclosure;

FIG. 7 is a flow chart of a method of determining a characteristic of a store and determining a fourth security index provided by an embodiment of the present disclosure;

fig. 8 is a schematic flowchart of another method for determining a safety level of walking at night according to an embodiment of the present disclosure;

fig. 9 is a block diagram illustrating a night walk navigation device according to an embodiment of the present disclosure;

fig. 10 is a schematic structural diagram of an electronic device suitable for executing a nighttime walking navigation method according to an embodiment of the present disclosure.

Detailed Description

Exemplary embodiments of the present disclosure are described below with reference to the accompanying drawings, in which various details of the embodiments of the disclosure are included to assist understanding, and which are to be considered as merely exemplary. Accordingly, those of ordinary skill in the art will recognize that various changes and modifications of the embodiments described herein can be made without departing from the scope and spirit of the present disclosure. Also, descriptions of well-known functions and constructions are omitted in the following description for clarity and conciseness. It should be noted that, in the present disclosure, the embodiments and features of the embodiments may be combined with each other without conflict.

In the technical scheme of the disclosure, the collection, storage, use, processing, transmission, provision, disclosure and other processing of the personal information of the related user are all in accordance with the regulations of related laws and regulations and do not violate the good customs of the public order.

Fig. 1 illustrates an exemplary system architecture 100 to which embodiments of the night walk navigation method, apparatus, electronic device, and computer-readable storage medium of the present disclosure may be applied.

As shown in fig. 1, the system architecture 100 may include

terminal devices

101, 102, 103, a network 104, and a server 105. The network 104 serves as a medium for providing communication links between the

terminal devices

101, 102, 103 and the server 105. Network 104 may include various connection types, such as wired, wireless communication links, or fiber optic cables, to name a few.

The user may use the

terminal devices

101, 102, 103 to interact with the server 105 via the network 104 to receive or send messages or the like. Various applications for realizing information communication between the

terminal devices

101, 102, 103 and the server 105, such as data transmission type applications, navigation type applications, instant messaging type applications, etc., may be installed on the

terminal devices

101, 102, 103 and the server.

The

terminal devices

101, 102, 103 and the server 105 may be hardware or software. When the

terminal devices

101, 102, 103 are hardware, they may be various electronic devices with display screens, including but not limited to smart phones, tablet computers, laptop portable computers, desktop computers, and the like; when the

terminal devices

101, 102, and 103 are software, they may be installed in the electronic devices listed above, and they may be implemented as multiple software or software modules, or may be implemented as a single software or software module, and are not limited in this respect. When the server 105 is hardware, it may be implemented as a distributed server cluster composed of multiple servers, or may be implemented as a single server; when the server is software, the server may be implemented as a plurality of software or software modules, or may be implemented as a single software or software module, which is not limited herein.

The server 105 may provide various services through various built-in applications, taking a navigation application that may provide a travel navigation service as an example, when the server 105 runs the navigation application, the following effects may be achieved: first, a nighttime walking travel request transmitted from the terminal device 101 is received via the network 104; then, determining a walking navigation starting point and a walking navigation end point according to the night walking travel request; then, determining each candidate walking route according to the walking navigation starting point and the walking navigation end point; next, determining a safe walking route at night according to the safe walking degree at night of each candidate walking route; finally, the night walk guidance content corresponding to the night safe walk route is transmitted to the terminal apparatus 101 via the network 104. So that the terminal device 101 can safely reach the destination through the safe walking route at night by the navigation guidance information displayed on the display screen of the terminal device 101.

Since the map navigation operation needs to occupy more computation resources and stronger computation capability, the night walk navigation method provided in the following embodiments of the present disclosure is generally executed by the server 105 having stronger computation capability and more computation resources, and accordingly, the night walk navigation device is generally disposed in the server 105. However, it should be noted that, when the

terminal devices

101, 102, and 103 also have computing capabilities and computing resources meeting the requirements, the

terminal devices

101, 102, and 103 may also complete the above-mentioned operations performed by the server 105 through the navigation applications installed thereon, and then output the same result as the server 105. Especially, when there are a plurality of terminal devices having different computation capabilities at the same time, but the navigation application determines that the terminal device has a strong computation capability and a large amount of computation resources remaining, the terminal device may execute the computation to appropriately reduce the computation load of the server 105, and accordingly, the navigation device for walking at night may be provided in the

terminal devices

101, 102, and 103. In such a case, the exemplary system architecture 100 may also not include the server 105 and the network 104.

It should be understood that the number of terminal devices, networks, and servers in fig. 1 is merely illustrative. There may be any number of terminal devices, networks, and servers, as desired for implementation.

Referring to fig. 2, fig. 2 is a flowchart of a night walk navigation method according to an embodiment of the disclosure, where the process 200 includes the following steps:

step 201: determining a walking navigation starting point and a walking navigation end point according to the acquired night walking travel request;

this step is intended to determine a walking navigation start point and a walking navigation end point from a nighttime walking travel request (i.e., a navigation invocation request) incoming from a user by an execution subject of the nighttime walking navigation method (e.g., the server 105 shown in fig. 1). The walking navigation starting point may be a current position point of the user, or may be a certain position point set by the user, and the walking navigation ending point is usually set by the user.

The night walking travel request refers to a walking travel request sent in a time period when the local time is night, the night time period can be determined according to the current geographic position and the current season, and one core judgment mode is as follows: at the current time, the natural light illumination intensity and the visibility of the visual field are low.

Step 202: determining each candidate walking route according to the walking navigation starting point and the walking navigation end point;

in step 201, the present step is intended to determine candidate walking routes from the walking navigation start point and the walking navigation end point by the execution main body. In general, a plurality of routes may be generated that may navigate from a walking navigation start point to a walking navigation end point based on the walking navigation start point and the walking navigation end point.

That is, in determining the candidate pedestrian routes, only reachability is generally taken into consideration, and no more influencing factors are taken into consideration, so that a plurality of candidate pedestrian routes can generally be determined.

Step 203: determining a night safe walking route according to the night walking safety degree of each candidate walking route;

in step 202, the execution subject determines a candidate walking route having a high walking safety degree at night as a safe walking route at night based on the walking safety degree at night of each candidate walking route. Namely, the step aims to fully consider whether each candidate walking route can ensure the personal and property safety of the user when the user walks at night.

Namely, the safety degree of walking at night corresponding to each candidate walking route can more intuitively or quantitatively show the safety of the user walking according to the walking route at night, and further can better guarantee the personal and property safety of the user walking at night.

Step 204: and outputting night walking navigation content corresponding to the night safe walking route.

In step 203, the execution subject outputs the night walk guidance content corresponding to the night safe walk route. Generally, the night walking navigation content is transmitted to the terminal device of the user initiating the night walking travel request in an instruction manner, so that the terminal device presents a corresponding navigation guidance interface or sends out navigation guidance voice by analyzing the received instruction, and further guides the corresponding user to travel along a corresponding walking route.

The night walking navigation method provided by the embodiment of the disclosure determines a walking navigation starting point and a walking navigation end point after receiving a night walking travel request, determines a plurality of candidate walking routes based on the walking navigation starting point and the walking navigation end point, and then determines the night walking safety degree of each candidate walking route, namely determines the candidate walking route capable of safely walking at night as a night safety walking route by considering the safety influence on walking caused by being in the night, thereby providing a high-safety navigation content for a user and ensuring personal and property safety of the user walking at night.

To further enhance the understanding of the night walk safety procedure for determining each candidate walking route, the present embodiment further illustrates a flowchart of a method for determining the degree of night walk safety through fig. 3, wherein the process 300 includes the following steps:

step 301: acquiring at least one of a trajectory feature, an image feature, a road state feature, and a shop feature of each walking link constituting each candidate walking route;

considering that each candidate pedestrian route is generally formed by splicing a plurality of different pedestrian sections, the present embodiment acquires at least one of the trajectory feature, the image feature, the road status feature, and the shop feature of each pedestrian section, taking the smallest pedestrian section as a unit of consideration.

It should be understood that the track feature, the image feature, the road status feature and the shop feature are all determined from different dimensions of the walking road segment to represent the safety degree of the walking road segment when walking at night. Of course, besides the four listed in the embodiment, there may be other dimensional features that can also participate in determining the safety degree of the walking road segment during walking at night, and these are not listed here, and without exceeding the core concept provided by the present disclosure, the present disclosure should also fall within the protection scope of the present disclosure.

Step 302: responding to the acquired track characteristics, and determining a first safety index of the corresponding walking road section walking at night according to the track characteristics;

step 303: in response to the acquired image characteristics, determining a second safety index of the corresponding walking road section walking at night according to the image characteristics;

step 304: in response to the acquisition of the road state characteristics, determining a third safety index of the corresponding walking road section walking at night according to the road state characteristics;

step 305: in response to the obtained store characteristics, determining a fourth safety index of the corresponding walking road section walking at night according to the store characteristics;

step 302-step 305, respectively in case of containing the corresponding kind of features, each provides a step of determining a safety index of the corresponding walking road section walking at night using the corresponding kind of features. Namely, steps 302-305 aim to independently determine a safety index for each feature for walking on the walking road segment at night.

Step 306: determining a comprehensive safety index of each walking road section according to at least one of the first safety index, the second safety index, the third safety index and the fourth safety index;

on the basis of steps 302-305, this step is intended to determine, by the execution agent mentioned above, a composite safety index for each walking route section on the basis of at least one of the first safety index, the second safety index, the third safety index and the fourth safety index.

In general, since different kinds of features contribute differently to the final composite safety index, for better combination with the actual situation, the weighting weight of each safety index can be determined in advance, so as to obtain a more accurate composite safety index through a weighting calculation method.

For example, the above various features may be combined, the weight of each feature may be trained by constructing a machine learning model, and the combined safety index may be output, that is, the degree to which the road is recommended as the road for night trip.

Step 307: the nighttime walking safety degree of each candidate walking route is determined based on the composite safety index of each walking section constituting each candidate walking route.

On the basis of step 306, this step is intended to determine the nighttime walking safety degree of each candidate walking route by the execution subject described above based on the composite safety index (equivalent to the road safety perception coefficient shown in fig. 8) of each walking link constituting each candidate walking route. That is, a plurality of different walking links constitute one candidate walking route, and therefore, when the integrated safety index of each walking link is determined, the integrated safety index of each walking link included in the candidate walking route is also integrated, so that the nighttime walking safety degree corresponding to each candidate walking link can be obtained.

One implementation, including and not limited to, is:

the sum of the composite safety indexes of the individual walking links constituting each candidate walking route is determined as the nighttime walking safety degree of the corresponding candidate walking route. That is, the composite safety index of each of the plurality of pedestrian sections included in the candidate pedestrian route is added up to finally obtain the composite safety index and the nighttime walking safety degree as the corresponding candidate pedestrian route.

Of course, besides the accumulation calculation method, other similar calculation methods may be used as long as they can perform comparison, and meanwhile, when calculating the summation, different walking road segments may be weighted in combination with the weighting idea.

The embodiment provides a specific implementation manner for determining the walking safety degree of each candidate walking route at night through steps 301 to 307, and combines at most four characteristics (namely, a track characteristic, an image characteristic, a road state characteristic and a shop characteristic) of each walking route, which can be used for determining the walking safety of the route at night, to evaluate the walking safety of each walking route as comprehensively as possible, and combines a plurality of walking routes possibly included in the candidate walking route, so as to finally obtain a more accurate walking safety degree of each candidate walking route at night.

In order to more specifically illustrate how the four features mentioned in fig. 3 are determined, the following description also refers to fig. 4 to fig. 7, respectively, and a specific implementation is given for how each feature is determined and how the corresponding safety index is determined:

fig. 4 is a flowchart of a method for determining a track characteristic and determining a first safety index according to an embodiment of the present disclosure, in which the track characteristic is used to determine whether each walking road segment is a safe road during nighttime walking, and the method includes the following steps:

step 401: determining each of the walking sections constituting each of the candidate walking routes;

step 402: determining the night track number proportion of each walking road section according to historical track data;

if the day and night trajectories on a pedestrian road suddenly drop, it can be shown that the day PV (Present Value, which is used in this disclosure to represent a metric property of the road) of the pedestrian road is high, but the night PV is low, i.e., there are few people walking at night. The calculation mode may be such that the proportion of the number of night tracks to the number of day tracks is less than 50%.

Step 403: determining the average driving speed at night of each walking road section according to historical driving speed data;

when the user walks at night, the walking speed of the user A on some road sections is lower than that of the user A on other road sections for the same user, and accounts for less than 70% of the total average speed. The road section may be considered to have characteristics unsuitable for walking, such as icing on the ground. And accumulating multi-user low-speed road segment clusters for more than one month to obtain all sections which are not suitable for walking.

Step 404: a first safety index for the corresponding walking road segment walking at night is determined based on at least one of the night trajectory and the night average driving speed.

On the basis of

steps

402 and 403, this step is intended to determine, by the executing entity, a first safety index for the corresponding walking section walking at night, i.e. a night trajectory number ratio and a night average driving speed, both of which are in direct proportion to the first safety index, according to at least one of the night trajectory and the night average driving speed. That is, the higher the night trajectory number ratio, the higher the first safety index, the higher the night average traveling speed, the higher the first safety index, and the higher the first safety index, the higher the safety of walking on the walking route at night.

Besides the two sub-track features mentioned in step 402 and step 403, the low PV road segments of multiple users can be clustered, that is, for multiple users, that is, for the whole track, the low PV road is not suitable for walking road segments. Such as walking PV below 10. And then the accuracy of the finally determined first safety index is improved by combining more sub-track characteristics. Similarly, when the first safety index is determined by combining multiple sub-track features, the accuracy can be improved by combining the weighting idea.

Fig. 5 is a flowchart of a method for determining an image feature and determining a second safety index, which is to determine whether each walking road segment is a safe road during nighttime walking by using the image feature, according to an embodiment of the present disclosure, including the following steps:

step 501: determining each of the walking sections constituting each of the candidate walking routes;

step 502: acquiring an image database obtained by shooting a walking road section by a vehicle event data recorder;

the vehicle traveling data recorder provided on the vehicle can take a picture of a walking road section passing near the road section and record image information, and thus can acquire the image database accordingly.

Step 503: determining street lamp characteristics and construction characteristics of each walking road section according to the image database;

the street lamp is characterized in that the street lamp is mainly used for indicating whether a street lamp exists on the walking road section or not and determining the street lamp density under the condition that the street lamp exists, and the existence of the street lamp in a larger number mean that the visibility of the walking road section is higher, and the walking safety of the walking road section at night is higher.

The construction characteristics are mainly used for indicating whether construction barriers influencing the safety of the user walking at night are placed on the walking road section or not and the number of the construction barriers when the construction barriers exist. However, the smaller the number of construction obstacles is, the fewer the risk factors are, and the higher the safety of walking at night is.

Step 504: and determining a second safety index of the corresponding walking road section walking at night according to at least one of the street lamp characteristics and the construction characteristics.

The street lamp feature represents that the street lamp density and the second safety index are in a direct proportion relation, and the construction feature represents that the quantity of the construction obstacles and the second safety index are in an inverse proportion relation.

Fig. 6 is a flowchart of a method for determining a road status characteristic and determining a third safety index according to an embodiment of the present disclosure, in which the road status characteristic is used to determine whether each walking section is a safe road during nighttime walking, and the method includes the following steps:

step 601: determining each of the walking sections constituting each of the candidate walking routes;

step 602: determining at least one of the public traffic station density, the road laying mode, the construction state, the monitoring camera density, the number of non-motor vehicle lanes and the average occurrence number of illegal events of each walking road section according to a road network database;

wherein the mass transit station density may include: the density of the buses or subway stations (for example, the number of the buses or subway stations exists in 30m nearby) and the density of the shared single-bus parking areas (for example, whether the parking areas are arranged in 100 meters nearby or not) are both higher, that is, the higher the density is, the higher the safety of walking on the walking road section at night is. Since it is generally indicated that the traffic is high if a shared single-car parking area is set up.

The road paving mode is a concrete state of whether the walking road section is a cement road, a brick road or an unpaved road, and is mainly used for representing whether different road paving modes are suitable for a user to walk at night or not on the walking road section, namely, the higher the ground flatness indicated by the road paving mode is, the higher the safety of walking at night on the walking road section is.

The construction state is mainly used for indicating whether the walking road is in the construction state or not, and if the walking road is not in the construction state, the risk factors of the walking road are less, and the walking safety of the walking road at night is higher.

The higher the density of the monitoring cameras, the more comprehensive the monitoring coverage, that is, the higher the safety of walking on the walking road section at night.

The number of non-motorway is mainly used for representing the number of bicycle-specific lanes, and if the bicycle-specific lanes exist or exist more, the bicycle-specific lanes mean that the bicycle can be ridden on a walking road, so that the danger coefficient for a user walking on the road section is increased.

The average number of illegal events is the number of illegal events occurring on the walking road section before being determined according to historical data, for example, the accident occurrence place in nearly 3 years is crawled, and the number of accidents occurring on the road section in 3 years is counted. It is understood that the lower the average number of illegal events, the higher the safety of walking on the walking route at night. And the priority of the road sections with accidents in 3 years participating in navigation path planning can be reduced.

Step 603: and determining a third safety index of the corresponding walking road section walking at night according to at least one of the density of public transportation stations, the road laying mode, the construction state, the density of monitoring cameras, the number of non-motor vehicle lanes and the average number of illegal events.

The public transport station density, the ground flatness represented by the road paving mode and the monitoring camera density are in direct proportion to the third safety index, and the construction barrier number, the non-motor vehicle lane number and the average illegal event occurrence number represented by the construction state are in direct proportion to the third safety index.

FIG. 7 is a flowchart of a method for determining characteristics of a store and determining a fourth security index according to an embodiment of the disclosure

Step 701: determining each of the walking sections constituting each of the candidate walking routes;

step 702: determining at least one of the number of nighttime business shops and the average shop level of each walking road section according to the shop distribution data;

specifically, the number of shops along the street on the road section with the business time at night being later than the current path planning time can be counted; and the grades of shops along the street on the road section with the business time at night being later than the current path planning time can be counted. Wherein, higher grade can be given to the street-following shops with civil security shops such as chain shops, hospital drug stores and the like, government agencies such as police departments and the like, public civil facilities such as parks and the like. The shop level of the night non-profit shop may be higher than the shop level of the night-profit shop, i.e. the non-profit shop is generally more secure.

Step 703: determining a fourth safety index for the corresponding pedestrian section walking at night according to at least one of the number of night business stores and the average store level.

Wherein, the number of night business shops and the average shop grade are both in direct proportion to the fourth safety index.

In addition to the two sub-store characteristics provided in step 702, the PV values of the night business stores may be combined, for example, the amount of passengers of the shops along the street where the night business time is later than the current route planning time on the road section is counted, so as to improve the accuracy of the fourth safety index by increasing the number of the sub-store characteristics.

The above description in conjunction with fig. 4-7 shows how to determine the safety index of a walking road segment using four different features, each using data from different sources, and how to acquire and process the data for subsequent feature extraction, respectively, and this disclosure also shows a specific way:

1) the walking track of the user is obtained. Performing road network matching calculation of the tracks and the road network through an HMM (Hidden Markov Model) algorithm to obtain the corresponding relation between each track and each road section;

2) and acquiring a picture of the vehicle-mounted camera and a vehicle-mounted GPS track. Track processing is as above; the image part is subjected to network model segmentation through an image semantic segmentation model ResNet50 (a residual network) + PSP (a semantic segmentation network) to identify a baffle, a fence, a road surface and the like;

3) the sunset time is calculated from the geographic location. The calculation mode is to calculate the sunset time of the city where the track is located according to the longitude and latitude coordinates of the track. Only the trajectory and image after sunset time are used later. The purpose of this is to accurately judge whether the city where the user is located is a night scene after the track occurrence time is sunset.

On the basis of any of the above embodiments, for the step of determining a nighttime walking route according to the nighttime walking safety degree of each candidate walking route, the present embodiment further provides a preferred processing scheme combining preset multiple nighttime walking preferences, including the steps of:

dividing each candidate walking route into a plurality of preset walking preferences at night;

the candidate walking route having the highest degree of walking safety at night for each nighttime walking preference is determined as the nighttime safe walking route for the corresponding nighttime walking preference.

The walking preference at night can be various, including the highest visibility, the shortest distance, the best road condition and the like, so as to better meet the requirements of different users.

On the basis of any of the above embodiments, in order to improve the accuracy of the determined composite safety index of the walking road segment as much as possible, the real image or the real area can be verified by the inspector.

A more complete implementation architecture of the solution may refer to the overall flow diagram of the solution shown in fig. 8, where parts are mentioned in the foregoing embodiments and are not described herein again.

With further reference to fig. 9, as an implementation of the methods shown in the above-mentioned figures, the present disclosure provides an embodiment of a night walk navigation device, which corresponds to the method embodiment shown in fig. 2, and which is particularly applicable to various electronic devices.

As shown in fig. 9, the night walk navigation device 900 of the present embodiment may include: walking navigation start/end point determination section 901, walking route candidate determination section 902, safe walking route at night determination section 903, and walking navigation content at night output section 904. Wherein, the walking navigation start/end point determining unit 901 is configured to determine a walking navigation start point and a walking navigation end point according to the acquired night walking travel request; a candidate walking route determining unit 902 configured to determine each candidate walking route based on the walking navigation start point and the walking navigation end point; a nighttime safe walking route determining unit 903 configured to determine a nighttime safe walking route according to the nighttime walking safety degree of each candidate walking route; a night walk guidance content output unit 904 configured to output night walk guidance content corresponding to the night safe walk route.

In the present embodiment, the night walk navigation device 900: the detailed processing and the technical effects of the walking navigation start/end point determining unit 901, the candidate walking route determining unit 902, the night safe walking route determining unit 903, and the night walking navigation content outputting unit 904 can refer to the related descriptions of step 201 and step 204 in the corresponding embodiment of fig. 2, and are not repeated herein.

In some optional implementations of the present embodiment, the night walk navigation device 900 may further include:

a feature acquisition unit configured to acquire at least one of a trajectory feature, an image feature, a road state feature, and a shop feature of each walking link constituting each candidate walking route;

a first safety index determination unit configured to determine a first safety index of the corresponding walking road section walking at night according to the track characteristics in response to the track characteristics being acquired;

a second safety index determination unit configured to determine, in response to the acquisition of the image feature, a second safety index at which the corresponding walking section walks at night according to the image feature;

a third safety index determination unit configured to determine, in response to the acquisition of the road state feature, a third safety index at which the corresponding walking section walks at night according to the road state feature;

a fourth safety index determination unit configured to determine, in response to the acquisition of the store characteristics, a fourth safety index at which the corresponding walking section walks at night according to the store characteristics;

a comprehensive safety index determining unit configured to determine a comprehensive safety index for each pedestrian section according to at least one of the first safety index, the second safety index, the third safety index, and the fourth safety index;

a nighttime walking safety degree determination unit configured to determine a nighttime walking safety degree for each candidate walking route based on the composite safety index of each walking link constituting each candidate walking route.

In some optional implementations of the present embodiment, the feature obtaining unit may include a trajectory feature obtaining subunit that obtains a trajectory feature of each walking road segment constituting each candidate walking route, and the trajectory feature obtaining subunit may be further configured to:

determining each of the walking sections constituting each of the candidate walking routes;

determining the night track number proportion of each walking road section according to historical track data;

determining the average driving speed at night of each walking road section according to historical driving speed data;

correspondingly, the first safety index determination unit is further configured to:

determining a first safety index of the corresponding walking road section walking at night according to at least one of the night track and the average driving speed at night; and the night track quantity ratio and the night average driving speed are in direct proportion to the first safety index.

In some optional implementations of the present embodiment, the feature acquiring unit may include an image feature acquiring subunit that acquires an image feature of each walking road segment constituting each candidate walking route, and the image feature acquiring subunit may be further configured to:

acquiring an image database obtained by shooting a walking road section by a vehicle event data recorder;

determining street lamp characteristics and construction characteristics of each walking road section according to the image database;

correspondingly, the second safety index determining unit may be further configured to:

determining a second safety index of the corresponding walking road section walking at night according to at least one of the street lamp characteristics and the construction characteristics; the street lamp feature represents that the street lamp density and the second safety index are in a direct proportion relation, and the construction feature represents that the quantity of the existing construction obstacles and the second safety index are in an inverse proportion relation.

In some optional implementations of the present embodiment, the feature obtaining unit may include a road state feature obtaining subunit that obtains a road state feature of each walking segment constituting each candidate walking route, and the road state feature obtaining subunit may be further configured to:

determining at least one of the public traffic station density, the road laying mode, the construction state, the monitoring camera density, the number of non-motor vehicle lanes and the average occurrence number of illegal events of each walking road section according to a road network database;

correspondingly, the third safety index determining unit may be further configured to:

determining a third safety index of walking at night on a corresponding walking road section according to at least one of the density of public transport stations, the road laying mode, the construction state, the density of monitoring cameras, the number of non-motorized lanes and the average number of illegal events; the public transport station density, the ground flatness represented by the road paving mode and the monitoring camera density are in direct proportion to the third safety index, and the construction barrier number, the non-motor vehicle lane number and the average illegal event occurrence number represented by the construction state are in direct proportion to the third safety index.

In some optional implementations of the present embodiment, the feature acquisition unit may include a store feature acquisition subunit that acquires a store feature of each walking link constituting each candidate walking route, and the store feature acquisition subunit may be further configured to:

determining at least one of the number of night business stores and the average store level of each walking road section according to the store distribution data; wherein the store level of the nighttime non-profit stores is higher than the store level of the nighttime profit stores;

correspondingly, the fourth safety index determining unit may be further configured to:

determining a fourth safety index of the corresponding walking road section walking at night according to at least one of the number of the night business shops and the average shop level; the number of the night business shops and the average shop grade are in direct proportion to the fourth safety index.

In some optional implementations of the present embodiment, the night walk safety level determination unit may be further configured to:

the sum of the composite safety indexes of the individual walking segments constituting each candidate walking route is determined as the nighttime walking safety degree of the corresponding candidate walking route.

In some optional implementations of this embodiment, the night safe walking route determining unit 903 may be further configured to:

dividing each candidate walking route to a plurality of preset nighttime walking preferences;

the candidate walking route having the highest nighttime walking safety level in each nighttime walking preference is determined as the nighttime safe walking route in the corresponding nighttime walking preference.

This embodiment exists as an embodiment of the device corresponding to the above method embodiment, and provides a night walk navigation device，The method comprises the steps of determining a walking navigation starting point and a walking navigation end point after receiving a night walking travel request, determining a plurality of candidate walking routes based on the walking navigation starting point and the walking navigation end point, and then determining the night walking safety degree of each candidate walking route, namely determining the candidate walking route capable of walking safely at night as the night walking route by considering the safety influence on walking caused by night, so that navigation content with high safety can be provided for a user, and the personal and property safety of the user walking at night can be guaranteed.

According to an embodiment of the present disclosure, the present disclosure also provides an electronic device including: at least one processor; and a memory communicatively coupled to the at least one processor; wherein the memory stores instructions executable by the at least one processor, the instructions being executable by the at least one processor to enable the at least one processor, when executed, to implement the method for night walk navigation as described in any of the embodiments above.

According to an embodiment of the present disclosure, there is also provided a readable storage medium storing computer instructions for enabling a computer to implement the night walk navigation method described in any of the above embodiments when executed.

According to an embodiment of the present disclosure, there is also provided a computer program product, which when executed by a processor, is capable of implementing the night walk navigation method described in any of the above embodiments.

FIG. 10 illustrates a schematic block diagram of an example electronic device 1000 that can be used to implement embodiments of the present disclosure. Electronic devices are intended to represent various forms of digital computers, such as laptops, desktops, workstations, personal digital assistants, servers, blade servers, mainframes, and other appropriate computers. Electronic devices may also represent various forms of mobile devices, such as personal digital processors, cellular telephones, smart phones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions, are meant to be examples only, and are not meant to limit implementations of the disclosure described and/or claimed herein.

As shown in fig. 10, the apparatus 1000 includes a computing unit 1001 that can perform various appropriate actions and processes according to a computer program stored in a Read Only Memory (ROM)1002 or a computer program loaded from a storage unit 1008 into a Random Access Memory (RAM) 1003. In the RAM 1003, various programs and data necessary for the operation of the device 1000 can also be stored. The calculation unit 1001, the ROM 1002, and the RAM 1003 are connected to each other by a bus 1004. An input/output (I/O) interface 1005 is also connected to bus 1004.

A number of components in device 1000 are connected to I/O interface 1005, including: an input unit 1006 such as a keyboard, a mouse, and the like; an output unit 1007 such as various types of displays, speakers, and the like; a storage unit 1008 such as a magnetic disk, an optical disk, or the like; and a communication unit 1009 such as a network card, a modem, a wireless communication transceiver, or the like. The communication unit 1009 allows the device 1000 to exchange information/data with other devices through a computer network such as the internet and/or various telecommunication networks.

Computing unit 1001 may be a variety of general and/or special purpose processing components with processing and computing capabilities. Some examples of the computing unit 1001 include, but are not limited to, a Central Processing Unit (CPU), a Graphics Processing Unit (GPU), various dedicated Artificial Intelligence (AI) computing chips, various computing units running machine learning model algorithms, a Digital Signal Processor (DSP), and any suitable processor, controller, microcontroller, and so forth. The calculation unit 1001 executes the respective methods and processes described above, such as the nighttime walking navigation method. For example, in some embodiments, the night walk navigation method may be implemented as a computer software program tangibly embodied in a machine-readable medium, such as storage unit 1008. In some embodiments, part or all of the computer program may be loaded and/or installed onto device 1000 via ROM 1002 and/or communications unit 1009. When the computer program is loaded into RAM 1003 and executed by the computing unit 1001, one or more steps of the nighttime walking navigation method described above may be performed. Alternatively, in other embodiments, the computing unit 1001 may be configured to perform the night walk navigation method by any other suitable means (e.g., by means of firmware).

Various implementations of the systems and techniques described here above may be implemented in digital electronic circuitry, integrated circuitry, Field Programmable Gate Arrays (FPGAs), Application Specific Integrated Circuits (ASICs), Application Specific Standard Products (ASSPs), system on a chip (SOCs), load programmable logic devices (CPLDs), computer hardware, firmware, software, and/or combinations thereof. These various embodiments may include: implemented in one or more computer programs that are executable and/or interpretable on a programmable system including at least one programmable processor, which may be special or general purpose, receiving data and instructions from, and transmitting data and instructions to, a storage system, at least one input device, and at least one output device.

Program code for implementing the methods of the present disclosure may be written in any combination of one or more programming languages. These program codes may be provided to a processor or controller of a general purpose computer, special purpose computer, or other programmable data processing apparatus, such that the program codes, when executed by the processor or controller, cause the functions/operations specified in the flowchart and/or block diagram to be performed. The program code may execute entirely on the machine, partly on the machine, as a stand-alone software package, partly on the machine and partly on a remote machine or entirely on the remote machine or server.

In the context of this disclosure, a machine-readable medium may be a tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. The machine-readable medium may be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. More specific examples of a machine-readable storage medium would include an electrical connection based on one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

To provide for interaction with a user, the systems and techniques described here can be implemented on a computer having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to a user; and a keyboard and a pointing device (e.g., a mouse or a trackball) by which a user can provide input to the computer. Other kinds of devices may also be used to provide for interaction with a user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user may be received in any form, including acoustic, speech, or tactile input.

The systems and techniques described here can be implemented in a computing system that includes a back-end component (e.g., as a data server), or that includes a middleware component (e.g., an application server), or that includes a front-end component (e.g., a user computer having a graphical user interface or a web browser through which a user can interact with an implementation of the systems and techniques described here), or any combination of such back-end, middleware, or front-end components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: local Area Networks (LANs), Wide Area Networks (WANs), and the Internet.

The computer system may include clients and servers. A client and server are generally remote from each other and typically interact through a communication network. The relationship of client and server arises by virtue of computer programs running on the respective computers and having a client-server relationship to each other. The Server may be a cloud Server, which is also called a cloud computing Server or a cloud host, and is a host product in a cloud computing service system, so as to solve the defects of high management difficulty and weak service extensibility in the conventional physical host and Virtual Private Server (VPS) service.

According to the technical scheme of the embodiment of the disclosure, the walking navigation starting point and the walking navigation end point are determined after the night walking travel request is received, the plurality of candidate walking routes are determined based on the walking navigation starting point and the walking navigation end point, then the night walking safety degree of each candidate walking route is determined, namely the influence of night walking on walking is considered, and further the candidate walking route which can walk safely at night is determined as the night walking route, so that the navigation content with high safety can be provided for the user, and the personal and property safety of the user walking at night is guaranteed.

It should be understood that various forms of the flows shown above, reordering, adding or deleting steps, may be used. For example, the steps described in the present disclosure may be executed in parallel, sequentially, or in different orders, as long as the desired results of the technical solutions disclosed in the present disclosure can be achieved, and the present disclosure is not limited herein.

The above detailed description should not be construed as limiting the scope of the disclosure. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions may be made in accordance with design requirements and other factors. Any modification, equivalent replacement, and improvement made within the spirit and principle of the present disclosure should be included in the protection scope of the present disclosure.

Claims

1. A night walk navigation method, comprising:

determining a walking navigation starting point and a walking navigation end point according to the acquired night walking travel request;

determining each candidate walking route according to the walking navigation starting point and the walking navigation end point;

determining a safe walking route at night according to the safe walking degree at night of each candidate walking route;

and outputting night walking navigation content corresponding to the night safe walking route.

2. The method according to claim 1, wherein before determining the night safe walking route based on the night walk safe degree of each of the candidate walking routes, further comprising:

acquiring at least one of a trajectory feature, an image feature, a road state feature, and a shop feature of each walking link constituting each of the candidate walking routes;

in response to the acquisition of the track characteristics, determining a first safety index of the corresponding walking road section walking at night according to the track characteristics;

in response to the image characteristics are obtained, determining a second safety index of the corresponding walking road section walking at night according to the image characteristics;

in response to the road state characteristics being obtained, determining a third safety index of the corresponding walking road section walking at night according to the road state characteristics;

in response to obtaining the store characteristics, determining a fourth safety index of the corresponding walking road section walking at night according to the store characteristics;

determining a composite safety index for each pedestrian segment based on at least one of the first safety index, the second safety index, the third safety index, and the fourth safety index;

determining a nighttime walking safety degree of each of the candidate walking routes based on the composite safety index of each walking link constituting each of the candidate walking routes.

3. The method of claim 2, wherein obtaining the trajectory characteristic for each pedestrian segment that constitutes each of the candidate pedestrian routes comprises:

determining each of the walking links constituting each of the candidate walking routes;

correspondingly, the determining a first safety index of the corresponding walking road section walking at night according to the track characteristics comprises the following steps:

determining a first safety index of the corresponding walking road section walking at night according to at least one of the night track and the night average driving speed; and the night track quantity ratio and the night average driving speed are in a direct proportion relation with the first safety index.

4. The method according to claim 2, wherein obtaining the image feature of each walking road segment constituting each of the candidate walking routes includes:

correspondingly, the determining the second safety index of the corresponding walking road section walking at night according to the image characteristics comprises the following steps:

determining a second safety index of the corresponding walking road section walking at night according to at least one of the street lamp characteristics and the construction characteristics; the street lamp feature represents that the street lamp density is in a direct proportion relation with the second safety index, and the construction feature represents that the number of the construction obstacles is in an inverse proportion relation with the second safety index.

5. The method according to claim 2, wherein acquiring the road-state feature of each of the walking segments constituting each of the candidate walking routes includes:

determining at least one of the public transportation station density, the road laying mode, the construction state, the monitoring camera density, the number of non-motor vehicle lanes and the average occurrence number of illegal events of each walking road section according to a road network database;

correspondingly, the determining the third safety index of the corresponding walking section walking at night according to the road state characteristics comprises:

determining a third safety index of the corresponding walking road section walking at night according to at least one of the public transport station density, the road laying mode, the construction state, the monitoring camera density, the number of the non-motorized lanes and the average illegal event occurrence number; the public transport station density, the ground flatness represented by the road paving mode and the monitoring camera density are in direct proportion to the third safety index, and the number of construction obstacles represented by the construction state, the number of non-motor vehicle lanes and the average illegal event occurrence number are in direct proportion to the third safety index.

6. The method according to claim 2, wherein acquiring the store characteristics of each of the pedestrian sections constituting each of the candidate pedestrian routes includes:

determining at least one of the number of night business shops and the average shop level of each walking road section according to shop distribution data; wherein the store level of the nighttime non-profit store is higher than the store level of the nighttime profit store;

correspondingly, the determining a fourth safety index of the corresponding walking road section walking at night according to the shop characteristics comprises:

determining a fourth safety index of walking at night on the corresponding walking road section according to at least one of the number of the night business stores and the average store level; wherein the number of night shop and the average shop level are both proportional to the fourth safety index.

7. The method according to claim 2, wherein the determining the nighttime walking safety degree of each of the candidate walking routes based on the composite safety index for each walking segment constituting each of the candidate walking routes includes:

and determining the sum of the composite safety indexes of the walking sections constituting each of the candidate walking routes as the nighttime walking safety degree of the corresponding candidate walking route.

8. The method according to any one of claims 1 to 7, wherein the determining a nighttime safe walking route according to the nighttime walking safety level of each of the candidate walking routes comprises:

dividing each candidate walking route into a plurality of preset nighttime walking preferences;

determining the candidate walking route having the highest walking safety degree at night under each of the walking preferences at night as a safe walking route at night under the corresponding walking preference at night.

9. A night walk navigation device comprising:

a walking navigation starting/end point determining unit configured to determine a walking navigation starting point and a walking navigation end point according to the acquired night walking travel request;

a candidate walking route determination unit configured to determine each candidate walking route based on the walking navigation start point and the walking navigation end point;

a nighttime safe walking route determination unit configured to determine a nighttime safe walking route based on a nighttime walking safety degree of each of the candidate walking routes;

a night walk guidance content output unit configured to output night walk guidance content corresponding to the night safe walk route.

10. The apparatus of claim 9, further comprising:

a feature acquisition unit configured to acquire at least one of a trajectory feature, an image feature, a road state feature, and a shop feature of each of the walking links constituting each of the candidate walking routes;

a first safety index determining unit configured to determine a first safety index of the corresponding walking road section walking at night according to the track characteristics in response to the track characteristics being acquired;

a second safety index determination unit configured to determine, in response to acquisition of the image feature, a second safety index at which the corresponding walking section walks at night according to the image feature;

a third safety index determination unit configured to determine, in response to acquisition of the road state feature, a third safety index at which the corresponding walking section walks at night according to the road state feature;

a fourth safety index determination unit configured to determine, in response to acquisition of the store characteristics, a fourth safety index at which the corresponding walking section walks at night according to the store characteristics;

a comprehensive safety index determination unit configured to determine a comprehensive safety index for each pedestrian section according to at least one of the first safety index, the second safety index, the third safety index, and the fourth safety index;

a nighttime walking safety degree determination unit configured to determine a nighttime walking safety degree for each of the candidate walking routes based on the composite safety index for each walking link constituting each of the candidate walking routes.

11. The apparatus according to claim 10, wherein the feature acquisition unit includes a trajectory feature acquisition subunit that acquires a trajectory feature of each walking road segment constituting each of the candidate walking routes, the trajectory feature acquisition subunit being further configured to:

determining a first safety index of the corresponding walking road section walking at night according to at least one of the night track and the night average driving speed; and the proportion of the number of the night tracks and the average driving speed at night are in direct proportion to the first safety index.

12. The apparatus according to claim 10, wherein the feature acquisition unit includes an image feature acquisition subunit that acquires an image feature of each walking road segment constituting each of the candidate walking routes, the image feature acquisition subunit being further configured to:

correspondingly, the second safety index determination unit is further configured to:

13. The apparatus according to claim 10, wherein the feature acquisition unit includes a road-state-feature acquisition subunit that acquires road-state features of the respective walking segments that constitute the respective candidate walking routes, the road-state-feature acquisition subunit being further configured to:

correspondingly, the third safety index determination unit is further configured to:

determining a third safety index of the corresponding walking road section walking at night according to at least one of the density of public transportation stations, the road laying mode, the construction state, the density of monitoring cameras, the number of non-motor vehicle lanes and the average illegal events; the public transport station density, the ground flatness represented by the road paving mode and the monitoring camera density are in direct proportion to the third safety index, and the number of construction obstacles represented by the construction state, the number of non-motor vehicle lanes and the average illegal event occurrence number are in direct proportion to the third safety index.

14. The apparatus according to claim 10, wherein the feature acquisition unit includes a store feature acquisition subunit that acquires a store feature of each walking link constituting each of the candidate walking routes, the store feature acquisition subunit being further configured to:

determining at least one of the number of night business shops and the average shop level of each walking road section according to shop distribution data; wherein the store level of the nighttime non-profit stores is higher than the store level of the nighttime profit stores;

correspondingly, the fourth safety index determining unit is further configured to:

15. The apparatus of claim 10, wherein the night walk safety level determination unit is further configured to:

and determining the sum of the composite safety indexes of the walking sections forming each candidate walking route as the nighttime walking safety degree of the corresponding candidate walking route.

16. The apparatus according to any one of claims 9-15, wherein the night safe walking route determining unit is further configured to:

dividing each candidate walking route into preset multiple nighttime walking preferences;

17. An electronic device, comprising:

at least one processor; and

a memory communicatively coupled to the at least one processor; wherein the content of the first and second substances,

the memory stores instructions executable by the at least one processor to enable the at least one processor to perform the method of night walk navigation of any one of claims 1-8.

18. A non-transitory computer-readable storage medium storing computer instructions for causing a computer to perform the night walk navigation method of any one of claims 1-8.

19. A computer program product comprising a computer program which, when being executed by a processor, carries out the steps of the method for night walk navigation according to any one of claims 1-8.