Destination arrival time estimation method and apparatus, and computer readable storage medium for executing method

Abstract

The invention relates to a destination arrival time estimation method, a destination arrival time estimation device and a computer readable storage medium for executing the method. The destination arrival time estimation method comprises: a link set setting step of setting a link set for an entrance / exit road of a rest area so as to obtain driving information of vehicles entering and leaving the rest area; a vehicle travel data collection step of collecting, by a global positioning system (GPS), travel data of the vehicle generated in units of link sets; a rest area congestion condition determination step of determining a congestion condition in the rest area based on the collected driving data of the vehicle, and providing information about the congestion condition to the driver; and an estimated time-of-arrival providing step of deriving, on the basis of the collected travel data of the vehicle, an average stay time at which the driver stays in the rest area, and providing the changed estimated time-of-arrival (ETA) to the driver who intends to use the rest area.

Description

[0001] Cross-references to related applications This application claims the benefit and priority of Korean Patent Application No. 10-2024-0166068, filed on November 20, 2024, the entire contents of which are hereby incorporated by reference. Technical Field

[0002] This disclosure relates to a method for estimating time of arrival at a destination and an apparatus for estimating time of arrival at a destination using the method. Background Technology

[0003] Navigation systems have been developed to guide users in choosing the optimal route to their destination. These systems primarily rely on the Global Positioning System (GPS) and operate to identify the user's current location and calculate the route to the destination using map databases. However, navigation systems typically provide routes simply based on distance and road information. Therefore, they have limitations because they cannot reflect real-time traffic conditions.

[0004] In addition, traffic information such as real-time speed and predicted speed provided by navigation systems is generated and processed on a road link basis in a Geographic Information System (GIS), and this traffic information is used to derive the estimated time of arrival (ETA).

[0005] Beyond simple route guidance, modern navigation systems offer a variety of information, such as traffic conditions at the destination and parking availability. However, they fail to specifically reflect factors indirectly related to vehicle movement, such as the driver's use of rest areas.

[0006] The discussion in this background section is intended to provide background information only and does not constitute an endorsement of the prior art. Summary of the Invention

[0007] Embodiments of this disclosure provide a destination arrival time estimation method and a destination arrival time estimation apparatus that can solve the above-mentioned problems.

[0008] Embodiments of this disclosure provide a destination arrival time estimation method and a destination arrival time estimation device using the method, which more accurately estimates the expected arrival time at the destination by reflecting the driver's dwell time at highway rest areas.

[0009] Embodiments of this disclosure provide a destination arrival time estimation method and a destination arrival time estimation device using the method, which estimates and reflects the driver's dwell time in the rest area by taking into account congestion in the rest area, thereby predicting a more accurate destination arrival time.

[0010] Embodiments of this disclosure provide a destination arrival time estimation method and a destination arrival time estimation device using the method to predict congestion to determine whether parking spaces in each rest area are available and / or accurately predict the driver's stay time in the rest area and reflect the predicted time in the estimated arrival time.

[0011] The embodiments of this disclosure provide a destination arrival time estimation method and a destination arrival time estimation device, which set up a link set for the entrance / exit roads of the rest area and collect vehicle driving data to derive the congestion situation in the rest area.

[0012] The embodiments of this disclosure provide a destination arrival time estimation method and a destination arrival time estimation device. A link set is set for the entrance / exit roads of the rest area, vehicle driving data is collected to derive the dwell time of the vehicle in the rest area, and an estimated arrival time reflecting the dwell time is provided.

[0013] According to embodiments of this disclosure, a destination arrival time estimation method is provided. The destination arrival time estimation method includes: a link set setting step, setting up link sets for rest area entrance / exit roads to obtain driving information of vehicles entering and leaving the rest area; and a vehicle driving data collection step, collecting vehicle driving data generated in units of link sets via a Global Positioning System (GPS). The destination arrival time estimation method further includes: a rest area congestion determination step, determining the congestion situation within the rest area based on the collected vehicle driving data, and providing drivers with information about the congestion situation. Furthermore, the destination arrival time estimation method includes: an estimated arrival time provision step, deriving the average dwell time of vehicles in the rest area based on the collected vehicle driving data, and providing drivers intending to use the rest area with a modified estimated arrival time (ETA).

[0014] The attributes of a link set can be at least one of the following: main line entrance road from the main line to the rest area, main line exit road from the rest area to the main line, connecting road entrance road from the connecting road to the rest area, and connecting road exit road from the rest area to the connecting road.

[0015] Connecting roads can include all roads that connect to rest areas, in addition to the main road which serves as the main road.

[0016] The steps for determining congestion in the rest area may include: a first detection data selection step, where first detection data is selected as the processing target for determining congestion in the rest area. The steps may also include: an entrance link set detection data aggregation step, where, based on the processing time point, detection data matching past entrance link sets is aggregated from the first detection data. Furthermore, the steps may include: an exit link set detection data aggregation step, where, based on the processing time point in the first detection data, detection data not matching the current exit link set is aggregated, and the number of vehicles that have not left the rest area is derived; and a rest area congestion determination step, where the congestion in the rest area is determined by considering the number of parking spaces within the rest area.

[0017] The first detection data may include: the link set attributes of the main line entrance road and the main line exit road, as well as the link set attributes of the main line entrance road and the connecting road exit road.

[0018] In the ingress link set probing data aggregation step, probing data that matches the ingress link set within the past 60 minutes can be aggregated based on the processing time point.

[0019] In the step of determining congestion in the rest area, the congestion can be determined as (number of vehicles that have not left the rest area / number of parking spaces in the rest area) × 100.

[0020] In the process of determining congestion in rest areas, the congestion situation can be identified through four stages: "No information available," "Sufficient parking spaces," "Normal state," and "Congested state." "No information available" can refer to a situation where there is no information about the rest area.

[0021] "Sufficient parking spaces" can refer to a situation where congestion is less than 10%, "normal state" can refer to a situation where congestion is more than 10% but less than 70%, and "congested state" can refer to a situation where congestion is more than 70%.

[0022] The estimated arrival time provision step may include: a second probe data selection step, selecting second probe data, which is the processing target used to provide the estimated arrival time. The estimated arrival time provision step may also include: an inbound link set probe data aggregation step, aggregating probe data that matches past inbound link sets based on the processing time points in the second probe data. Furthermore, the estimated arrival time provision step may include: an outbound link set probe data aggregation step, aggregating probe data that matches the current outbound link set and probe data that does not match the current outbound link set based on the processing time points in the second probe data. The estimated arrival time provision step may also include: deriving the current estimated dwell time based on rest area dwell time information derived from the probe data matching the outbound link set and past dwell time information of vehicles corresponding to the probe data that does not match the outbound link set, and reflecting the current estimated dwell time in the estimated arrival time.

[0023] The second detection data may include: the link set attributes of the main line entrance road and the main line exit road.

[0024] In the ingress link set probing data aggregation step, probing data that matches the ingress link set within the past 60 minutes can be aggregated based on the processing time point.

[0025] For vehicles corresponding to detection data that match the ingress link set, the current estimated dwell time can be derived by calculating the average dwell time of the vehicle's real-time rest area dwell time information and the vehicle's past rest area dwell time information. The real-time rest area dwell time information is derived from the detection data that matches the exit link set, while the past rest area dwell time information is derived from the detection data that does not match the exit link set.

[0026] The current estimated duration of stay may include either a first estimated duration of stay reflecting a short stay in the rest area or a second estimated duration of stay reflecting a long stay in the rest area.

[0027] The first estimated dwell time can be applied using dwell time data corresponding to the bottom 25% of the average dwell time data distribution, and the second estimated dwell time can be applied using dwell time data corresponding to the bottom 75% of the average dwell time data distribution.

[0028] The system can provide drivers with rest area stay time information in three stages: "no stop in the rest area," "short stop in the rest area," and "long stop in the rest area." In the case of "no stop in the rest area," the previously provided estimated arrival time can be maintained. In the case of "short stop in the rest area," the estimated arrival time can reflect the first estimated stay time, and in the case of "long stop in the rest area," the estimated arrival time can reflect the second estimated stay time.

[0029] According to another embodiment of the present disclosure, a computer-readable recording medium is provided that stores a program that enables a computer to perform a destination arrival time estimation method.

[0030] According to another embodiment of this disclosure, a destination arrival time estimation device is provided. The destination arrival time estimation device includes: a link set setting circuit configured to set link sets for rest area entrance / exit roads to obtain driving information of vehicles entering and leaving the rest area. The destination arrival time estimation device also includes: a vehicle driving data collection circuit configured to collect vehicle driving data generated in units of link sets via a Global Positioning System (GPS). Furthermore, the destination arrival time estimation device includes: a rest area congestion determination circuit configured to determine congestion within the rest area based on the collected vehicle driving data and provide drivers with information about the congestion. The destination arrival time estimation device also includes: an estimated arrival time providing circuit configured to derive the average dwell time of vehicles in the rest area based on the collected vehicle driving data and provide drivers intending to use the rest area with a modified estimated arrival time (ETA).

[0031] The rest area congestion determination circuit may include: a first detection data selection unit configured to select first detection data, which is the processing target for determining the congestion situation of the rest area. The rest area congestion determination circuit may further include: an entrance link set detection data aggregation unit configured to aggregate detection data matching past entrance link sets based on processing time points in the first detection data. Furthermore, the rest area congestion determination circuit may include: an exit link set detection data aggregation unit configured to aggregate detection data not matching the current exit link set in the first detection data based on processing time points, and to derive the number of vehicles that have not left the rest area. The rest area congestion determination circuit may also include: a rest area congestion determination unit configured to determine the congestion situation within the rest area by considering the number of parking spaces within the rest area.

[0032] The estimated arrival time providing circuit may include: a second detection data selection unit, which selects second detection data, which is a processing target for providing the estimated arrival time. The estimated arrival time providing circuit may also include: an inbound link set detection data aggregation unit, which aggregates detection data that matches past inbound link sets based on the processing time points in the second detection data. Furthermore, the estimated arrival time providing circuit may include: an outbound link set detection data aggregation unit, which aggregates detection data that matches the current outbound link set and detection data that does not match the current outbound link set based on the processing time points in the second detection data. The estimated arrival time providing circuit may also include: an estimated dwell time derivation unit, which derives the current estimated dwell time based on rest area dwell time information derived from detection data that matches the outbound link set and past dwell time information of vehicles corresponding to detection data that does not match the outbound link set, and reflects the current estimated dwell time in the estimated arrival time.

[0033] The current estimated stay time may include: a first estimated stay time reflecting a short stay in the rest area or a second estimated stay time reflecting a long stay in the rest area, wherein the first estimated stay time applies to the bottom 25% of stay time data in the average stay time data distribution, and the second estimated stay time applies to the bottom 75% of stay time data in the average stay time data distribution.

[0034] As described above, according to embodiments of this disclosure, even in spaces where no link is established, the time required for parking can be predicted by collecting vehicle link driving data and trajectory data.

[0035] Furthermore, according to embodiments of this disclosure, a destination arrival time estimation method and a destination arrival time estimation device can be provided. The destination arrival time estimation method and the destination arrival time estimation device can derive the congestion situation in the rest area by setting up a link set for the entrance / exit roads of the rest area and collecting vehicle driving data.

[0036] Furthermore, according to embodiments of this disclosure, a destination arrival time estimation method and a destination arrival time estimation device can be provided. The destination arrival time estimation method and the destination arrival time estimation device can derive the dwell time of vehicles by setting up a link set for the entrance / exit roads of the rest area and collecting the driving data of vehicles in the rest area, thereby providing an estimated arrival time reflecting the dwell time.

[0037] The technical aspects to be implemented in this disclosure are not limited to those described above. Other technical aspects not described herein should be more clearly understood by those skilled in the art from the following description. Attached Figure Description

[0038] To enable those skilled in the art to understand this disclosure, various forms of the disclosure are described by way of example with reference to the accompanying drawings, wherein: Figure 1 This is a diagram showing the link set of entrance and exit roads of a rest area according to an embodiment; Figure 2 This is a flowchart illustrating a destination arrival time estimation method according to an embodiment; Figure 3 This is a diagram illustrating the link set attributes of the main line entrance road and the main line exit road according to the implementation method; Figure 4 This is a diagram illustrating the link set attributes of the main route entrance road and the connecting road exit road according to the implementation method; Figure 5 This is a diagram illustrating the link set attributes of the connecting road entrance road and the main road exit road according to an embodiment; Figure 6 This is a diagram illustrating the link set attributes of connecting road entrance roads and connecting road exit roads according to an embodiment; Figure 7 This is a flowchart illustrating the detailed process of determining the congestion situation in the rest area according to the implementation method; Figure 8 This is a flowchart illustrating the detailed process of providing the estimated arrival time according to an implementation method; Figure 9 This is a diagram illustrating an example of the process of selecting and aggregating probe data according to an implementation method; Figure 10 This is a diagram illustrating an example of the process of processing aggregated probe data according to an embodiment; Figure 11 This is a diagram illustrating an example of providing drivers with information on congestion in a rest area according to an embodiment; Figure 12 This is a diagram illustrating an example of providing drivers with estimated arrival times reflecting rest area dwell time information according to an embodiment; and Figure 13 This is a schematic diagram illustrating a destination arrival time estimation device according to an embodiment. Detailed Implementation

[0039] In the following description, embodiments of the present disclosure are described in detail with reference to the illustrative drawings. When assigning reference numerals to components in the figures, care should be taken to assign the same reference numerals to the same components whenever possible, even if the same components appear in different figures. Furthermore, in describing the present disclosure, detailed descriptions of configurations or functions known in the prior art have been omitted where such detailed descriptions might obscure the concepts of the present disclosure.

[0040] Furthermore, terms such as first, second, a, and b may be used to describe components of embodiments of this disclosure. These terms are intended only to distinguish one component from another and do not limit the characteristics, order, or sequence of the components. When describing a component as “connected,” “coupled,” or “engaged” to another component, a component may be directly connected or engaged to another component. However, it should be understood that yet another component may be “connected,” “coupled,” or “engaged” between these components.

[0041] When components, controllers, devices, elements, equipment, circuits, units, etc., of this disclosure are described as having a purpose or performing an operation or function, they should be considered herein as being "configured" to satisfy that purpose or perform that operation or function. Each component, controller, device, element, equipment, circuit, unit, etc., may be embodied separately or included as part of a device together with a processor and memory (a non-transitory computer-readable medium).

[0042] Terms such as "...circuit", "...unit", etc., used in this specification may refer to a unit capable of performing at least one function or operation described in this specification, and this may be implemented by hardware, software, or a combination of hardware and software. Furthermore, according to the embodiments described below, at least a portion of the configuration or function of the destination arrival time estimation method and apparatus may be implemented as a program or software, and this program or software may be stored in a computer-readable recording medium or storage medium.

[0043] Figure 1 This is a diagram showing the link set of entrance and exit roads for a rest area according to an embodiment.

[0044] refer to Figure 1 The rest area has entrance and exit roads for vehicles 10 to enter and exit. The entrance and exit roads are provided with a main road 11 for the main customers using the rest area and connecting roads 12 that connect to the rest area in addition to the main road 11.

[0045] Each entrance road and each exit road may include a main road entrance road 101 for vehicles traveling from the main road 11 to the rest area, a main road exit road 102 for vehicles traveling from the rest area to the main road 11, a connecting road entrance road 103 for vehicles traveling from the connecting road 12 to the rest area, and a connecting road exit road 104 for vehicles traveling from the rest area to the connecting road 12.

[0046] The destination arrival time estimation method according to the implementation method may include: a link set setting step, setting up link sets for rest area entrance / exit roads to obtain driving information of vehicles entering and leaving the rest area; a vehicle driving data collection step, collecting vehicle driving data generated in units of link sets via a global positioning system (GPS); a rest area congestion determination step, determining the congestion situation in the rest area based on the collected vehicle driving data, and providing the determined congestion situation to the driver; and an estimated arrival time providing step, deriving the average dwell time of vehicles in the rest area based on the collected vehicle driving data, and providing the modified estimated arrival time (ETA) to the driver intending to use the rest area.

[0047] Figure 2 This is a flowchart illustrating a destination arrival time estimation method according to an implementation method.

[0048] refer to Figure 2 The destination arrival time estimation method S200 may include a link set setting step or operation S210, a vehicle driving data collection step or operation S220, a rest area congestion determination step or operation S230, and an estimated arrival time provision step or operation S240. In an implementation, the rest area congestion determination step or operation S230 and the estimated arrival time provision step or operation S240 may be performed in parallel.

[0049] In the link set setting step or operation S210, a link set can be set for the exit road or entrance road of the rest area to obtain the driving information of vehicles leaving or entering the rest area.

[0050] Links are the basic units for configuring road networks and are essentially a concept used for route finding and providing real-time traffic information. A link represents a specific area and is typically defined as a short area with independent traffic flow, such as a road or sloping area between intersections. These links are combined to form a road network. Through these links, navigation systems guide routes and provide traffic information.

[0051] Figures 3 to 6 This is a diagram showing the link set attributes of the entrance and exit roads.

[0052] refer to Figures 3 to 6 This allows us to confirm the properties of the set of links required to estimate the expected arrival time at the destination by reflecting the dwell time in the rest area.

[0053] Specifically, Figure 3 The link set attributes of the main line entrance road for vehicles 10 entering the rest area from the main line 11 and the main line exit road for vehicles 10 entering the main line 11 from the rest area are shown according to an embodiment. Figure 4The link set attributes of the main line entrance road for vehicles 10 entering the rest area from the main line 11 and the connecting road exit road for vehicles 10 entering the connecting road 12 from the rest area are shown according to an embodiment. Figure 5 The link set attributes of the connecting road entrance road for vehicles 10 entering the rest area from connecting road 12 and the main line exit road for vehicles 10 entering the main line 11 from the rest area are shown according to an embodiment. Figure 6 The link set attributes of the connecting road entrance road for vehicles 10 entering the rest area from the connecting road 12 and the connecting road exit road for vehicles 10 entering the connecting road 12 from the rest area are shown according to an embodiment.

[0054] Links in navigation systems possess various attributes. These typically include the link's start and end points, i.e., the geographic coordinates of where the link begins and ends. These points are usually distinguished by intersections or major junctions. The link's length indicates the distance within the corresponding area, and its directionality indicates whether the link is one-way or two-way. Furthermore, links have specified speed limits within their corresponding areas, and these speed limits are used as a key factor in the navigation system's calculation of estimated arrival times.

[0055] Road type is a standard used to distinguish road types (such as highways, general roads, and local roads). More specifically, links include traffic control information, such as prohibitions on right turns at intersections, the presence of traffic lights, and the number of lanes. This information plays a crucial role in enabling navigation systems to provide accurate route guidance.

[0056] Based on various properties of links, navigation systems find and guide paths. Pathfinding is the process of finding the optimal path by connecting the various links required for a vehicle to travel from its starting point to its destination. Pathfinding algorithms utilize graph-based algorithms (such as Dijkstra's algorithm and A*). Algorithms are used to calculate the shortest distance or the fastest path.

[0057] Navigation systems use these algorithms to calculate the optimal path to a destination based on the connections between links. This process takes into account information such as link lengths, speed limits, and traffic volume, and the travel time within each link is reflected in the estimated arrival time calculation.

[0058] Furthermore, the navigation system reflects real-time traffic conditions by updating traffic volume, accident information, and other data on a link-by-link basis. This configuration allows real-time traffic data to be coupled with link information on the network, enabling the provision of optimal routes. For example, when a particular link is congested due to an accident, construction work, or a rapid increase in traffic volume, the navigation system can reflect this situation and suggest an alternative route via another link.

[0059] To provide real-time traffic information link by link, various sensors and data collection devices need to be installed. Methods for collecting traffic information for each link can generally be classified into detection data collected from fixed sensors installed on the road and detection data collected from moving vehicles.

[0060] Fixed sensors include CCTV, radar, loop coils, etc., installed at specific points on the road. These fixed sensors detect traffic volume, vehicle speed, and accidents in the link and transmit traffic data in real time.

[0061] The detection data is location data collected from GPS devices installed on moving vehicles and used to calculate average speed and traffic conditions along the link. Based on this data, the navigation system identifies real-time traffic conditions along the link and updates the route.

[0062] Furthermore, congestion is measured link-by-link to predict road conditions. Congestion is calculated by comprehensively analyzing factors such as the number of vehicles in the link and their average speed. Based on this calculated congestion information, the navigation system can provide the user with congestion status information at each link and guide the user to a less congested route.

[0063] This link is used to run the Estimated Time of Arrival (ETA) function in the navigation system. This function calculates the total travel time by summing the travel times of each link from the origin to the destination. The travel time of each link is calculated by taking into account factors such as link distance, speed limits, and real-time traffic conditions.

[0064] For example, during peak traffic times (such as holidays or peak hours), travel times within links are extended, thus affecting ETA (Electronic Toll Collection). Specifically, navigation systems analyze past traffic patterns and real-time data to predict changes in traffic volume and travel time during specific time periods. In this way, the accuracy of ETA can be improved.

[0065] The concept of links can be used to predict dwell time and analyze congestion within highway rest areas. The entrance and exit areas of a rest area are each designated as a link, and the average dwell time is calculated by measuring the time it takes for vehicles to traverse the entrance link and the time it takes for vehicles to traverse the exit link. In this scenario, the navigation system can monitor vehicle flow link by link and determine congestion within the rest area in real time.

[0066] With this configuration, the navigation system provides congestion information for rest areas and guides drivers to avoid congested rest areas. For example, the navigation system analyzes information such as parking lot vacancy rates and average dwell times on a link-by-link basis, and can assist drivers in choosing rest areas with shorter dwell times. In addition to rest areas, the navigation system can monitor traffic conditions in road construction zones, accident zones, etc., on a link-by-link basis and provide drivers with real-time traffic information.

[0067] To obtain information such as congestion levels and dwell times at rest areas, link sets are established for the roads leading to or from the rest area. In this way, the navigation system can obtain driving information about vehicles entering or leaving the rest area.

[0068] In the vehicle driving data collection step or operation S220, the navigation system can collect driving data of vehicle 10 generated in units of link set units through the Global Positioning System (GPS).

[0069] Driving data collected through the Global Positioning System includes information recorded when a vehicle passes through a specific link, and includes information such as location, speed, time, and traffic volume.

[0070] Location data is collected via GPS devices and is crucial information for confirming whether a vehicle is located at any point on the link. Location data is used to track the vehicle's path based on the link's start and end points and serves as the basis for navigation systems to find and guide routes. Speed ​​data indicates how fast a vehicle is traveling within the link and is used to identify average and real-time speeds in the area. By collecting speed information link by link, the navigation system analyzes traffic flow within the link and calculates estimated travel time. This estimated travel time serves as an important indicator for determining traffic congestion or jams.

[0071] Time data is used to record the times when vehicles enter and leave a link, and to calculate the time required for a vehicle to traverse that link. Using this time data, the navigation system can calculate the average travel time link by link. Therefore, this time data can be used to calculate the estimated time of arrival (ETA). Time data is coupled with real-time traffic information to analyze traffic patterns over a specific time period and is also used to build traffic prediction models. Traffic volume data is used to determine congestion by measuring the number of vehicles within a link. Traffic volume can be calculated based on the number of vehicles passing through the link during a specific time period. Using this data, the navigation system can analyze congested traffic conditions and suggest alternative routes.

[0072] Acceleration and deceleration data indicate changes in vehicle speed as it travels along a link. Links where rapid acceleration or sudden braking occurs have a higher probability of traffic accidents or unexpected situations. Navigation systems use acceleration and deceleration data to provide drivers with safe driving information and predict accident risks. Lane change and lane keeping data are useful for identifying how vehicles are moving as they approach intersections or enter merging areas. High-precision navigation systems, such as those for autonomous vehicles, can use this lane information to provide more detailed driving guidance. Navigation systems can guide safe lane changes and safe driving by identifying whether there is traffic congestion or frequent lane changes in a specific lane.

[0073] Road condition data is information detected by a vehicle's sensors to check road surface conditions and the presence of obstacles, and includes various environmental factors such as road moisture, snow, and ice. This data plays a particularly important role in autonomous vehicles and safe driving systems. When roads are slippery, navigation systems can recommend that drivers reduce vehicle speed.

[0074] The detection data is various driving information collected from moving vehicles, including data on speed, acceleration, deceleration, and GPS location information. This data plays an important role in navigation systems for estimating real-time traffic conditions, identifying traffic congestion, and finding routes.

[0075] When traffic congestion or accidents occur on a link, congestion and accident data are collected in real time and used to update traffic conditions. Accident information is used in the navigation system to suggest alternative routes or provide road safety information. Using this data, the navigation system again searches for routes in real time to avoid links where accidents or congestion have occurred.

[0076] In the step or operation S230 of determining congestion in the rest area, the congestion situation in the rest area can be determined based on the vehicle driving data collected in this way, and this information can be provided to the driver.

[0077] Specifically, the navigation system can select first detection data, which is target data that needs to be processed to determine the congestion situation in the rest area. The first detection data may include link set attributes of mainline entrance roads and mainline exit roads, as well as link set attributes of mainline entrance roads and connecting road exit roads.

[0078] Next, in the ingress link set detection data aggregation step or operation, in the first detection data, the navigation system can aggregate detection data that matches past ingress link sets based on the processing time point. In the implementation, past ingress link sets refer to detection data that matches ingress link sets within the past 60 minutes based on the processing time point.

[0079] In the exit link set detection data aggregation step or operation, in the first detection data, the navigation system can derive the number of vehicles that have not left the rest area by aggregating detection data that does not match the current exit link set based on the processing time point.

[0080] In the steps or operations for determining congestion in the rest area, the navigation system can derive the number of vehicles that have not left the rest area through this process, and thereafter, the congestion situation in the rest area can be determined by taking into account the number of parking spaces within the rest area. Specifically, the congestion situation can be determined by using the following equation (1).

[0081] Equation (1): (Number of vehicles that have not left the rest area / Number of parking spaces in the rest area) × 100 Based on the congestion information determined through this process, the navigation system can provide drivers with congestion information about rest areas.

[0082] The congestion information provided to drivers can include four stages: "no information available", "sufficient parking spaces", "normal condition", and "congestion condition".

[0083] "No information available" means there is no information about the rest area. "Sufficient parking spaces" means congestion is less than 10%. "Normal" means congestion is more than 10% but less than 70%. "Congested" means congestion is more than 70%.

[0084] In the estimated arrival time provision step or operation S240, the navigation system can derive the average dwell time of the vehicle at the rest area based on the collected vehicle driving data, and can provide the modified estimated arrival time (ETA) to the driver intending to use the rest area.

[0085] For example, the navigation system can select second probe data, which is target data that needs to be processed to provide an estimated time of arrival. This second probe data may include link set attributes of mainline entrance roads and mainline exit roads.

[0086] Next, in the ingress link set probe data aggregation step or operation, within the second probe data, the navigation system can aggregate probe data that matches past ingress link sets based on the processing time point. In this implementation, past ingress link sets refer to probe data that matches ingress link sets within the past 60 minutes based on the processing time point. However, past ingress link sets are not limited to this, and the past time standard can be changed as needed.

[0087] In the step or operation of aggregating probe data for the exit link set, in the second probe data, the navigation system can aggregate probe data that matches the current exit link set and probe data that does not match the current exit link set based on the processing time point.

[0088] In the estimated dwell time derivation step or operation, the navigation system can derive the current estimated dwell time based on the rest area dwell time information derived from the detection data matched with the exit link set and the past dwell time information of vehicles corresponding to the detection data that does not match the exit link set, and can reflect the current estimated dwell time in the estimated arrival time.

[0089] In this implementation, for vehicles corresponding to detection data matching the entry link set, the current estimated dwell time can be derived by calculating the average dwell time of the vehicle's real-time rest area dwell time information and its past rest area dwell time information. The real-time rest area dwell time information is derived from detection data matching the exit link set, while the past rest area dwell time information is derived from detection data not matching the exit link set. Therefore, the navigation system can derive a more accurate dwell time based on real-time data of vehicles entering and leaving the rest area and past data of vehicles that have entered but not left the rest area. More specifically, the navigation system can use the average dwell time information of vehicles staying in the rest area based on the past driving data of vehicles that have entered but not left the rest area.

[0090] In addition, the current estimated stay time may include a first estimated stay time reflected in a short stay in the rest area, or a second estimated stay time reflected in a long stay in the rest area.

[0091] In one implementation, the first estimated stay time may be applied to the 25% of stay time data that rank lower in the average stay time data distribution, and the second estimated stay time may be applied to the 75% of stay time data that rank lower in the average stay time data distribution.

[0092] As used in this article, "the lower x%" can refer to the bottom x% of the data or to data at or below the xth percentile. Therefore, for example, "the lower 25% of the average stay time data distribution" can refer to the bottom 25% of the stay time data distribution or to stay time data at or below the 25th percentile. Similarly, "the lower 75% of the average stay time data distribution" can refer to the bottom 75% of the stay time data distribution or to stay time data at or below the 75th percentile.

[0093] For example, the average stay time data distribution used in estimating stay time refers to the distribution of data derived from the processing time point, based on the stay time data of vehicles using rest areas over the past four weeks.

[0094] The estimated dwell time information derived in this way can be provided to drivers in three phases: "no stay in the rest area", "short stay in the rest area", and "long stay in the rest area".

[0095] In the case of "no stop in the rest area", the previously provided estimated arrival time can be maintained; in the case of "short stop in the rest area", the first estimated stay time can be reflected in the estimated arrival time; and in the case of "long stay in the rest area", the second estimated stay time can be reflected in the estimated arrival time.

[0096] The roads connecting to the rest area may include a main road 11 and connecting roads 12. In this embodiment, the main road 11 refers to the main road used by the main customers of the rest area and may include highways, etc. Connecting roads 12 may include all roads connecting to the rest area other than the main road 11, which serves as the main road.

[0097] Figure 7 This is a flowchart illustrating the detailed process of determining the congestion situation in the rest area according to the implementation method.

[0098] refer to Figure 7 The steps or operations for determining congestion in the rest area S230 may include: a first detection data selection step or operation S231, an ingress link set detection data aggregation step or operation S232, an egress link set detection data aggregation step or operation S233, and a rest area congestion determination step or operation S234.

[0099] In the first detection data selection step or operation S231, the navigation system may aggregate first detection data as target data to be processed to determine the congestion situation of the rest area. The first detection data may include link set attributes of mainline entrance roads and mainline exit roads, as well as link set attributes of mainline entrance roads and connecting road exit roads.

[0100] In the ingress link set probe data aggregation step or operation S232, the navigation system can aggregate probe data that matches past ingress link sets based on the processing time point in the first probe data. In this implementation, past ingress link sets refer to probe data that matches ingress link sets within the past 60 minutes based on the processing time point. However, past ingress link sets are not limited to this, and the past time reference can be changed if necessary.

[0101] In the exit link set detection data aggregation step or operation S233, in the first detection data, the navigation system can aggregate detection data that does not match the current exit link set based on the processing time point, and can derive the number of vehicles that have not left the rest area.

[0102] In the step or operation S234 of determining congestion in the rest area, the navigation system can derive the number of vehicles that have not left the rest area through this process, and thereafter, the congestion situation in the rest area can be determined by taking into account the number of parking spaces in the rest area. Specifically, the congestion situation can be determined by using the above equation (1).

[0103] Based on the congestion situation determined through this step / operation, drivers can be provided with congestion information about rest areas.

[0104] The congestion information provided to drivers can include four stages: "no information available", "sufficient parking spaces", "normal condition", and "congestion condition".

[0105] "No information available" means there is no information about the rest area; "sufficient parking spaces" means congestion is less than 10%; "normal" means congestion is more than 10% but less than 70%; and "congested" means congestion is more than 70%.

[0106] Figure 8 This is a flowchart illustrating the detailed process of providing the estimated arrival time according to an implementation method.

[0107] refer to Figure 8 The estimated arrival time provision step or operation S240 may include: a second probe data selection step or operation S241, an ingress link set probe data aggregation step or operation S242, an egress link set probe data aggregation step or operation S243, and an estimated dwell time derivation step or operation S244.

[0108] In the second detection data selection step or operation S241, the navigation system can select second detection data, which is target data that needs to be processed to provide an estimated time of arrival. The second detection data may include link set attributes of the main route entrance roads and main route exit roads.

[0109] In the ingress link set probe data aggregation step or operation S242, the navigation system can aggregate probe data matching past ingress link sets based on the processing time point in the second probe data. In this implementation, past ingress link sets refer to probe data matching ingress link sets within the past 60 minutes based on the processing time point. However, past ingress link sets are not limited to this, and the past time reference can be changed if necessary.

[0110] In the step or operation S243 of aggregating probe data for the exit link set, the navigation system can aggregate probe data that matches the current exit link set and probe data that does not match the current exit link set based on the processing time point in the second probe data.

[0111] In the estimated dwell time deriving step or operation S244, the navigation system can derive the current estimated dwell time based on the rest area dwell time information derived from the detection data matched with the exit link set and the past dwell time information of vehicles corresponding to the detection data that does not match the exit link set, and can reflect the current estimated dwell time in the estimated arrival time.

[0112] In this implementation, for vehicles corresponding to detection data matching the entry link set, the current estimated dwell time can be derived by calculating the average dwell time of the vehicle's real-time rest area dwell time information and its past rest area dwell time information. The real-time rest area dwell time information is derived from detection data matching the exit link set, while the past rest area dwell time information is derived from detection data not matching the exit link set. Therefore, the navigation system can derive a more accurate dwell time based on real-time data of vehicles entering and leaving the rest area and past data of vehicles that have entered but not left the rest area. More specifically, the navigation system can use the average dwell time information of vehicles staying in the rest area based on the past driving data of vehicles that have entered but not left the rest area.

[0113] In addition, the current estimated stay time may include a first estimated stay time reflecting a short stay in the rest area, or a second estimated stay time reflecting a long stay in the rest area.

[0114] In one implementation, the first estimated stay time may be applied to the 25% of stay time data that rank lower in the average stay time data distribution, and the second estimated stay time may be applied to the 75% of stay time data that rank lower in the average stay time data distribution.

[0115] Specifically, the average stay time data distribution used in estimating stay time refers to the distribution of data derived from the processing time point, based on the stay time data of vehicles using the rest area over the past four weeks.

[0116] The estimated dwell time information derived in this way can be provided to drivers in three phases: "no stay in the rest area", "short stay in the rest area", and "long stay in the rest area".

[0117] In the case of "no stop in the rest area", the previously provided estimated arrival time can be maintained; in the case of "short stop in the rest area", the first estimated stay time can be reflected in the estimated arrival time; and in the case of "long stay in the rest area", the second estimated stay time can be reflected in the estimated arrival time.

[0118] Figure 9 This is a diagram illustrating an example of the process of selecting and aggregating probe data.

[0119] refer to Figure 9 Vehicle 10 has a unique vehicle terminal number. This vehicle terminal number allows vehicle 10 to be identified. The navigation system generates collection time data when each vehicle A, B, or C passes through the rest area entrance link ID 11111 and when each vehicle A or B passes through the rest area exit link ID 22222. Data generated in this way can be integrated to derive the dwell time. In the case of vehicle C, while there is data indicating that vehicle C entered the rest area, there is no data indicating that vehicle C left the rest area. Therefore, the real-time dwell time cannot be determined, but the dwell time can be derived based on vehicle C's past dwell time information.

[0120] Figure 10 This is a diagram illustrating an example of the process of processing aggregated probe data.

[0121] refer to Figure 10 The dwell time can be derived based on the collection time data generated when each of vehicles A, B, C, E, F, and G passes through the rest area entrance link ID 11111 and exit link ID 22222. In the implementation, the average dwell time (25%) refers to the bottom 25% of dwell time in the dwell time data distribution corresponding to the processing time point over the past 4 weeks. The average dwell time (75%) refers to the bottom 75% of dwell time in the dwell time data distribution corresponding to the processing time point over the past 4 weeks. The average remaining traffic volume refers to the proportion of vehicles that have been dwelling in the past 4 weeks based on the processing time. The real-time dwell time (25%) refers to the bottom 25% of dwell time in the real-time dwell time data distribution corresponding to the processing time point. The real-time dwell time (75%) refers to the bottom 75% of dwell time in the real-time dwell time data distribution corresponding to the processing time point. The real-time remaining traffic volume refers to the proportion of vehicles currently dwelling in the rest area based on the processing time point. Congestion is derived based on real-time remaining traffic volume and can be represented as 1 in the case of "sufficient parking spaces", 2 in the case of "normal state", and 3 in the case of "congested state".

[0122] Figure 11This is a diagram illustrating an example of providing drivers with information about congestion in a rest area according to an embodiment.

[0123] refer to Figure 11 When a vehicle approaches a rest area, the driver can check the congestion situation within the rest area on the navigation system's display.

[0124] Figure 12 This is a diagram illustrating an example of a state in which an estimated arrival time reflecting rest area dwell time information is provided to the driver according to an embodiment.

[0125] refer to Figure 12 In the cases of "no stop in the rest area", "short stop in the rest area", and "long stop in the rest area", the driver can confirm that the driver has been provided with each piece of information about the expected arrival time.

[0126] According to another embodiment of the present disclosure, a computer-readable recording medium is provided that stores a program for causing a computer to execute a destination arrival time estimation method.

[0127] Another embodiment of this disclosure provides a destination arrival time estimation device, comprising: a link set setting circuit configured to set a link set for rest area entrance / exit roads to obtain driving information of vehicles entering and leaving the rest area; a vehicle driving data collection circuit configured to collect vehicle driving data generated in units of link sets via a global positioning system (GPS); a rest area congestion determination circuit configured to determine congestion in the rest area based on the collected vehicle driving data and provide information to the driver; and an estimated arrival time providing circuit configured to determine the average dwell time of vehicles in the rest area based on the collected vehicle driving data and provide a modified estimated arrival time (ETA) to the driver intending to use the rest area.

[0128] Figure 13 This is a schematic diagram illustrating a destination arrival time estimation device according to an embodiment.

[0129] refer to Figure 13 The destination arrival time estimation device 110 may include: a link set setting circuit 111, a vehicle driving data collection circuit 112, a rest area congestion determination circuit 113, and an estimated arrival time providing circuit 114.

[0130] In the link set setting circuit 111, a link set can be set for the exit road or entrance road of the rest area to obtain the driving information of vehicles leaving or entering the rest area.

[0131] Links are the basic units for configuring road networks and are essentially a concept used for route finding and providing real-time traffic information. A link represents a specific area and is typically defined as a short area with independent traffic flow, such as a road or sloping area between intersections. These links are combined to form a road network. Through these links, navigation systems guide routes and provide traffic information.

[0132] The rest area congestion determination circuit 113 can determine the congestion situation in the rest area based on vehicle driving data collected in this manner, and can provide this information to the driver.

[0133] Specifically, the first detection data selection unit can select first detection data, which is target data that needs to be processed to determine the congestion situation in the rest area. This first detection data may include link set attributes of the mainline entrance roads and mainline exit roads, as well as link set attributes of the mainline entrance roads and connecting road exit roads.

[0134] The ingress link set probe data aggregation unit can aggregate probe data that matches past ingress link sets from the first probe data based on the processing time point. In this implementation, past ingress link sets refer to probe data that matches ingress link sets within the past 60 minutes based on the processing time point. However, past ingress link sets are not limited to this, and the past time reference can be changed if necessary.

[0135] The exit link set detection data aggregation unit can, based on the processing time point, derive the number of vehicles that have not left the rest area by aggregating detection data that does not match the current exit link set in the first detection data.

[0136] The congestion determination unit for the rest area can derive the number of vehicles that have not left the rest area through this process, and then determine the congestion situation in the rest area by taking into account the number of parking spaces in the rest area. For example, the congestion situation can be determined by the above equation (1).

[0137] Based on the congestion situation determined through this step / operation, drivers can be provided with congestion information about rest areas.

[0138] The congestion information provided to drivers can include four stages: "no information available", "sufficient parking spaces", "normal condition", and "congestion condition".

[0139] "No information available" means there is no information about the rest area; "sufficient parking spaces" means congestion is less than 10%; "normal" means congestion is more than 10% but less than 70%; and "congested" means congestion is more than 70%.

[0140] The estimated arrival time providing circuit 114 can derive the average dwell time of a vehicle at a rest area based on the collected vehicle driving data, and can provide a modified estimated arrival time (ETA) to drivers intending to use the rest area.

[0141] Specifically, the second detection data selection unit can select second detection data, which is target data that needs to be processed to provide an estimated time of arrival. This second detection data may include link set attributes of the mainline entrance roads and mainline exit roads.

[0142] The ingress link set probe data aggregation unit of the estimated arrival time providing circuit 114 can aggregate probe data that matches past ingress link sets in the second probe data based on the processing time point. In an implementation, past ingress link sets refer to probe data that matches ingress link sets within the past 60 minutes based on the processing time point. However, past ingress link sets are not limited to this, and the past time reference can be changed if necessary.

[0143] The estimated arrival time providing circuit 114's egress link set probe data aggregation unit can aggregate probe data that matches the current egress link set and probe data that does not match the current egress link set in the second probe data based on the processing time point.

[0144] In the estimated dwell time derivation unit, the current estimated dwell time can be derived based on the rest area dwell time information derived from the detection data matched with the exit link set and the past dwell time information of vehicles corresponding to the detection data that does not match the exit link set, and the current estimated dwell time can be reflected in the estimated arrival time.

[0145] In this implementation, for vehicles corresponding to detection data matching the entry link set, the estimated current dwell time can be derived by calculating the average dwell time of the vehicle's real-time rest area dwell time information and its past rest area dwell time information. The real-time rest area dwell time information is derived from detection data matching the exit link set, while the past rest area dwell time information is derived from detection data not matching the exit link set. Therefore, the navigation system can derive a more accurate dwell time based on real-time data of vehicles entering and leaving the rest area and past data of vehicles that have entered but not left the rest area. More specifically, the navigation system can use the average dwell time information of vehicles staying in the rest area based on the past driving data of vehicles that have entered but not left the rest area.

[0146] In addition, the current estimated stay time may include a first estimated stay time reflecting a short stay in the rest area, or a second estimated stay time reflecting a long stay in the rest area.

[0147] In one implementation, the first estimated stay time may be applied to the 25% of stay time data that rank lower in the average stay time data distribution, and the second estimated stay time may be applied to the 75% of stay time data that rank lower in the average stay time data distribution.

[0148] Specifically, the average stay time data distribution used in estimating stay time refers to the distribution of data derived from the processing time point, based on the stay time data of vehicles using the rest area over the past four weeks.

[0149] The estimated dwell time information derived in this way can be provided to drivers in three phases: "no stay in the rest area", "short stay in the rest area", and "long stay in the rest area".

[0150] In the case of "no stop in the rest area", the previously provided estimated arrival time can be maintained; in the case of "short stop in the rest area", the first estimated stay time can be reflected in the estimated arrival time; and in the case of "long stay in the rest area", the second estimated stay time can be reflected in the estimated arrival time.

[0151] Unless otherwise specifically described, the terms “comprising,” “configuration,” or “having” as used herein mean that the corresponding component can be inserted internally. Therefore, it should be understood that other components may be included, but not excluded. Unless otherwise defined, all terms including technical or scientific terms have the same meaning as commonly understood by one of ordinary skill in the art to which this disclosure pertains. Commonly used terms (such as those defined in dictionaries) should be interpreted as consistent with their meaning in the context of the relevant art and should not be interpreted in an idealized or overly formalized sense unless expressly defined in this disclosure.

[0152] The above description is merely an illustration of the technical concept of this disclosure, and those skilled in the art to which this disclosure pertains can make various corrections and modifications without departing from the spirit and scope of this disclosure. Therefore, the embodiments disclosed herein are not intended to limit the technical concept of this disclosure, but rather to describe it. The scope of the technical concept of this disclosure is not limited by these embodiments. The scope of this disclosure should be interpreted by the appended claims, and all technical concepts within the scope of the appended claims should be interpreted as included within the scope of this disclosure.

Claims

1. A method for estimating arrival time at a destination, comprising: The link set setup steps involve setting up link sets for the entrance or exit roads of the rest area to obtain driving information of vehicles entering and leaving the rest area. The vehicle driving data collection step involves collecting vehicle driving data generated in units of the link set via the Global Positioning System (GPS). The steps for determining congestion in the rest area involve determining the congestion situation within the rest area based on the collected vehicle driving data, and providing the driver with information about the congestion situation. as well as The estimated arrival time provides a step to determine the average dwell time of the driver at the rest area based on the collected driving data of the vehicle, and to provide a revised estimated arrival time (ETA) to drivers intending to use the rest area.

2. The destination arrival time estimation method according to claim 1, wherein, The attributes of the link set include at least one of the following: i) the main line entrance road from the main line to the rest area, ii) the main line exit road from the rest area to the main line, iii) the connecting road entrance road from the connecting road to the rest area, and iv) the connecting road exit road from the rest area to the connecting road.

3. The destination arrival time estimation method according to claim 2, wherein, The connecting roads include all roads that connect to the rest area, except for the main road, which serves as the main road.

4. The destination arrival time estimation method according to claim 1, wherein, The steps for determining the congestion situation in the rest area include: The first detection data selection step involves selecting the first detection data, which is a processing target used to determine the congestion situation in the rest area. The ingress link set detection data aggregation step involves aggregating detection data that matches past ingress link sets from the first detection data, based on the processing time point. The exit link set detection data aggregation step, based on the processing time point, aggregates detection data that does not match the current exit link set from the first detection data, and determines the number of vehicles that have not left the rest area; and The steps for determining congestion in the rest area involve determining the congestion situation of the rest area based on the number of parking spaces within the rest area.

5. The destination arrival time estimation method according to claim 4, wherein, The first detection data includes: i) the link set attributes of the main line entrance road and the main line exit road, and ii) the link set attributes of the main line entrance road and the connecting road exit road.

6. The destination arrival time estimation method according to claim 4, wherein, In the ingress link set detection data aggregation step, based on the processing time point, the detection data that matches the past ingress link set within the past 60 minutes is aggregated.

7. The destination arrival time estimation method according to claim 4, wherein, In the step of determining the congestion situation in the rest area, the congestion situation is determined as: (the number of vehicles that have not left the rest area or the number of parking spaces in the rest area) × 100.

8. The destination arrival time estimation method according to claim 7, wherein, In the step of determining the congestion situation in the rest area, the congestion situation is determined to be one of the following: i) no information available, indicating that there is no information about the rest area; ii) sufficient parking spaces, indicating that the congestion situation is less than 10%; iii) normal state, indicating that the congestion situation is more than 10% and less than 70%; and iv) congestion state, indicating that the congestion situation is more than 70%.

9. The destination arrival time estimation method according to claim 1, wherein, The steps for providing the estimated arrival time include: The second detection data selection step involves selecting second detection data, which is a processing target used to provide the estimated time of arrival. The ingress link set detection data aggregation step involves aggregating detection data that matches past ingress link sets from the second detection data, based on the processing time point. The outbound link set detection data aggregation step, based on the processing time point, aggregates detection data matching the current outbound link set and detection data not matching the current outbound link set from the second detection data; and The estimated dwell time derivation step determines the current estimated dwell time based on the rest area dwell time information derived from the detection data that matches the current exit link set and the past dwell time information of vehicles corresponding to the detection data that does not match the current exit link set, and reflects the current estimated dwell time in the estimated arrival time.

10. The destination arrival time estimation method according to claim 9, wherein, The second detection data includes the link set attributes of the main line entrance road and the main line exit road.

11. The destination arrival time estimation method according to claim 9, wherein, In the ingress link set detection data aggregation step, based on the processing time point, the detection data that matches the past ingress link set within the past 60 minutes is aggregated.

12. The destination arrival time estimation method according to claim 9, wherein, For a vehicle corresponding to the detection data that matches the past entry link set, the current estimated dwell time is determined by calculating i) the real-time rest area dwell time information of the vehicle and ii) the average dwell time of the past rest area dwell time information of the vehicle. The real-time rest area dwell time information is derived from the detection data that matches the current exit link set, and the past rest area dwell time information is derived from the detection data that does not match the current exit link set.

13. The destination arrival time estimation method according to claim 9, wherein, The current estimated stay time includes: a first estimated stay time reflecting a short stay in the rest area or a second estimated stay time reflecting a long stay in the rest area.

14. The destination arrival time estimation method according to claim 13, wherein, The first estimated dwell time application corresponds to the bottom 25% of the dwell time data in the average dwell time data distribution, and the second estimated dwell time application corresponds to the bottom 75% of the dwell time data in the average dwell time data distribution.

15. The destination arrival time estimation method according to claim 13, wherein, The driver is provided with rest area stay time information as one of the following: i) no stay in the rest area, ii) short stay in the rest area, and iii) long stay in the rest area, wherein i) when there is no stay in the rest area, the previously provided estimated arrival time is maintained, ii) when there is a short stay in the rest area, the first estimated stay time is reflected in the estimated arrival time, and iii) when there is a long stay in the rest area, the second estimated stay time is reflected in the estimated arrival time.

16. A computer-readable recording medium storing a program, which, when executed by a processor, causes the processor to: Link sets are set up for the entrance or exit roads of the rest area to obtain the driving information of vehicles entering and leaving the rest area; The vehicle's driving data is collected via the Global Positioning System (GPS) and generated in units of the link set. Based on the collected vehicle driving data, the congestion situation in the rest area is determined, and the driver is provided with information about the congestion situation; as well as Based on the collected vehicle driving data, the average dwell time of the driver at the rest area is determined, and the driver intending to use the rest area is provided with a revised estimated time of arrival (ETA).

17. A destination arrival time estimation device, comprising: The link set setting circuit is configured to set up a link set for the rest area entrance road or rest area exit road to obtain driving information of vehicles entering and leaving the rest area; The vehicle driving data collection circuit is configured to collect driving data of the vehicle generated in units of the link set via the Global Positioning System (GPS); The rest area congestion determination circuit is configured to determine the congestion situation in the rest area based on the collected driving data of the vehicle, and provide the driver with information about the congestion situation; as well as An estimated arrival time providing circuitry is configured to determine the average dwell time of the vehicle at the rest area based on collected vehicle driving data, and to provide a modified estimated arrival time (ETA) to the driver intending to use the rest area.

18. The destination arrival time estimation device according to claim 17, wherein, The circuit for determining congestion in the rest area includes: The first detection data selection unit is configured to select first detection data, which is a processing target for determining the congestion situation in the rest area; The ingress link set detection data aggregation unit is configured to aggregate detection data that matches past ingress link sets in the first detection data based on the processing time point; An exit link set detection data aggregation unit is configured to, based on the processing time point, aggregate detection data that does not match the current exit link set from the first detection data, and determine the number of vehicles that have not left the rest area; and The rest area congestion determination unit is configured to determine the congestion status of the rest area based on the number of parking spaces in the rest area.

19. The destination arrival time estimation device according to claim 17, wherein, The estimated arrival time providing circuitry includes: The second detection data selection unit is configured to select second detection data, which is a processing target used to provide the estimated time of arrival; The ingress link set detection data aggregation unit is configured to aggregate detection data that matches past ingress link sets in the second detection data based on the processing time point; An egress link set detection data aggregation unit is configured to, based on the processing time point, aggregate detection data matching the current egress link set and detection data not matching the current egress link set from the second detection data; and The estimated dwell time derivation unit is configured to determine the current estimated dwell time based on rest area dwell time information derived from detection data that matches the current exit link set and past dwell time information of the vehicle corresponding to detection data that does not match the current exit link set, and to reflect the current estimated dwell time in the estimated arrival time.

20. The destination arrival time estimation device according to claim 19, wherein, The current estimated stay time includes: a first estimated stay time reflecting a short stay in the rest area or a second estimated stay time reflecting a long stay in the rest area, wherein i) the first estimated stay time applies to the bottom 25% of stay time data in the average stay time data distribution, and ii) the second estimated stay time applies to the bottom 75% of stay time data in the average stay time data distribution.

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