System and method for assisting a vehicle at a toll station

Abstract

The present disclosure relates to a system and method for assisting a vehicle at a toll plaza. It includes detecting toll plaza 320 at 402 and, accordingly, initiating the automatic toll assist (ATA) function at 404. At 406, the role is analyzed and corresponding automatic toll lanes are detected, and then, at 408, an automatic toll lane with the lowest traffic density is selected. At 410, a route estimation is performed and, accordingly, an automatic maneuver of the vehicle 110 is performed. At 414, the toll barrier 318 in the selected lane is detected. Furthermore, at 416, key tokens are transmitted to the toll barrier 318 so that, upon receipt of the key tokens, the toll barrier 318 opens to allow the vehicle 110 to pass through. In addition, at 418, the vehicle 110 is restarted and driven manually / automatically to the next toll station 318, where the same process is repeated again.

Description

The present disclosure relates to the field of advanced driver-assistance systems (ADAS). In particular, the present disclosure provides a system and method for assisting a vehicle at a toll station to maneuver towards an automatic toll trail with minimal traffic density and thus efficiently traverse the toll station.Advanced driver assistance systems (ADAS) is a set of safety features and technologies designed to assist drivers and improve vehicle safety. These systems use sensors, cameras, radar, LiDAR, navigation modules, and other technologies to provide information about the environment of the vehicle and assist the driver with various driving tasks, such as lane keeping assist, lane departure warning, oncoming traffic warning, congestion assist, and the like.ADAS systems continue to develop through advances in sensor technology, machine learning, and connectivity. These technologies level the way for higher degrees of automation and ultimately result in fully autonomous vehicles. However, the current level L2++ congestion assist feature is deactivated prior to arriving at the toll gate, so the driver must take control of the vehicle throughout the toll gate trip, which may result in a confusion situation for the driver.Patent Document No. CN115402353A discloses a method and apparatus for controlling an automatically controlled vehicle for passing through an ETC toll station, including the steps of: obtaining a target ETC channel when an ETC toll station is detected in advance; determining a charging induction position of the target ETC channel as a target point; and controlling a host vehicle to travel to the target point. When it is judged that the host vehicle cannot reach the destination point, a new destination ETC channel is obtained and the charge induction position of the new destination ETC channel is used as the destination point, and the step of controlling the host vehicle to travel to the destination point is repeated. When it is detected that the host vehicle has reached the destination point, the host vehicle is controlled to pass through the ETC channel based on the state of a barrier in front of the destination point.Patent Document No. CN111402613A discloses a method for selecting the driving lane of a toll station in an autonomous vehicle. This includes: constructing, upon arriving at the toll station, a simplified toll station model by combining the complex situation of the automatically driving vehicle; analyzing and determining the information acquisition mode of the vehicle when the vehicle is about to enter the toll station; analyzing the lane having the smallest delay time and calculating a virtual speed value representing the amount of possible lane delay depending on the average service rate, the relative longitudinal position of the vehicle relative to the toll gate, and the corresponding number of vehicles in front of the vehicle, and analyzing the safety of the lane change of the vehicle and determining the safe lane change distance.Patent document EP3114668B1 discloses a recommended lane method for a user driving a roadway having at least two lanes, one of which is a toll lane for users who are ready to pay a toll. The method includes receiving a predicted travel duration for the lanes from a travel service, the predicted travel duration based on a travel state of the lanes. Thereafter, the method identifies a selected lane, wherein identifying the selected lane comprises: comparing the predicted travel durations of the lanes of the roadway; and instructing the user to select the selected lane while driving the roadway. The comparison is made based on the road toll of the driving lanes and an advantage ratio, and a specific driving lane is proposed only when the shortening of the travel duration exceeds a specific threshold value of the shortening of the travel duration.However, the references referenced disclose various systems, methods, and apparatuses for avoiding the problems referenced above and provide support for the vehicle while driving. However, there remains room for an improved, more efficient, and user-friendly system and method that supports the vehicle at the toll station and improves the experience of the user seated in the vehicle.A general object of the present disclosure is to avoid the above problems and provide a solution for supporting a vehicle at a toll station.An object of the present disclosure is to provide a system and method for selecting an automatic toll lane with low traffic density and maneuvering the vehicle through the selected lane.Another object of the present disclosure is to provide an automatic maneuvering system and method for facilitating stopping and restarting of the vehicle in front of the tollgate.Another object of the present disclosure is to improve a vehicle user's experience.Aspects of the present disclosure relate to the field of advanced driver-assistance systems (ADAS).In particular, the present disclosure provides a system and method for assisting a vehicle at a toll station to maneuver towards an automatic toll trail with minimal traffic density and thus efficiently traverse the toll station.One aspect of the present disclosure relates to a system for supporting a vehicle at a toll station. The system comprises: an image acquisition unit configured with the vehicle to capture one or more images associated with a predefined area around the vehicle. The system also includes a controller communicating with the image acquisition unit, the controller includes one or more processors connected to a memory storing instructions executable by the processors, and the controller causes: to receive, from the image acquisition unit, the acquired images in real-time; select, from the received images, a region-of-interest (Rol) related to the presence of the toll station within the predefined range of the vehicle; identify, by analyzing the selected rol, one or more lanes passing through the toll station and the corresponding type, the type including a manual toll lane, an automatic toll lane, and a stationary lane; determining, for each of the identified automatic toll lanes, the traffic density on that lane; and selecting the automatic toll lane having the lowest traffic density and maneuvering the vehicle accordingly from the current lane to the selected lane.In one aspect, the system includes an automatic toll assistance (ATA) unit configured with the controller that is actuated when the toll station is detected by the system. Upon actuation, the ATA unit may be configured to: interact with an electronic control unit (ECU) associated with the vehicle to slow the speed of the vehicle to a predefined safe range; determine and select the automated toll lane having the lowest traffic density; and estimate a travel path from the current lane to the selected lane and correspondingly control lateral and longitudinal movement of the vehicle to maneuver the vehicle to the estimated travel path.In one aspect, when the vehicle is moving on the selected lane, it may be configured to recognize the corresponding tollgate and verify its position and status, and further transmit key tokens by establishing a secure communication channel with the tollgate; wherein the tollgate allows the vehicle to pass through after receiving the key tokens.In one aspect, the system may include one or more sensors communicating with the controller, each of the one or more sensors providing data related to the current roadway associated with the vehicle. The controller merges the data provided by the sensors to perform lane localization, thus facilitating identification of the toll station, the one or more lanes, and the corresponding types in the rol.In one aspect of determining traffic density, the system may be configured to: determine the distance of dynamic objects present on each of the one or more lanes from the vehicle in consideration of the predefined lane offset factor; identify, for each lane, the object that is at a minimum distance from the vehicle; and select one of the lanes corresponding to one of the identified objects that is at a closest distance from the vehicle, wherein the selected lane refers to the lane having the lowest traffic density.Another aspect of the present disclosure relates to a method of supporting a vehicle at a toll station. The method comprises: capturing, by an image capturing unit, one or more images associated with a predefined area around the vehicle using an image capturing unit; receiving, at a controller, the captured images in real time from the image capturing unit; selecting, at a controller, a region of interest (Rol) from the received images that relates to the presence of the toll station within the predefined area from the vehicle; identifying, at the controller, one or more lanes passing through the toll station and the corresponding type by analyzing the selected Rol, wherein the type includes manual toll lane, automatic toll lane, and stationary lane; determining, at the controller, the traffic density on each of the identified automatic toll lanes; selecting the automated toll lane with the lowest traffic density at the controller and maneuvering the vehicle accordingly from the current lane to the selected lane.In one aspect, the method may include, upon detecting the toll station, actuating an automatic toll assistant unit (ATA) configured with the controller, and upon actuating, the ATA unit may be configured to: interact with an electronic control unit (ECU) associated with the vehicle to slow the speed of the vehicle to a predefined safety range; determine and select the automatic toll lane having the lowest traffic density; and estimate a travel path from the current lane to the selected lane and correspondingly control lateral and longitudinal movement of the vehicle to maneuver the vehicle to the estimated travel path.In one aspect, when the vehicle is moving on the selected lane, the method may include detecting the corresponding tollgate and checking its position and status by the controller, and further transmitting key tokens by establishing a secure communication channel with the tollgate; wherein the tollgate allows the vehicle to pass through after receiving the key tokens.In one aspect, the method may include: collecting, at the controller, data regarding the current roadway associated with the vehicle from one or more sensors communicating with the controller; and merging, at the controller, the collected data to enable lane localization, thereby facilitating identification of the toll station, the one or more lanes, and the corresponding types in the rol.In another aspect of determining traffic density, the method may include: determining the distance of dynamic objects present on each of the one or more lanes from the vehicle in consideration of the predefined lane offset factor; identifying, for each lane, the object that is at a minimum distance from the vehicle; and selecting one of the lanes corresponding to one of the identified objects that is at a greatest distance from the vehicle, wherein the selected lane refers to the lane having the smallest traffic density.Various objects, features, aspects and advantages of the inventive subject matter will become more apparent from the following detailed description of preferred embodiments, taken in conjunction with the accompanying drawing figures, in which like reference numerals designate like components.The accompanying drawings are for better understanding of the present disclosure. They are incorporated in and form part of this specification. The drawings illustrate exemplary embodiments of the present disclosure and, together with the description, serve to explain the principles of the present disclosure. FIG. 1 illustrates an exemplary network architecture of the proposed system to explain its general operation according to an embodiment of the present invention. FIG. 2 illustrates an example block diagram illustrating functional units of a controller in connection with the proposed system, according to an embodiment of the present disclosure. FIG. 3 illustrates an example diagram illustrating operations performed by the proposed system when the vehicle is near the toll station, according to an embodiment of the present invention. FIG. 4 illustrates an example flow diagram illustrating the step-by-step operation of the proposed system according to an embodiment of the present disclosure. FIG. 5 illustrates an example block diagram illustrating the process of object classification and lane localization according to an embodiment of the present disclosure. FIG. 6 illustrates an exemplary diagram illustrating various functions of the proposed system according to an embodiment of the present invention. FIG. 7 illustrates an example flow diagram illustrating the proposed method for assisting the vehicle at the toll station according to an embodiment of the present disclosure.The following is a detailed description of the embodiments of the disclosure illustrated in the accompanying drawings. The embodiments are so detailed as to clearly convey the disclosure. The amount of details provided, however, is not intended to limit the expected variations of the embodiments; on the contrary, the intention is to cover all modifications, equivalents, and alternatives falling within the spirit and scope of the present disclosure as defined in the appended claims.The embodiments discussed herein relate to the field of advanced driver-assistance systems (ADAS). In particular, the present disclosure provides a system and method for assisting a vehicle at a toll station to assist in maneuvering the vehicle towards an automatic toll lane with minimal traffic density and, accordingly, to efficiently traverse the toll station.Referring to FIG. 1, the proposed system 100 for supporting a vehicle 110 at toll station 320 (as illustrated in FIG. 6 ) is disclosed. The system 100 may include an image capture unit 102 configured with the vehicle 110 to capture one or more images or videos associated with a predefined area around the vehicle 110. In an exemplary embodiment, the image acquisition unit 102 may include, but is not limited to, a camera, a thermal camera, and / or an IR camera. In an exemplary embodiment, the image capturing unit 102 may include multiple cameras located at predefined positions on the vehicle 110 to cover all directions around the vehicle 110. In another exemplary embodiment, the image capturing unit 102 may include a rotatable camera.In one embodiment, the system 100 further includes a controller 106 that can communicate with the image capture device 102 such that the controller 106 can receive the captured images from the image capture unit 102 in real-time. In an example embodiment, the controller 106 may be a processing device placed in the vehicle 110. In another exemplary embodiment, the controller 106 may also be a central server that may communicate with the image capture unit 102.In one embodiment, the controller 106 may select, from the received images, a region of interest (Rol) that relates to the presence of the toll station 320 within the predefined area of the vehicle 110. Further, the controller 106 may analyze and thoroughly check the selected rol to determine one or more lanes 302- 1, 302- 2,..., as illustrated in FIG. 3. 302-N (collectively referred to herein as lanes 302 and individually as lane 302) traversing toll station 320. Further, it may specify the type of each of the identified lanes 302, where the type of lanes 302 may include a manual toll lane, an automatic toll lane, and a stationary lane.In one implementation, the controller 106 may interact with one or more sensors 104 (collectively referred to as sensors 104 and individually referred to as sensor 104) associated with the vehicle 110, where the sensors 104 may provide data regarding the current roadway 304 being traversed by the vehicle 110. In an exemplary embodiment, the sensors 104 may include imaging sensors, proximity sensors, RADAR, LiDAR, and a navigation module. In a preferred embodiment, the system 100 may receive from the navigation module map data relating to the roadway 304, where the map data may relate to the lanes 302 present on the roadway 304, their types, and the traffic dynamics on the roadway 304.Further, the controller 106 may merge the data provided by the sensors 104 to perform lane localization for the selected rol, thereby facilitating identifying the toll station 320, lanes 302, and corresponding types in the rol.In an exemplary embodiment, radar and camera may provide object position and velocity (object states) information for all real objects on the road at predefined time intervals. Further, the object states may be merged in the controller 106 using a recursive estimation (Kalman filter), thereby producing a final list of the road objects.In a preferred embodiment, the controller 106 may focus on the automated toll lanes (also referred to as ETC lanes below) and determine the traffic density on the respective lane for each of the ETC lanes. In an example embodiment, all ETC lanes may be detected using semantic segmentation based on input data provided by the camera. The term "ETC" may be painted onto the ETC lanes and may also be displayed on the traffic signs.Further, the controller 106 may select the automated toll lane with the lowest traffic density and correspondingly maneuver the vehicle 110 from the current lane to the selected lane. Once all ETC lanes are visible, the fastest ETC lane, i.e., the ETC lane with the lowest traffic density, may be determined at a moment using the Euclidean distance technique. The Euclidean distance of each object in each ETC lane is calculated with respect to the vehicle 110, along with the addition of the corresponding lane offset factor from the current lane). Then, the minimum distance is calculated for each track, and the track having the maximum distance is selected as the fastest track.In one embodiment, upon detection of toll station 320, system 100 may interact with an electronic control unit 112 (ECU 112) associated with vehicle 110 to slow the speed of vehicle 110 to a predefined safe range, for example, between 20 km / h and 30 km / h. On the other hand, the system 100 may determine and select the automatic toll trail with the lowest traffic density. The system 100 may further estimate a travel path from the current lane to the selected lane and further control lateral and longitudinal movement of the vehicle 110 by interacting with the ECU 112 to maneuver the vehicle 110 onto the estimated travel path.In another embodiment, when the vehicle 110 is moving on the selected lane, the system 100 may recognize the corresponding tollgate 318 and verify its position and status, and further transmit key tokens by establishing a secure communication channel with the tollgate 318. Upon receiving the key tokens, tollgate 318 may allow vehicle 110 to pass through.In one embodiment, the system 100 may include a display device 108 that may communicate with the controller 106. The display device 108 may be configured to display the rol, the associated roadway 304, and the corresponding lanes 302, traffic density, and objects, particularly dynamic objects, such as other vehicles, in each lane, the toll station 320, and the like. In an exemplary embodiment, the display device 108 may be configured in the form of a dashboard, an LED display panel, an LCD display module, and a GUI module integrated with the vehicle 110. In another exemplary embodiment, the display device 108 may be part of a user device such as a personal laptop, smartphone, tablet, or other mobile computing device present in the vehicle 110.In one embodiment, the controller 106 may communicate with the image capture unit 102, the sensors 104, and the display device 108 through a network 114. Further, the network 114 may be a wireless network, a wired network, or a combination thereof, which may be implemented as any of various types of networks, such as intranet, local area network (LAN), wide area network (WAN), Internet, and the like. Further, the network 114 may be either a dedicated network or a shared network. The shared network may represent an association of different types of networks that may use a variety of protocols, such as hypertext transfer protocol (HTTP), transmission control protocol / internet protocol (TCP / IP), wireless application protocol (WAP), and the like.In an embodiment, the system 100 may be implemented using any one or a combination of hardware components and software components such as a cloud, a server 116, a computing system 100, a computing device, a network device, and the like. Further, the controller 106 may interact with the image capture unit 102, the sensors 104, and the display device 108 via a website or application that may be located in the proposed system 100. In one implementation, system 100 may be accessed via a website / application that may be configured with any operating system, including, but not limited to, Android™ iOS™ and the like.Referring to FIG. 2, the block diagram 200 illustrates example functional units of the controller 106, which may include one or more processors 202, memory 204, interface(s) 206, processing engine(s) 208, and database 210. The one or more processor(s) 202 may be implemented as one or more microprocessors, microcomputers, microcontrollers, digital signal processors, central processing units, logic circuits, and / or any devices that manipulate data based on operating instructions. Among other capabilities, the one or more processor(s) 202 are configured to fetch and execute computer readable instructions stored in a memory 204 of the controller 106. The memory 204 may store one or more computer readable instructions or routines that may be fetched and executed to create or release the data units via a service on the network. The memory 204 may include any non-transitory memory device including, for example, volatile memory such as RAM, or nonvolatile memory such as EPROM, flash memory, and the like.In an embodiment, the controller 106 may also include one or more interfaces 206. The interface(s) 206 may include a variety of interfaces, for example, interfaces for data input and output devices, so-called I / O devices, storage devices, or the like. The interface(s) 206 may / may facilitate communication of the controller 106 with various devices coupled to the controller 106. The interface(s) 206 may also provide a communication path for one or more components of the controller 106. Examples of such components include, but are not limited to, processing engine(s) 208 and database 210.In one embodiment, the processing engine(s) 208 may be implemented as a combination of hardware and programming (e.g., programmable instructions) to implement one or more functionalities of the processing engine(s) 208. In the examples described herein, such combinations of hardware and programming may be implemented in various ways. For example, the programming for the processing engine 208 may consist of processor-executable instructions stored on a non-transitory machine-readable storage medium, and the hardware for the processing engine 208 may include a processing resource (e.g., one or more processors) for executing such instructions. In the present examples, the machine readable storage medium may store instructions that, when executed by the processing resource, implement the processing engine(s) 208. In such examples, the controller 106 may include the machine readable storage medium on which the instructions and the processing resource for executing the instructions are stored, or the machine readable storage medium may be separate but accessible to the controller 106 and the processing resource. In other examples, the processing engine(s) 208 may be implemented by electronic circuitry. Database 210 may include data that is either stored or generated as a result of functionalities implemented by one of the components of processing engine(s) 208.In one embodiment, the processing engine(s) 208 may include a lane determination unit 212, an automatic toll assistant unit 214, a token transfer unit 216, and other unit(s) 218. The other entity(s) 218 may / may implement functions complementing applications or functions performed by the controller 106 or the processing engine(s) 208.According to an embodiment, the lane determination unit 212 may select, from the images received via the image acquisition unit 102, a rol related to the presence of the toll station 320 within the predefined area of the vehicle 110. In one embodiment, the lane determination unit 212 may analyze and thoroughly check the selected rol to identify lanes 302 passing through the toll station 320. Further, the lane determination unit 212 may set the type of each of the identified lanes 302, wherein the type of the lanes 302 may include a manual toll lane, an automatic toll lane, and a stationary lane.In a preferred embodiment, the lane determination unit 212 may further analyze the automatic toll lanes and determine the traffic density on the respective lane for each of the automatic lanes. Moreover, the lane determination unit 212 may select the automatic toll lane with the lowest traffic density suitable for maneuvering the vehicle 110.In one embodiment, the lane determination unit 212 may merge the data provided by the sensors 104 to perform lane localization, thus facilitating identification of the toll station 318, the one or more lanes, and the corresponding types in the rol.In one implementation, the lane determination unit 212 may determine the traffic density of dynamic objects 306- 1, 306- 2, 306- 3... 306-N (collectively referred to herein as objects 306 and individually as object 306) present on each of the lanes 302, and further determine the distance of the tracked objects 306 from the vehicle 110 by considering a predefined lane offset factor. Further, for each lane 302, it may identify the object 306 that is closest to the vehicle 110 and select one of the lanes 302 corresponding to one of the identified objects 306 that is closest to the vehicle 110, where the selected lane may refer to the lane having the lowest traffic density.According to one embodiment, the ATA unit 214 may be activated when the toll station 320 is detected by the system 100. When actuated, the ATA unit 214 may be configured to interact with the ECU 112 of the vehicle 110 to facilitate slowing the speed of the vehicle 110 to a predefined safe area.Further, the ATA unit 214 may estimate a travel path from the current lane to the selected lane and correspondingly control the lateral and longitudinal movement of the vehicle 110 to maneuver the vehicle 110 onto the estimated travel path.According to an embodiment, the ATA unit 214 may also detect the tollgate 318 present on the selected lane and check its position and status. In one embodiment, the token transmission unit 216 may further transmit key tokens by establishing a secure communication channel with the tollgate 318, wherein the tollgate 318, upon receiving the key tokens, allows the vehicle 110 to pass through.Referring to FIGS. 3 and 4, at block 402, the system 100 may recognize the toll station 320 (hereinafter interchangeably referred to as toll booth 320) through the image acquisition unit 102, such as a camera, or through map data obtained using the sensors 104, such as a navigation module. Further, at block 404, system override may be initiated when the automatic toll assist function is initiated by actuating the ATA unit 214.In one embodiment, at block 406, the system 100 may analyze the scenario in the rol and recognize automatic toll lanes using the camera and navigation module, and then recognize and select an automatic toll lane with the lowest traffic density using radar or a camera at block 408.In another embodiment, at block 410, the system 100 may perform a travel path estimation (based on the current lane of the vehicle 110 and the selected lane) and then the system 100 may perform an automatic maneuver of the vehicle 110 based on the estimated travel path, wherein during the automatic maneuver, at block 412, the system 100 may control the longitudinal and lateral movement of the vehicle 110 to travel along the estimated travel path.In one embodiment, at block 414, the system 100 may detect the tollgate 318 on the selected lane using the camera and stop the vehicle 110 (by controlled maneuvering) accordingly in front of the tollgate 318. Further, at block 416, the system 100 may transmit key tokens to the tollgate 318 by establishing a secure communication channel with it such that the tollgate 318 opens after receiving the key tokens to allow the vehicle 110 to pass. Moreover, at block 418, the vehicle 110 may be restarted and driven manually or automatically to the next toll gate 318, where the same process is repeated again. Once tollgate 318 has passed, at block 420, system 100 may pass control of maneuvering vehicle 110 to the driver of vehicle 110 or to an ADAS module (e.g., L2 module) associated with vehicle 110.Referring to FIG. 5, the system 100 may include the sensors 104, such as, but not limited to, camera, LiDAR, and RADAR, which may communicate with the controller 106. In one embodiment, at blocks 502, 504, and 506, real-time data relating to the vehicle 110 may be obtained from the camera, the LiDAR, and the RADAR, respectively. Further, in block 508, the obtained data may be pre-processed to perform a merging of these data.In one embodiment, at block 510, the system 100 may recognize other dynamic objects 306, such as cars, buses, trucks, and other such vehicles present on the roadway 304. In another embodiment, at block 512, the system 100 may detect other static objects, such as signs, partitions, shot holes, braking bumps, and the like, present on the roadway 304. Further, based on the detected dynamic objects 306, at block 514, the system 100 may analyze the lanes (virtual lanes shown on the map).In individual cases, it occurs that the lane markings are missing at toll gate 320. In such a case, lanes are constructed using moving and static objects by lane recognition and virtual lane recognition, for example barriers are kept on the road marking the road partition. In one embodiment, object detection and tracking processes the estimated position and speed to form travel paths (i.e., lanes of vehicles). In addition, based on the comparison of the formed spatial travel paths, an appropriate travel path is selected for the own lane (current lane on which the vehicle 110 travels) and adjacent lanes, and then, by merging all the selected travel paths, the final own lanes and adjacent lanes are formed.At block 516, the system 100 may initiate the ATA function to perform object classification, lane location, and virtual lane marking by considering the dynamic objects 306 at block 510, the static objects at block 512, and the virtual lanes at block 514.Referring to FIG. 6, the proposed system 100 may also support the vehicle 110 in a highway congestion at block 602 and on a ramp at block 604, and also at the toll station 320 at block 606.Referring to FIG. 7, the proposed method 700 (hereinafter interchangeably referred to as method 700) for supporting a vehicle at a toll station will be described. The method 700 includes step 702 of capturing, by an image capture unit, one or more images associated with a predefined area around the vehicle via an image capture unit.In one embodiment, the method 700 includes the step 704 of receiving, at a controller, the captured images in real-time from the image capturing unit; and step 706 of selecting, at a controller, a region of interest (Rol) from the received images that relates to the presence of the toll station within the predefined area from the vehicle.In another embodiment, the method 700 includes step 708 of identifying, at the controller, one or more lanes passing through the toll station and the corresponding type by analyzing the selected rol, wherein the type may include manual toll lane, automatic toll lane, and stationary lane; step 710 of determining, at the controller, the traffic density on each of the identified automatic toll lanes; and further step 712 of selecting the automatic toll lane having the lowest traffic density at the controller and correspondingly maneuvering the vehicle from the current lane to the selected lane.In one embodiment, upon detecting the toll station, the method 700 may include actuating an automatic toll assistance unit (ATA) configured with the controller. Upon actuation, the ATA unit may interact with an ECU associated with the vehicle to slow the speed of the vehicle to a predefined safe range; determine and select the automatic toll lane having the lowest traffic density; and estimate a travel path from the current lane to the selected lane and correspondingly control the lateral and longitudinal movement of the vehicle to maneuver the vehicle to the estimated travel path.In another embodiment, when the vehicle is moving on the selected lane, the method 700 may include recognizing, by the controller, the corresponding tollgate and checking its position and status, and further transmitting key tokens by establishing a secure communication channel with the tollgate, the tollgate allowing the vehicle to pass through upon receiving the key tokens.In another embodiment, the method 700 may include collecting, at the controller, data regarding the current roadway associated with the vehicle from one or more sensors communicating with the controller; and merging, at the controller, the collected data to enable lane localization, thereby facilitating identification of the toll station, the one or more lanes, and the corresponding types in the rol.In a preferred embodiment, the method 700 for determining traffic density may include determining the distance of dynamic objects present on each of the one or more lanes from the vehicle taking into account a predefined lane offset factor, then identifying the object that is closest to the vehicle for each lane, and further selecting one of the lanes corresponding to one of the identified objects that are closest to the vehicle, wherein the selected lane refers to the lane with the lowest traffic density.Therefore, the proposed system 100 and method 700 may facilitate automatic maneuvering of the vehicle across the toll gate through an automatic toll lane with minimal traffic, thereby improving the experience of a user seated in the vehicle.While various embodiments of the invention are described above, other and further embodiments of the invention may be devised without departing from the basic scope thereof. The scope of the invention is defined by the following claims. The invention is not limited to the described embodiments, versions or examples. These are included herein to enable one of ordinary skill in the art to make and use the invention in combination with information and knowledge available to those skilled in the art.The present disclosure provides a solution for supporting a vehicle at a toll station.The present disclosure provides a system and method for selecting an automatic toll lane with low traffic density and maneuvering the vehicle through the selected lane.The present disclosure provides an automatic maneuvering system and method to facilitate stopping and restarting the vehicle in front of the toll gate.The present disclosure provides an improved, efficient, and user-friendly system and method that enhances the experience of a user seated in the vehicle.References included in the specificationThis list of documents cited by the applicant has been produced in an automated manner and is only included for the better information of the reader. The list is not part of the German patent application or utility model application. The DPMA does not take any adhesion for any faults or omissions.Patent Literature citedCN 115402353A

[0004] CN 111402613A

[0005] EP 3114668B1

[0006]

Claims

A system (100) for supporting a vehicle (110) at a toll station (320), the system (100) comprising: an image capture unit (102) configured with the vehicle (110) to capture one or more images associated with a predefined area around the vehicle (110); and a controller (106) communicating with the image capture unit (102), the controller (106) comprising one or more processors coupled to a memory storing instructions executable by the processors, and the controller causing: receiving the images captured by the image capture unit (102) in real-time; selecting, from the received images, a region of interest (Rol) that relates to the presence of the toll station (320) within the predefined area from the vehicle (110); identifying, by analyzing the selected rol, one or more lanes (302) passing through the toll station (320) and the corresponding type, the type including a manual toll lane, an automatic toll lane, and a stationary lane; determining, for each of the identified automatic toll lanes, the traffic density on that lane; and selecting the automatic toll lane having the lowest traffic density and correspondingly maneuvering the vehicle (110) from the current lane to the selected lane.The system (100) of claim 1, wherein the system (100) comprises an automatic toll assistance unit (ATA) (214) configured with the controller (106), which is actuated when the toll station is detected by the system (100); wherein the ATA unit (214), when actuated, is configured to: interact with an electronic control unit (ECU) associated with the vehicle (110) to slow the speed of the vehicle to a predefined safe range; determine and select the automatic toll trail having the lowest traffic density; and estimate a travel path from the current trail to the selected trail and correspondingly control lateral and longitudinal movement of the vehicle to maneuver the vehicle (110) to the estimated travel path.The system (100) of claim 2, wherein when the vehicle (110) is moving in the selected lane, the controller (106) is configured to recognize the corresponding tollgate (318) and verify its position and status, and further transmit key tokens by establishing a secure communication channel with the tollgate (318); wherein the tollgate (318) allows the vehicle (110) to pass through upon receiving the key tokens.The system (100) of claim 1, wherein the system (100) comprises one or more sensors (104) communicating with the controller (106), each of the one or more sensors (104) providing data related to the current roadway (304) associated with the vehicle (110), wherein the controller (106) merges the data provided by the sensors (104) to perform lane localization to facilitate identification of the toll station (320), the one or more lanes (302), and the corresponding types in the rol.The system (100) of claim 1, wherein to determine the traffic density, the system (100) is configured to: determine the distance of dynamic objects (306) present on each of the one or more lanes (302) from the vehicle (110) in consideration of the predefined lane offset factor; identify, for each lane (302), the object (306) that is at a minimum distance from the vehicle (110); and select one of the lanes (302) that corresponds to one of the identified objects (306) that is at a closest distance from the vehicle (110), wherein the selected lane (302) relates to the lane having the lowest traffic density.A method (700) of supporting a vehicle at a toll station, the method (700) comprising: capturing (702), by an image capturing unit, one or more images associated with a predefined area around the vehicle by an image capturing unit; receiving (704), at a controller, the captured images in real time from the image capturing unit; selecting (706), at a controller, a region of interest (Rol) from the received images that relates to the presence of the toll station within the predefined area from the vehicle; identifying (708), at the controller, one or more lanes passing through the toll station and the corresponding type by analyzing the selected rol, wherein the type includes manual toll lane, automatic toll lane, and stationary lane; determining (710), at the controller, the traffic density on each of the identified automated toll lanes; and selecting (712) the automated toll lane having the lowest traffic density at the controller and maneuvering the vehicle accordingly from the current lane to the selected lane.The method (700) of claim 6, wherein the method (700), upon detection of the toll station, comprises actuating an automatic toll assistance unit (ATA) configured with the controller, and the ATA unit, upon actuation, is configured to: interact with an electronic control unit (ECU) associated with the vehicle to slow the speed of the vehicle to a predefined safe range; determine and select the automatic toll lane having the lowest traffic density; and estimate a travel path from the current lane to the selected lane and correspondingly control lateral and longitudinal movement of the vehicle to maneuver the vehicle to the estimated travel path.The method (700) of claim 7, wherein when the vehicle is moving on the selected lane, the method (700) comprises the controller detecting the corresponding tollgate and checking its position and status, and further transmitting key tokens by establishing a secured communication channel with the tollgate; wherein the tollgate allows the vehicle to pass after receiving the key tokens.The method (700) of claim 6, wherein the method (700) comprises: collecting, at the controller, data regarding the current roadway associated with the vehicle from one or more sensors communicating with the controller; and merging, at the controller, the collected data to enable lane localization, thereby facilitating identification of the toll station, the one or more lanes, and the corresponding types in the rol.The method (700) of claim 9, wherein to determine the traffic density, the method (700) comprises: determining the distance of dynamic objects present on each of the one or more lanes from the vehicle taking into account the predefined lane offset factor; identifying, for each lane, the object that is at a minimum distance from the vehicle; and selecting one of the lanes corresponding to one of the identified objects that is at a greatest distance from the vehicle, wherein the selected lane refers to the lane having the smallest traffic density.

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