Intelligent vehicle speed limiting system and method

Abstract

The invention provides an intelligent vehicle speed limiting system and method. A system for controlling a vehicle is disclosed. The system may include a transceiver configured to receive vehicle information associated with a vehicle. The vehicle information may include a vehicle geographic location, a vehicle speed, and a vehicle travel route. The system may also include a memory and a processor. The memory may store a mapping of a plurality of predetermined conditions with corresponding maximum speed limits. A processor may obtain vehicle information and information associated with a geographic area in which the vehicle may be traveling. The processor may determine a predetermined condition that may be satisfied from a plurality of predetermined conditions based on the obtained information. The processor may determine a maximum speed limit associated with the predetermined condition based on the mapping and generate a signal to control the vehicle speed based on the maximum speed limit.

Description

Technical Field

[0001] The present disclosure relates to an intelligent vehicle speed limit system and method, and more particularly to a system and method for automatically controlling a vehicle speed based on the vehicle's geographic location. Background Art

[0002] Many commercial fleet companies have fleets of vehicles distributed across remote geographic locations. Commercial fleet companies proactively monitor and manage their fleet vehicles to improve efficiency and minimize operating expenses. In addition, commercial fleet companies provide guidance to drivers to properly operate the vehicles, such as slowing down during inclement weather or when maneuvering turns. Despite driver guidance and monitoring, adverse situations may occur. Summary of the invention

[0003] The present disclosure describes a system and method for controlling the speed of a vehicle based on a geographic area in which the vehicle may be traveling (i.e., crossing). The system may be configured to obtain vehicle information and geographic area information associated with the geographic area in which the vehicle may be traveling. The system may be configured to determine a predetermined condition that the vehicle may meet when traveling from a plurality of predetermined conditions based on the information obtained. In response to determining the predetermined condition, the system may determine a maximum speed limit corresponding to the predetermined condition satisfied by the vehicle. The system may then compare the vehicle speed (i.e., the current vehicle speed) with the maximum speed limit and determine that the vehicle speed may be greater than the maximum speed limit. In response to determining that the vehicle speed may be greater than the maximum speed limit, the system may generate a signal to control (e.g., reduce) the vehicle speed to the maximum speed limit and transmit the signal to the vehicle. The vehicle may receive the signal and may control / reduce the vehicle speed accordingly.

[0004] In some aspects, the vehicle information may include vehicle speed (or other vehicle driving parameters), vehicle geographic location, vehicle driving route, etc. The geographic area information may include historical adverse condition information, traffic violations, traffic congestion, weather conditions in the geographic area, historical user driving behavior in the geographic area, target point locations on the vehicle driving route in the geographic area, road slope information, real-time road adverse conditions, etc.

[0005] In some aspects, the system can obtain vehicle information from the vehicle (e.g., from vehicle sensors, vehicle cameras, etc.). The system can obtain geographic area information from the vehicle, other vehicles (e.g., crowd-sourced information from other vehicles), servers / external devices, etc.

[0006] In another aspect, the system can use a mapping of multiple predetermined conditions and corresponding maximum speed limits to determine the maximum speed limit that the vehicle can travel based on the predetermined conditions satisfied by the vehicle. The mapping can be pre-stored in the system memory or can be obtained by the system from a server.

[0007] In some aspects, in addition to transmitting a signal to the vehicle, the system may also transmit a notification to a human machine interface (HMI) or user device installed in the vehicle indicating that the user may have exceeded the maximum speed limit (corresponding to a predetermined condition satisfied by the vehicle).

[0008] The present disclosure discloses a system and method that can facilitate automatic control of vehicle speed based on the geographic area in which the vehicle may be traveling. The system can determine the probability of an adverse situation based on predetermined conditions satisfied by the vehicle and can control the vehicle speed accordingly.

[0009] Advantages of the present disclosure are provided herein in detail. BRIEF DESCRIPTION OF THE DRAWINGS

[0010] Detailed description is set forth with reference to the accompanying drawings. The use of the same reference numerals may indicate similar or identical items. Various embodiments may utilize elements and / or components other than those shown in the accompanying drawings, and some elements and / or components may not be present in various embodiments. The elements and / or components in the accompanying drawings are not necessarily drawn to scale. Throughout this disclosure, singular and plural terms may be used interchangeably, depending on the context.

[0011] Figure 1 An exemplary environment is depicted in which techniques and structures for providing the systems and methods disclosed herein may be implemented.

[0012] Figure 2 An exemplary fleet management system according to the present disclosure is depicted.

[0013] Figure 3 Depicted are exemplary geographic region information in accordance with the present disclosure.

[0014] Figure 4 Depicted are exemplary scenarios for controlling a vehicle according to the present disclosure.

[0015] Figure 5 A flow chart depicts an exemplary method for controlling a vehicle according to the present disclosure. DETAILED DESCRIPTION

[0016] The present disclosure will be described more fully hereinafter with reference to the accompanying drawings, in which exemplary embodiments of the disclosure are shown and which are not intended to be limiting.

[0017] Figure 1An exemplary environment 100 is depicted in which techniques and structures for providing the systems and methods disclosed herein may be implemented. The environment 100 may include a vehicle 102 (or multiple vehicles) and a fleet management system 104 (or system 104) that may be communicatively coupled to each other via a network 106. The vehicle 102 may travel on a road 108, such as Figure 1 Depicted.

[0018] The vehicle 102 may take the form of any vehicle, such as, for example, an SUV, a sedan, a crossover vehicle, a van, a minivan, a bus, a truck, etc. In addition, the vehicle 102 may include any powertrain, such as, for example, a gasoline engine, one or more electrically actuated motors, a hybrid powertrain, etc. Furthermore, the vehicle 102 may be configured and / or programmed to operate in a fully autonomous (e.g., driverless) mode (e.g., Level 5 autonomy) or in one or more partially autonomous modes that may include driver assistance technologies.

[0019] The network 106 illustrates an exemplary communication infrastructure in which the connected devices discussed in various embodiments of the present disclosure may communicate. The network 106 may be and / or include the Internet, a private network, a public network, or other configurations operating using any one or more known communication protocols, such as, for example, Transmission Control Protocol / Internet Protocol (TCP / IP), Wi-Fi, UWB based on the Institute of Electrical and Electronics Engineers (IEEE) standard 802.11, and cellular technologies such as Time Division Multiple Access (TDMA), Code Division Multiple Access (CDMA), High Speed ​​Packet Access (HSPDA), Long Term Evolution (LTE), Global System for Mobile Communications (GSM), and Fifth Generation (5G), to name a few examples.

[0020] In some aspects, the system 104 may be associated with a vehicle fleet company / operator that may manage / operate multiple vehicles, including the vehicle 102. In other aspects, the system 104 may be associated with a user that may manage the speed of the vehicle 102 that may be driven by another user.

[0021] The system 104 can monitor and control multiple vehicles. For example, the system 104 can be configured to control the vehicle speed when a predetermined condition may be met. The system 104 can also be configured to control other vehicle driving parameters or operations, such as the rate of change of speed, the distance to the vehicle ahead, etc.

[0022] The system 104 may be configured to obtain vehicle information associated with each vehicle (including the vehicle 102). The vehicle information may include the vehicle geographic location, the current vehicle speed, the vehicle travel route (including the destination location), etc. The system 104 may obtain the vehicle information from the corresponding vehicle. The system 104 may also be configured to obtain information associated with the geographic area in which the vehicle 102 may be traveling (or "geographic area information") based on the vehicle geographic location and the vehicle travel route. The system 104 may obtain geographic area information from the vehicle 102 (e.g., from vehicle sensors, vehicle cameras, etc.), other vehicles or user devices (e.g., by using crowdsourced information), and / or external devices (such as servers). The geographic area information may include, but is not limited to, historical adverse situation information, traffic violations, traffic congestion, weather conditions in a geographic area, historical user driving behavior in a geographic area, target point locations on the vehicle travel route, etc. This will be discussed later in conjunction with Figure 3 Describes the details of the geographic area information.

[0023] In response to obtaining the geographic area information, the system 104 may determine a predetermined condition that may be satisfied from a plurality of predetermined conditions based on the obtained information. For example, the system 104 may determine that the vehicle 102 may be traveling under severe weather conditions (e.g., a first predetermined condition), or traveling in an area where the historical incidence of adverse conditions is greater than a threshold (e.g., a second predetermined condition), or that the vehicle 102 may be approaching a turn or exit point in the vehicle's driving route (e.g., a third predetermined condition), etc.

[0024] The system 104 may also be configured to retrieve data from the system memory (in Figure 2 The system 104 may obtain a mapping of a plurality of predetermined conditions and corresponding maximum speed limits from a system memory 224 (shown as system memory 224 in FIG. 1 ) and / or an external device (such as a server). The system 104 may determine the maximum speed limit associated with the determined predetermined condition based on the mapping. The system 104 may then compare the current vehicle speed with the maximum speed limit and determine that the current vehicle speed may be greater than the maximum speed limit. In response to determining that the current vehicle speed may be greater than the maximum speed limit, the system 104 may generate a signal to reduce the vehicle speed to the maximum speed limit. In other words, the system 104 may generate a signal to control the vehicle speed based on the maximum speed limit and transmit the signal to the vehicle 102. The vehicle 102 may receive the signal from the system 104 and control (e.g., reduce) the vehicle speed based on the signal.

[0025] The vehicle 102 , vehicle fleet company / operator, and system 104 may implement and / or perform operations as described herein in the present disclosure in accordance with the vehicle owner's manual and safety guidelines.

[0026] Figure 2An example fleet management system 200 according to the present disclosure is depicted. Fleet management system 200 can be the same as fleet management system 104. As described herein, fleet management system 200 can be implemented in hardware, software (e.g., firmware), or a combination thereof. Figure 2 When you can refer to Figure 3 to Figure 4 .although Figure 2 Fleet management system 200 is depicted, but a user (eg, a parent) may use the same or a similar system to control a vehicle driven by another user (eg, a child).

[0027] The fleet management system 200 can communicate with a plurality of vehicles 202 (in Figure 2 The fleet management system 200 may be connected to the fleet computing device 204 (shown as a single vehicle 202 in the figure). Multiple vehicles 202 and fleet computing devices 204 may also be connected to each other via a network 206. Network 206 may be the same as network 106. In some aspects, the fleet management system 200 may be part of the fleet computing device 204. In other aspects, the fleet management system 200 may be separate from the fleet computing device 204 (e.g., Figure 2 In some aspects, the fleet computing device 204 may be a server that may store geographic region information and may transmit the geographic region information to the fleet management system 200.

[0028] Multiple vehicles 202 can be combined with the above Figure 1 The plurality of vehicles depicted are identical and may form a fleet of vehicles. In some aspects, the movement, storage, use, etc. of each vehicle 202 may be controlled and / or managed by a fleet operator (not shown) using a fleet management system 200 .

[0029] In some aspects, the vehicle 202 can be programmed to operate in a fully autonomous (e.g., driverless) mode (e.g., Level 5 autonomy) or in one or more partially autonomous modes that can include driver assistance technologies. Examples of partially autonomous (or driver assistance) modes are widely understood in the art as autonomy levels 1 to 4.

[0030] The vehicle 202 may include multiple units including, but not limited to, a vehicle control unit (VCU) 208, one or more vehicle processors 210 (or vehicle processors 210), and a vehicle memory 212 (which may be part of an onboard vehicle computer (not shown)) that are communicatively connected to one another. The VCU 208 may include multiple units including, but not limited to, a driver assistance technology (DAT) controller 214, a vehicle transceiver 216, multiple electronic control units (ECUs) 218, and the like. In some aspects, the vehicle transceiver 216 may be external to the VCU 208. The VCU 208 may be configured and / or programmed to coordinate vehicle units, connected computing devices (e.g., fleet computing device 204), other vehicles operating as part of a vehicle fleet, and a fleet management system 200 (e.g., a fleet computing device 204). Figure 2 The data in (not shown) is not shown.

[0031] The DAT controller 214 can provide Level 1 to Level 4 autonomous driving and driver assistance functions to the vehicle operator. One or more ECUs 218 can be configured to determine vehicle information such as vehicle speed, vehicle geographic location, vehicle route, vehicle payload, etc. (e.g., by using a vehicle navigation receiver, vehicle sensors, infotainment system, etc.). In some aspects, the ECU 218 can be further configured to determine information associated with a geographic area in which the vehicle 202 may be traveling (or geographic area information). For example, the ECU 218 can determine traffic congestion, road grade information, time of day, road hazard conditions, etc. by using vehicle sensors / cameras, etc.

[0032] The vehicle processor 210 may be configured to communicate with one or more memory devices (e.g., vehicle memory 212 and / or Figure 2 The vehicle processor 210 may utilize the vehicle memory 212 to store programs and / or store data in code form to perform various vehicle 202 operations according to the present disclosure. The vehicle memory 212 may be a non-transitory computer-readable memory. The vehicle memory 212 may include any one or combination of volatile memory elements (e.g., dynamic random access memory (DRAM), synchronous dynamic random access memory (SDRAM), etc.), and may include any one or more non-volatile memory elements (e.g., erasable programmable read-only memory (EPROM), flash memory, electronically erasable programmable read-only memory (EEPROM), programmable read-only memory (PROM), etc.).

[0033] In some aspects, the vehicle memory 212 can store vehicle information determined by the ECU 218. In some aspects, the VCU 210 / ECU 218 can send vehicle information to the vehicle memory 212 at a predefined frequency for storage purposes. In other aspects, the vehicle memory 212 can store geographic area information determined by the ECU 218.

[0034] In additional aspects, the vehicle memory 212 may store information associated with vehicle type, vehicle model, vehicle manufacturing year, vehicle battery type (and other vehicle component types), vehicle battery manufacturing year, etc. as vehicle information.

[0035] The vehicle transceiver 216 can be configured to obtain vehicle information and / or geographic area information from the vehicle memory 212 and transmit the information to one or more external systems or servers. For example, the vehicle transceiver 216 can transmit information to the fleet computing device 204 and / or the fleet management system 200 via the network 206 at a predefined frequency or when the vehicle transceiver 216 receives a request to transmit information.

[0036] It can be understood by those skilled in the art that Figure 2 The vehicle architecture shown may omit certain vehicle units and / or vehicle computing modules. Figure 2 The vehicle 202 depicted in FIG. 2 is an example of possible implementations according to the present disclosure and, therefore, should not be considered limiting or exclusive.

[0037] In addition, although the above description describes that the vehicle transceiver 216 can obtain vehicle information and geographic area information from the vehicle memory 212 and transmit the information to one or more external systems (e.g., the fleet management system 200), it can be appreciated by one of ordinary skill in the art that some portions of the vehicle information and geographic area information can be obtained from other systems other than the vehicle 202. For example, the fleet management system 200 can obtain the geographic area information from the fleet computing device 204 and / or an external server (not shown). In an exemplary aspect, the fleet management system 200 can additionally obtain the geographic area information from crowd sourcing (e.g., other vehicles or user devices).

[0038] The fleet management system 200 may receive vehicle information and / or geographic area information from the vehicle transceiver 216, the fleet computing device 204, other vehicles / devices, etc. The fleet management system 200 may include multiple units, including but not limited to a system transceiver 220, one or more system processors 222 (or system processors 222), and a system memory 224. The system transceiver 220 may be configured to transmit information, data, notifications, instructions, etc. to and receive information, data, notifications, instructions, etc. from the vehicle 202, the fleet computing device 204, other vehicles, and other external devices via the network 206. For example, the system transceiver 220 may be configured to receive vehicle information and geographic area information from the vehicle transceiver 216 and / or the fleet computing device 204.

[0039] Although the above description describes the system transceiver 220 receiving vehicle information and geographic area information from the vehicle 202 , one of ordinary skill in the art will appreciate that the system transceiver 220 receives such associated vehicle information and geographic area information from each vehicle in the fleet of vehicles.

[0040] The system processor 222 may be configured to communicate with one or more memory devices (eg, the system memory 224 and / or one or more external databases ( Figure 2 The system processor 222 may utilize the system memory 224 to store programs and / or store data in code form to perform various system operations according to the present disclosure. The system memory 224 may be a non-transitory computer-readable memory that stores fleet management program code. The system memory 224 may include any one or combination of volatile memory elements (e.g., dynamic random access memory (DRAM), synchronous dynamic random access memory (SDRAM), etc.), and may include any one or more non-volatile memory elements (e.g., erasable programmable read-only memory (EPROM), flash memory, electronically erasable programmable read-only memory (EEPROM), programmable read-only memory (PROM), etc.).

[0041] In some aspects, the system memory 224 may include a plurality of modules and databases, including but not limited to a vehicle information database 226, a geographic area information database 228, a mapping database 230, and a vehicle management module 232. The vehicle management module 232 as described herein may be stored in the form of computer executable instructions, and the system processor 222 may be configured and / or programmed to execute the stored computer executable instructions to manage / control a vehicle according to the present disclosure.

[0042] The vehicle information database 226 can store vehicle information that the system transceiver 220 can receive from each vehicle (e.g., from the vehicle transceiver 216). Specifically, in response to receiving the vehicle information, the system transceiver 220 can send the vehicle information to the vehicle information database 226 for storage purposes. Similarly, the geographic area information database 228 can store geographic area information associated with the geographic area in which the vehicle 202 may be traveling. The system transceiver 220 can receive the geographic area information from the vehicle transceiver 216 and / or the fleet computing device 204 (or other device) and send the information to the geographic area information database 228 for storage purposes. The mapping database 230 can store a mapping of multiple predetermined conditions to corresponding maximum speed limits. The use of the mapping as mentioned herein is described later in the description below.

[0043] In operation, the system processor 222 may obtain vehicle information from the vehicle information database 226. As described above, the vehicle information may include vehicle geographic location, current vehicle speed, vehicle travel route, vehicle payload, etc. The system processor 222 may also obtain geographic region information (associated with a geographic region in which the vehicle 202 may be traveling) from the geographic region information database 228.

[0044] Figure 3 An example of geographic area information is shown in FIG. The geographic area information may include, but is not limited to: target point location information on the vehicle's driving route (such as the location of road exits, turns, stop lights, etc., Figure 3 302 in FIG. 30 ), historical adverse situation information (shown as FIG. 304 ) indicating a count of adverse situations that may have occurred in a geographic area within a predefined duration. Figure 3 304 in FIG. 1 ) and historical traffic violation information (shown as FIG. 1 ) associated with the user of the vehicle 202 and the geographic area, which may indicate a count of traffic violations performed by the user in the geographic area within a predefined duration. Figure 3 The geographic area information may also include real-time road adverse condition information associated with the geographic area (shown as Figure 3 308 in FIG. 1 ), real-time weather information associated with the geographic area (e.g., strong winds, heavy rain, below freezing temperatures, etc., shown as Figure 3 310 in FIG. 310 ) and current time information associated with the geographic area (e.g., time of day, day of the week, etc., shown as Figure 3 The geographic area information may also include road slope information associated with the geographic area (shown as Figure 3 314 in the figure), historical user driving behavior information indicating historical user driving behavior in the geographic area (shown as Figure 3316 in FIG. 1 ), current user status information indicating current user status in the geographic area (e.g., driver reaction time, shown as Figure 3 Box 318 in), etc.

[0045] Additionally, geographic area information may include traffic violation rates / police stop rates, following distance based on geofence location (e.g., distance to the vehicle ahead and location of vehicle 202 (such as a highway)), posted speed limits, traffic congestion, time-enforced speed limits (e.g., speed limits that depend on time of day, day of the week, such as speed limits in school zones during morning hours), etc.

[0046] In response to obtaining the vehicle information and the geographic area information, the system processor 222 (via the vehicle management module 232) may determine a predetermined condition that may be satisfied from a plurality of predetermined conditions based on the obtained information (e.g., the geographic area information and / or the vehicle information). In response to the predetermined condition determination, the system processor 222 (via the vehicle management module 232) may obtain a mapping of a plurality of predetermined conditions and corresponding maximum speed limits from the mapping database 230. In some aspects, the mapping may include a mapping of each predetermined condition and a maximum speed limit associated with the predetermined condition. For example, when the vehicle 202 may be moving in inclement weather, the maximum speed limit may be 20 mph, when the vehicle 202 may be moving in an area where the historical incidence of adverse conditions may be greater than a threshold, the maximum speed limit may be 10 mph, and so on.

[0047] Then, the system processor 222 (via the vehicle management module 232) can determine the maximum speed limit associated with the determined predetermined condition by using the map. Specifically, the system processor 222 can obtain the map from the mapping database 230 and determine the maximum speed limit corresponding to the predetermined condition that the vehicle 202 may meet in the geographic area. In response to determining the maximum speed limit, the system processor 222 can compare the current vehicle speed (determined according to the vehicle information) with the maximum speed limit. The system processor 222 can determine based on the comparison that the current vehicle speed may be greater than the maximum speed limit. Then, the system processor 222 can generate a signal to reduce the vehicle speed to the maximum speed limit and transmit the signal to the vehicle 202 (via the system transceiver 220). The vehicle 202 (e.g., VCU 208) can receive the signal and automatically control the vehicle speed via ECU218. In an additional aspect, the system processor 222 can transmit a notification indicating that the vehicle user may have exceeded the maximum speed limit as a reason for reducing the vehicle speed to a user interface (such as a human-machine interface (HMI) installed in the vehicle 202) or a user device. Aspects of controlling vehicle speed may be understood in conjunction with the examples described below.

[0048] Figure 4 An exemplary scenario for controlling a vehicle 400 according to the present disclosure is depicted. The vehicle 400 may be the same as the vehicles 102, 202. The vehicle 400 may be traveling on a road 402 on the vehicle's route. The road 402 may be the same as the road 108. In some aspects, the road 402 may be a curved road that may have curves or turns, or the road 402 may be a highway that may have an exit point from the highway. Information about the road 402 (e.g., a road map) may be stored as geographic area information in the geographic area information database 228. The road information (e.g., a map of the road) may be stored as geographic area information in the geographic area information database 228. Figure 4 404 and 406 in the fleet computing device 204 may include, but is not limited to, radii, curvatures, slopes, maximum speed limits, etc. associated with different points on the road 402. For example, view 404 may depict road information associated with a road turn / area 408, and view 406 may depict road information associated with another road point / area 410. Such information may be pre-stored in the fleet computing device 204, an external device, and / or the system memory 224.

[0049] The system processor 222 may be configured to obtain vehicle information (e.g., vehicle geographic location, vehicle speed, vehicle travel route, etc.) from the vehicle information database 226 (or from the vehicle transceiver 216). The system processor 222 may also be configured to obtain road information associated with the road 402 on which the vehicle 202 may be traveling based on the vehicle geographic location from the geographic area information database 228 (as part of the geographic area information).

[0050] In response to obtaining vehicle information and geographic area information (e.g., road information), the system processor 222 may be configured to determine the distance between the vehicle 202 (e.g., vehicle geographic location) and the target point location (such as turn 408). The system processor 222 may then compare the distance between the vehicle 202 (e.g., vehicle geographic location) and the turn 408 (such as the start of the turn) with a first threshold. In response to the comparison, the system processor 222 may determine that the distance may be less than the first threshold. In response to determining that the distance may be less than the first threshold, the system processor 222 may determine that a predetermined condition may be satisfied. In other words, when the vehicle 202 may be approaching the turn 408, the system processor 222 may determine that the predetermined condition may be satisfied. The system processor 222 may then determine the maximum speed limit associated with the turn 408 (a mapping stored in the mapping database 230) in the manner described above, and control the vehicle speed (e.g., reduce the vehicle speed) to the determined maximum speed limit. The system processor 222 may also control the rate of change of the speed based on the distance so that the vehicle speed may be reduced to the maximum speed limit before reaching the target point location.

[0051] In another example, the system processor 222 may obtain historical adverse condition information (depicted as Figure 3 404) as geographic area information. In some aspects, the historical adverse condition information may indicate a count of adverse conditions that may have occurred within a predefined duration in a geographic area (e.g., in an area including road 402). In response to obtaining the historical adverse condition information, the system processor 222 may compare the count of adverse conditions with a second threshold. In response to the comparison, the system processor 222 may determine that the count may be greater than the second threshold. In response to determining that the count may be greater than the second threshold, the system processor 222 may determine that a predetermined condition may be satisfied. The system processor 222 may then determine (based on a mapping stored in the mapping database 230) a maximum speed limit corresponding to the condition when the count of adverse conditions is greater than the second threshold, and control or reduce the vehicle speed to be equal to the determined maximum speed limit.

[0052] In some aspects, the historical adverse condition information may indicate a count of adverse conditions that may have occurred for a particular vehicle type. For example, the historical adverse condition information may indicate a historical analysis of adverse conditions that may have occurred for long vehicles (e.g., 18-wheel vehicles) and / or short vehicles (e.g., passenger vehicles). In this case, when the vehicle 202 may be a long vehicle (or a short vehicle) and the corresponding count of historical adverse conditions may be greater than a second threshold, the system processor 222 may determine that the predetermined condition may be met.

[0053] In another example, the system processor 222 may obtain historical traffic violation information associated with vehicle users in a geographic area (depicted as Figure 3 In some aspects, the historical traffic violation information may indicate a count of violations that the vehicle user may have committed within a predefined duration in a geographic area in which the vehicle 202 may be traveling. In response to obtaining the historical traffic violation information, the system processor 222 may compare the count of violations to a third threshold. In response to the comparison, the system processor 222 may determine that the count may be greater than the third threshold. In response to determining that the count may be greater than the third threshold, the system processor 222 may then determine that a predetermined condition may be satisfied. The system processor 222 may then determine (based on a mapping stored in the mapping database 230) a maximum speed limit corresponding to the condition associated with the count of violations and control / reduce the vehicle speed to the determined maximum speed limit.

[0054] In another example, the system processor 222 may obtain real-time road adverse condition information associated with a geographic area (depicted as Figure 3The system processor 222 may determine the presence of a road adverse condition based on the real-time road adverse condition information, and determine that a predetermined condition may be satisfied in response to determining the presence of the road adverse condition. The system processor 222 may then determine (based on a map stored in the map database 230) a maximum speed limit corresponding to the condition associated with the road adverse condition, and control / reduce the vehicle speed to the determined maximum speed limit.

[0055] In another example, the system processor 222 may obtain real-time weather conditions (depicted as Figure 3 310 in the mapping database 230) as geographic area information. The system processor 222 may determine the presence of severe weather conditions in the geographic area based on the real-time weather information, and determine that a predetermined condition may be satisfied in response to determining the presence of severe weather conditions. For example, when high winds may blow perpendicular to the surface of the vehicle, the system processor 222 may determine that the predefined condition may be satisfied. In this case, the system processor 222 may determine (based on a mapping stored in the mapping database 230) a maximum speed limit corresponding to a condition associated with the severe weather condition, and control the vehicle speed accordingly. In some aspects, the system processor 222 may generate a signal to reduce the vehicle speed to 5 mph below the posted speed limit.

[0056] In another example, the system processor 222 can obtain current time information (e.g., time of day, which is depicted as Figure 3 312 in the figure) as geographic area information. The system processor 222 may associate the time of day with the vehicle travel route and determine the probability of an adverse situation based on the association. In response to determining that the probability may be greater than a fourth threshold, the system processor 222 may determine that a predetermined condition may be met. For example, when the vehicle 202 may be moving in a direction where the sun may impair the driver's vision during the day, the system processor 222 may determine that the probability of an adverse situation may be high (e.g., greater than the fourth threshold). In this case, the system processor 222 may determine that the predetermined condition may be met, and may then determine (based on a mapping stored in the mapping database 230) a maximum speed limit corresponding to the condition associated with the probability of an adverse situation. In response to determining the maximum speed limit, the system processor 222 may compare the speed limit with the current vehicle speed, and when the current vehicle speed may be greater than the maximum speed limit, the vehicle speed may be reduced.

[0057] In another example, the system processor 222 may obtain road grade information (depicted as Figure 3 314 in FIG. 314) as geographic area information. In an exemplary aspect, the system processor 222 may determine that the vehicle 202 may be traveling downhill based on the road grade information and the vehicle geographic location. In response to determining that the vehicle 202 may be traveling downhill, the system processor 222 may determine that a predetermined condition may be satisfied. The system processor 222 may then determine a maximum speed limit corresponding to the condition associated with traveling downhill, and may control the vehicle speed accordingly.

[0058] Similarly, the system processor 222 may obtain historical user driving behavior and / or current user status information (depicted as Figure 3 314 and 316 in FIG. 314) as geographic area information. The system processor 222 may then determine the probability of an adverse situation based on historical user driving behavior and / or current user condition information. In response to determining that the probability may be greater than the fifth threshold, the system processor 222 may determine that a predetermined condition may be satisfied. For example, when the driver's reaction time may be greater than the sixth threshold, the system processor 222 may determine that the probability of an adverse situation may be high (e.g., greater than the fifth threshold). The system processor 222 may control the vehicle speed accordingly.

[0059] In some aspects, the system processor 222 may determine that more than one predetermined condition may be satisfied when the vehicle 202 may be traveling through the geographic area. In this case, the system processor 222 may determine a maximum speed limit corresponding to each predetermined condition, associating the multiple maximum speed limits to determine a final speed limit. The system processor 222 may then use the final speed limit to control the vehicle 202. In some aspects, the system processor 222 may determine the final speed limit by selecting a minimum speed limit from the maximum speed limits determined for the "applicable" or "relevant" predetermined conditions associated with the vehicle 202 in the geographic area.

[0060] In other aspects, the mapping of the predetermined condition to the maximum speed limit may be different for different vehicles / users. In other aspects, the mapping may be the same for multiple vehicles. In addition, the fleet operator may update the mapping regularly.

[0061] Figure 5 A flow chart of an exemplary fleet management method 500 according to the present disclosure is depicted. Figures 1 to 4 To describe Figure 5The following process is exemplary and is not limited to the steps described below. Furthermore, alternative embodiments may include more or fewer steps shown or described herein, and may include the steps in an order different from that described in the exemplary embodiments below.

[0062] refer to Figure 5 At step 502, the method 500 may begin. At step 504, the method 500 may include obtaining vehicle information from the vehicle information database 226 by the system processor 222 (via the system transceiver 220). As described above, the vehicle information may include vehicle speed, vehicle geographic location, vehicle travel route, etc.

[0063] At step 506, method 500 may include obtaining, by system processor 222 (via system transceiver 220), geographic region information associated with the geographic region in which vehicle 202 may be traveling from geographic region information database 228. Details associated with geographic region information have been described above.

[0064] At step 508, the method 500 may include determining, by the system processor 222, a predetermined condition that may be satisfied by the vehicle 202 from a plurality of predetermined conditions based on the geographic area information. At step 510, the method 500 may include determining, by the system processor 222, a maximum speed limit corresponding to the predetermined condition. Specifically, the system processor 222 may obtain a mapping of a plurality of predetermined conditions and corresponding maximum speed limits from the mapping database 230, and then determine the maximum speed limit corresponding to the predetermined condition based on the mapping.

[0065] At step 512 , method 500 may include generating a signal by system processor 222 to control the vehicle speed to a maximum speed limit. System processor 222 may then transmit a signal to vehicle 202 via system transceiver 220 to control the vehicle speed.

[0066] At step 514 , method 500 ends.

[0067] In the above disclosure, reference has been made to the accompanying drawings that form a part of the above disclosure, which illustrate specific embodiments in which the present disclosure can be practiced. It should be understood that other embodiments may be utilized and structural changes may be made without departing from the scope of the present disclosure. References to "one embodiment," "embodiment," "example embodiment," etc. in this specification indicate that the described embodiment may include specific features, structures, or characteristics, but each embodiment may not necessarily include the specific features, structures, or characteristics. In addition, such phrases do not necessarily refer to the same embodiment. In addition, when features, structures, or characteristics are described in conjunction with an embodiment, whether or not explicitly described, those skilled in the art will recognize such features, structures, or characteristics in conjunction with other embodiments.

[0068] In addition, where appropriate, the functions described herein may be performed in one or more of the following: hardware, software, firmware, digital components, or analog components. For example, one or more application specific integrated circuits (ASICs) may be programmed to perform one or more of the systems and programs described herein. Certain terms are used throughout the specification and claims to refer to specific system components. As will be appreciated by those skilled in the art, components may be referred to by different names. This document is not intended to distinguish between components that have different names but the same function.

[0069] It should also be understood that the word "example" as used herein is intended to be non-exclusive and non-limiting in nature. More specifically, the word "example" used herein indicates one of several examples, and it should be understood that no undue emphasis or preference is placed on the specific example described.

[0070] Computer-readable media (also referred to as processor-readable media) include any non-transitory (e.g., tangible) media that participate in providing data (e.g., instructions) that can be read by a computer (e.g., by a processor of a computer). Such media can take many forms, including but not limited to non-volatile media and volatile media. A computing device may include computer-executable instructions, where the instructions can be executed by one or more computing devices (such as those listed above) and stored on a computer-readable medium.

[0071] With respect to the processes, systems, methods, heuristics, etc. described herein, it should be understood that although the steps of such processes, etc. have been described as occurring according to a certain ordered sequence, such processes may be practiced by performing the described steps in an order different from the order described herein. It should also be understood that certain steps may be performed simultaneously, other steps may be added, or certain steps described herein may be omitted. In other words, the descriptions of processes herein are provided for the purpose of illustrating various embodiments and should in no way be construed as limiting the claims.

[0072] Therefore, it should be understood that the above description is intended to be illustrative rather than restrictive. Upon reading the above description, many embodiments and applications other than the examples provided will be apparent. The scope should not be determined with reference to the above description, but should be determined with reference to the entire scope of the appended claims and equivalents to which such claims are entitled. It is anticipated and expected that the technology discussed herein will develop in the future, and the disclosed systems and methods will be incorporated into such future embodiments. In short, it should be understood that the present application is capable of modification and change.

[0073] Unless explicitly indicated to the contrary in this article, all terms used in the claims are intended to be given their ordinary meanings as understood by the skilled person described herein. Specifically, unless the claims state an explicit limitation to the contrary, the use of singular articles such as "one", "the", "said" and the like should be interpreted as describing one or more of the indicated elements. Unless otherwise specifically stated or understood in other ways within the context when used, conditional language such as, in particular, "can", "may", "can" or "may" is generally intended to express that certain embodiments may include certain features, elements and / or steps, while other embodiments may not include certain features, elements and / or steps. Therefore, such conditional language is generally not intended to imply that one or more embodiments require each feature, element and / or step in any way.

[0074] In one aspect of the invention, the method includes comparing a vehicle speed to a maximum speed limit; determining based on the comparison that the vehicle speed is greater than the maximum speed limit; and generating a signal to reduce the vehicle speed to the maximum speed limit in response to the determination.

[0075] In one aspect of the invention, the method includes transmitting a notification to a user device associated with the user in response to generating the signal, and wherein the notification indicates that the user has exceeded a maximum speed limit.

[0076] In one aspect of the invention, the method includes obtaining information associated with the geographic area from vehicle sensors, other vehicles, or a server.

[0077] According to the present invention, a non-transitory computer-readable storage medium is provided, on which instructions are stored, which, when executed by a processor, cause the processor to: obtain vehicle information associated with a vehicle, wherein the vehicle information includes a vehicle geographic location, a vehicle speed, and a vehicle travel route; obtain information associated with a geographic area through which the vehicle is traversing; determine a predetermined condition that is satisfied from a plurality of predetermined conditions based on the information associated with the geographic area; determine a maximum speed limit associated with the predetermined condition based on a mapping stored in a memory, wherein the mapping includes an association of a plurality of predetermined conditions with corresponding maximum speed limits; and generate a signal to control the vehicle speed based on the maximum speed limit.

[0078] According to one embodiment, the invention is further characterized by having stored thereon additional instructions for: comparing the vehicle speed to a maximum speed limit; determining based on the comparison that the vehicle speed is greater than the maximum speed limit; and generating a signal in response to the determination to reduce the vehicle speed to the maximum speed limit.

Claims

1. A system comprising: a transceiver configured to receive vehicle information associated with the vehicle, wherein the vehicle information includes a geographic location of the vehicle, a speed of the vehicle, and a route of travel of the vehicle; a memory configured to store a mapping of a plurality of predetermined conditions and corresponding maximum speed limits; a processor communicatively coupled to the transceiver and the memory, wherein the processor is configured to: obtaining the vehicle information from the transceiver; obtaining information associated with a geographic area in which the vehicle is traveling; determining a satisfied predetermined condition from among the plurality of predetermined conditions based on the information associated with the geographic area; determining a maximum speed limit associated with the predetermined condition based on the mapping; and A signal is generated based on the maximum speed limit to control the vehicle speed.

2. The system of claim 1, wherein the processor is further configured to: comparing the vehicle speed to the maximum speed limit; determining, based on the comparison, that the vehicle speed is greater than the maximum speed limit; and The signal is generated in response to the determination to reduce the vehicle speed to the maximum speed limit.

3. The system of claim 2, wherein the transceiver is further configured to transmit a notification to a user device associated with a user in response to generating the signal, and wherein the notification indicates that the user has exceeded the maximum speed limit.

4. The system of claim 1, wherein the information associated with the geographic area includes a location of a target point on the vehicle's travel route, and wherein the target point includes a road exit, a turn, or a stop light.

5. The system of claim 4, wherein the processor is further configured to: Determining the distance between the vehicle's geographic location and the target point; comparing the distance between the vehicle geographic location and the target point with a first threshold; determining, based on the comparison, that the distance is less than the first threshold; and The predetermined condition is determined to be satisfied in response to determining that the distance is less than the first threshold.

6. The system of claim 1 , wherein the information associated with the geographic area includes historical adverse condition information associated with the geographic area, wherein the historical adverse condition information includes a count of adverse conditions that occurred within a predefined duration in the geographic area, and wherein the processor is further configured to: comparing the count of adverse conditions to a second threshold; determining, based on the comparison, that the count is greater than the second threshold; and The predetermined condition is determined to be satisfied in response to determining that the count is greater than the second threshold.

7. The system of claim 6, wherein the historical adverse condition information further includes a count of the adverse conditions that occurred for a vehicle type.

8. The system of claim 1 , wherein the information associated with the geographic area includes historical traffic violation information associated with a user and the geographic area, wherein the historical traffic violation information includes a count of violations that occurred within a predefined duration for the user, and wherein the processor is further configured to: comparing the count of violations to a third threshold; determining that the count is greater than the third threshold; and The predetermined condition is determined to be satisfied in response to determining that the count is greater than the third threshold.

9. The system of claim 1 , wherein the information associated with the geographic area includes real-time road adverse condition information associated with the geographic area, and wherein the processor is further configured to: determining the presence of an adverse road condition based on the real-time adverse road condition information; and The predetermined condition is determined to be satisfied in response to determining that the road adverse condition exists.

10. The system of claim 1, wherein the information associated with the geographic area includes real-time weather information associated with the geographic area, and wherein the processor is further configured to: determining the presence of severe weather conditions based on the real-time weather information; and The predetermined condition is determined to be satisfied in response to determining that the severe weather condition exists.

11. The system of claim 1 , wherein the information associated with the geographic area comprises current time information associated with the geographic area, wherein the current time information comprises a time of day, and wherein the processor is further configured to: Associating the time of day with the vehicle travel route; determining a probability of an adverse condition based on the association; and The predetermined condition is determined to be satisfied in response to determining that the probability is greater than a fourth threshold.

12. The system of claim 1, wherein the information associated with the geographic area includes road grade information associated with the geographic area, and wherein the processor is further configured to: Determining that the vehicle is traveling downhill based on the road slope information and the vehicle geographic location; and The predetermined condition is determined to be satisfied in response to a determination that the vehicle is traveling down a downhill slope.

13. The system of claim 1 , wherein the information associated with the geographic area includes historical user driving behavior information associated with the geographic area, and wherein the processor is further configured to: determining a probability of an adverse situation based on the historical user driving behavior information; and The predetermined condition is determined to be satisfied in response to determining that the probability is greater than a fifth threshold.

14. The system of claim 1, wherein the transceiver is further configured to receive the information associated with the geographic area from a vehicle sensor, another vehicle, or a server.

15. A method for controlling a vehicle, the method comprising: Obtaining vehicle information associated with the vehicle, wherein the vehicle information includes a vehicle geographic location, a vehicle speed, and a vehicle travel route; obtaining information associated with a geographic area through which the vehicle is traversing; determining a predetermined condition to be satisfied from a plurality of predetermined conditions based on the information associated with the geographic area; determining a maximum speed limit associated with the predetermined condition based on a map stored in a memory, wherein the map includes an association of the plurality of predetermined conditions with corresponding maximum speed limits; as well as A signal is generated based on the maximum speed limit to control the vehicle speed.

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