Subscription Switching for Vehicle Emergency Calls Based on Accident Probability Prediction

Abstract

In one aspect, the method includes determining, by a processor of the vehicle, that an original equipment manufacturer (OEM) subscription for the vehicle is set to a low-capacity subscription. The method includes determining, by the processor, that the low-capacity subscription is unable to access a network at a current location of the vehicle based on the low-capacity subscription. The method also includes determining, by the processor and based on sensor data received from one or more sensors of the vehicle, a probability that an accident will occur to the vehicle. The method further includes determining, by the processor, that the probability meets a threshold. The method includes switching, by the processor, the OEM subscription from the low-capacity subscription to a high-capacity subscription.

Description

[Technical field]

[0001] Aspects of the present disclosure relate generally to wireless communications, and more particularly, to emergency calling (eCall) using original equipment manufacturer (OEM) subscriptions. [Background technology]

[0002] An emergency call (eCall) is an emergency call that a vehicle automatically initiates to bring immediate assistance after it detects that an accident has occurred. eCall is currently mandatory for vehicles in the European Union and may be adopted by other regions / countries. With eCall, the vehicle automatically initiates a call to a Public Safety Answering Point (PSAP) after the vehicle's sensors detect that the vehicle has crashed, which then dispatches emergency assistance to the vehicle's location.

[0003] A vehicle may include a dual SIM dual active (DSDA) modem with support for two subscriber identity module (SIM) cards. The two SIM cards may enable the vehicle to access (1) a high-capability subscription and (2) a low-capability subscription that has lower capabilities (e.g., accesses fewer types of networks) than the high-capability subscription. Each vehicle has an original equipment manufacturer (OEM) subscription that is used by the vehicle to place an eCall. The manufacturer of the vehicle may configure the OEM subscription to be associated with either the high-capability subscription or the low-capability subscription. If (1) the manufacturer configures the OEM subscription to be associated with the low-capability subscription and (2) the vehicle has an accident in a location where a type of network accessible to the low-capability subscription is not available, the vehicle may not be able to promptly place an eCall. For example, after an accident occurs, the OEM subscription (associated with the low-capability subscription) scans for a type of network that the low-capability subscription can access. After the scan fails to identify an available network, the vehicle may take corrective action in an attempt to place an eCall. The time taken to (i) scan for networks to which the low-capacity subscription has access, (ii) determine that such networks are not available, and (iii) take corrective action can take more than a minute, wasting valuable time after an incident occurs. Summary of the Invention [Means for solving the problem]

[0004] The following presents a simplified summary of one or more aspects disclosed herein. As such, the following summary is not intended to be an extensive overview of all contemplated aspects, nor is it intended to identify key or critical elements of all contemplated aspects or to define the scope associated with any particular aspect. As such, the following summary is intended solely to present some concepts of one or more aspects of the mechanisms disclosed herein in a simplified form prior to the detailed description presented below.

[0005] In a first aspect, the method includes determining, by a processor of the vehicle, that an original equipment manufacturer (OEM) subscription for the vehicle is set to a low-capacity subscription. The method includes determining, by the processor, that the low-capacity subscription is unable to access a network at a current location of the vehicle based on the low-capacity subscription. The method also includes determining, by the processor and based on sensor data received from one or more sensors of the vehicle, a probability that an accident will occur to the vehicle. The method further includes determining, by the processor, that the probability meets a threshold. The method includes switching, by the processor, the OEM subscription from the low-capacity subscription to a high-capacity subscription.

[0006] In a second aspect, a vehicle includes one or more sensors, a memory, a transceiver, and a processor communicatively coupled to the memory and the transceiver. The processor is configured to determine that an original equipment manufacturer (OEM) subscription for the vehicle is set to a low-capacity subscription. The processor is configured to determine that the low-capacity subscription is unable to access a network at a current location of the vehicle based on the low-capacity subscription. The processor is configured to determine a probability that an accident will occur to the vehicle based on sensor data received from the one or more sensors. The processor is configured to determine that the probability meets a threshold and switch the OEM subscription from the low-capacity subscription to the high-capacity subscription.

[0007] In a third aspect, a non-transitory computer-readable storage medium is configured to store instructions, the instructions being executable by one or more processors to determine that an original equipment manufacturer (OEM) subscription for the vehicle is set to a low-capacity subscription, determine that the low-capacity subscription is unable to access a network at a current location of the vehicle based on the low-capacity subscription, determine a probability that the vehicle will have an accident based on sensor data received from one or more sensors, determine that the probability meets a threshold, and switch the OEM subscription from the low-capacity subscription to the high-capacity subscription.

[0008] In a fourth aspect, an apparatus includes means for determining that an original equipment manufacturer (OEM) subscription of a vehicle is set to a low-capability subscription, means for determining that the low-capability subscription is unable to access a network at a current location of the vehicle based on the low-capability subscription, means for determining a probability that an accident will occur to the vehicle based on sensor data received from one or more sensors, means for determining that the probability meets a threshold, and means for changing the OEM subscription from the low-capability subscription to a high-capability subscription.

[0009] Other objects and advantages associated with the embodiments disclosed herein will become apparent to those skilled in the art based on the accompanying drawings and detailed description.

[0010] The accompanying drawings are presented to aid in the explanation of various aspects of the present disclosure and are provided only for illustration of the aspects, not for limitation of the aspects. A more complete understanding of the present disclosure can be obtained by reference to the following detailed description in conjunction with the accompanying drawings. In the figures, the left-most digit(s) of a reference number identifies the figure in which that reference number first appears. The same reference numbers in different drawings indicate similar or identical items. [Brief description of the drawings]

[0011] [Figure 1] FIG. 1 illustrates an example of a system for automatically switching an original equipment manufacturer (OEM) subscription before making an emergency call (eCall) in accordance with various aspects of the present disclosure. [Diagram 2] FIG. 1 illustrates an example of a vehicle-based system for switching an OEM subscription to a high-capability subscription in accordance with various aspects of the disclosure. [Diagram 3] FIG. 1 illustrates an example of a system for training a machine learning algorithm in accordance with various aspects of the present disclosure. [Figure 4]FIG. 1 illustrates an example process that includes determining that a low-capability subscription cannot access a network at a current location of a vehicle based on the low-capability subscription, according to aspects of the disclosure. [Diagram 5] FIG. 1 illustrates an example process including determining whether a probability meets a threshold, according to an aspect of the disclosure. [Figure 6] FIG. 1 illustrates an example of a user equipment (UE) that may be used to implement the systems, techniques, and processes described herein. [Figure 7A] 1 is a simplified block diagram of several sample aspects of components that may be employed in a wireless communication node and configured to support communications as described herein; [Figure 7B] 1 is a simplified block diagram of several sample aspects of components that may be employed in a wireless communication node and configured to support communications as described herein; DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0012] Systems and techniques are disclosed for reducing the time to make an emergency call (eCall) after a vehicle is involved in an accident. When the vehicle is moving, a call control module (sometimes called an access point because the call control module allows the vehicle to access one or more networks) of the vehicle determines whether the original equipment manufacturer (OEM) subscription is set to a low-capability subscription. If the OEM subscription is set to a low-capability subscription, the call control module determines the coverage (e.g., which networks are currently available for access) associated with the OEM subscription. If the OEM subscription is set to a low-capability subscription and a network accessible by the low-capability subscription is not available at the vehicle's current location, the call control module may use current sensor data to determine the probability that the vehicle will be involved in an accident. For example, the call control module may take into account the speed of the vehicle, the posted speed limit of the road on which the vehicle is currently traveling, the proximity of the vehicle to other vehicles (e.g., whether the vehicle is in light traffic or heavy traffic), weather conditions (e.g., rain, sleet, snow, fog, etc.), whether the vehicle is on a relatively straight road or a relatively curvy road (e.g., with multiple curves), how many accidents have occurred in the past on the road on which the vehicle is currently traveling, and other factors when determining the probability that the vehicle will be involved in an accident. In some cases, a weighted average of various factors may be used. In other cases, a machine learning algorithm trained at least in part on accident data may be used to predict the probability that the vehicle will be involved in an accident. If the probability that the vehicle will be involved in an accident meets a certain threshold, the call control module may automatically switch the OEM subscription to a high-capability subscription, for example, before an accident occurs.The call control module automatically switches the OEM subscription to the high-capability subscription because, at the vehicle's current location, the low-capability subscription does not have access to a network to place an eCall. If the vehicle is involved in an accident, the vehicle can immediately place an eCall using the OEM subscription that has now been switched to the high-capability subscription. Thus, an advantage provided by the systems and techniques disclosed herein is that when an accident occurs, the OEM subscription is already associated with the high-capability subscription, thereby enabling the vehicle to immediately place an eCall. In this way, the delay (e.g., at least one minute) caused by the call control module scanning for available networks when the OEM subscription is associated with a low-capability subscription is avoided.

[0013] After the probability of an accident falls below a certain threshold, the call control module switches the OEM subscription back to the low-capacity subscription if the OEM subscription was initially associated with the low-capacity subscription. To prevent the call control module from switching the OEM subscription back and forth from the high-capacity subscription to the low-capacity subscription, a timer (e.g., a hysteresis timer) is used after switching the OEM subscription to the high-capacity subscription. For example, a relatively curvy road may have relatively straight sections. Without the timer, the call control module may switch the OEM subscription to the high-capacity subscription in the relatively curvy sections and switch the OEM subscription to the low-capacity subscription in the relatively straight sections. To prevent the call control module from frequently switching the OEM subscription back and forth between the low-capacity subscription and the high-capacity subscription, the timer may keep the OEM subscription associated with the high-capacity subscription for the time the vehicle is traveling through the relatively straight sections. As another example, when severe weather conditions temporarily abate, the timer may keep the OEM subscription associated with the high-capacity subscription for the duration of the temporary abate.

[0014] Thus, (1) when the OEM subscription is associated with a lower-capability subscription, and (2) by anticipating (e.g., predicting) when the vehicle may be involved in an accident when a network using the lower-capability subscription is not available (e.g., at the vehicle's current location), the vehicle may switch the OEM subscription to the higher-capability subscription. By doing so, if the vehicle is involved in an accident, the vehicle may quickly (e.g., without delays caused by scanning for available networks and not finding them) initiate an eCall to the PSAP. In this manner, emergency vehicles may be quickly dispatched to assist potentially injured vehicle occupants and reduce the impact of injuries resulting from the accident.

[0015] Aspects of the present disclosure are provided in the following description and associated drawings, directed to various examples provided for illustrative purposes. Alternative aspects may be devised without departing from the scope of the present disclosure. Additionally, well-known elements of the present disclosure will not be described in detail or will be omitted so as not to obscure the relevant details of the present disclosure.

[0016] The words "example" and / or "exemplary" are used herein to mean "serving as an example, instance, or illustration." Any aspect described herein as "example" and / or "exemplary" is not necessarily to be construed as preferred or advantageous over other aspects. Similarly, the term "aspects of the disclosure" does not require that all aspects of the disclosure include the discussed feature, advantage or mode of operation.

[0017] Those skilled in the art will appreciate that the information and signals described below may be represented using any of a variety of different technologies and techniques. For example, data, instructions, commands, information, signals, bits, symbols, and chips that may be referred to throughout the following description may be represented by voltages, currents, electromagnetic waves, magnetic fields or particles, optical fields or particles, or any combination thereof, depending in part on the specific application, in part on the desired design, in part on the corresponding technology, etc.

[0018] Further, many aspects are described in terms of a sequence of actions to be performed, for example, by elements of a computing device. It will be appreciated that the various actions described herein may be performed by specific circuitry (e.g., an application specific integrated circuit (ASIC)), by program instructions executed by one or more processors, or by a combination of both. In addition, a sequence of actions described herein may be considered to be fully embodied in any form of non-transitory computer-readable storage medium storing a corresponding set of computer instructions that, when executed, cause or instruct an associated processor of a device to perform the functions described herein. Thus, various aspects of the present disclosure may be embodied in a number of different forms, all of which are contemplated to fall within the scope of the claimed subject matter. In addition, for each of the aspects described herein, the corresponding form of any such aspect may be described herein, for example, as "logic configured to" perform the described actions.

[0019] The terms "user equipment" (UE) and "base station" as used herein are not intended to be specific or otherwise limited to any particular radio access technology (RAT) unless otherwise stated. In general, a UE may be any wireless communication device (e.g., a mobile phone, a router, a tablet computer, a laptop computer, a consumer asset tracking device, a wearable device (e.g., a smart watch, glasses, an augmented reality (AR) / virtual reality (VR) headset, etc.), a vehicle (e.g., an automobile, a motorcycle, a bicycle, etc.), an Internet of Things (IoT) device, etc.) used by a user to communicate over a wireless communication network. A UE may be mobile or stationary (e.g., at some time) and may communicate with a radio access network (RAN). The term "UE" as used herein may be referred to interchangeably as an "access terminal" or "AT", "client device", "wireless device", "subscriber device", "subscriber terminal", "subscriber station", "user terminal" or UT, "mobile device", "mobile terminal", "mobile station", or variations thereof. In general, a UE can communicate with a core network via the RAN, through which the UE can be connected to external networks, such as the Internet, and to other UEs. Of course, other mechanisms for connecting to the core network and / or the Internet are also possible for a UE, such as via a wired access network, a wireless local area network (WLAN) network (e.g., based on the Institute of Electrical and Electronics Engineers (IEEE) 802.11, etc.), etc.

[0020] A base station may operate according to one of several RATs in communication with UEs depending on the network in which the base station is deployed and may alternatively be referred to as an access point (AP), network node, NodeB, evolved NodeB (eNB), next generation eNB (ng-eNB), New Radio (NR) NodeB (also referred to as gNB or gNodeB), etc. A base station may be used primarily to support wireless access by UEs, including supporting data, voice, and / or signaling connections for supported UEs. In some systems, a base station may provide purely edge node signaling functionality, while in other systems, a base station may provide additional control and / or network management functionality. A communication link through which a UE may transmit a radio frequency (RF) signal to a base station is referred to as an uplink (UL) channel (e.g., a reverse traffic channel, a reverse control channel, an access channel, etc.). A communication link through which a base station may transmit a signal to a UE is referred to as a downlink (DL) or forward link channel (e.g., a paging channel, a control channel, a broadcast channel, a forward traffic channel, etc.). The term Traffic Channel (TCH) as used herein can refer to either an uplink / reverse traffic channel or a downlink / forward traffic channel.

[0021] The term "base station" may refer to a single physical transmission / reception point (TRP) or multiple physical TRPs that may or may not be co-located. For example, when the term "base station" refers to a single physical TRP, the physical TRP may be an antenna of the base station corresponding to a cell (or several cell sectors) of the base station. When the term "base station" refers to multiple physical TRPs that are co-located, the physical TRPs may be an array of antennas of the base station (e.g., as in a multiple-input multiple-output (MIMO) system or when the base station employs beamforming). When the term "base station" refers to multiple physical TRPs that are not co-located, the physical TRPs may be a distributed antenna system (DAS) (a network of spatially separated antennas connected to a common source via a transport medium) or a remote radio head (RRH) (a remote base station connected to a serving base station). Alternatively, a non-co-located physical TRP may be a serving base station that receives measurement reports from the UE and neighboring base stations whose reference RF signals (or simply "reference signals") the UE is measuring. Since a TRP is a point from which a base station transmits and receives wireless signals, as used herein, references to transmission from or reception at a base station should be understood as references to a particular TRP of the base station.

[0022] In some implementations that support positioning of UEs, a base station may not support wireless access by the UE (e.g., may not support data, voice, and / or signaling connections for the UE) but may instead transmit reference signals to the UE to be measured by the UE and / or receive and measure signals transmitted by the UE. Such a base station may be referred to as a positioning beacon (e.g., when it transmits signals to the UE) and / or a location measurement unit (e.g., when it receives and measures signals from the UE).

[0023] An "RF signal" includes electromagnetic waves of a given frequency that transport information through space between a transmitter and a receiver. As used herein, a transmitter may transmit a single "RF signal" or multiple "RF signals" to a receiver. However, the receiver may receive multiple "RF signals" corresponding to each transmitted RF signal due to the propagation characteristics of RF signals through a multipath channel. The same RF signal transmitted on different paths between a transmitter and a receiver may be referred to as a "multipath" RF signal. As used herein, RF signals may be referred to as "wireless signals," "positioning signals," "waves," "waveforms," ​​etc., or simply as "signals" when it is clear from the context that the term "signal" refers to a wireless signal or an RF signal.

[0024] The vehicle determines that the original equipment manufacturer (OEM) subscription is set to a low-capability subscription. When the vehicle determines that a type of network that the low-capability subscription can access is not available at the vehicle's current location, the vehicle performs an analysis of sensor data from multiple sensors to determine the probability that an accident will occur. For example, the analysis may include determining whether the vehicle's speed exceeds a posted speed limit and whether the vehicle is traveling in severe weather (e.g., rain, sleet, snow, or fog). If the probability meets a threshold, the vehicle automatically switches the OEM subscription to a high-capability subscription that has access to at least one type of network that the low-capability subscription cannot access. When an accident occurs, the high-capability subscription enables the vehicle to automatically place an emergency call (eCall).

[0025] As a first example, the method may include determining that an original equipment manufacturer (OEM) subscription for the vehicle is set to a low-capability subscription, determining that the low-capability subscription cannot access a network at the vehicle's current location, determining a probability that the vehicle will have an accident based on sensor data received from one or more sensors of the vehicle, determining that the probability meets a threshold, and switching the OEM subscription from the low-capability subscription to a high-capability subscription. The high-capability subscription may be able to access at least one type of network that the low-capability subscription cannot access. The method may include determining that the vehicle has an accident and initiating an emergency call (eCall) to a public safety answering point (PSAP). Determining the probability that the vehicle will have an accident may include receiving sensor data from one or more sensors and using a machine learning algorithm (e.g., a support vector machine, etc.) to determine the probability that the vehicle will have an accident based on the sensor data. The method may include setting a timer; determining a second probability based on second sensor data received from one or more sensors of the vehicle; determining that the second probability fails to meet a threshold; and switching the OEM subscription from a high-capability subscription to a low-capability subscription after determining that the timer has expired.The method may include determining that determining a probability that an accident will occur to the vehicle based on sensor data received from one or more sensors of the vehicle includes at least one of: (1) determining that the vehicle speed exceeds the posted limit for a road on which the vehicle is traveling, (2) determining that the vehicle is traveling in severe weather including at least one of rain, sleet, snow, or fog, (3) determining that at least one of the gyroscope or accelerometer data indicates reckless driving, or (4) determining that the cellular vehicle-to-everything (C-V2X) data indicates a relatively high traffic density (e.g., greater than a threshold number T of automobiles, where T>0) in the immediate vicinity of the vehicle. The method may include determining an estimated time of arrival at a destination programmed into a navigation system of the vehicle and setting a timer based in part on a difference between the estimated time of arrival and a current time. The method may include determining a destination programmed into a navigation system of the vehicle, determining an amount of time that severe weather is expected to be encountered en route to the destination, and setting a timer based at least in part on the amount of time.The method may include determining a destination programmed into a navigation system of the vehicle, determining an estimate of a time spent navigating one or more curves en route to the destination, and setting a timer based at least in part on the estimate of time.

[0026] As a second example, a vehicle may include one or more sensors, one or more processors, and one or more non-transitory computer-readable storage media for storing instructions executable by the one or more processors to perform various operations. For example, the operations may include determining that an original equipment manufacturer (OEM) subscription of the vehicle is set to a low-capability subscription, determining that the low-capability subscription cannot access a network at the current location of the vehicle, determining a probability that the vehicle will have an accident based on sensor data received from the one or more sensors, determining that the probability meets a threshold, and switching the OEM subscription from the low-capability subscription to a high-capability subscription. The operations may include determining that the vehicle will have an accident and initiating an emergency call (eCall) to a public safety answering point (PSAP). Determining a probability that the vehicle will have an accident based on sensor data received from the one or more sensors of the vehicle may include receiving sensor data from the one or more sensors, and using a machine learning algorithm to determine a probability that the vehicle will have an accident based on the sensor data. The operations may include setting a timer, determining a second probability based on second sensor data received from one or more sensors of the vehicle, determining that the second probability fails to meet a threshold, and switching the OEM subscription from the high capability subscription to a low capability subscription after determining that the timer has expired, wherein the high capability subscription is accessible to at least one type of network that the low capability subscription cannot access.Determining the probability that the vehicle will experience an accident based on sensor data received from one or more sensors of the vehicle includes at least one of: (1) determining that the vehicle speed exceeds the posted limit of the road on which the vehicle is traveling; (2) determining that the vehicle is traveling in severe weather including at least one of rain, sleet, snow, or fog; (3) determining that at least one of the gyroscope data or accelerometer data indicates reckless driving; or (4) determining that the Cellular Vehicle-to-Everything (C-V2X) data indicates a relatively high traffic density around the vehicle. The operations may include determining an estimated time of arrival at a destination programmed into a navigation system of the vehicle and setting a timer based in part on a difference between the estimated time of arrival and a current time. The operations may include determining a destination programmed into a navigation system of the vehicle, determining an amount of time that severe weather is expected to be encountered en route to the destination, and setting a timer based at least in part on the amount of time. The operations may include determining a destination programmed into the vehicle's navigation system, determining an estimate of a time that will be spent navigating one or more curves en route to the destination, and setting a timer based at least in part on the estimate of time.

[0027] As a third example, one or more non-transitory computer-readable storage media may store instructions executable by one or more processors to perform various operations. For example, the operations may include determining that an original equipment manufacturer (OEM) subscription for the vehicle is set to a low-capability subscription, determining that the low-capability subscription cannot access a network at the vehicle's current location, determining a probability that the vehicle will have an accident based on sensor data received from one or more sensors, determining that the probability meets a threshold, and switching the OEM subscription from the low-capability subscription to a high-capability subscription. The high-capability subscription is accessible to at least one type of network that the low-capability subscription cannot access. The operations may include determining that the vehicle will have an accident and initiating an emergency call (eCall) to a public safety answering point (PSAP). Determining a probability that the vehicle will have an accident based on sensor data received from one or more sensors of the vehicle may include receiving sensor data from the one or more sensors and using a machine learning algorithm to determine a probability that the vehicle will have an accident based on the sensor data. The operations may include setting a timer, determining a second probability based on second sensor data received from one or more sensors of the vehicle, determining that the second probability fails to meet a threshold, and switching the OEM subscription from the high-capability subscription to the low-capability subscription after determining that the timer has expired.Determining the probability that the vehicle will experience an accident based on sensor data received from one or more sensors of the vehicle includes at least one of: (1) determining that the vehicle speed exceeds the posted limit of the road on which the vehicle is traveling; (2) determining that the vehicle is traveling in severe weather including at least one of rain, sleet, snow, or fog; (3) determining that at least one of the gyroscope data or accelerometer data indicates reckless driving; or (4) determining that the Cellular Vehicle-to-Everything (C-V2X) data indicates a relatively high traffic density around the vehicle. The operations may include determining an estimated time of arrival at a destination programmed into a navigation system of the vehicle and setting a timer based in part on a difference between the estimated time of arrival and a current time. The operations may include determining a destination programmed into a navigation system of the vehicle, determining an amount of time that severe weather is expected to be encountered en route to the destination, and setting a timer based at least in part on the amount of time. The operations may include determining a destination programmed into the vehicle's navigation system, determining an estimate of a time that will be spent navigating one or more curves en route to the destination, and setting a timer based at least in part on the estimate of time.

[0028] 1 illustrates an example of a system 100 for automatically switching an OEM subscription before making an eCall in accordance with various aspects of the disclosure. In the system 100, a vehicle 102 is connected to a Public Safety Answering Point (PSAP) 104 via one or more networks 106. For example, the one or more networks 106 may include Long Term Evolution (LTE), Global System for Mobile (GSM), Code Division Multiple Access (CDMA), Wideband CDMA (WCDMA), 5G New Radio (NR) radio access technology (RAT), another type of wireless technology, or any combination thereof.

[0029] The vehicle 102 includes a dual SIM dual active (DSDA) modem 108 having two subscriber identity module (SIM) cards, SIM1 110 and SIM2 112. SIM1 110 is associated with a low capability subscription 114, and SIM2 112 is associated with a high capability subscription 116. The high capability subscription 116 can communicate with multiple networks, such as, for example, LTE, GSM, CDMA, WCDMA, NR RAT, etc. In contrast, the low capability subscription 114 can communicate with a smaller number of networks, such as, for example, LTE and GSM. A manufacturer of the vehicle 102 may configure an original equipment manufacturer (OEM) subscription 118 to be associated with either the low capability subscription 114 or the high capability subscription 116. The vehicle 102 includes a transceiver 140 for transmitting and receiving signals from various sources (e.g., positioning signals 134 from a positioning signal source 136). Transceiver 140 may include one or more transceivers for transmitting and receiving cellular-based or WWAN signals, for example, LTE, GSM, CDMA, WCDMA, 5G, etc. Transceiver 140 may also include one or more transceivers for short-range communications, including WLAN, Bluetooth, UWB, etc.

[0030] The vehicle 102 includes a call control module 120 and a sensor 122 for providing sensor data 124. The call control module 120 includes a determination module 126 for analyzing the sensor data 124 to determine a probability 127. The determination module 126 determines that the vehicle 102 will be involved in an accident when the probability 127 meets a threshold 128 (e.g., probability >= 75%, 80%, 90%, 95%, etc.). In some cases, the determination module 126 may determine whether the sensor data 124 meets one or more criteria. The call control module 120 may include a timer 130 (e.g., a timer).

[0031] The vehicle 102 may include one or more positioning components, such as a satellite positioning system (SPS) 138, to receive positioning signals 134 from one or more positioning signal sources 136. For example, the positioning signals 134 may include satellite positioning system (SPS) signals, global navigation satellite system (GNSS) signals, etc. The transceiver 140 may be used to transmit and receive cellular signals, including positioning signals such as Code Division Multiple Access (CDMA), Global System for Mobile Communications (GSM), Long Term Evolution (LTE), 5G, etc. The sensor data 124 may include various types of sensor data generated from the sensors 122. For example, the sensor data 124 may include data captured by the camera 204, detailed map data, acceleration data, gyro data, weather data, vehicle sensor data (e.g., speed, tire pressure, etc.), Radio Detection and Ranging (RADAR) and Light Detection and Ranging (LIDAR), and similar data received from the sensors. In some aspects, the vehicle 102 may combine positioning signal sources 136 (including, for example, satellite signals, cellular signals, and short-range signals such as WLAN) and sensor data 124 to perform hybrid positioning to determine the location of the vehicle 102. For example, hybrid positioning may use satellite signals, cellular signals, Wi-Fi signals, other types of positioning signals, sensor data, or any combination thereof.

[0032] When the vehicle 102 is moving, the call control module 120 may determine whether the OEM subscription 118 is set to the low capability subscription 114 or the high capability subscription 116. If the call control module 120 determines that the OEM subscription 118 is set to the high capability subscription 116, no further action is taken because the high capability subscription 116 provides access to the largest number of available networks. If the call control module 120 determines that the OEM subscription 118 is set to the low capability subscription 114, the call control module 120 periodically (e.g., every M milliseconds, where M>0) determines whether the low capability subscription 114 has access to at least one network (e.g., of a limited number of networks accessible to the low capability subscription 114) at the current location of the vehicle 102.

[0033] If the call control module 120 determines that the OEM subscription 118 does not have access to any networks (e.g., of a limited number of network types accessible to the low-capability subscription 114) at the current location of the vehicle 102, the call control module 120 uses the determination module 126 to monitor the sensor data 124 to predict a probability 127 that the vehicle 102 will be involved in an accident. In some cases, the determination module 126 may use a formula, such as a weighted sum of one or more of the sensor data 124, to predict the probability 127 associated with the vehicle 102 being involved in an accident. In other cases, the determination module 126 may determine whether the sensor data 124 meets one or more criteria (e.g., one or more of the thresholds 128) to predict whether the vehicle 102 will be involved in an accident. For example, the determination module 126 may predict that the vehicle 102 may be involved in an accident if the speed of the vehicle 102 exceeds a first one of the thresholds 128, the type of weather being experienced meets a second one of the thresholds 128, the amount of traffic surrounding the vehicle 102 meets a third one of the thresholds 128, etc. In still other cases, the determination module 126 may use machine learning to predict whether the vehicle 102 will be involved in an accident. For example, the machine learning may use supervised learning (e.g., active learning, classification, or regression) to predict the probability 127 that the vehicle 102 will be involved in an accident. If the probability 127 meets the threshold 128, the call control module 120 automatically switches the OEM subscription 118 from the low-capability subscription 114 to the high-capability subscription 116, thereby making more network available to the vehicle 102 (e.g., compared to the low-capability subscription 114). If the vehicle 102 is involved in an accident, the call control module 120 initiates an eCall 132 to the PASP 104. In response, the PASP 104 issues a dispatch 133 to one or more emergency personnel, such as paramedics, to provide medical assistance to the occupants of the vehicle 102 .

[0034] To reduce the likelihood that the call control module 120 frequently switches the OEM subscription 118 from the low-capability subscription 114 to the high-capability subscription 116 and vice versa, after switching the OEM subscription 118 to the high-capability subscription 116, the call control module 120 sets a timer 130 (e.g., a hysteresis timer) for a certain time (e.g., between about 5 minutes and about 30 minutes). The call control module 120 may wait until the timer 130 expires before switching the OEM subscription 118 back to the low-capability subscription 114. The call control module 120 may take into account the length of the journey programmed into the satellite navigation system of the vehicle 102 when setting the timer 130. For example, assuming that the satellite navigation system of the vehicle 102 is programmed for a journey that is estimated to take X (e.g., 30) minutes and the journey is Y (e.g., 10) minutes, the determination module 126 determines that the probability of accident 127 meets the threshold 128. In this example, the call control module 120 may set the timer 130 to XY (=20) minutes, e.g., the remaining of the journey. The call control module 120 may take into account the remaining length of the curved portion of the road on which the vehicle 102 is traveling. For example, assume that the vehicle 102 is traveling on a road that was previously straight but now has multiple curves. The decision module 126 determines that the probability of accident 127 met the threshold 128 when the first curve was encountered, and determines that the remaining curves will take approximately Z minutes to traverse, and sets the timer 130 to Z minutes. The call control module 120 may take weather conditions into account when setting the timer 130. For example, assume that due to severe weather (e.g., rain), the decision module 126 determines that the probability of accident 127 meets the threshold 128. In this example, the call control module 120 may determine that the severe weather is expected to last for W minutes and set the timer 130 for W minutes, e.g., when the weather is estimated to clear. Thus, the timer 130 may be set based on the time of the journey, road conditions, weather conditions, traffic density, other sensor data, or any combination thereof.For example, assume that the low-capability subscription 114 is associated with two types of networks (e.g., LTE and GSM), while the high-capability subscription 116 is associated with four types of networks (e.g., LTE, GSM, CDMA, WCDMA, and 5G). Thus, in this example, the high-capability subscription 116 can access four types of networks, while the low-capability subscription can only access half as many, e.g., two types of networks. When the call control module 120 determines that LTE or GSM networks are not available at the current location of the vehicle 102 and the probability of accident 127 meets the threshold 128, the call control module 120 automatically switches the OEM subscription 118 from the low-capability subscription 114 to the high-capability subscription 116 to enable the OEM subscription 118 to access two additional types of networks (e.g., WCDMA and NR RAT), which makes it more likely that an eCall 132 can be made when the vehicle 102 has an accident.

[0035] Thus, (1) when the OEM subscription 118 is set to the low-capability subscription 114 at the factory, (2) when the call control module 120 determines that the OEM subscription 118 cannot access any of the networks associated with the low-capability subscription 114 at the current location of the vehicle 102, and (3) when the call control module 120 predicts that the probability 127 of the vehicle 102 having an accident meets the threshold 128 based on the sensor data 124 and indicates that the probability 127 of the vehicle 102 being involved in an accident is high (e.g., 80%, 90%, 95%, or greater), the call control module 120 automatically (e.g., without human intervention) switches the OEM subscription 118 from the low-capability subscription 114 to the high-capability subscription 116. In this way, a maximum number of networks 106 are available for the OEM subscription 118 to make an eCall 132 when the vehicle 102 is involved in an accident.

[0036] Automatically and proactively switching the OEM subscription 118 from the low capability subscription 114 to the high capability subscription 116 has several advantages. First, by switching the OEM subscription 118 to the high capability subscription 116 before the vehicle 102 is involved in an accident, a maximum number of networks 106 are made available to initiate an eCall 132 after the vehicle 102 is involved in an accident. Second, the call control module 120 does not spend time (e.g., one minute or more) scanning for available networks and then taking corrective action. For example, if the OEM subscription 118 was associated with the low capability subscription 114, the call control module 120 would spend time scanning for available networks, determine that a network was not available, terminate the initial eCall 132, switch the OEM subscription 118 from the low capability subscription 114 to the high capability subscription 116, and resume the eCall 132. In a vehicle accident, such time savings could mean the difference between life and death, or between a relatively minor injury (e.g., because an accident injury was promptly treated due to the timely dispatch of an eCall132) and a serious injury (e.g., because an accident injury was left untreated for an extended period of time).

[0037] 2 illustrates an example of a vehicle-based system 200 for switching an OEM subscription to a high-capability subscription in accordance with various aspects of the disclosure. In some aspects, at least some of the components of the vehicle 102 may be referred to as user equipment (UE).

[0038] In system 200, the decision module 126 may, in some cases, use machine learning 202 to predict whether vehicle 102 may be involved in an accident. For example, machine learning 202 may use supervised learning (e.g., active learning, classification, or regression) or another machine learning technique to predict the probability 127 that vehicle 102 will be involved in an accident within a specific time period (e.g., within the next Y seconds, where Y > 0). For illustration purposes, machine learning 202 may be trained on accident data to predict when vehicle 102 will be involved in an accident. For example, the main reasons for vehicle accidents include speeding (e.g., the speed of vehicle 102 exceeds the posted speed limit of the road on which vehicle 102 is traveling), reckless driving (e.g., aggressive maneuvers including sudden lane changes, hard accelerations, hard brakes, etc.), severe weather (e.g., rain, sleet, snow, fog, or other conditions such as reduced traction or reduced visibility), tailgating (e.g., vehicle 102 getting too close to another vehicle in front of it), and poor road conditions (e.g., potholes in the road, road construction, etc.). Machine learning 202 may be trained to recognize that at a specific location on a specific road, the speed and weather conditions of vehicle 102 predict (e.g., with a high probability such as probability 127 ≥ 70%, 80%, 90%, 95%, etc.) that vehicle 102 will be involved in an accident within a specific time period (e.g., within the next Y seconds, where 0 < Y ≤ 300).

[0039] The sensors 122 may include a camera 204, a map detail 206, an accelerometer 208, a gyroscope 210, a weather sensor 212, an inertial measurement unit (IMU) 226, short range communications 228 (e.g., Wi-Fi, Bluetooth, ultra-wideband, etc.), a magnetometer 230, a light detection and ranging (LIDAR) 232, a vehicle sensor 216, or any combination thereof. The camera 204 and map detail 206 provide detailed information related to the current location of the vehicle 102, including the map detail 206 such as whether the road the vehicle is traveling on is straight or curved (and if curved, the angle of the curve), how many curves are present during the programmed journey, the posted speed limit, whether there are dividers between lanes in both directions, the number of lanes, how many accidents have occurred previously, etc. For example, when determining the probability 127, the decision module 126 may take into account, among other things, the current speed of the vehicle 102 (e.g., obtained from a speed sensor of the vehicle sensors 216), the posted speed limit of the road on which the vehicle 102 is traveling, and the angle of the curvature of the road.

[0040] As another example, the determination module 126 may use data from the accelerometer 208 to determine whether the vehicle 102 is accelerating and decelerating rapidly (e.g., due to braking). The determination module 126 may use data from the gyroscope 210 to determine whether the vehicle 102 is undergoing abrupt back and forth motions indicative of a sudden lane change. The determination module 126 may use data from a G-force sensor among the vehicle sensors 216 to determine whether the vehicle 102 is undergoing large G-forces caused by turning a curve in the road too quickly. Thus, the determination module 126 may use data from the accelerometer 208, the gyroscope 210, and the G-force sensor, among others, to determine whether the driver of the vehicle 102 is driving dangerously or erratically when determining the probability 127.

[0041] For example, the weather sensors 212 may include a first temperature sensor that determines the temperature outside the vehicle 102, a second temperature sensor that determines the temperature inside the vehicle 102, and a rain sensor that detects when rain is falling on the vehicle 102. For example, most vehicles use a rain sensor to detect when it is raining and automatically turn on the wiper blades. When the rain sensor detects that it is no longer raining, the rain sensor may automatically turn off the wiper blades. The determination module 126 may determine a difference between the temperature inside the vehicle 102 and the temperature outside the vehicle 102 to determine whether the vehicle is traveling in severe weather. For example, if the temperature difference between the inside and outside of the vehicle 102 is greater than a threshold amount (e.g., a difference of 15 degrees Celsius or more), the determination module 126 may determine that the vehicle is traveling in severe weather. The determination module 126 may use data from the weather sensors 212 to determine whether the vehicle 102 is traveling in severe weather, such as rain, snow, sleet, fog, etc. The determination module 126 may use the current speed of the vehicle 102 along with a determination as to whether the vehicle 102 is traveling in severe weather, among other factors, to determine the probability 127. For example, the speed of the vehicle 102 may be at or below the posted speed limit. However, the speed of the vehicle 102 in severe weather may increase the probability 127. To illustrate, the vehicle 102 may safely travel around a curve in a road at a first speed under ideal conditions (e.g., sunny, no rainfall, etc.), but in severe weather the vehicle 102 may travel more safely at a second speed that is slower than the first speed. Thus, the determination module 126 may take into account, among other factors, the current speed of the vehicle 102, the posted speed limit of the road on which the vehicle 102 is located, and the weather conditions when determining the probability 127.

[0042] For example, the transceiver 140 may include a Cellular Vehicle-to-Everything (C-V2X) component that allows the vehicle 102 to communicate with vehicles and other objects around the vehicle 102 to provide 360° non-line-of-sight awareness. The C-V2X component may include vehicle-to-vehicle (V2V), vehicle-to-infrastructure (V2I), vehicle-to-pedestrian (V2P), and vehicle-to-cloud (V2C) communications. Data from the C-V2X component, in conjunction with the sensor data, may be used to determine how many vehicles are in the vicinity of the vehicle 102, vehicle density in the vicinity of the vehicle 102, pedestrians, and other information related to the surroundings of the vehicle 102. The determination module 126 may take into account the sensor data and data from the C-V2X component when determining the probability 127. For example, when the vehicle 102 is traveling faster than the posted speed limit, when the vehicle 102 is undergoing rapid acceleration / deceleration, when the vehicle 102 is undergoing rapid lane changes, or any combination thereof, such characteristics may be deemed relatively safe when there are few (or no) other vehicles near the vehicle 102. However, such characteristics may be deemed relatively dangerous and potentially causing an accident when there are many vehicles near the vehicle 102. Thus, the determination module 126 may determine that high speed and erratic driving increases the probability 127 of an accident when the vehicle 102 is surrounded by many other vehicles.

[0043] The vehicle sensors 216 may include a vehicle speed sensor (e.g., used by a speedometer to indicate the speed of the vehicle 102), an engine temperature sensor, a wiper sensor indicating whether the windshield wiper blades are on (e.g., for severe weather such as rain, sleet, snow, fog, etc.), a brake sensor (e.g., indicating the temperature of the brakes, the amount of brake wear, etc.), a demister sensor (e.g., indicating whether the demister has been activated to defog the windshield, rear windshield, or both), a tire pressure sensor (e.g., indicating whether the pressure in each of the tires is within or below the normal range), etc. For example, if the driver turns on the wiper blades, the demister, or both, the determination module 126 may determine that the driver has less than ideal visibility and take the reduced visibility into account when determining the probability 127. If the tire pressure sensor indicates that one or more of the tires has a pressure below the normal range (e.g., recommended by the manufacturer of the vehicle 102), the determination module 126 may take that into account when determining the probability 127. For example, if at least one of the tires has a lower than normal pressure and the vehicle 102 is traveling at a certain speed, the decision module 126 may predict that the probability 127 of the vehicle 102 being involved in an accident is higher compared to when all of the tires have normal pressure. The brake sensor may indicate the temperature of the brakes. For example, frequent braking may cause the brake temperature to be high. Thus, a relatively high brake temperature may indicate that the driver of the vehicle 102 is aggressively driving or traveling too fast, frequently using the brakes to slow down to avoid a collision with a vehicle in front or to slow down for an upcoming road curve.

[0044] The vehicle 102 (e.g., a type of user equipment) may include a memory 218, one or more processors 220, and a transceiver 140 for receiving cellular signals, such as LTE, GSM, CDMA, WCDMA, 5G, etc., and short range communication signals, such as WLAN, Bluetooth, UWB, or other short range communication signals. The vehicle 102 may include a satellite positioning system (SPS) 138 for receiving positioning signals 134 (e.g., GPS, GNSS, etc.) of FIG. 1 from a positioning signal source 136.

[0045] Thus, a call control module in the vehicle may use sensor data from various sensors in the vehicle to determine the probability that the vehicle will be involved in an accident in the near future (e.g., within the next 300 seconds). The sensor data may include the vehicle's current location, map details (e.g., posted speed limits, curves in the road, amount of curvature of each curve, etc.), accelerometer data, gyroscope data, data from temperature sensors, data from rain sensors, data from C-V2X sensors, and data from vehicle sensors (e.g., vehicle speed, engine temperature, brake temperature, are the wipers on or off, one or more demisters on or off, tire pressure, etc.), other sensor data, or any combination thereof.

[0046] 3 illustrates an example process 300 for training a machine learning algorithm according to various aspects of the disclosure. The process 300 may be performed by a manufacturer of the vehicle 102 prior to making the vehicle 102 available for acquisition (e.g., purchase or lease).

[0047] At 302, a machine learning algorithm (e.g., software code) may be generated by one or more software designers. At 304, the machine learning algorithm may be trained using pre-classified training data 306. For example, the training data 306 may be pre-classified by a human, by machine learning, or a combination of both. After the machine learning is trained using the pre-classified training data 306, the machine learning may be tested at 308 using test data 310 to determine the accuracy of the machine learning. For example, in the case of a classifier (e.g., a support vector machine), the accuracy of the classification may be determined using the test data 310.

[0048] If the accuracy of the machine learning does not meet the desired accuracy at 308 (e.g., 95%, 98%, 99% accurate), the machine learning code may be adjusted at 312 to achieve the desired accuracy. For example, a software designer may modify the machine learning software code to improve the accuracy of the machine learning algorithm at 312. After the machine learning is adjusted at 312, the machine learning may be retrained at 304 using the pre-classified training data 306. In this manner, 304, 308, 312 may be repeated until the machine learning can classify the test data 310 with the desired accuracy.

[0049] After determining at 308 that the accuracy of the machine learning meets the desired accuracy, the process may proceed to 314 where validation data 316 may be used to validate the accuracy of the machine learning. After the accuracy of the machine learning is validated at 314, the trained machine learning 202 that was trained to provide a particular level of accuracy may be used by the decision module 126.

[0050] The pre-classified training data 306, testing data 310, and validation data 316 may include data associated with vehicle accidents. For example, each vehicle accident may include associated data such as, for example, weather conditions, road type, vehicle speed, vehicle sensor data, traffic density, etc.

[0051] In the flow diagrams of Figures 4 and 5, each block represents one or more operations that may be implemented in hardware, software, or a combination thereof. In the context of software, the blocks represent computer-executable instructions that, when executed by one or more processors, cause the processors to perform the described operations. Generally, computer-executable instructions include routines, programs, objects, modules, components, data structures, etc. that perform particular functions or implement particular abstract data types. The order in which the blocks are described is not intended to be construed as limiting, and any number of the described operations may be combined in any order and / or in parallel to implement a process. For illustrative purposes, the processors 400 and 500 are described with reference to Figures 1, 2, and 3 as described above, although other models, frameworks, systems, and environments may be used to implement these processes.

[0052] 4 illustrates an example process 400 that includes determining that a low-capability subscription cannot access a network at a current location of a vehicle based on a low-capability subscription, according to aspects of the disclosure. Process 400 may be performed by one or more components of the vehicle (e.g., user equipment), such as the call control module 120 or the DSDA modem 108 of FIGS. 1 and 2.

[0053] At 402, process 400 determines that the vehicle's original equipment manufacturer (OEM) subscription is set to a low-capability subscription. For example, in FIG. 2, call control module 120 may determine that OEM subscription 118 is associated with low-capability subscription 114.

[0054] At 404, process 400 may determine that the low-capability subscription is unable to access a network at the current location of the vehicle. For example, in FIG. 2, the call control module 120 may determine that the low-capability subscription 114 is unable to access a network at the current location of the vehicle 102.

[0055] At 406, process 400 may determine a probability that the vehicle will experience an accident based on sensor data received from one or more sensors of the vehicle. At 408, process 400 may determine that the probability meets a threshold. At 410, process 400 may automatically (e.g., without human intervention) switch the OEM subscription from a low-capacity subscription to a high-capacity subscription. For example, in FIG. 2, call control module 120 receives sensor data 124 from sensor 122 and uses determination module 126 to determine a probability 127 that vehicle 102 will be involved in an accident within a particular time period (e.g., within the next five minutes) based on sensor data 124. If the decision module 126 determines that the probability 127 meets the threshold 128, e.g., there is a high probability that the vehicle 102 will be involved in an accident in the near future (e.g., the probability 127 ≧ 75%, 80%, 90%, 95%, etc.), the call control module 120 automatically (e.g., without human intervention) switches the OEM subscription 118 from the low-capability subscription 114 to the high-capability subscription 116.

[0056] Thus, one or more components, such as a call control module in the vehicle, may determine that the vehicle's OEM subscription is set to a low-capability subscription, determine that the low-capability subscription cannot access a network at the vehicle's current location, determine (e.g., based on sensor data) that a probability that the vehicle will experience an accident meets a threshold, and automatically switch the OEM subscription from the low-capability subscription to a high-capability subscription. As will be appreciated, technical advantages of process 400 include enabling a vehicle to access one or more networks via a high-capability subscription, thereby enabling the vehicle to initiate an eCall to emergency services if the vehicle is involved in an accident.

[0057] 5 illustrates an example process 500 that includes determining a probability of an accident according to an embodiment of the present disclosure. The process 500 may be performed by one or more components of a vehicle, such as the call control module 120 or the DSDA modem 108 of FIGS. 1 and 2.

[0058] At 502, process 500 determines whether the OEM subscription ("sub") is set to a low capability subscription. If process 500 determines that the OEM subscription is not set to a low capability subscription (e.g., the OEM subscription is set to a high capability subscription), process 500 ends. If process 500 determines that the OEM subscription is set to a low capability subscription, process 500 proceeds to 504. For example, in FIG. 2, call control module 120 determines whether OEM subscription 118 is associated with low capability subscription 114 or high capability subscription 116. If call control module 120 determines that OEM subscription 118 is associated with high capability subscription 116, call control module 120 takes no further action.

[0059] At 504, the process 500 determines which networks are available for the currently configured OEM subscription (low capability subscription). At 506, the process 500 determines whether at least one network is currently accessible. If the process 500 determines at 506 that at least one network is currently accessible to the OEM subscription, the process 500 returns to 504. If the process 500 determines at 506 that no networks are currently accessible to the OEM subscription, the process 500 proceeds to 508. For example, in FIG. 2, if the call control module 120 determines that the OEM subscription 118 is associated with the low capability subscription 114, the call control module 120 determines which networks are currently accessible (e.g., at the current location of the vehicle 102). If the call control module 120 determines that at least one network is currently available via the OEM subscription 118, the call control module 120 continues to monitor which networks are accessible as the location of the vehicle 102 changes. If the call control module 120 determines that no networks are currently accessible via the OEM subscription 118 , the process proceeds to 508 .

[0060] At 508, process 500 obtains sensor data from one or more sensors. At 510, process 500 determines a probability that an accident will occur (e.g., within a particular time period, such as within the next 5 minutes) based on the sensor data. At 512, process 500 determines whether the probability meets a threshold. If process 500 determines at 512 that the probability does not meet the threshold, the process proceeds to 516. If process 500 determines at 516 that the timer has expired, process 500 switches the OEM subscription to a low-capacity subscription. If process 500 determines that the timer has not expired, process 500 does not take any action with respect to the OEM subscription. After 516, process 500 returns to 504. For example, in FIG. 2 , the call control module 120 receives sensor data 124 from the sensor 122 and uses a determination module 126 to determine a probability 127 that the vehicle 102 will be involved in an accident within a certain time period (e.g., within the next 5 minutes) based on the sensor data 124. The determination module 126 determines whether the probability 127 meets a threshold 128. If the determination module 126 determines that the probability 127 fails to meet the threshold 128, the determination module 126 checks to see if a timer 130 has expired. If the timer 130 has expired, the determination module 126 switches the OEM subscription 118 back to the low-capability subscription 114. If the timer 130 has not expired, the determination module retains the OEM subscription 118 associated with the high-capability subscription 116. The call control module 120 then determines the networks currently accessible to the OEM subscription 118 at the current location of the vehicle 102.

[0061] If at 512, the process 500 determines that the probability meets the threshold, the process 500 proceeds to 514. At 514, the process 500 automatically (e.g., without human intervention) switches the OEM subscription (e.g., from the low-capacity subscription) to the high-capacity subscription, sets a timer (e.g., a hysteresis timer), and returns to 504. For example, in FIG. 2, if the determination module 126 determines that the probability 127 meets the threshold 128, e.g., there is a high probability that the vehicle 102 will be involved in an accident in the near future (e.g., the probability 127≧75%, 80%, 90%, 95%, etc.), the call control module 120 automatically switches the OEM subscription 118 from the low-capacity subscription 114 to the high-capacity subscription 116. The call control module 120 then determines the networks currently accessible to the OEM subscription 118 at the current location of the vehicle 102.

[0062] Thus, the call control module in the vehicle may determine whether the OEM subscription is set to a low-capability subscription or a high-capability subscription. If the OEM subscription is set to a low-capability subscription, the call control module monitors which networks are available for the OEM subscription at the vehicle's current location. If neither network is available for the OEM subscription, the call control module monitors the sensor data to determine the probability that the vehicle will be involved in an accident in the near future. If the sensor data indicates a high probability that the vehicle will be involved in an accident in the near future, the call control module automatically switches the OEM subscription from the low-capability subscription to the high-capability subscription. In this way, in the event of an accident, the vehicle can automatically originate an eCall to the PSAP using the OEM subscription switched to the high-capability subscription because the high-capability subscription provides access to more networks compared to the low-capability subscription. To prevent the call control module from rapidly switching the OEM subscription back and forth between the low-capability subscription and the high-capability subscription, a timer is set after the call control module switches the OEM subscription to the high-capability subscription.

[0063] 6 illustrates an example of a user equipment (UE) 600 that may be used to implement the systems, techniques, and processes described herein. For example, the vehicle 102 of FIGS. 1 and 2 may include at least a portion of the user equipment 600.

[0064] The UE 600 may include one or more processors 602 (e.g., central processing unit (CPU), graphics processing unit (GPU), etc.), memory 604, a communication interface 606 (including a transceiver 140), a display device 608, other input / output (I / O) devices 610 (e.g., a keyboard, a trackball, etc.), and one or more mass storage devices 612 (e.g., disk drives, solid-state disk drives, etc.) configured to communicate with each other, for example, via one or more system buses 614 or other suitable connections. Although a single system bus 614 is shown for ease of understanding, it should be understood that the system bus 614 may include multiple buses, such as a memory device bus, a storage device bus (e.g., Serial Advanced Technology Attachment (SATA), etc.), a data bus (e.g., Universal Serial Bus (USB), etc.), a video signal bus (e.g., ThunderBolt®, Digital Video Interface (DVI), High Definition Media Interface (HDMI®), etc.), a power bus, etc.

[0065] The processor 602 is one or more hardware devices that may include a single processing unit or several processing units, all of which may include a single or multiple computing units or multiple cores. The processor 602 may include a graphics processing unit (GPU) integrated into the CPU, or the GPU may be a processor device separate from the CPU. The processor 602 may be implemented as one or more microprocessors, microcomputers, microcontrollers, digital signal processors, central processing units, graphics processing units, state machines, logic circuits, and / or any device that manipulates signals based on operational instructions. Among other capabilities, the processor 602 may be configured to fetch and execute computer-readable instructions stored in the memory 604, the mass storage device 612, or other computer-readable medium.

[0066] The memory 604 and the mass storage device 612 are examples of computer storage media (e.g., memory storage devices) for storing instructions that may be executed by the processor 602 to perform various functions described herein. For example, the memory 604 may include both volatile and non-volatile memory (e.g., RAM, ROM, etc.) devices. Additionally, the mass storage device 612 may include hard disk drives, solid state drives, removable media including external removable drives, memory cards, flash memory, floppy disks, optical disks (e.g., compact disks (CDs), digital video disks (DVDs)), storage arrays, network attached storage, storage area networks, etc. Both the memory 604 and the mass storage device 612 may be collectively referred to herein as memory or computer storage media, and may be any type of non-transitory medium capable of storing computer-readable, processor-executable program instructions as computer program code that may be executed by the processor 602 as a particular machine configured to perform the operations and functions described in the implementations herein.

[0067] The UE 600 may include one or more communication interfaces 606 for exchanging data. The communication interface 606 may facilitate communication within a wide variety of network and protocol types, including wired networks such as Ethernet, Data Over Cable Service Interface Specification (DOCSIS), Digital Subscriber Line (DSL), fiber, USB, etc., and wireless networks such as Wireless Local Area Network (WLAN), cellular (e.g., Global System for Mobile Communications (GSM), Code Division Multiple Access (CDMA), 5G, Long Term Evolution (LTE), etc.), short range communications (e.g., 802.11, Bluetooth, Wireless USB, Ultra Wideband (UWB), ZigBee, millimeter (mm) Wave, and other types of short range wireless communications protocols), satellite (Satellite Positioning System (SPS), Global Positioning System (GPS), Global Navigation Satellite System (GNSS), etc.), the Internet, etc. The communications interface 606 may also provide communication with external storage devices such as storage arrays, network attached storage, storage area networks, cloud storage, and the like.

[0068] The display device 608 may be used to display content (e.g., information and images) to a user. The other I / O devices 610 may be devices that receive various inputs from and provide various outputs to a user, and may include a keyboard, a touchpad, a mouse, a printer, audio input / output devices, etc.

[0069] Computer storage media, such as memory 616 and mass storage device 612, may be used to store software and data. For example, the computer storage media may be used to store OEM subscription 118, call control module 120, DSDA modem 108, low capability subscription 114, high capability subscription 116, additional applications 418, and additional data 420.

[0070] 7A and 7B, several example components (represented by corresponding blocks) that may be incorporated in a UE (e.g., vehicle 102 of FIG. 1), a base station (which may correspond to any of the base stations described herein), and a network entity (which may correspond to or embody any of the network functions described herein) to support file transmission operations are shown. It will be understood that these components may be implemented in different types of devices in different implementations (e.g., in an ASIC, in a system on a chip (SoC), etc.). The illustrated components may also be incorporated in other devices in a communication system. For example, other devices in the system may include components similar to the illustrated components to provide similar functionality. Also, a given device may include one or more of the components. For example, a device may include multiple transceiver components that enable the device to operate on multiple carriers and / or communicate via different technologies.

[0071] A UE, a base station, or a network entity may include a wireless wide area network (WWAN) transceiver 710 and 750 (e.g., transceiver 140 of FIG. 1, FIG. 2, and FIG. 6), respectively, configured to communicate over one or more wireless communications networks (not shown), such as an NR network, an LTE network, a GSM network, etc. The WWAN transceivers 710 and 750 may be connected to one or more antennas 716 and 756, respectively, to communicate with other network nodes, such as other UEs, access points, base stations (e.g., eNBs, gNBs), etc., over at least one designated RAT (e.g., NR, LTE, GSM, etc.) over a wireless communications medium of interest (e.g., some set of time / frequency resources in a particular frequency spectrum). The WWAN transceivers 710 and 750 may be variously configured to transmit and encode signals 718 and 758 (e.g., messages, instructions, information, etc.), respectively, and conversely, to receive and decode signals 718 and 758 (e.g., messages, instructions, information, pilots, etc.), respectively, in accordance with the designated RAT. Specifically, transceivers 710 and 750 include one or more transmitters 714 and 754, respectively, for transmitting and encoding signals 718 and 758, respectively, and include one or more receivers 712 and 752, respectively, for receiving and decoding signals 718 and 758, respectively.

[0072] The UE and base station also, at least in some cases, include wireless local area network (WLAN) transceivers 720 and 760, respectively. The WLAN transceivers 720 and 760 may be connected to one or more antennas 726 and 766, respectively, for communicating with other network nodes, such as other UEs, access points, base stations, etc., via at least one designated RAT (e.g., WiFi, LTE-D, Bluetooth, etc.) over a wireless communication medium of interest. The WLAN transceivers 720 and 760 may be variously configured to transmit and encode signals 728 and 768, respectively (e.g., messages, instructions, information, etc.), and conversely, to receive and decode signals 728 and 768, respectively (e.g., messages, instructions, information, pilots, etc.), in accordance with the designated RAT. Specifically, transceivers 720 and 760 include one or more transmitters 724 and 764, respectively, for transmitting and encoding signals 728 and 768, respectively, and include one or more receivers 722 and 762, respectively, for receiving and decoding signals 728 and 768, respectively.

[0073] The transceiver circuitry including at least one transmitter and at least one receiver may in some implementations comprise an integrated device (e.g., embodied as transmitter and receiver circuitry of a single communications device), in some implementations comprise separate transmitter devices and separate receiver devices, or in other implementations may be embodied in other manners. In an aspect, the transmitter may include or be coupled to multiple antennas such as an antenna array (e.g., antennas 716, 726, 756, 766) that enable the respective devices to perform transmit "beamforming" as described herein. Similarly, the receiver may include or be coupled to multiple antennas such as an antenna array (e.g., antennas 716, 726, 756, 766) that enable the respective devices to perform receive beamforming as described herein. In an aspect, the transmitters and receivers may share the same multiple antennas (e.g., antennas 716, 726, 756, 766) such that each device can only receive or transmit at a given time, but not both at the same time. The UE and / or base station wireless communication devices (e.g., one or both of the transceivers 710 and 720 and / or 750 and 760) may also comprise a network listen module (NLM), etc. for performing various measurements.

[0074] The UE and / or base station may, at least in some cases, include satellite positioning system (SPS) receivers 730 and 770 (e.g., SPS 138 of FIGS. 1, 2, and 6). The SPS receivers 730 and 770 may be connected to one or more antennas 736 and 776, respectively, for receiving SPS signals 738 and 778, respectively, such as Global Positioning System (GPS) signals, Global Navigation Satellite System (GLONASS) signals, Galileo signals, Beidou signals, Navigation Satellite System of India (NAVIC), Quasi-Zenith Satellite System (QZSS), etc. The SPS receivers 730 and 770 may comprise any suitable hardware and / or software for receiving and processing the SPS signals 738 and 778, respectively. The SPS receivers 730 and 770 appropriately request information and actions from other systems and perform the necessary calculations to determine the position of the UE and base station using measurements obtained by any suitable SPS algorithms.

[0075] The base station and the network entities may each include at least one network interface 780 for communicating with other network entities. For example, the network interface 780 (e.g., one or more network access ports) may be configured to communicate with one or more network entities via a wire-based or wireless backhaul connection. In some aspects, the network interface 780 may be implemented as a transceiver configured to support wire-based or wireless signal communication. This communication may involve, for example, transmitting and receiving messages, parameters, and / or other types of information.

[0076] The UE, base station, and network entities may include other components that may be used in conjunction with operations as disclosed herein. The UE may include processor circuitry implementing a processing system 732, for example, for providing functionality related to RF sensing and for providing other processing functions. The base station may include a processing system 784, for example, for providing functionality related to RF sensing as disclosed herein and for providing other processing functions. The network entities may include processing systems, for example, for providing functionality related to Wi-Fi positioning or RF sensing as disclosed herein and for providing other processing functions. In an aspect, the processing systems 732, 784 may include, for example, one or more general-purpose processors, multi-core processors, ASICs, digital signal processors (DSPs), field programmable gate arrays (FPGAs), or other programmable logic devices or processing circuits.

[0077] The UE, base station, and network entity may include memory circuitry implementing memory components 740, 786 (e.g., each including a memory device) for maintaining information (e.g., information indicative of reserved resources, thresholds, parameters, etc.). In some cases, the UE, base station, and network entity may include positioning components 742, 788, respectively. The positioning components 742, 788 may be hardware circuits that are part of or coupled to the processing systems 732, 784, respectively, that, when executed, cause the UE, base station, and network entity to perform the functions described herein. In other aspects, the positioning components 742, 788 may be external to the processing systems 732, 784 (e.g., may be part of a modem processing system, may be integrated with another processing system, etc.). Alternatively, the positioning components 742, 788 may be memory modules (as shown in FIGS. 7A, 7B) stored in memory components 740, 786, respectively, that when executed by the processing systems 732, 784 (or a modem processing system, another processing system, etc.) cause the UE, base station, and network entities to perform the functionality described herein.

[0078] The UE may include one or more sensors 744 coupled to the processing system 732 to provide motion and / or orientation information independent of motion data derived from signals received by the WWAN transceiver 710, the WLAN transceiver 720, and / or the SPS receiver 730. By way of example, the sensors 744 may include an accelerometer (e.g., a microelectromechanical system (MEMS) device), a gyroscope, a geomagnetic sensor (e.g., a compass), an altimeter (e.g., a barometric altimeter), and / or any other type of motion detection sensor. Additionally, the sensors 744 may include multiple different types of devices and combine their outputs to provide motion information. For example, the sensors 744 may use a combination of a multi-axis accelerometer and an orientation sensor to provide the ability to calculate location in a 2D and / or 3D coordinate system.

[0079] Additionally, the UE may include a user interface 746 for providing instructions (e.g., audible and / or visual instructions) to a user and / or receiving user input (e.g., upon user actuation of a sensing device such as a keypad, touch screen, microphone, etc.) Although not shown, base stations and network entities may also include user interfaces.

[0080] Referring more particularly to the processing system 784, on the downlink, IP packets from a network entity may be provided to the processing system 784. The processing system 784 may implement functionality for an RRC layer, a Packet Data Convergence Protocol (PDCP) layer, a Radio Link Control (RLC) layer, and a Medium Access Control (MAC) layer. The processing system 784 may provide RRC layer functions related to broadcasting of system information (e.g., Master Information Block (MIB), System Information Block (SIB)), RRC connection control (e.g., RRC connection paging, RRC connection establishment, RRC connection modification, and RRC connection release), inter-RAT mobility, and measurement configuration for UE measurement reporting; PDCP layer functions related to header compression / decompression, security (encryption, decryption, integrity protection, integrity verification), and handover support functions; RLC layer functions related to transfer of upper layer packet data units (PDUs), error correction through automatic repeat request (ARQ), concatenation, segmentation, and reassembly of RLC service data units (SDUs), resegmentation of RLC data PDUs, and reordering of RLC data PDUs; and MAC layer functions related to mapping between logical channels and transport channels, scheduling information reporting, error correction, priority handling, and logical channel prioritization.

[0081] The transmitter 754 and receiver 752 may implement Layer 1 functions associated with various signal processing functions. Layer 1, including the physical (PHY) layer, may include error detection on the transport channel, forward error correction (FEC) coding / decoding of the transport channel, interleaving, rate matching, mapping onto the physical channel, modulation / demodulation of the physical channel, and MIMO antenna processing. The transmitter 754 handles mapping to signal constellations based on various modulation schemes (e.g., binary phase shift keying (BPSK), quadrature phase shift keying (QPSK), M-phase shift keying (M-PSK), M-quadrature amplitude modulation (M-QAM)). The coded and modulated symbols may then be split into parallel streams. Each stream may then be mapped to an orthogonal frequency division multiplexing (OFDM) subcarrier, multiplexed with a reference signal (e.g., pilot) in the time and / or frequency domain, and then combined together using an inverse fast Fourier transform (IFFT) to generate a physical channel carrying a time-domain OFDM symbol stream. The OFDM symbol stream is spatially precoded to generate multiple spatial streams. Channel estimates from a channel estimator may be used to determine the coding and modulation scheme, as well as for spatial processing. The channel estimates may be derived from a reference signal and / or channel condition feedback transmitted by the UE. Each spatial stream may then be provided to one or more different antennas 756. The transmitter 754 may modulate an RF carrier with each spatial stream for transmission.

[0082] At the UE, the receiver 712 receives the signal through its respective antenna 716. The receiver 712 recovers the information demodulated onto the RF carrier and provides the information to the processing system 732. The transmitter 714 and the receiver 712 implement Layer 1 functions associated with various signal processing functions. The receiver 712 may perform spatial processing on the information to recover any spatial streams destined for the UE. If multiple spatial streams are destined for the UE, they may be combined by the receiver 712 into a single OFDM symbol stream. The receiver 712 then converts the OFDM symbol stream from the time domain to the frequency domain using a Fast Fourier Transform (FFT). The frequency domain signal includes a separate OFDM symbol stream for each subcarrier of the OFDM signal. The symbols on each subcarrier, as well as the reference signal, are recovered and demodulated by determining the most likely signal constellation point transmitted by the base station. These soft decisions may be based on channel estimates calculated by a channel estimator. The soft decisions are then decoded and deinterleaved to recover the data and control signals originally transmitted by the base station on the physical channel. The data and control signals are then provided to a processing system 732 that implements Layer 3 and Layer 2 functions.

[0083] In the uplink, the processing system 732 performs demultiplexing between transport and logical channels, packet reassembly, decryption, header decompression, and control signal processing to recover IP packets from the core network. The processing system 732 is also responsible for error detection.

[0084] Similar to the functionality described with respect to downlink transmissions by the base station, the processing system 732 provides RRC layer functionality related to system information (e.g., MIBs, SIBs) acquisition, RRC connection, and measurement reporting; PDCP layer functionality related to header compression / decompression and security (encryption, decryption, integrity protection, integrity verification); RLC layer functionality related to transfer of upper layer PDUs, error correction via ARQ, concatenation, segmentation, and reassembly of RLC SDUs, resegmentation of RLC data PDUs, and reordering of RLC data PDUs; and MAC layer functionality related to mapping between logical channels and transport channels, multiplexing of MAC SDUs onto transport blocks (TBs), demultiplexing of MAC SDUs from TBs, scheduling information reporting, error correction via hybrid automatic repeat request (HARQ), priority handling, and logical channel prioritization.

[0085] Channel estimates derived by the channel estimator from a reference signal or feedback transmitted by the base station may be used by the transmitter 714 to select an appropriate coding and modulation scheme and to facilitate spatial processing. The spatial streams generated by the transmitter 714 may be provided to different antennas 716. The transmitter 714 may modulate an RF carrier with each spatial stream for transmission.

[0086] The uplink transmission is processed at the base station in a manner similar to that described for the receiver function at the UE. The receiver 752 receives the signal through its respective antenna 756. The receiver 752 recovers the information demodulated onto the RF carrier and provides the information to a processing system 784.

[0087] In the uplink, the processing system 784 performs demultiplexing between transport and logical channels, packet reassembly, decryption, header decompression, and control signal processing to recover IP packets from the UE. The IP packets from the processing system 784 may be provided to the core network. The processing system 784 is also responsible for error detection.

[0088] For convenience, the UE, base station, and / or network entities are illustrated in Figures 7A-7B as including various components that may be configured in accordance with various examples described herein, however, it will be understood that the illustrated blocks may have different functions in different designs.

[0089] The various components of the UE, base station, and network entity may communicate with each other via data buses 734, 782, respectively. The components of FIG. 7A, 7B may be implemented in various ways. In some implementations, the components of FIG. 7A, 7B may be implemented in one or more circuits, such as, for example, one or more processors and / or one or more ASICs (which may include one or more processors). Here, each circuit may use and / or incorporate at least one memory component for storing information or executable code used by the circuit to provide this functionality. For example, some or all of the functionality represented by blocks 710-746 may be implemented by the processor and memory components of the UE (e.g., by execution of appropriate code and / or by appropriate configuration of the processor components). Similarly, some or all of the functionality represented by blocks 750-788 may be implemented by the processor and memory components of the base station (e.g., by execution of appropriate code and / or by appropriate configuration of the processor components). For simplicity, various operations, acts, and / or functions are described herein as being performed "by a UE," "by a base station," "by a positioning entity," etc. However, it will be understood that such operations, acts, and / or functions may actually be performed by a particular component or combination of components, such as a UE, a base station, a positioning entity, such as processing systems 732, 784, transceivers 710, 720, 750, and 760, memory components 740, 786, positioning components 742, 788, etc.

[0090] It should be understood that any reference to an element herein using a designation such as "first," "second," etc., does not generally limit the quantity or order of those elements. Rather, these designations may be used herein as a convenient way of distinguishing between two or more elements or instances of an element. Thus, reference to a first element and a second element does not imply that only two elements may be employed therein, or that the first element must precede the second element in some manner. Also, unless otherwise stated, a set of elements may comprise one or more elements. In addition, a term of the form "at least one of A, B, or C" or "one or more of A, B, or C" or "at least one of the group consisting of A, B, and C" as used in this description or claims means "A or B or C or any combination of these elements." For example, the term may include A, or B, or C, or A and B, or A and C, or A and B and C, or 2A, or 2B, or 2C, etc.

[0091] In view of the above description and explanation, those skilled in the art will appreciate that the various exemplary logic blocks, modules, circuits, and algorithm steps described in connection with the aspects disclosed herein may be implemented as electronic hardware, computer software, or a combination of both. To clearly illustrate this interchangeability of hardware and software, various exemplary components, blocks, modules, circuits, and steps have been described above generally in terms of their functionality. Whether such functionality is implemented as hardware or software depends on the particular application and design constraints imposed on the overall system. Those skilled in the art may implement the described functionality in various ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present disclosure.

[0092] Thus, for example, it will be appreciated that a device or any component of a device may be configured (or enabled or adapted) to provide functionality as taught herein. This may be accomplished, for example, by manufacturing (e.g., fabricating) the device or component to provide the functionality, by programming the device or component to provide the functionality, or through the use of some other suitable implementation technique. As one example, an integrated circuit may be fabricated to provide the requisite functionality. As another example, an integrated circuit may be fabricated to support the requisite functionality and then configured (e.g., via programming) to provide the requisite functionality. As yet another example, a processor circuit may execute code to provide the requisite functionality.

[0093] Moreover, the methods, sequences, and / or algorithms described in connection with the aspects disclosed herein may be embodied directly in hardware, in a software module executed by a processor, or in a combination of the two. The software module may reside in a random access memory (RAM), a flash memory, a read only memory (ROM), an erasable programmable ROM (EPROM), an electrically erasable programmable ROM (EEPROM), a register, a hard disk, a removable disk, an optical disk, or any other form of storage medium known in the art. An exemplary storage medium is coupled to the processor such that the processor can read information from and write information to the storage medium. Alternatively, the storage medium may be integral to the processor (e.g., a cache memory).

[0094] In the above detailed description, it is seen that various features are grouped together in the examples. This manner of disclosure should not be understood as an intention that the exemplary clauses have more features than are expressly stated in each clause. Rather, various aspects of the disclosure may include fewer than all features of each disclosed exemplary clause. Thus, the following clauses should be considered to be incorporated in the description, and each clause may stand alone as a separate example. Although each dependent clause may refer to a specific combination with one of the other clauses in the clause, the aspects of that dependent clause are not limited to that specific combination. It will be understood that other exemplary clauses may also include combinations of aspects of the dependent clause with the subject matter of any other dependent clause or independent clause, or combinations of any features with other dependent clauses and independent clauses. Unless a specific combination is not intended (e.g., conflicting aspects such as defining an element as both an insulator and a conductor) is expressly expressed or can be easily inferred, the various aspects disclosed herein expressly include these combinations. It is further intended that aspects of a clause may be included in any other independent clause, even if the clause is not directly dependent on the independent clause. Example implementations are described in the following numbered clauses.

[0095] Clause 1. A method comprising: determining, by a processor of the vehicle, that an original equipment manufacturer (OEM) subscription of the vehicle is set to a low-capacity subscription; determining, by the processor, that the low-capacity subscription is unable to access a network at the vehicle's current location based on the low-capacity subscription; determining, by the processor and based on sensor data received from one or more sensors of the vehicle, a probability that an accident will occur to the vehicle; determining, by the processor, that the probability meets a threshold; and switching, by the processor, the OEM subscription from the low-capacity subscription to a high-capacity subscription.

[0096] Clause 2. The method of clause 1, further comprising the steps of determining that an accident has occurred in the vehicle and initiating an emergency call (eCall) to a public safety answering point (PSAP).

[0097] Clause 3. The method of any one of clauses 1 to 2, wherein the step of determining the probability that an accident will occur in the vehicle based on sensor data received from one or more sensors of the vehicle comprises the steps of receiving sensor data from the one or more sensors and using a machine learning algorithm to determine the probability that an accident will occur in the vehicle based on the sensor data.

[0098] Clause 4. The method of any one of clauses 1 to 3, further comprising: setting a timer; determining a second probability based on second sensor data received from one or more sensors of the vehicle; determining that the second probability fails to satisfy a threshold; and switching the OEM subscription from a high-capability subscription to a low-capability subscription in response to determining that the timer has expired.

[0099] Clause 5. The method of any one of clauses 1 to 4, wherein a higher capacity subscription provides access to a particular network that a lower capacity subscription cannot access.

[0100] Clause 6. The method of clause 5, wherein the particular network includes one of a Long Term Evolution (LTE) network, a Global System for Mobile Communications (GSM) network, a Code Division Multiple Access (CDMA) network, a Wideband Code Division Multiple Access (WCDMA) network, or a 5G New Radio (NR) radio access technology (RAT) network.

[0101] Clause 7. The method of any one of clauses 1 to 6, wherein determining the probability that the vehicle will have an accident based on sensor data received from one or more sensors of the vehicle includes at least one of the following steps: determining that the vehicle speed exceeds the posted limit for a road on which the vehicle is traveling; determining that the vehicle is traveling in severe weather including at least one of rain, sleet, snow or fog; determining that at least one of the gyroscope data or accelerometer data indicates reckless driving; or determining that Cellular Vehicle-to-Everything (C-V2X) data indicates a relatively high traffic density around the vehicle.

[0102] Clause 8. The method of any one of clauses 1 to 7, further comprising the steps of determining an estimated time of arrival at a destination programmed into the vehicle's navigation system, and setting a timer based in part on the difference between the estimated time of arrival and a current time.

[0103] Clause 9. The method of any one of clauses 1 to 8, further comprising determining a destination programmed into a navigation system of the vehicle, determining an amount of time that severe weather is expected to be encountered en route to the destination, and setting a timer based at least in part on the amount of time.

[0104] Clause 10. The method of any one of clauses 1 to 9, further comprising determining a destination programmed into a navigation system of the vehicle, determining an estimate of the time that will be spent navigating one or more curves en route to the destination, and setting a timer based at least in part on the estimate of time.

[0105] While the above disclosure sets forth various exemplary aspects, it should be noted that various changes and modifications may be made to the illustrated examples without departing from the scope defined by the appended claims. The present disclosure is not intended to be limited to only the specifically illustrated examples. For example, unless otherwise stated, the functions, steps, and / or actions of the method claims according to the aspects of the present disclosure described herein need not be performed in any particular order. Furthermore, although some aspects may be described or claimed in the singular, the plural is contemplated unless limitation to the singular is explicitly stated. [Explanation of symbols]

[0106] 100 Systems 102 vehicles 104 Public Safety Answering Point (PSAP) 106 Network 108 Dual SIM Dual Active (DSDA) modem 110 SIM1 112 SIM2 114 Low-Capacity Subscription 116 High-Capacity Subscription 118 Original Equipment Manufacturer (OEM) Subscription 120 Call Control Module 122 Sensors 124 Sensor Data 126 Decision Module 127 Probability 128 Threshold 130 Timer 132 Emergency call (eCall) 133 Special Report 134 Positioning Signal 136 Positioning signal source 138 Satellite Positioning System (SPS) 140 Transceiver 200 Vehicle-Based Systems 202 Machine Learning 204 Camera 206 Map Details 208 Accelerometer 210 Gyroscope 212 Weather Sensor 216 Vehicle Sensor 218 Memory 220 Processor 226 Inertial Measurement Unit (IMU) 228 Short Range Communications 230 Magnetometer 232 Light Detection and Ranging (LIDAR) 300 processes 306 pre-classified training data 310 Test Data 316 Validation Data 400 processes 418 Additional Applications 420 Additional Data 500 processes 600 User Equipment (UE) 602 Processor 604 Memory 606 Communication Interface 608 Display Devices 610 Input / Output (I / O) Devices 612 Mass Storage Device 614 System Bus 616 Memory 710 Wireless Wide Area Network (WWAN) Transceiver 712 Receiver 714 Transmitter 716 Antenna 718 Signal 720 WLAN Transceiver 722 Receiver 724 Transmitter 726 Antenna 728 signal 730 SPS Receiver 732 Processing System 734 Data Bus 736 Antenna 738 SPS signal 740 Memory Components 742 Positioning Component 744 Sensors 746 User Interface 750 Wireless Wide Area Network (WWAN) Transceiver 752 Receiver 754 Transmitter 756 Antenna 758 signal 760 WLAN Transceiver 762 Receiver 764 Transmitter 766 Antenna 768 signal 770 SPS Receiver 776 Antenna 778 SPS signal 780 Network Interface 782 Data Bus 784 Processing System 786 Memory Components 788 Positioning Component

Claims

1. 1. A method comprising: determining, by a processor of a vehicle, that an original equipment manufacturer (OEM) subscription for said vehicle is set to a low capacity subscription; determining, by the processor, that the low capacity subscription is unable to access a network at a current location of the vehicle based on the low capacity subscription; determining, by the processor and based on sensor data received from one or more sensors of the vehicle, a probability that an accident will occur to the vehicle; determining, by the processor, that the probability satisfies a threshold; switching, by the processor, the OEM subscription from the lower capacity subscription to a higher capacity subscription; Including, The method, wherein the higher capacity subscription provides access to a particular network that the lower capacity subscription cannot access.

2. determining that the accident has occurred on the vehicle; Initiating an emergency call (eCall) to a Public Safety Answering Point (PSAP); The method of claim 1, further comprising:

3. determining the probability that the accident will occur on the vehicle based on the sensor data received from the one or more sensors of the vehicle, receiving the sensor data from the one or more sensors; using a machine learning algorithm to determine the probability that the accident will occur to the vehicle based on the sensor data; 2. The method of claim 1, comprising:

4. setting a timer; determining a second probability that the accident will occur to the vehicle based on second sensor data received from the one or more sensors of the vehicle; determining that the second probability fails to satisfy the threshold; in response to determining that the timer has expired, switching the OEM subscription from the higher capacity subscription to the lower capacity subscription; The method of claim 1, further comprising:

5. 10. The method of claim 1, wherein the particular network comprises one of a Long Term Evolution (LTE) network, a Global System for Mobile Communications (GSM) network, a Code Division Multiple Access (CDMA) network, a Wideband Code Division Multiple Access (WCDMA) network, or a 5G New Radio (NR) radio access technology (RAT) network.

6. determining the probability that the accident will occur on the vehicle based on the sensor data received from the one or more sensors of the vehicle, determining whether a vehicle speed exceeds the posted limit for a road along which the vehicle is traveling; determining that the vehicle is traveling in severe weather including at least one of rain, sleet, snow, or fog; determining that at least one of the gyroscope data or the accelerometer data is indicative of reckless driving; or determining that cellular vehicle-to-everything (C-V2X) data indicates a relatively high traffic density around the vehicle; The method of claim 1 , comprising at least one of:

7. determining an estimated time of arrival at a destination programmed into a navigation system of said vehicle; setting the timer based in part on a difference between the estimated arrival time and a current time; 5. The method of claim 4, further comprising:

8. determining a destination programmed into a navigation system of the vehicle; determining an amount of time severe weather is expected to be encountered en route to the destination; setting the timer based at least in part on the amount of time; 5. The method of claim 4, further comprising:

9. determining a destination programmed into a navigation system of the vehicle; determining an estimate of the time spent navigating one or more curves en route to the destination; setting the timer based at least in part on the estimate of the time; 5. The method of claim 4, further comprising:

10. A vehicle, One or more sensors; Memory, A transceiver; a processor communicatively coupled to the memory and the transceiver, A processor configured to perform the method according to any one of claims 1 to 9. A vehicle comprising:

11. A non-transitory computer-readable storage medium for storing instructions executable by one or more processors to perform a method according to any one of claims 1 to 9.

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