The following six applications, including this one, are being filed concurrently and the other five are hereby incorporated by reference in their entirety for all purposes:
1. U.S. patent application Ser. No. 17/404,139, titled “Systems and Methods for Generating Virtual Characters for a Virtual Game”;
2. U.S. patent application Ser. No. 17/404,144, titled “Systems and Methods for Generating Virtual Experiences for a Virtual Game”;
3. U.S. patent application Ser. No. 17/404,152, titled “Systems and Methods for Generating Virtual Encounters in Virtual Games”;
4. U.S. patent application Ser. No. 17/404,158, titled “Systems and Methods for Generating Virtual Maps in Virtual Games”;
5. U.S. patent application Ser. No. 17/404,164, titled “Systems and Methods for Generating Shared Virtual Maps in Virtual Games”; and
6. U.S. patent application Ser. No. 17/404,172, titled “Systems and Methods for Presenting Shared In-Game Objectives in Virtual Games”.
Some embodiments of the present disclosure are directed to presenting shared in-game objectives in a virtual game. More particularly, certain embodiments of the present disclosure provide methods and systems for generating the shared in-game objectives based at least in part upon a shared virtual map. Merely by way of example, the present disclosure has been applied to presenting the shared in-game objectives to virtual characters associated with different users to accomplish in the shared virtual map. But it would be recognized that the present disclosure has much broader range of applicability.
While individuals generally exercise care while operating vehicles, it is still challenging for many vehicle operators to fully appreciate the risks associated with vehicle operations. As such, many vehicle operators may not be readily mindful of reducing such risks. Hence, it is highly desirable to develop new technologies that can increase a vehicle operator's appreciation and awareness of the risks posed by vehicle operation.
Some embodiments of the present disclosure are directed to presenting shared in-game objectives in a virtual game. More particularly, certain embodiments of the present disclosure provide methods and systems for generating the shared in-game objectives based at least in part upon a shared virtual map. Merely by way of example, the present disclosure has been applied to presenting the shared in-game objectives to virtual characters associated with different users to accomplish in the shared virtual map. But it would be recognized that the present disclosure has much broader range of applicability.
According to certain embodiments, a method for presenting one or more in-game objectives in one or more virtual games includes receiving first real-world telematics data associated with one or more prior first real-world vehicle trips made by a first real-world user and determining one or more first real-world driving characteristics based at least in part upon the first real-world telematics data. Also, the method includes receiving second real-world telematics data associated with one or more prior second real-world vehicle trips made by a second real-world user and determining one or more second real-world driving characteristics based at least in part upon the second real-world telematics data. The first real-world user is different from the second real-world user. Further, the method includes generating a shared virtual map based at least in part upon the one or more first real-world driving characteristics and the one or more second real-world driving characteristics. The method then includes processing information associated with the shared virtual map. Additionally, the method includes generating a shared in-game objective based at least in part upon the shared virtual map and presenting the shared in-game objective to a first virtual character and a second virtual character in a virtual game. The first virtual character is associated with the one or more first real-world driving characteristics of the first real-world user while the second virtual character is associated with the one or more second real-world driving characteristics of the second real-world user. The first virtual character and the second virtual character are different. Moreover, the method includes allowing the first virtual character and the second virtual character to accomplish, in the shared virtual map, the shared in-game objective.
According to some embodiments, a computing device for presenting one or more in-game objectives in one or more virtual games includes one or more processors and a memory that stores instructions for execution by the one or more processors. The instructions, when executed, cause the one or more processors to receive first real-world telematics data associated with one or more prior first real-world vehicle trips made by a first real-world user and determine one or more first real-world driving characteristics based at least in part upon the first real-world telematics data. Also, the instructions, when executed, cause the one or more processors to receive second real-world telematics data associated with one or more prior second real-world vehicle trips made by a second real-world user and determine one or more second real-world driving characteristics based at least in part upon the second real-world telematics data. The first real-world user is different from the second real-world user. Further, the instructions, when executed, cause the one or more processors to generate a shared virtual map based at least in part upon the one or more first real-world driving characteristics and the one or more second real-world driving characteristics. The instructions, when executed, then cause the one or more processors to process information associated with the shared virtual map. Additionally, the instructions, when executed, then cause the one or more processors to generate a shared in-game objective based at least in part upon the shared virtual map and present the shared in-game objective to a first virtual character and a second virtual character in a virtual game. The first virtual character is associated with the one or more first real-world driving characteristics of the first real-world user while the second virtual character is associated with the one or more second real-world driving characteristics of the second real-world user. The first virtual character and the second virtual character are different. Moreover, the instructions, when executed, then cause the one or more processors to allow the first virtual character and the second virtual character to accomplish, in the shared virtual map, the shared in-game objective.
According to certain embodiments, a non-transitory computer-readable medium stores instructions for presenting one or more in-game objectives in one or more virtual games. The instructions are executed by one or more processors of a computing device. The non-transitory computer-readable medium includes instructions to receive first real-world telematics data associated with one or more prior first real-world vehicle trips made by a first real-world user and determine one or more first real-world driving characteristics based at least in part upon the first real-world telematics data. Also, the non-transitory computer-readable medium includes instructions to receive second real-world telematics data associated with one or more prior second real-world vehicle trips made by a second real-world user and determine one or more second real-world driving characteristics based at least in part upon the second real-world telematics data. The first real-world user is different from the second real-world user. Further, the non-transitory computer-readable medium includes instructions to generate a shared virtual map based at least in part upon the one or more first real-world driving characteristics and the one or more second real-world driving characteristics. The non-transitory computer-readable medium then includes instructions to process information associated with the shared virtual map. Additionally, the non-transitory computer-readable medium includes instructions to generate a shared in-game objective based at least in part upon the shared virtual map and present the shared in-game objective to a first virtual character and a second virtual character in a virtual game. The first virtual character is associated with the one or more first real-world driving characteristics of the first real-world user while the second virtual character is associated with the one or more second real-world driving characteristics of the second real-world user. The first virtual character and the second virtual character are different. Moreover, the non-transitory computer-readable medium includes instructions to allow the first virtual character and the second virtual character to accomplish, in the shared virtual map, the shared in-game objective.
Depending upon the embodiment, one or more benefits may be achieved. These benefits and various additional objects, features and advantages of the present disclosure can be fully appreciated with reference to the detailed description and accompanying drawings that follow.
Some embodiments of the present disclosure are directed to presenting shared in-game objectives in a virtual game. More particularly, certain embodiments of the present disclosure provide methods and systems for generating the shared in-game objectives based at least in part upon a shared virtual map. Merely by way of example, the present disclosure has been applied to presenting the shared in-game objectives to virtual characters associated with different users to accomplish in the shared virtual map. But it would be recognized that the present disclosure has much broader range of applicability.
At the process 110, first real-world telematics data associated with one or more prior first real-world vehicle trips made by the first real-world user are received according to some embodiments. In various embodiments, the first real-world user is a real-world driver of a first real-world vehicle. In certain embodiments, the one or more prior first real-world vehicle trips correspond to actual vehicle trips that the first real-world user has made in the past. For example, the one or more prior first real-world vehicle trips include actual vehicle trips made by the first real-world user for any personal and/or business reasons (e.g., commuting to work, grocery shopping, going to a bank, road trips, etc.).
In some embodiments, the first real-world telematics data are collected from one or more sensors associated with the first real-world vehicle operated by the first real-world user. For example, the one or more sensors include any type and number of accelerometers, gyroscopes, magnetometers, barometers, location sensors (e.g., GPS sensors), tilt sensors, yaw rate sensors, brake sensors, airbag deployment sensors, windshield wiper sensors, headlight sensors, steering angle sensors, gear position sensors, proximity detectors, throttle sensors, gas tank sensors, battery sensors, etc. As an example, the first real-world telematics data include data collected by any type and number of accelerometers, gyroscopes, magnetometers, barometers, location sensors, tilt sensors, yaw rate sensors, speedometers, brake sensors, airbag sensors, windshield wiper sensors, headlight sensors, steering angle sensors, gear position sensors, proximity detectors, throttle sensors, gas tank sensors, battery sensors, etc. In certain embodiments, the first real-world telematics data indicate the operational state of the first real-world vehicle, such as speed, acceleration, braking event, etc. In some embodiments, the one or more sensors are part of or located in the first real-world vehicle. For example, the one or more sensors communicate and store sensor data in an electronic control module (ECM) or an engine control unit (ECU) of the first real-world vehicle. In certain embodiments, the one or more sensors are part of a computing device (e.g., a mobile device, a smart watch) that is connected to the first real-world vehicle. For example, the computing device is connected to the first real-world vehicle while the first real-world vehicle is in operation. As an example, the computing device is connected to the first real-world vehicle while the first real-world vehicle is stationary.
At the process 120, one or more first real-world driving characteristics are determined based at least in part upon the first real-world telematics data according to certain embodiments. In various embodiments, the one or more first real-world driving characteristics indicate how the first real-world user drives, such as how frequently the first real-world user drives, type of maneuvers that the first real-world user makes while driving (e.g., hard cornering, hard braking, sudden acceleration, smooth acceleration, slowing before turning, etc.), types of dangerous driving events (e.g., eating while driving, falling asleep while driving, etc.), types of safe driving events (e.g., maintaining safe following distance, turning on headlights, observing traffic lights, yielding to pedestrians, etc.), etc.
In some embodiments, the one or more first real-world driving characteristics refer to one or more driving skills of the first real-world user. For example, the one or more first real-world driving characteristics include a first braking characteristic, a first steering characteristic, a first speeding characteristic, and/or a first focus characteristic. As an example, the first braking characteristic corresponds to the first real-world user's ability to decelerate the first real-world vehicle upon encountering braking obstacles (e.g., T-junctions, stop signs, pedestrian crossings, etc.). For example, the first steering characteristic corresponds to the first real-world user's ability to steer the first real-world vehicle upon encountering steering obstacles (e.g., potholes, road kills, sharp turns, etc.). As an example, the first speeding characteristic corresponds to the first real-world user's ability to decelerate the first real-world vehicle upon encountering speeding obstacles (e.g., approaching a school zone, entering city limit, etc.). For example, the first focus characteristic corresponds to the first real-world user's ability to maintain or regain focus while operating the first real-world vehicle upon encountering focus obstacles (e.g., using a cell phone while driving).
In certain embodiments, the one or more first real-world driving characteristics include one or more first driving attributes associated with the first real-world user. For example, the one or more first driving attributes may include a first driving alertness (e.g., how attentive is the first real-world user while driving), a first driving reaction time (e.g., how fast can the first real-world user react to a given driving situation), a first driving risk-taking (e.g., how likely is the first real-world user to engage in risky driving behavior), a first driving information processing (e.g., how well can the first real-world user interpret inputs from driving environment), a first driving endurance (e.g., how long can the first real-world user drive without rest), and/or other suitable driving traits attributable to the first real-world user.
At the process 130, second real-world telematics data and second real-world geolocation data associated with one or more prior second real-world vehicle trips made by the second real-world user are received according to some embodiments. In various embodiments, the second real-world user is a real-world driver of a second real-world vehicle, and the second real-world user is different from the first real-world user. In certain embodiments, the one or more prior second real-world vehicle trips correspond to actual vehicle trips that the second real-world user has made in the past. For example, the one or more prior second real-world vehicle trips include actual vehicle trips made by the second real-world user for any personal and/or business reasons (e.g., going to the pharmacy, picking up kids from school, dropping off packages at the post office, etc.).
In some embodiments, the second real-world telematics data and/or the second real-world geolocation data are collected from one or more sensors associated with the second real-world vehicle operated by the second real-world user. For example, the one or more sensors include any type and number of accelerometers, gyroscopes, magnetometers, barometers, location sensors (e.g., GPS sensors), tilt sensors, yaw rate sensors, brake sensors, airbag deployment sensors, windshield wiper sensors, headlight sensors, steering angle sensors, gear position sensors, proximity detectors, throttle sensors, gas tank sensors, battery sensors, etc. As an example, the second real-world telematics data include data collected by any type and number of accelerometers, gyroscopes, magnetometers, barometers, location sensors, tilt sensors, yaw rate sensors, speedometers, brake sensors, airbag sensors, windshield wiper sensors, headlight sensors, steering angle sensors, gear position sensors, proximity detectors, throttle sensors, gas tank sensors, battery sensors, etc. In certain embodiments, the second real-world telematics data indicate the operational state of the second real-world vehicle. In some embodiments, the one or more sensors are part of or located in the second real-world vehicle. For example, the one or more sensors communicate and store sensor data in an ECM or ECU of the second real-world vehicle. In certain embodiments, the one or more sensors are part of a computing device that is connected to the second real-world vehicle. For example, the computing device is connected to the second real-world vehicle while the second real-world vehicle is in operation. As an example, the computing device is connected to the second real-world vehicle while the second real-world vehicle is stationary.
At the process 140, one or more second real-world driving characteristics are determined based at least in part upon the second real-world telematics data according to some embodiments. In various embodiments, the one or more second real-world driving characteristics indicate how the second real-world user drives, such as how frequently the second real-world user drives, type of maneuvers that the second real-world user makes while driving, types of dangerous driving events, types of safe driving events, etc.
In certain embodiments, the one or more second real-world driving characteristics refer to one or more driving skills of the second real-world user. For example, the one or more second real-world driving characteristics include a second braking characteristic, a second steering characteristic, a second speeding characteristic, and/or a second focus characteristic. As an example, the second braking characteristic corresponds to the second real-world user's ability to decelerate the second real-world vehicle upon encountering braking obstacles. For example, the second steering characteristic corresponds to the second real-world user's ability to steer the second real-world vehicle upon encountering steering obstacles. As an example, the second speeding characteristic corresponds to the second real-world user's ability to decelerate the second real-world vehicle upon encountering speeding obstacles. For example, the second focus characteristic corresponds to the second real-world user's ability to maintain or regain focus while operating the second real-world vehicle upon encountering focus obstacles.
In certain embodiments, the one or more second real-world driving characteristics include one or more second driving attributes associated with the second real-world user. For example, the one or more second driving attributes may include a second driving alertness (e.g., how attentive is the second real-world user while driving), a second driving reaction time (e.g., how fast can the second real-world user react to a given driving situation), a second driving risk-taking (e.g., how likely is the second real-world user to engage in risky driving behavior), a second driving information processing (e.g., how well can the second real-world user interpret inputs from driving environment), a second driving endurance (e.g., how long can the second real-world user drive without rest), and/or other suitable driving traits attributable to the second real-world user.
At the process 150, the shared virtual map is generated based at least in part upon the one or more first real-world driving characteristics and the one or more second real-world driving characteristics according to some embodiments. In various embodiments, a network of virtual roads is generated in the shared virtual map based at least in part upon a combination of the one or more first real-world driving characteristics and the one or more second real-world driving characteristics. For example, the combination of the one or more first real-world driving characteristics and the one or more second real-world driving characteristics indicates that both the first real-world user and the second real-world user brake frequently while driving. As an example, the network of virtual roads would include virtual road intersections that correspond to an averaged frequency of braking by the first real-world user and the second real-world user. For example, the combination of the one or more first real-world driving characteristics and the one or more second real-world driving characteristics indicates that the first real-world user makes sharp turns while driving and the second real-world user makes smooth turns while driving. As an example, the network of virtual roads would include virtual roads with a variety of curves/bends that correspond to the sharp turns made by the first real-world user as well as virtual roads with little or no curves/bends that correspond to the smooth turns made by the second real-world user.
In certain embodiments, the network of virtual roads is generated based at least in part upon the geolocations of the first real-world vehicle and the second real-world vehicle. For example, the first real-world user is operating the first real-world vehicle in an urban setting and the second real-world user is operating the second real-world vehicle in a rural setting. As an example, the network of virtual roads would include virtual city streets or highways that correspond to the urban setting as well as virtual country roads that correspond to the rural setting.
In some embodiments, the shared virtual map includes landmarks that the first real-world user and the second real-world user have visited while operating their respective real-world vehicles. For example, the shared virtual map shows virtual bridges corresponding to real-world bridges, virtual buildings corresponding to real-world buildings, virtual parks corresponding to real-world parks, virtual tunnels corresponding to real-world tunnels, virtual stadiums corresponding to real-world stadiums, virtual museums corresponding to real-world museums, etc.
At the process 160, information associated with the shared virtual map are processed according to certain embodiments. In various embodiments, processing the information includes determining characteristics of the shared virtual map such as a size of the shared virtual map, boundaries on the shared virtual map, virtual characters using the shared virtual map, etc.
At the process 170, the shared in-game objective is generated based at least in part upon the shared virtual map according to certain embodiments. In various embodiments, the shared in-game objective is a task that needs to be completed in the shared virtual map. For example, the shared virtual map includes a virtual monster and the shared in-game objective is to defeat the virtual monster. As an example, the shared virtual map includes a virtual element (e.g., a virtual treasure) and the shared in-game objective to capture or claim ownership of the virtual element. For example, the shared virtual map includes various virtual foes (e.g., virtual zombies) and the shared in-game objective is to destroy as many of the virtual foes as possible. As an example, the shared virtual map includes a virtual competition (e.g., a virtual race) and the shared in-game objective is to win the virtual competition.
At the process 180, the shared in-game objective is presented to a first virtual character and a second virtual character in a virtual game according to some embodiments. For example, the shared in-game objective is presented in a remote display (e.g., in a mobile device of the first real-world user and a mobile device of the second real-world user). In various embodiments, the first virtual character is associated with the one or more first real-world driving characteristics of the first real-world user and the second virtual character is associated with the one or more second real-world driving characteristics of the second real-world user. In certain embodiments, the virtual game simulates a virtual driving environment in which the first virtual character operates a first virtual vehicle and the second virtual character operates a second virtual vehicle. For example, the first virtual character exists as a playable character that the first real-world user can control to operate the first virtual vehicle in the shared virtual map. As an example, the second virtual character exists as a playable character that the second real-world user can control to operate the second virtual vehicle in the shared virtual map.
At the process 190, the first virtual character and the second virtual character are allowed to accomplish the shared in-game objective in the shared virtual map according to certain embodiments. In some embodiments, accomplishing the shared in-game objective entails determining whether the first virtual character and the second virtual character have accomplished the shared in-game objective in the shared virtual map by satisfying respective virtual performance conditions (e.g., whether the first virtual character has satisfied one or more first virtual performance conditions and whether the second virtual character has satisfied one or more second virtual performance conditions). For example, if the one or more first virtual performance conditions are determined to be not satisfied by the first virtual character, then the first virtual character and the second virtual character are determined to have not accomplished the shared in-game objective in the shared virtual map. As an example, if the one or more second virtual performance conditions are determined to be not satisfied by the second virtual character, then the first virtual character and the second virtual character are determined to have not accomplished the shared in-game objective in the shared virtual map. For example, if the one or more first virtual performance conditions are determined to be satisfied by the first virtual character and the one or more second virtual performance conditions have been determined to be satisfied by the second virtual character, then the first virtual character and the second virtual character are determined to have accomplished the shared in-game objective in the shared virtual map.
In certain embodiments, accomplishing the shared in-game objective entails determining whether the first virtual character and the second virtual character have accomplished the shared in-game objective in the shared virtual map by collectively satisfying one or more virtual performance conditions. In various embodiments, the one or more virtual performance conditions include the one or more first virtual performance conditions and/or the one or more second virtual performance conditions. For example, if the one or more virtual performance conditions are determined to be collectively satisfied by the first virtual character and the second virtual character, then the first virtual character and the second virtual character are determined to have accomplished the shared in-game objective in the shared virtual map. As an example, if the one or more virtual performance conditions are determined to be not collectively satisfied by the first virtual character and the second virtual character, then the first virtual character and the second virtual character are determined to have not accomplished the shared in-game objective in the shared virtual map.
In some embodiments, satisfying the one or more first virtual performance conditions relates to the first virtual character achieving certain levels of virtual driving skills. For example, the first virtual character needs to achieve a certain score (e.g., a score of 4 out of 5) for a first virtual braking skill, a first virtual steering skill, a first virtual speeding skill, a first virtual focus skill, a first virtual alertness, a first virtual reaction time, a first virtual risk-taking, a first virtual information processing, and/or a first virtual endurance. In various embodiments, the first virtual braking skill is based at least in part upon the first braking characteristic, the first virtual steering skill is based at least in part upon the first steering characteristic, the first virtual speeding skill is based at least in part upon the first speeding characteristic, the first virtual focus skill is based at least in part upon the first focus characteristic, the first virtual alertness is based at least in part upon the first driving alertness, the first virtual reaction time is based at least in part upon the first driving reaction time, the first virtual risk-taking is based at least in part upon the first driving risk-taking, the first virtual information processing is based at least in part upon the first driving information processing, and the first virtual endurance is based at least in part upon the first driving endurance.
In certain embodiments, satisfying the one or more second virtual performance conditions relates to the second virtual character achieving certain levels of virtual driving skills. For example, the second virtual character needs to achieve a certain score (e.g., a score of 4 out of 5) for a second virtual braking skill, a second virtual steering skill, a second virtual speeding skill, a second virtual focus skill, a second virtual alertness, a second virtual reaction time, a second virtual risk-taking, a second virtual information processing, and/or a second virtual endurance. In various embodiments, the second virtual braking skill is based at least in part upon the second braking characteristic, the second virtual steering skill is based at least in part upon the second steering characteristic, the second virtual speeding skill is based at least in part upon the second speeding characteristic, the second virtual focus skill is based at least in part upon the second focus characteristic, the second virtual alertness is based at least in part upon the second driving alertness, the second virtual reaction time is based at least in part upon the second driving reaction time, the second virtual risk-taking is based at least in part upon the second driving risk-taking, the second virtual information processing is based at least in part upon the second driving information processing, and the second virtual endurance is based at least in part upon the second driving endurance.
In some embodiments, the one or more first virtual performance conditions are the same as the one or more second virtual performance conditions. For example, the both the first virtual character and the second virtual character need to achieve a certain score for the first virtual braking skill and the second virtual braking skill. In certain embodiments, the one or more first virtual performance conditions are different from the one or more second virtual performance conditions. For example, the first virtual character needs to achieve a certain score for the first virtual steering skill while the second virtual character needs to achieve a certain score for the second virtual reaction time.
In various embodiments, the shared virtual map and the shared in-game objective are generated based upon any suitable number of users. For example, the real-world driving characteristics associated with N users used to generate the shared virtual map which in turn is used to generate the shared in-game objective for the N users.
In certain embodiments, instead of the virtual driving environment, the virtual game simulates a virtual role-playing environment. For example, the shared virtual map presented in the virtual role-playing environment depicts virtual paths (e.g., virtual trails, virtual rivers, virtual mountain passes, etc.). As an example, the shared in-game objective is for the first virtual character and the second virtual character to complete a quest in the shared virtual map. For example, to successfully complete the quest, the one or more first virtual performance conditions relating to the first virtual character achieving certain levels of virtual driving skills and/or the one or more second virtual performance conditions relating to the second virtual character achieving certain levels of virtual driving skills need to be satisfied.
In some embodiments, instead of the virtual driving environment, the virtual game simulates a virtual battle environment. For example, the shared virtual map presented in the virtual battle environment depicts virtual battlefields. As an example, the shared in-game objective is for the first virtual character and the second virtual character to fight in a battle (e.g., against each other or against a common enemy). For example, to successfully fight in the battle, the one or more first virtual performance conditions relating to the first virtual character achieving certain levels of virtual driving skills and/or the one or more second virtual performance conditions relating to the second virtual character achieving certain levels of virtual driving skills need to be satisfied.
As discussed above and further emphasized here,
In some embodiments where the virtual driving environment is simulated in the virtual game, the shared in-game objective that has been generated by the method 100 is to be completed by the virtual characters while operating respective virtual vehicles. For example, a first virtual vehicle 202 operated by the first virtual character and a second virtual vehicle 204 operated by the second virtual character are traveling on a virtual route 206. As an example, the shared in-game objective is to destroy as many virtual zombies 208 as possible that are blocking the virtual route 206. For example, to accomplish the shared in-game objective, the first virtual character operating the first virtual vehicle 202 needs to satisfy a set of virtual performance conditions 210 in the form of achieving a passable score (e.g., 6 out of 10) for a first virtual steering skill 212 and a first virtual braking skill 214. As an example, the first virtual character has only achieved a score of 1 out of 10 for the first virtual steering skill 212 and a score of 5 out of 10 for the first virtual braking skill 214. For example, to accomplish the shared in-game objective, the second virtual character in the second virtual vehicle 204 needs to satisfy a set of virtual performance conditions 220 in the form of achieving a passable score (e.g., 6 out of 10) for a second virtual steering skill 222 and a second virtual braking skill 224. As an example, the second virtual character has only achieved a score of 3 out of 10 for the second virtual steering skill 222 and a score of 4 out of 10 for the second virtual braking skill 224.
In various embodiments, the system 300 is used to implement the method 100. According to certain embodiments, the vehicle system 302 includes a vehicle 310 and a client device 312 associated with the vehicle 310. For example, the client device 312 is an on-board computer embedded or located in the vehicle 310. As an example, the client device 312 is a mobile device (e.g., a smartphone) that is connected (e.g., via wired or wireless links) to the vehicle 310. As an example, the client device 312 includes a processor 316 (e.g., a central processing unit (CPU), a graphics processing unit (GPU)), a memory 318 (e.g., random-access memory (RAM), read-only memory (ROM), flash memory), a communications unit 320 (e.g., a network transceiver), a display unit 322 (e.g., a touchscreen), and one or more sensors 324 (e.g., an accelerometer, a gyroscope, a magnetometer, a barometer, a GPS sensor). In certain embodiments, the client device 312 represents the on-board computer in the vehicle 310 and the mobile device connected to the vehicle 310. For example, the one or more sensors 324 may be in the vehicle 310 and in the mobile device connected to the vehicle 310.
In some embodiments, the vehicle 310 is operated by a real-world user, such as the first real-world user and/or the second real-world user. In certain embodiments, multiple vehicles 310 exist in the system 300 which are operated by respective users. For example, the first real-world user operates the first real-world vehicle and the second real-world user operates the second real-world vehicle.
In various embodiments, during vehicle trips, the one or more sensors 324 monitor the vehicle 310 by collecting data associated with various operating parameters of the vehicle, such as speed, acceleration, braking, location, and other suitable parameters. In certain embodiments, the collected data include telematics data. According to some embodiments, the data are collected continuously, at predetermined time intervals, and/or based on a triggering event (e.g., when each sensor has acquired a threshold amount of sensor measurements). In various embodiments, the collected data represent the first real-world telematics data and/or the second real-world telematics data in the method 100.
According to certain embodiments, the collected data are stored in the memory 318 before being transmitted to the server 306 using the communications unit 320 via the network 304 (e.g., via a local area network (LAN), a wide area network (WAN), the Internet). In some embodiments, the collected data are transmitted directly to the server 306 via the network 304. For example, the collected data are transmitted to the server 306 without being stored in the memory 318. In certain embodiments, the collected data are transmitted to the server 306 via a third party. For example, a data monitoring system stores any and all data collected by the one or more sensors 324 and transmits those data to the server 306 via the network 304 or a different network.
According to some embodiments, the server 306 includes a processor 330 (e.g., a microprocessor, a microcontroller), a memory 332, a communications unit 334 (e.g., a network transceiver), and a data storage 336 (e.g., one or more databases). In some embodiments, the server 306 is a single server, while in certain embodiments, the server 306 includes a plurality of servers with distributed processing. In
According to various embodiments, the server 306 receives, via the network 304, the data collected by the one or more sensors 324 using the communications unit 334 and stores the data in the data storage 336. For example, the server 306 then processes the data to perform one or more processes of the method 100.
According to certain embodiments, any related information determined or generated by the method 100 (e.g., real-world driving characteristics, shared in-game objectives, shared virtual maps, etc.) are transmitted back to the client device 312, via the network 304, to be provided (e.g., displayed) to the user via the display unit 322.
In some embodiments, one or more processes of the method 100 are performed by the client device 312. For example, the processor 316 of the client device 312 processes the data collected by the one or more sensors 324 to perform one or more processes of the method 100.
In various embodiments, the processing unit 404 is configured for executing instructions, such as instructions to implement the method 100 of
In various embodiments, the memory unit 406 includes a device allowing information, such as executable instructions and/or other data to be stored and retrieved. In some embodiments, the memory unit 406 includes one or more computer readable media. In certain embodiments, the memory unit 406 includes computer readable instructions for providing a user interface, such as to the user 416, via the output unit 410. In some embodiments, a user interface includes a web browser and/or a client application. For example, a web browser enables the user 416 to interact with media and/or other information embedded on a web page and/or a website. In certain embodiments, the memory unit 406 includes computer readable instructions for receiving and processing an input via the input unit 408. In some embodiments, the memory unit 406 includes RAM such as dynamic RAM (DRAM) or static RAM (SRAM), ROM, erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), and/or non-volatile RAM (NVRAM).
In various embodiments, the input unit 408 is configured to receive input (e.g., from the user 416). In some embodiments, the input unit 408 includes a keyboard, a pointing device, a mouse, a stylus, a touch sensitive panel (e.g., a touch pad or touch screen), a gyroscope, an accelerometer, a position sensor (e.g., GPS sensor), and/or an audio input device. In certain embodiments, the input unit 408 is configured to function as both an input unit and an output unit.
In various embodiments, the output unit 410 includes a media output unit configured to present information to the user 416. In some embodiments, the output unit 410 includes any component capable of conveying information to the user 416. In certain embodiments, the output unit 410 includes an output adapter such as a video adapter and/or an audio adapter. For example, the output unit 410 is operatively coupled to the processing unit 404 and/or a visual display device to present information to the user 416 (e.g., a liquid crystal display (LCD), a light emitting diode (LED) display, an organic light emitting diode (OLED) display, a cathode ray tube (CRT) display, a projected display, etc.). As an example, the output unit 410 is operatively coupled to the processing unit 404 and/or an audio display device to present information to the user 416 (e.g., a speaker arrangement or headphones).
In various embodiments, the communication unit 412 is configured to be communicatively coupled to a remote device. In some embodiments, the communication unit 412 includes a wired network adapter, a wireless network adapter, a wireless data transceiver for use with a mobile phone network (e.g., 3G, 4G, 5G, Bluetooth, near-field communication (NFC), etc.), and/or other mobile data networks. In certain embodiments, other types of short-range or long-range networks may be used. In some embodiments, the communication unit 412 is configured to provide email integration for communicating data between a server and one or more clients.
In various embodiments, the storage unit 414 is configured to enable communication between the computing device 400 and the storage device 418. In some embodiments, the storage unit 414 is a storage interface. For example, the storage interface is any component capable of providing the processing unit 404 with access to the storage device 418. In certain embodiments, the storage unit 414 includes an advanced technology attachment (ATA) adapter, a serial ATA (SATA) adapter, a small computer system interface (SCSI) adapter, a RAID controller, a SAN adapter, a network adapter, and/or any other component capable of providing the processing unit 404 with access to the storage device 418.
In various embodiments, the storage device 418 includes any computer-operated hardware suitable for storing and/or retrieving data. In certain embodiments, the storage device 418 is integrated in the computing device 400. In some embodiments, the storage device 418 includes a database such as a local database or a cloud database. In certain embodiments, the storage device 418 includes one or more hard disk drives. In some embodiments, the storage device 418 is external and is configured to be accessed by a plurality of server systems. In certain embodiments, the storage device 418 includes multiple storage units such as hard disks or solid state disks in a redundant array of inexpensive disks configuration. In some embodiments, the storage device 418 includes a storage area network and/or a network attached storage system.
According to certain embodiments, a method for presenting one or more in-game objectives in one or more virtual games includes receiving first real-world telematics data associated with one or more prior first real-world vehicle trips made by a first real-world user and determining one or more first real-world driving characteristics based at least in part upon the first real-world telematics data. Also, the method includes receiving second real-world telematics data associated with one or more prior second real-world vehicle trips made by a second real-world user and determining one or more second real-world driving characteristics based at least in part upon the second real-world telematics data. The first real-world user is different from the second real-world user. Further, the method includes generating a shared virtual map based at least in part upon the one or more first real-world driving characteristics and the one or more second real-world driving characteristics. The method then includes processing information associated with the shared virtual map. Additionally, the method includes generating a shared in-game objective based at least in part upon the shared virtual map and presenting the shared in-game objective to a first virtual character and a second virtual character in a virtual game. The first virtual character is associated with the one or more first real-world driving characteristics of the first real-world user while the second virtual character is associated with the one or more second real-world driving characteristics of the second real-world user. The first virtual character and the second virtual character are different. Moreover, the method includes allowing the first virtual character and the second virtual character to accomplish, in the shared virtual map, the shared in-game objective. For example, the method is implemented according to at least
According to some embodiments, a computing device for presenting one or more in-game objectives in one or more virtual games includes one or more processors and a memory that stores instructions for execution by the one or more processors. The instructions, when executed, cause the one or more processors to receive first real-world telematics data associated with one or more prior first real-world vehicle trips made by a first real-world user and determine one or more first real-world driving characteristics based at least in part upon the first real-world telematics data. Also, the instructions, when executed, cause the one or more processors to receive second real-world telematics data associated with one or more prior second real-world vehicle trips made by a second real-world user and determine one or more second real-world driving characteristics based at least in part upon the second real-world telematics data. The first real-world user is different from the second real-world user. Further, the instructions, when executed, cause the one or more processors to generate a shared virtual map based at least in part upon the one or more first real-world driving characteristics and the one or more second real-world driving characteristics. The instructions, when executed, then cause the one or more processors to process information associated with the shared virtual map. Additionally, the instructions, when executed, then cause the one or more processors to generate a shared in-game objective based at least in part upon the shared virtual map and present the shared in-game objective to a first virtual character and a second virtual character in a virtual game. The first virtual character is associated with the one or more first real-world driving characteristics of the first real-world user while the second virtual character is associated with the one or more second real-world driving characteristics of the second real-world user. The first virtual character and the second virtual character are different. Moreover, the instructions, when executed, then cause the one or more processors to allow the first virtual character and the second virtual character to accomplish, in the shared virtual map, the shared in-game objective. For example, the computing device is implemented according to at least
According to certain embodiments, a non-transitory computer-readable medium stores instructions for presenting one or more in-game objectives in one or more virtual games. The instructions are executed by one or more processors of a computing device. The non-transitory computer-readable medium includes instructions to receive first real-world telematics data associated with one or more prior first real-world vehicle trips made by a first real-world user and determine one or more first real-world driving characteristics based at least in part upon the first real-world telematics data. Also, the non-transitory computer-readable medium includes instructions to receive second real-world telematics data associated with one or more prior second real-world vehicle trips made by a second real-world user and determine one or more second real-world driving characteristics based at least in part upon the second real-world telematics data. The first real-world user is different from the second real-world user. Further, the non-transitory computer-readable medium includes instructions to generate a shared virtual map based at least in part upon the one or more first real-world driving characteristics and the one or more second real-world driving characteristics. The non-transitory computer-readable medium then includes instructions to process information associated with the shared virtual map. Additionally, the non-transitory computer-readable medium includes instructions to generate a shared in-game objective based at least in part upon the shared virtual map and present the shared in-game objective to a first virtual character and a second virtual character in a virtual game. The first virtual character is associated with the one or more first real-world driving characteristics of the first real-world user while the second virtual character is associated with the one or more second real-world driving characteristics of the second real-world user. The first virtual character and the second virtual character are different. Moreover, the non-transitory computer-readable medium includes instructions to allow the first virtual character and the second virtual character to accomplish, in the shared virtual map, the shared in-game objective. For example, the non-transitory computer-readable medium is implemented according to at least
According to some embodiments, a processor or a processing element may be trained using supervised machine learning and/or unsupervised machine learning, and the machine learning may employ an artificial neural network, which, for example, may be a convolutional neural network, a recurrent neural network, a deep learning neural network, a reinforcement learning module or program, or a combined learning module or program that learns in two or more fields or areas of interest. Machine learning may involve identifying and recognizing patterns in existing data in order to facilitate making predictions for subsequent data. Models may be created based upon example inputs in order to make valid and reliable predictions for novel inputs.
According to certain embodiments, machine learning programs may be trained by inputting sample data sets or certain data into the programs, such as images, object statistics and information, historical estimates, and/or actual repair costs. The machine learning programs may utilize deep learning algorithms that may be primarily focused on pattern recognition and may be trained after processing multiple examples. The machine learning programs may include Bayesian Program Learning (BPL), voice recognition and synthesis, image or object recognition, optical character recognition, and/or natural language processing. The machine learning programs may also include natural language processing, semantic analysis, automatic reasoning, and/or other types of machine learning.
According to some embodiments, supervised machine learning techniques and/or unsupervised machine learning techniques may be used. In supervised machine learning, a processing element may be provided with example inputs and their associated outputs and may seek to discover a general rule that maps inputs to outputs, so that when subsequent novel inputs are provided the processing element may, based upon the discovered rule, accurately predict the correct output. In unsupervised machine learning, the processing element may need to find its own structure in unlabeled example inputs.
For example, some or all components of various embodiments of the present disclosure each are, individually and/or in combination with at least another component, implemented using one or more software components, one or more hardware components, and/or one or more combinations of software and hardware components. As an example, some or all components of various embodiments of the present disclosure each are, individually and/or in combination with at least another component, implemented in one or more circuits, such as one or more analog circuits and/or one or more digital circuits. For example, while the embodiments described above refer to particular features, the scope of the present disclosure also includes embodiments having different combinations of features and embodiments that do not include all of the described features. As an example, various embodiments and/or examples of the present disclosure can be combined.
Additionally, the methods and systems described herein may be implemented on many different types of processing devices by program code comprising program instructions that are executable by the device processing subsystem. The software program instructions may include source code, object code, machine code, or any other stored data that is operable to cause a processing system to perform the methods and operations described herein. Certain implementations may also be used, however, such as firmware or even appropriately designed hardware configured to perform the methods and systems described herein.
The systems' and methods' data (e.g., associations, mappings, data input, data output, intermediate data results, final data results) may be stored and implemented in one or more different types of computer-implemented data stores, such as different types of storage devices and programming constructs (e.g., RAM, ROM, EEPROM, Flash memory, flat files, databases, programming data structures, programming variables, IF-THEN (or similar type) statement constructs, application programming interface). It is noted that data structures describe formats for use in organizing and storing data in databases, programs, memory, or other computer-readable media for use by a computer program.
The systems and methods may be provided on many different types of computer-readable media including computer storage mechanisms (e.g., CD-ROM, diskette, RAM, flash memory, computer's hard drive, DVD) that contain instructions (e.g., software) for use in execution by a processor to perform the methods' operations and implement the systems described herein. The computer components, software modules, functions, data stores and data structures described herein may be connected directly or indirectly to each other in order to allow the flow of data needed for their operations. It is also noted that a module or processor includes a unit of code that performs a software operation, and can be implemented for example as a subroutine unit of code, or as a software function unit of code, or as an object (as in an object-oriented paradigm), or as an applet, or in a computer script language, or as another type of computer code. The software components and/or functionality may be located on a single computer or distributed across multiple computers depending upon the situation at hand.
The computing system can include client devices and servers. A client device and server are generally remote from each other and typically interact through a communication network. The relationship of client device and server arises by virtue of computer programs running on the respective computers and having a client device-server relationship to each other.
This specification contains many specifics for particular embodiments. Certain features that are described in this specification in the context of separate embodiments can also be implemented in combination in a single embodiment. Conversely, various features that are described in the context of a single embodiment can also be implemented in multiple embodiments separately or in any suitable subcombination. Moreover, although features may be described above as acting in certain combinations, one or more features from a combination can in some cases be removed from the combination, and a combination may, for example, be directed to a subcombination or variation of a subcombination.
Similarly, while operations are depicted in the drawings in a particular order, this should not be understood as requiring that such operations be performed in the particular order shown or in sequential order, or that all illustrated operations be performed, to achieve desirable results. In certain circumstances, multitasking and parallel processing may be advantageous. Moreover, the separation of various system components in the embodiments described above should not be understood as requiring such separation in all embodiments, and it should be understood that the described program components and systems can generally be integrated together in a single software product or packaged into multiple software products.
Although specific embodiments of the present disclosure have been described, it will be understood by those of skill in the art that there are other embodiments that are equivalent to the described embodiments. Accordingly, it is to be understood that the present disclosure is not to be limited by the specific illustrated embodiments.
Number | Name | Date | Kind |
---|---|---|---|
6726567 | Khosla | Apr 2004 | B1 |
7278920 | Klamer et al. | Oct 2007 | B1 |
8645029 | Kim et al. | Feb 2014 | B2 |
8799035 | Coleman et al. | Aug 2014 | B2 |
9140567 | Fryer et al. | Sep 2015 | B2 |
9327189 | Bavitz et al. | May 2016 | B2 |
9352216 | Mullen | May 2016 | B2 |
9373203 | Fields et al. | Jun 2016 | B1 |
9381426 | Hughes et al. | Jul 2016 | B1 |
9473893 | Kuramura et al. | Oct 2016 | B2 |
9478150 | Fields et al. | Oct 2016 | B1 |
9498704 | Cohen et al. | Nov 2016 | B1 |
9586591 | Fields et al. | Mar 2017 | B1 |
9643089 | Ishikawa | May 2017 | B2 |
9691298 | Hsu-Hoffman | Jun 2017 | B1 |
9754425 | Iqbal et al. | Sep 2017 | B1 |
9786170 | Roy et al. | Oct 2017 | B2 |
9858832 | Hsu-Hoffman | Jan 2018 | B1 |
9892573 | Hsu et al. | Feb 2018 | B1 |
9916693 | Carr et al. | Mar 2018 | B1 |
9943754 | Prasad et al. | Apr 2018 | B2 |
10013883 | Farnham et al. | Jul 2018 | B2 |
10055794 | Konrardy et al. | Aug 2018 | B1 |
10086287 | Krietzman et al. | Oct 2018 | B2 |
10127570 | Cote et al. | Nov 2018 | B1 |
10181238 | Hate | Jan 2019 | B2 |
10262375 | Howard | Apr 2019 | B1 |
10282786 | Osborne et al. | May 2019 | B1 |
10282911 | Carr et al. | May 2019 | B2 |
10360576 | Hsu-Hoffman | Jul 2019 | B1 |
10369472 | Mattar et al. | Aug 2019 | B1 |
10384130 | Parisi | Aug 2019 | B2 |
10403043 | Kaufman et al. | Sep 2019 | B2 |
10430745 | Rani et al. | Oct 2019 | B2 |
10445758 | Bryer et al. | Oct 2019 | B1 |
10521983 | Hsu-Hoffman | Dec 2019 | B1 |
10557715 | Caldas et al. | Feb 2020 | B2 |
10603591 | Navulur | Mar 2020 | B1 |
10617938 | Chen et al. | Apr 2020 | B2 |
10681181 | Hamill | Jun 2020 | B2 |
10703378 | Russo et al. | Jul 2020 | B1 |
10713543 | Skuin et al. | Jul 2020 | B1 |
10723312 | Potter et al. | Jul 2020 | B1 |
10737184 | Baszucki | Aug 2020 | B2 |
10775179 | Hayward | Sep 2020 | B1 |
10782699 | Tao et al. | Sep 2020 | B2 |
10788332 | Deluca et al. | Sep 2020 | B2 |
10831207 | Leung et al. | Nov 2020 | B1 |
10832593 | Dahl | Nov 2020 | B1 |
10885539 | Purgatorio et al. | Jan 2021 | B1 |
10915964 | Purgatorio et al. | Feb 2021 | B1 |
10916075 | Webster et al. | Feb 2021 | B1 |
11037382 | Lei et al. | Jun 2021 | B2 |
11504622 | Sanchez | Nov 2022 | B1 |
20010006908 | Fujioka et al. | Jul 2001 | A1 |
20020028704 | Bloomfield et al. | Mar 2002 | A1 |
20020070916 | Noro et al. | Jun 2002 | A1 |
20020075286 | Yonezawa et al. | Jun 2002 | A1 |
20020082068 | Singhal | Jun 2002 | A1 |
20020082082 | Stamper et al. | Jun 2002 | A1 |
20020090985 | Tochner et al. | Jul 2002 | A1 |
20020178033 | Yoshioka et al. | Nov 2002 | A1 |
20020198055 | Bull et al. | Dec 2002 | A1 |
20030062675 | Noro et al. | Apr 2003 | A1 |
20030144047 | Sprogis | Jul 2003 | A1 |
20030224855 | Cunningham | Dec 2003 | A1 |
20040005927 | Bonilla et al. | Jan 2004 | A1 |
20040046655 | Benes et al. | Mar 2004 | A1 |
20040058732 | Piccionelli | Mar 2004 | A1 |
20040224740 | Ball et al. | Nov 2004 | A1 |
20040248653 | Barros et al. | Dec 2004 | A1 |
20040259059 | Aoki et al. | Dec 2004 | A1 |
20050009608 | Robarts et al. | Jan 2005 | A1 |
20050049022 | Mullen | Mar 2005 | A1 |
20060105838 | Mullen | May 2006 | A1 |
20060154710 | Serafat | Jul 2006 | A1 |
20060258420 | Mullen | Nov 2006 | A1 |
20070257804 | Gunderson et al. | Nov 2007 | A1 |
20070281765 | Mullen | Dec 2007 | A1 |
20070281766 | Mullen | Dec 2007 | A1 |
20070296723 | Williams | Dec 2007 | A1 |
20080015018 | Mullen | Jan 2008 | A1 |
20080015024 | Mullen | Jan 2008 | A1 |
20080081694 | Hong et al. | Apr 2008 | A1 |
20080280684 | McBride et al. | Nov 2008 | A1 |
20080309675 | Fleury et al. | Dec 2008 | A1 |
20090005140 | Rose et al. | Jan 2009 | A1 |
20090076784 | Ong et al. | Mar 2009 | A1 |
20100205012 | McClellan | Aug 2010 | A1 |
20100227688 | Lee | Sep 2010 | A1 |
20100271367 | Vaden et al. | Oct 2010 | A1 |
20110090075 | Armitage et al. | Apr 2011 | A1 |
20110212766 | Bowers et al. | Sep 2011 | A1 |
20110319148 | Kinnebrew | Dec 2011 | A1 |
20120052953 | Annambhotla et al. | Mar 2012 | A1 |
20120069131 | Abelow | Mar 2012 | A1 |
20120072241 | Krause et al. | Mar 2012 | A1 |
20120142429 | Muller | Jun 2012 | A1 |
20120185282 | Gore et al. | Jul 2012 | A1 |
20130090821 | Abboud et al. | Apr 2013 | A1 |
20130164715 | Hunt et al. | Jun 2013 | A1 |
20130182116 | Arima | Jul 2013 | A1 |
20130268156 | Schumann et al. | Oct 2013 | A1 |
20130311250 | Hickethier et al. | Nov 2013 | A1 |
20140125678 | Wang et al. | May 2014 | A1 |
20140128146 | Story et al. | May 2014 | A1 |
20140129130 | Kuramura et al. | May 2014 | A1 |
20140180725 | Ton-That | Jun 2014 | A1 |
20140195106 | McQuade et al. | Jul 2014 | A1 |
20140195272 | Sadiq | Jul 2014 | A1 |
20140322674 | Livneh | Oct 2014 | A1 |
20140322676 | Raman | Oct 2014 | A1 |
20140347368 | Kishore | Nov 2014 | A1 |
20140364238 | Koh et al. | Dec 2014 | A1 |
20150011315 | Sofman et al. | Jan 2015 | A1 |
20150081404 | Basir | Mar 2015 | A1 |
20150093722 | Fitzgerald et al. | Apr 2015 | A1 |
20150112504 | Binion et al. | Apr 2015 | A1 |
20150112540 | Rutkowski et al. | Apr 2015 | A1 |
20150120408 | Liu | Apr 2015 | A1 |
20150178998 | Attard et al. | Jun 2015 | A1 |
20150187224 | Moncrief et al. | Jul 2015 | A1 |
20150212722 | Leung et al. | Jul 2015 | A1 |
20150294422 | Carver et al. | Oct 2015 | A1 |
20150310758 | Daddona et al. | Oct 2015 | A1 |
20160003636 | Ng-Thow-Hing et al. | Jan 2016 | A1 |
20160003836 | Stauber et al. | Jan 2016 | A1 |
20160084661 | Gautama et al. | Mar 2016 | A1 |
20160219024 | Verzun et al. | Jul 2016 | A1 |
20160371553 | Farnham et al. | Dec 2016 | A1 |
20170061733 | Gulla et al. | Mar 2017 | A1 |
20170089710 | Slusar | Mar 2017 | A1 |
20170259177 | Aghdaie et al. | Sep 2017 | A1 |
20170323244 | Rani et al. | Nov 2017 | A1 |
20180247558 | Livneh | Aug 2018 | A1 |
20180286268 | Ni | Oct 2018 | A1 |
20180322700 | Carr et al. | Nov 2018 | A1 |
20180350144 | Rathod | Dec 2018 | A1 |
20190096134 | Amacker et al. | Mar 2019 | A1 |
20190108768 | Mohamed | Apr 2019 | A1 |
20190113927 | Englard et al. | Apr 2019 | A1 |
20190265703 | Hicok et al. | Aug 2019 | A1 |
20190384292 | Aragon et al. | Dec 2019 | A1 |
20200013306 | McQuade et al. | Jan 2020 | A1 |
20200050719 | Fuerstenberg et al. | Feb 2020 | A1 |
20200074266 | Peake et al. | Mar 2020 | A1 |
20200104326 | Ricci | Apr 2020 | A1 |
20200139250 | Curtis et al. | May 2020 | A1 |
20200286253 | Chilcote-Bacco | Sep 2020 | A1 |
20200334762 | Carver et al. | Oct 2020 | A1 |
20200357075 | Dahl | Nov 2020 | A1 |
20200391104 | Nakamura et al. | Dec 2020 | A1 |
20210049925 | Robinson et al. | Feb 2021 | A1 |
20210232632 | Howard | Jul 2021 | A1 |
20210346805 | Daniali | Nov 2021 | A1 |
20220242450 | Sokolov et al. | Aug 2022 | A1 |
20220284077 | Dahl | Sep 2022 | A1 |
Number | Date | Country |
---|---|---|
105718065 | Jun 2016 | CN |
107543554 | Jan 2018 | CN |
108253982 | Jul 2018 | CN |
108334090 | Jul 2018 | CN |
108446027 | Aug 2018 | CN |
109491394 | Mar 2019 | CN |
110427682 | Nov 2019 | CN |
210021183 | Feb 2020 | CN |
102013213179 | Jan 2015 | DE |
102018122864 | Mar 2020 | DE |
102019205083 | Oct 2020 | DE |
2014-181927 | Sep 2014 | JP |
10-2013-0107481 | Oct 2013 | KR |
2016148753 | Sep 2016 | WO |
2019245578 | Dec 2019 | WO |
2020172634 | Aug 2020 | WO |
2020181001 | Sep 2020 | WO |
Entry |
---|
Ali et al., “Virtual Environment for Automobile Driving Test”, In 2018 International Conference on Computing Sciences and Engineering (ICCSE), Mar. 2018, pp. 1-6. |
Avouris et al., “A review of mobile location-based games for learning across physical and virtual spaces”, J. UCS, vol. 18, No. 15, 2012, pp. 2120-2142. |
Bozorgi et al., “A Time and Energy Efficient Routing Algorithm for Electric Vehicles Based on Historical Driving Data”, IEEE Transactions on Intelligent Vehicles, vol. 2, No. 4, 2017, pp. 1-16. |
Bui et al., “The Effects of Gamification on Driver Behavior: An Example from a Free Float Carsharing Service”, 2015. |
Cullk et al., “Creating a Virtual Environment for Practical Driving Tests”, In International Conference on Transport Systems Telematics, 2019, pp. 95-108. |
Dooren et al., “Rewards That Make You Play: the Distinct Effect of Monetary Rewards, Virtual Points and Social Rewards on Play Persistence in Substance Dependent and Non-Dependent Adolescents”, In 2018 IEEE 6th International Conference on Serious Games and Applications for Health (SeGAH), May 2018, pp. pp. 1-7. |
Esser et al., “Towards learning a realistic rendering of human behavior”, In Proceedings of the European Conference on Computer Vision (ECCV), 2018, (pp. 0-0). |
Handel et al., “Insurance telematics: Opportunities and challenges with the smartphone solution”, IEEE Intelligent Transportation Systems Magazine, vol. 6, No. 4, 2014, pp. 57-70. |
Helvaci et al., “Improving Driver Behavior Using Gamication”, In International Conference on Mobile Web and Intelligent Information Systems, Aug. 2018, pp. 193-204. |
Herrtwich et al., “Cooperative Driving: Taking Telematics to the Next Level”, In Traffic and Granular Flow'01, 2003, pp. 271-280. |
International Search Report and Written Opinion received for PCT Patent Application No. PCT/US2021/013911, dated Mar. 31, 2021, 9 pages. |
International Search Report and Written Opinion received for PCT Patent Application No. PCT/US2021/013918, dated Apr. 8, 2021, 10 pages. |
International Search Report and Written Opinion received for PCT Patent Application No. PCT/US2021/013928, dated Apr. 2, 2021, 8 pages. |
International Search Report and Written Opinion received for PCT Patent Application No. PCT/US2021/013930, dated Apr. 23, 2021, 12 pages. |
Lang et al., “Synthesizing Personalized Training Programs for Improving Driving Habits via Virtual Reality”, In 2018 IEEE Conference on Virtual Reality and 3D User Interfaces, Mar. 2018, pp. 297-304. |
Liu et al., “Two Techniques for Assessing Virtual Agent Personality”, IEEE Transactions on Affective Computing, vol. 7, No. 1, May 19, 2015, pp. 94-105. |
Lopez et al., “Using pervasive games as learning tools in educational contexts: a systematic review”, International Journal of Learning Technology, vol. 13, No. 2, 2018, pp. 93-114. |
Richter et al., “Studying Gamification: The Effect of Rewards and Incentives on Motivation”, In Gamification in education and business, 2015, pp. 21-46. |
Sha et al., “Social vehicle navigation: integrating shared driving experience into vehicle navigation”, In Proceedings of the 14th workshop on mobile computing systems and applications, Feb. 2013, pp. 1-6. |
Singh et al., “Real-time Collaboration Between Mixed Reality Users in Geo-referenced Virtual Environment”, arXiv preprint arXiv, 2020, 2010.01023. |
Stojaspal, Jan., “Gamification and telematics”, available online at https://www.tu-auto.com/gamification-and-telematics/, 2013, 6 pages. |
wiki.sc4devotion.com, SimCity4 Encyclopaedia, “Tutorial: Understanding the Traffic Simulator”, pp. 1-15. Retrieved from the Internet on Aug. 14, 2019: https://www.wiki.sc4devotion.com/index.php?title=Understanding_theTraffic_Simulator. |
Wilken et al., “Maps and the Autonomous Vehicle as a Communication Platform”, International Journal of Communication, vol. 13, 20'19, pp. 2703-2727. |
Vibhor Rastogi (Virtual Reality Based Simulation Testbed for Evaluation of Autonomous Vehicle Behavior Algorithms, Clemson University, 2017, pp. 1-69) (Year: 2017). |
“Drive Safe, Score Well: App Is A Driving ‘Report Card’,”by Lynn Jolicoeur and Sacha Pfeiffer, published Oct. 9, 2014. Source: https ://www.wbur.org/news/2014/10/09/safe-driving-app (Year: 2014). |
“UK Telematics Online. Submitted articles relating to Vehicle Telematics,” published Aug. 31, 2009. Source https://web.archive.org/web/20090831075032/http://www.uktelematicsonline.co.uk/html/telematics_articles.html (Year: 2009). |
Quinn, Nathan, “F1 2021 Drier Ratings Unveiled as Verstappen Equals Hamilton,” Jul. 8, 2021 available at https://the-race.com/gaming/f1-2021-driver-ratings-unveiled-as-verstappen-equals-hamilton/#:—:text=Codemasters%20has %20decided %20the %20overall, their%20performances%20in%20real %2Dlife. (Year: 2021). |