SYSTEM FOR COLLECTING EVIDENCE OF A COLLISION EVENT ON A ROAD WITH AN OBSERVER DEVICE

Abstract

A system and method for collecting evidence of a collision event involving a vehicle on a road with an observer device are provided. An image sensor captures image data during the collision event. A communication module receives a collision message sent by a vehicle involved in the collision event. An evidence collection module processes image data captured by the image sensor to determine whether the collision event was captured. The evidence collection module also compares temporal and geographical data from the collision message, collected from the vehicle involved during the collision event, with time and location metadata in the image data to identify an image of the collision event.A verification report, which includes the tagged image of the collision event, is generated when the time and location metadata matches the temporal and geographical data, and the image data has captured the collision event.

Description

The technical field generally relates to a third-party device that collects an indication of a collision event, and more particularly, to a third-party device that detects a collision between nearby vehicles.In recent years, advances in vehicle safety technologies have increasingly focused on improving the ability of vehicles to prevent and mitigate collisions. A significant area of development is vehicle-to-everything (V2X) communication systems that allow vehicles to exchange critical information with other road users and roadside infrastructure devices in real-time. These systems are designed to improve situational awareness, allowing vehicles to respond to potential hazards before becoming immediate threats.A primary use case for V2X communication is the transmission of vehicle data between vehicles. In the case of a minor collision event, the third-party human observers observing a subject vehicle may not feel that the minor collision is severe enough to stop and there is no need to exchange and share information about a collision event with other nearby vehicles drivers.DE 10 2018 210 211 A1 discloses an apparatus for requesting accident data comprising: a vehicle data interface for receiving vehicle data with information about a state of a first vehicle, a detection unit for detecting an accident of the first vehicle based on the vehicle data, a communication interface for transmitting a request to a second vehicle in a surrounding area of the first vehicle if an accident has been detected. The request includes a request for transmitting accident data with information about the accident of the first vehicle to the first vehicle and / or to a central information collection point. Furthermore, a device for providing accident data is disclosed, having: a sensor interface for receiving accident data containing information relating to an accident of a first vehicle in a surrounding area of a second vehicle, a communication interface for receiving a request from the first vehicle having a request for transmitting the accident data and for transmitting the accident data to the first vehicle and / or to a central information collection point if the request has been received.DE 10 2016 112 908 A1 discloses a crowdsourced server that receives sensor data of vehicles in a vicinity of a location of an event at a time of the event in response to notification of the vehicles about an occurrence of the event. The sensor data includes sensor data of the vehicles that is captured at the time of the event. The crowdsourced server associates the sensor data with the event. The event may be reconstructed using the sensor data associated with the event.Despite advances in traffic management, there are still challenges to reducing traffic associated with minor vehicle collisions. The present disclosure provides an approach to assist in the exchange of collected evidence by making it more quick, safe, and reliable for all occupants of the vehicle, thereby addressing the above problems and more. Desirable features and characteristics of embodiments herein will become apparent from the following detailed description and the appended claims, taken in conjunction with the accompanying drawings and this introduction.In one aspect, the present disclosure provides a system for collecting detection of a road collision event with an observer device independent of a vehicle involved therein. An image sensor is configured to capture image data of the road during the collision event. The image data includes time and location metadata. A communication module is configured to receive a collision message sent from a vehicle involved in the collision event. A detection collection module is in communication with the image sensor and includes a processing unit. The processing unit acquires image data from the image sensor and processes the image data to determine whether the collision event has been detected. Temporal and geographic data is acquired from the collision message collected by the involved vehicle during the collision event. The time and location metadata is compared to the time and geographic data to match the image data to the collision event. A evidence report is generated when (i) the time and location metadata matches the time and geographic data, and (ii) the image data has detected the collision event. The evidence report includes an image of the collision event. The system further includes a human machine interface (HMI) in communication with the detection collection module. The evidence collection module requests a response input to the HMI from a user to verify when the image data matches the collision event.In one embodiment, the image sensor, communication module, and detection collection module may be embodied in a traffic infrastructure platform, where the image sensor is disposed proximate the road for capturing image data.In another embodiment, the image sensor, the communication module, and the detection collection module may be embodied in a vehicle of a vehicle, wherein the image sensor is disposed proximate the roadway for capturing image data.In some embodiments, the processing unit described above may be configured to identify the involved vehicle that was detected in the image data with the collision event. An identified vehicle captured in the image data is classified with the collision event based on a vehicle make, a vehicle model, and a vehicle color. The vehicle make, model, and color of the identified vehicle are confirmed based on the collision message. The evidence report is transmitted to the involved vehicle when the vehicle tag, model and color of the identified vehicle are confirmed.In one embodiment, the communication module transmits the evidence report in response to a request therefor.In another embodiment, the evidence report is transmitted to the involved vehicle based on the collision message.In some embodiments, the processing unit described above may generate an encrypted proof report with a public key and transmit the encrypted proof report to the involved vehicle via a communication link.In yet another embodiment, the processing unit described above may transmit the encrypted evidence report in response to a request received by the communication module from the involved vehicle.In one embodiment, the system described above may include a human machine interface in communication with the communication module. The communication module receives an acknowledgement from the involved vehicle confirming that the encrypted evidence report has been received. The human-machine interface displays an indicator confirming receipt of the encrypted evidence report by the involved vehicle.In another aspect, the present disclosure provides a method for collecting detection of a collision event on a road with an observer device not involved in the collision event. Image data is captured with an image sensor having a field of view of the road. The image data includes time and location metadata. The image data is processed to determine whether the collision event has been detected. A collision message sent by a vehicle involved in the road collision event is received. The collision message includes temporal and geographic data collected from the involved vehicle during the collision event. The time and location metadata is compared to the time and geographic data to match the image data to the collision event. A evidence report is generated when (i) the time and location metadata matches the time and geographic data, and (ii) the image data has detected the collision event. The evidence report includes an image of the collision event. The method further comprises requesting a response input from a user to verify when the image data matches the collision event.In one embodiment, the observer device may be a traffic infrastructure platform that includes the image sensor for capturing image data, a communication module for receiving the collision message, and a collision detection module for processing the image data and the collision message. The image sensor is disposed in the vicinity of the road.In one embodiment, the observer device may be a vehicle of a vehicle located near the road. The vehicle includes the image sensor, a communication module to receive the collision message, and a collision detection module to process the image data and the collision message.In one embodiment, the method as described above identifies the involved vehicle that was captured in the image data with the collision event. An identified vehicle captured in the image data is classified with the collision event based on a vehicle make, a vehicle model, and a vehicle color. The vehicle tag, the vehicle model, and the vehicle color of the identified vehicle are confirmed based on the collision message; and the evidence report is transmitted to the involved vehicle when the vehicle tag, the vehicle model, and the vehicle color of the identified vehicle are confirmed.In yet another embodiment, the method as described above transmits the evidence report in response to a request therefor.In yet another embodiment, the method as described above transmits the evidence report to the involved vehicle based on the collision message.In one embodiment, the method as described above generates an encrypted proof report with a public key; and the encrypted proof report is transmitted to the involved vehicle.In one embodiment, the method receives a confirmation from the participating vehicle confirming that the encrypted proof report was received from the participating vehicle.In yet another aspect, the present disclosure includes a method of collecting detection of a collision event on a road with an observer device not involved in the collision event. Image data is captured with an image sensor having a field of view of the road. The image data includes time and location metadata. The image data is processed to determine whether the collision event has been detected. A collision message sent by a vehicle involved in the road collision event is received. The collision message includes temporal and geographic data collected from the involved vehicle during the collision event. A collided vehicle detected in the image data is identified with the collision event, and the identified vehicle is classified with the collision event based on a vehicle make, a vehicle model, and a vehicle color; the vehicle make, the vehicle model, and the vehicle color of the identified vehicle are confirmed based on the collision message. The time and location metadata is compared to the time and geographic data to match the image data to the collision event. A evidence report is generated when (i) the time and location metadata matches the time and geographic data, (ii) the image data has captured the collision event, and (iii) the vehicle make, model, and color of the identified vehicle are confirmed. The evidence report, which includes an image of the collision event, is encrypted with a public key and transmitted to the involved vehicle.The exemplary embodiments are described below in connection with the following drawing figures, wherein like reference numerals designate like elements, and wherein: FIG. 1 is an illustrative diagram illustrating a third-party observer device in an exemplary environment according to the present disclosure; FIG. 2 is a block diagram of a collision detection collection subsystem of a third-party observer device according to the present disclosure; and FIG. 3 is a flow chart illustrating a method of the third-party observer device of FIG. 1 in accordance with the present disclosure.Additional information regarding the subject matter described and claimed herein is provided in the following related applications filed by the assignee on the same date: System And Method For Collision Matching And Information Exchange (Attorney Docket No. P108567-PRI-NP-US01); Cloud-Based Collision Detection And Information Exchange (attorney docket No. P108929-PRI-NP-US01); and Platform To Search And Retain Collision Related Data (attorney docket No. P108926-PRI-NP-US01). The entire disclosures of each of the above applications are incorporated herein by reference.Referring to FIG. 1, the present disclosure provides a system for collecting and sharing collision detections, namely a collision detection collection and sharing system (CECS), or simply a system 100 disposed on or near a road 102. For example, the system 100 is disposed around an intersection 104 of the road 102 and monitors one or more vehicles 106. While the system 100 is shown proximate to or around the intersection 104, the system 100 may be positioned at any location where a collision event may occur involving a first involved vehicle 108. The system 100 includes an observation device 110 that detects collision events in the vicinity between the involved vehicle 108 and another involved object 112, which is a second involved vehicle 114 in FIG. 1. While in this example the involved object 112 is a second involved vehicle 114, the object 112 could include a pedestrian, a stationary object, a non-motorized vehicle, or similar object present along the road 102.The observation device 110 is the third-party device that is involved but generates or monitors the collision event. The observation device 110 is in communication with at least one of a first participating vehicle 108, a second participating vehicle 114, a cloud-based platform application, or a combination thereof. In one embodiment, the monitoring device 110 is a traffic infrastructure platform 118 that is integrated into a distributed road or traffic network to aid in managing, monitoring, or improving traffic flow, safety, or efficiency. The traffic infrastructure platform 118 may include a camera 120, a smart roadside unit (not shown), or a smart traffic light module 121 (not labeled in the drawings).In another embodiment, the observation device 110 is embodied in a vehicle 122. While FIG. 1 depicts the vehicle 122 stopped at the intersection 104, the vehicle 122 may be located at any location where a collision event may occur between the first involved vehicle 108 and the second involved vehicle 114. For example, the vehicle 122 may travel along the road 102 or be parked in a stationary location. These systems may be mechanical, electrical, electronic, hydraulic, or a combination thereof configured to ensure that the vehicle 122 is operating and operating effectively under one or more conditions.Referring to FIG. 2, the observation device 110 includes an image sensor 126, a collision detection module 130, a collision detection database 124, a communication module 128, and a human machine interface (HMI) 168. The image sensor 126 captures image data 146 that captures a field of view that includes the involved vehicle 108 and the object 112. The image sensor 126 may include a camera, a lidar sensor, a radar sensor, an ultrasonic sensor, or a combination thereof. The image data 146 may include one or more images (i.e., a still image or a video), as well as time and location metadata indicating when and where the image(s) was / have been captured. Depending on the field of view of the image sensor, the image data 146 includes the environment, namely the involved vehicle 108 and object 112, road signs, or objects along the road 102. The image data 146 may be stored in the collision detection database 124. The image data 146 can be used to determine whether a collision event has occurred between the involved vehicle 108 and the object 112.The collision detection module 130 monitors, detects, and responds to collision events. The collision detection module 130 is in communication with the image sensor 126, the collision detection database 124, and the communication module 128. The collision detection module 130 includes a processing unit 156 having a processor (not shown) and a non-transitory storage medium (not shown) having instructions executed by the processor. The collision detection module 130 is configured to detect a collision event involving the involved vehicle 108 and the object 112 and transmit a detection report 144 to the involved vehicle 108, the object 112, the cloud-based platform application 116, or a combination thereof. For brevity, the present disclosure provides an example of transmitting the evidence report 144 to the involved vehicle 108. However, one skilled in the art could understand that the collision detection module 130 may transmit the detection report 144 to a second participating vehicle 114 and / or upload the detection report 144 to a cloud-based application without departing from the spirit and scope of the present disclosure.Referring to FIG. 3, the system 100 employs a method 300 to transmit a collision detection report associated with a collision event from the observation device 110, which is initiated at step 302. At step 304, the system 100 captures image data 146 from the image sensor 126. The image data 146 captures still images and / or video within the field of view. The image data 146 may include an environment in which the first involved vehicle 108 and the second involved vehicle 114 are moving relative to each other. The system 100 stores the image data 146 in a collision detection database 124 as recorded image(s) as well as time and location metadata for the image(s). The system 100 continues to step 308 and analyzes the captured image data 146 to detect a collision event between the first and second participating vehicles 108, 114. If the system 100 determines that the collision event was detected in the image data, the method 300 continues to step 310. If no collision event has been detected in the image data, the method 300 is returned at step 320.At step 308, the system 100 receives a collision message sent from a participating vehicle, namely one of the first or second vehicles. The collision message indicates that the involved vehicle has experienced a collision event, and includes temporal and geographic data for the collision event. The system 100 processes the collision message to extract the temporal and geographic data and proceeds to step 310.At step 310, the system 100 compares time and location metadata to the time and geographic data to match the image data to the collision event. In particular, time and location metadata for image(s) stored in the collision detection database is compared to the time and geographic data from the collision message to identify the image or images that captured the collision event. If the system 100 identifies one or more images of the collision event, the method 300 continues to step 312. If the system 100 does not identify images, the method 300 returns at step 320.At step 312, the system 100 determines whether a request for a evidence report has been made. In one form, the request may be stored and retrieved from the collision detection database 124 as a user-selected preference. In another form, the system 100 may prompt a user of the observation device 110 via a human machine interface (HMI) 168 to request transmission of the evidence report. In yet another form, the system 100 is configured to receive a request from a requesting party, such as the vehicle involved. If a proof report is requested, the proof collection system proceeds to step 314. If no evidence report is requested, the method returns at step 320. For the example illustrated in FIG. 3, a request for the evidence report was generated by the involved vehicle 108.At step 314, the system 100 generates a evidence report that includes the labeled image(s) of the collision event(s). The evidence report may also include the time and location metadata, or a combination thereof. The content and format of the evidence report may be stored and retrieved as a report preference from the collision evidence database 124. After the evidence report is generated, the method 300 continues to step 316, where the system 100 and the participating vehicle 108 execute a protocol communication handshake to establish a secure connection for the system 100 to communicate with the participating vehicle 108. The system 100 requests a response to confirm that the involved vehicle 108 desires a detection report for the collision event. After initiating the protocol communication connection with the involved vehicle 108, the system 100 encrypts and transmits an encrypted evidence report to the involved vehicle 108 over the communication connection at step 318. The system 100 encrypts the proof report with a public key that can be decrypted by the participating vehicle 108 using an associated private key. Once the encrypted proof report has been transmitted, the method returns at step 320.Referring again to FIG. 2, the collision detection module 130 may use a collision detection model 160 to determine whether the collision event was detected in the image data 146. For example, the collision detection model 160 may be a machine learning model that analyzes the image data 146 to detect whether the involved vehicle has experienced a collision event. Based on detecting the collision event, the collision detection module 130 identifies a plurality of objects in the image data and determines which of the plurality of objects is the involved vehicle using an image processing model 162. The image processing model 162 includes a convolutional neural network (CNN) that is used to analyze the image data to detect the presence of objects in the vicinity. In doing so, the CNN extracts key features such as edges, contours, and textures to distinguish between objects. The collision detection module 130 identifies a vehicle that may have been involved in a collision with another object (i.e., a vehicle involved). Once a involved vehicle is identified, the collision detection module 130 may further classify the involved vehicle based on a vehicle make, a vehicle model, and a vehicle color. The collision detection module 130 may request confirmation of the vehicle make, model, and color of the collision-related vehicle by requesting a user, via the HMI 168, to create an image (images) of the involved vehicle based on a display of the vehicle make, model, and color.The collision detection module 130 may also determine whether the collision message 140 has been sent by the involved vehicle 108. The collision detection module 130 may further identify the involved vehicle 108 by comparing the image data of the involved vehicle to the vehicle make, model, and color provided in the collision message.The collision detection database 124 stores and manages data related to the operation, performance, and history of the system 100. In one example, the collision detection database 124 is in communication with the communication module 128, the image sensor 126, and the collision detection module 130. The collision detection database 124 continuously receives and stores the image data 146 from the image sensor 126. The collision detection database 124 also stores the collision message 140 sent from the involved vehicle 108. The collision message 140 may be a vehicle-to-vehicle protocol message sent by the participating vehicle 108 and indicating that it has collided with an object, such as a second participating vehicle 108. The collision message 140 also includes a location of the collision, a time of the collision, a vehicle identification, a vehicle make, a vehicle model, a vehicle color, and an impact location on the involved vehicle during the collision event. The collision evidence database 124 is also configured to store the evidence report once it is generated.In some forms, the collision evidence database 124 manages and stores a plurality of settings / preferences 148 for automatically generating and transmitting an evidence report 144 to the involved vehicle 108. For example, the collision evidence database 124 stores a first user setting set (not shown) related to requesting permission to transmit the evidence report set to "YES", indicating that the evidence report is automatically generated and transmitted to the involved vehicle 108. Conversely, the first user setting set (not shown) related to requesting permission to transmit the evidence report is set to "NO", indicating that the evidence report should not be automatically transmitted to the involved vehicle 108. The collision evidence database 124 stores at least one of a public encryption key 150 and a private decryption key 152. The public encryption key 150 is used to securely encrypt the proof report to be transmitted to the involved vehicle 108. The private encryption key 152 is maintained confidential and is used to decrypt encrypted messages received from another V2V vehicle or device. In one form, the collision detection database 124 includes a plurality of input responses based on selections set by a user of the HMI 168.The communication module 128 includes a processor (not shown) and a non-transitory computer readable storage medium (not shown) configured to store instructions executed by the processor. The communication module 128 enables the exchange of messages between the system 100 and vehicles 106 within a predetermined range. The communication module 128 transmits or sends messages (e.g., data packets containing messages or data) using a dedicated communication protocol such as dedicated short-range communication (DSRC), cellular vehicle-to-everything (C-V2X), vehicle-to-infrastructure (V2I), vehicle-to-people (V2P), 5GL cellular communication, or the like. The observer device 110 transmits with low latency to ensure that nearby vehicles 106 can quickly receive and process data from the communication module 128 of the system 100. Once a connection is established, communication module 128 also manages the incoming and outgoing data transmission for viewing device 110. The communication module 128 employs asymmetric encryption to secure transmitted or exchanged messages between the observation device and the involved vehicle 108. The communication module 128 receives the collision message 140 sent from the involved vehicle 108. The communication module 128 may also exchange text messages, either automatically or by user input, to transmit requests to transmit the evidence report with the vehicle 108 involved.The communication module 128 encrypts the proof report using the public key. After encryption, the communication module 128 transmits an encrypted evidence report 144 to the involved vehicle 108. The communication module 128 may determine whether a transmitted evidence report was successfully received from the participating vehicle 108. For example, the communication module 128 waits a predetermined period of time to determine whether the transmission to the involved vehicle 108 was successful. The communication module 128 may receive an acknowledgement message from the participating vehicle 108 112 indicating that the transmission was successful. In this example, the communication module 128 determines that a successful transmission has occurred if the acknowledgement message is received within the predetermined time period. The communication module 128 may display a successful transmission message to a user of the system 100. The communication module 128 may determine that successful transmission has not occurred if the acknowledgement message was not received from the involved vehicle within the predetermined time period. In this example, the communication module 128 may display an unsuccessful transmission message to a user of the system 100.The HMI 168 allows a user of the system 100 to interact with the collision detection module 130 and manage various functions of the system 100. The HMI 168 may include a plurality of user selection inputs that enable a user of the system 100 to respond to one or more prompts. For example, the HMI 168 may display and audibly output a prompt and / or response to a user of the system 100. In one form, the HMI 168 includes an audio system (not shown) and / or a display screen (not shown), such as a touch screen. The audio system may include a speaker and a microphone. The HMI 168 requests a message to verify that the image data 146 includes a collision event between the involved vehicle 108 and the identified object 112. The input associated with the user may include a positive response input ("YES") and a negative response input ("NO"). The positive response input confirms the user's selection to proceed to a selected task. The negative response input negates the user's desire to continue with the selected task. The HMI 168 may initiate a request for a message on the display with a user selection input to verify whether the involved vehicle 108 identified in the image data 146 matches the vehicle that sent the collision message. The HMI 168 requests a message displayed on the display for the user and includes a transmission request to transmit the evidence report to the involved vehicle. The HMI 168 may enable input associated with a text component to exchange communication with the vehicle involved, such as alphanumeric text.

Claims

A system (100) for collecting detection of a collision event on a road (102) with an observer device (110), comprising: an image sensor (126) configured to capture image data (146) of the road (102) during the collision event, the image data (146) including time and location metadata; a communication module (128) configured to receive a collision message (140) sent by a vehicle (106) involved in the collision event, the observer device (110) being independent of the involved vehicle (106); a detection collection module in communication with the image sensor (126) and including a processing unit configured to: capture image data (146) from the image sensor (126); process the image data (146) to determine whether the collision event has been captured; acquiring temporal and geographical data from the collision message (140) collected by the involved vehicle (106) during the collision event; comparing the time and location metadata to the temporal and geographical data to match the image data (146) to the collision event; To generate a proof report (144) when (i) the time and location metadata matches the time and geographic data, and (ii) the image data (146) captured the collision event, the proof report (144) including an image of the collision event, a human machine interface (168) in communication with the proof collection module, the human machine interface (168) configured to request a response input from a user to verify when the image data (146) matches the collision event.The system (100) of claim 1, wherein the image sensor (126), the communication module (128), and the detection collection module are embodied in a traffic infrastructure platform (118), and the image sensor (126) is disposed proximate the roadway (102) for capturing (304) image data (146).The system (100) of claim 1, wherein the image sensor (126), the communication module (128), and the detection collection module are embodied in a vehicular vehicle (122), and the image sensor (126) is disposed proximate the roadway (102) for capturing (304) image data (146).The system (100) of claim 1, wherein the processing unit is further configured to: identify the involved vehicle (106) captured in the image data (146) having the collision event; classify an identified vehicle (106) captured in the image data (146) having the collision event based on a vehicle make (106), a vehicle model (106), and a vehicle color (106); confirm the vehicle make (106), the vehicle model (106), and the vehicle color (106) of the identified vehicle (106) based on the collision message (140); and transmit the detection report (144) to the involved vehicle (106) when the vehicle make (106), the vehicle model (106), and the vehicle color (106) of the identified vehicle (106) are confirmed.The system (100) of claim 1, wherein the communication module (128) is further configured to transmit the evidence report (144) in response to a request therefor.The system (100) of claim 1, wherein the evidence report (144) is transmitted to the involved vehicle (106) based on the collision message (140).The system (100) of claim 1, wherein the processing unit is further configured to: generate an encrypted proof report (144) having a public key; and transmit the encrypted proof report (144) to the involved vehicle (106) over a communication link in response to a request received by the communication module (128) from the involved vehicle (106).The system (100) of claim 7, further comprising: a human machine interface (168) in communication with the communication module (128); wherein the communication module (128) is further configured to receive an acknowledgement from the involved vehicle (106) confirming that the encrypted evidence report (144) has been received; and wherein the human machine interface (168) is configured to display an indicator confirming receipt of the encrypted evidence report (144) by the involved vehicle (106).A method for collecting detection of a collision event on a road (102) with an observer device (110), the method comprising: acquiring (304) image data (146) with an image sensor (126) having a field of view of the road (102), the image data (146) including time and location metadata; processing the image data (146) to determine whether the collision event has been detected, the processing comprising: receiving (308) a collision message (140) sent by a vehicle (106) involved in the collision event on the road (102), the collision message (140) including time and geographical data collected by the involved vehicle (106) during the collision event, wherein the observer device (110) is independent of the involved vehicle (106); identifying a collided vehicle (106) detected in the image data (146) with the collision event; classifying an identified vehicle (106) detected in the image data (146) with the collision event based on a vehicle make (106), a vehicle model (106), and a vehicle color (106); confirming the vehicle make (106), the vehicle model (106), and the vehicle color (106) of the identified vehicle (106) based on the collision message (140); comparing the time and location metadata to the time and geographic data to match the image data (146) with the collision event; requesting a response input from a user to verify when the image data matches the collision event; generating (314) a evidence report (144) if (i) the time and location metadata matches the time and geographic data, (ii) the image data (146) detected the collision event, and (iii) the vehicle make up (106), the vehicle model (106), and the vehicle color (106) of the identified vehicle (106), the evidence report (144) including an image of the collision event; encrypting (318) the evidence report (144) with a public key; and transmitting the encrypted evidence report (144) to the involved vehicle (106).

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