Title of Invention: DETECTING AND HANDLING MATERIAL LEFT IN VEHICLES BY TRANSPORTATION REQUESTORS Abstract: The present disclosure includes embodiments of systems, methods, and computer readable media that enable a dynamic transportation system to detect when material has been left in a vehicle by a requestor. In some embodiments, the system detects the completion of the transportation request, analyzes data from a plurality of vehicle sensors, from a computing device associated with the vehicle, and from a computing device associated with the requestor, and then determines, based on the data analysis, that material has been left in the vehicle. The system then performs an action for handling the material based on one or more attributes of the material. Detailed Description: CROSS REFERENCE TO RELATED APPLICATIONS The present application is a continuation of U.S. application Ser. No. 16/189,866, filed on Nov. 13, 2018 which is a continuation of U.S. application Ser. No. 15/859,629, filed Dec. 31, 2017, which issued as U.S. Pat. No. 10,127,795. Each of the aforementioned applications are hereby incorporated by reference in their entirety. BACKGROUND Modern technologies now facilitate the use of mobile app-based transportation matching systems. For instance, when users are traveling or are in situations where renting a vehicle or using a user's own vehicle is burdensome, inefficient, or unavailable, users frequently utilize transportation matching systems to get to where they need to go. These transportation matching systems receive transportation requests from requestor computing devices, and then match the transportation requests to provider computing devices. However, conventional transportation matching systems suffer from several disadvantages that detrimentally affect system efficiency. One disadvantage posed by many conventional transportation matching systems is that technical issues limit conventional systems from detecting and properly handling material left in provider vehicles by requestors. For example, in many conventional transportation systems, if a requestor leaves something in the vehicle, the provider or requestor may not initially notice. Furthermore, in many instances, at the time a provider drops off one requestor, the transportation matching system has already matched the provider to another transportation request. As a result, once the left material is noticed, conventional systems often must cancel the provider's subsequent transportation request, which wastes time and resources for both the provider and the transportation matching system, and results in a negative transportation experience for the requestors. This problem is further aggravated if the requestor leaves a mobile device in the vehicle, in which case conventional systems are typically unable to contact or locate the requestor. Not only is this inconvenient for requestors and providers, it causes an undue strain on the bandwidth, efficiency, and processing time of conventional systems, which have to process and manage the resulting cancellations, additional transportation requests, and intermittent availability of providers. These and other disadvantages exist with regard to the conventional transportation systems. SUMMARY Systems, methods, and computer readable media described herein enable dynamic transportation matching systems to match transportation requests received from requestor computing devices with vehicle computing devices, detect completion of the transportation request, and analyze data from a plurality of sources, including but not limited to sensors within a vehicle, a computing device associated with the vehicle, and a requestor's computing device. Based on the analyzed data, the dynamic transportation matching system determines that material has been left in the vehicle by the requestor and performs an action for handling the material left in the vehicle based on attributes of the material. Embodiments of the present disclosure provide benefits and/or solve one or more of the foregoing or other problems in the art. Specifically, the disclosed system utilizes data obtained from multiple sources to efficiently detect and handle material (e.g., mobile devices, personal items, or waste) left within a vehicle associated with a transportation network. The features and embodiments disclosed herein allow transportation systems to resolve problems associated material left in vehicles without the typical inconvenience, inefficiency, and system strain caused in conventional transportation systems. Not only do the embodiments disclosed herein lessen frustration for transportation requestors and providers, but they also improve system efficiency by avoiding the resulting transportation request cancellations, repeated transportation requests, updated optimization calculations, and provider dispatch modifications from bogging down the system and slowing processing time. Indeed, the embodiments disclosed herein increase processing speed of the system overall by more effectively and efficiently detecting when material is left in a vehicle and identifying the actions necessary to handle the material that is left in a vehicle. Additional features and advantages of the present disclosure will be set forth in the description that follows, and in part will be obvious from the description, or may be learned by the practice of such exemplary embodiments. The features and advantages of such embodiments may be realized and obtained by means of the instruments and combinations particularly pointed out in the appended claims. These and other features will become more fully apparent from the following description and appended claims, or may be learned by the practice of such exemplary embodiments as set forth hereinafter. BRIEF DESCRIPTION OF THE DRAWINGS Various embodiments will be described and explained with additional specificity and detail through the use of the accompanying drawings in which: FIG. 1 illustrates an example environmental diagram of the dynamic transportation matching system in accordance with one or more embodiments; FIG. 2 illustrates an example sequence flow diagram of the transportation matching system determining that material has been left in a vehicle in accordance with one or more embodiments; FIGS. 3A-3C illustrate a plurality sensors associated with a vehicle detecting that material has been left in the vehicle, in accordance with an embodiment of the present techniques; FIG. 4 illustrates an example of the dynamic transportation matching system detecting that a requestor computing device has been left in the vehicle, in accordance with an embodiment; FIG. 5 illustrates an example flow diagram of training a machine learning model in accordance with one or more embodiments; FIG. 6 illustrates a further detailed environmental diagram of a dynamic transportation matching system in accordance with one or more embodiments disclosed herein; FIG. 7 illustrates a flowchart of a series of acts in a method of determining that material has been left in the vehicle in accordance with one or more embodiments; FIG. 8 illustrates a block diagram of an exemplary computing device in accordance with one or more embodiments; and FIG. 9 illustrates an example environment for a transportation system in accordance with one or more embodiments. DETAILED DESCRIPTION This disclosure describes a dynamic transportation matching system (hereinafter “transportation system”) that accesses and analyzes data from a plurality of vehicle sensors, computing devices associated with vehicles, and computing devices associated with requestors to determine that material (e.g., a cell phone or waste) has been left in the vehicle. In particular, a dynamic transportation matching system accesses data from the plurality of sensors, a requestor computing device, and a computing device associated with the vehicle (or “vehicle computing device”). After detecting that a transportation request is complete (i.e., that a requestor has been dropped off at a destination), the system analyzes the data to determine whether material has been left in the vehicle. If the transportation system detects that material has been left in the vehicle, the transportation system identifies and performs an action for handling the material based on one or more attributes of the material. In some embodiments, the system uses data received from requestor and vehicle computing devices to detect that the requestor computing device (e.g., the requestor's mobile device) has been left in the vehicle after the requestor was dropped off at a destination. For example, in at least one embodiment, in order to determine whether the requestor's computing device is still in the vehicle, the system determines a relative proximity or distance between the requestor computing device and vehicle computing device. For instance, the system may obtain GPS location data from both devices to compare the geographical locations of the devices. Additionally, the system may receive indications from each device regarding the presence and strength of communication signals (e.g., Bluetooth signals) sent/received between the devices to determine a proximity of the devices. Using the location and communication information, the system can detect whether the requestor computing device is within a proximity to the vehicle computing device even after the vehicle computing device has moved away from the dropoff location, thereby indicating that the requestor computing device was left in the vehicle. In addition to analyzing and comparing the locations of the computing devices, in some embodiments, the system analyzes motion data associated with the computing devices to determine if a requestor computing device has been left in a vehicle. For example, the system may receive data collected by motion sensors in the requestor computing device and the vehicle computing device (i.e., a provider computing device and/or a computing device integrated within a vehicle) indicating movement of the requestor computing device, the vehicle computing device, and/or the vehicle. For instance, the motion data can include accelerometer data, gyroscope data, proximity sensor data, magnetometer data, etc. Using the received motion sensor data, the system can, for example, determine acceleration, speed, and rotation of the requestor computing device, the vehicle computing device, and the vehicle. In some embodiments, the system compares the motion data from the requestor computing device to the motion data from the vehicle computing device to identify consistencies between the data (e.g., similar acceleration, speed, and rotation), thereby indicating that the devices are in the same vehicle. In further embodiments, the system analyzes the motion data from the requestor computing device independently to determine if the motion of the requestor computing device is more consistent with traveling in a vehicle (indicating that the device is still in the vehicle) or on a person walking (indicating that the device is being carried by the requestor after being dropped off by the vehicle). In addition to analyzing data from motion sensors in the requestor computing device and the vehicle computing device, the system may analyze interaction data associated with other sensors or detection devices (e.g., cameras, microphones, touchscreens, proximity sensors, buttons) of the requestor computing device to determine if the requestor computing device has been left in the vehicle. For example, the system may receive data collected by touchscreen sensors associated with the requestor computing device indicating requestor interaction with the requestor computing device. Additionally, the system may receive camera image data from the requestor computing device and determine whether the data is consistent with being left in the vehicle (e.g., if the image is of the interior of a car) as opposed to being consistent with being in the possession of the requestor (e.g., if the image includes the face of the requestor). The system may also access data from other sensors such as the ambient light sensor and identification sensors (e.g., fingerprint sensor or facial recognition) for the requestor computing device. For instance, the system may determine that the requestor computing device has not been left in the vehicle based on data indicating that the requestor has recently (i.e., after the requestor was dropped off) used a fingerprint sensor or facial recognition function on the requestor computing device to unlock the device. In yet further embodiments, the system may determine that the requestor computing device has been left in the vehicle if audio data collected by a microphone of the requestor computing device is similar to audio data collected by a microphone of the vehicle computing device. In addition to analyzing interaction data from the requestor computing device, in at least one embodiment, the system uses data received from a plurality of sensors associated with the vehicle (e.g., sensors within the vehicle) to detect that material has been left in the vehicle. For example, the plurality of sensors can include one or more microphones for collecting audio data within the vehicle, one or more cameras for capturing images/video within the vehicle, one or more weight sensors for sensing weight on the seats within the vehicle, one or more olfactory or air quality sensors for sensing impurities or irregularities within the air of the vehicle, and/or one or more moisture sensors for detecting moisture within the vehicle (e.g., on the seats or carpet of the vehicle). Using the data from the plurality of sensors, the system can, for example, detect sounds caused by an item left in the vehicle, detect objects within images of the interior of the vehicle (e.g., utilizing one or more object detection algorithms on the captured images), detect the weight of an item left on a seat in the vehicle, detect moisture in a seat or other upholstery of the vehicle, and/or detect odors caused by material left in the vehicle. In some embodiments, the system gathers data from the sensors before picking up a requestor, during transportation of the requestor, and/or after the requestor is dropped off. Using the gathered data, the system is able to, for example, learn a baseline for each sensor that represents a state of the vehicle prior to picking up a requestor. The system can then compare the data gathered after the requestor has been dropped off to the baseline data to identify changes indicating that material was left in the vehicle by the requestor. In some embodiments, the system trains a machine learning model to analyze the data and determine whether material has been left in the vehicle. By using a comprehensive suite of sensors and corresponding data analysis, the system is able to identify a wide range of material (e.g., personal items, garbage, and bodily fluids) as opposed to, for example, just electronic devices. Using the collected and analyzed data discussed above and in more detail below, the system is able to determine whether material has been left in a vehicle after a requestor has been dropped off at a location. In some embodiments, the system aggregates the date and calculates a confidence score indicating a likelihood that material has been left in the vehicle. For example, the system can determine whether each piece of data indicates that material has been left in the vehicle, and then aggregate these indications and calculate a confidence score of how strongly the data indicates the presence of material in the vehicle. Additionally, the system can weight the effect of each type of data on the confidence score based on, for example, a reliability of each type of data in predicting the presence of material in a vehicle, an amount of each type of data, a consistency of multiple sources of data, and a strength of correlation between different types of data and different materials. The system can then use the calculated score to determine whether material has been left in the vehicle (e.g., by comparing the confidence score to a predetermined threshold). In addition to determining whether material has been left in a vehicle, the system can identify one or more attributes of the material. For example, using the gathered data and corresponding analysis, the system can determine a type of material left in the vehicle, a quantity of the material left in the vehicle, a size and shape of the material left in the vehicle, a color of the material left in the vehicle, etc. Using the determined attributes of the material, the system can then identify and execute an action for handling the material that is customized for the specific attributes of the material. As mentioned, the system can perform an action for handling material left in a vehicle. Furthermore, the action can be specific to the attributes of the material. In some embodiments, the system automatically performs the action without human intervention. For example, the system can automatically take the vehicle out of service (e.g., by not matching additional transportation requests to the vehicle computing device), alert a driver of the vehicle (e.g., via an automated notification, text message, or phone call), reassign a subsequent transportation request originally matched to the vehicle to another vehicle/provider, cause the vehicle to return to the destination location of the requestor, alert the requestor (e.g., via an automated notification, text message, or phone call to the requestor computing device), alert a third-party associated with the requestor (e.g., a traveling companion or emergency contact), or cause the vehicle to travel to a service station. In accordance with the foregoing, the system is able to quickly and efficiently identify and remedy situations involving material left in vehicles by requestors, thereby easing the burden and processing drag typically resulting from such situations. For this and other reasons, the current disclosure improves the functioning of computer systems associated with transportation systems. Furthermore, the disclosed system is able to analyze, detect, and address materials left in vehicles, of which conventional systems are incapable. Turning now to the figures, FIG. 1 illustrates a schematic diagram of an environment 100 for implementing a dynamic transportation matching system 112 (or “transportation system 112”) in accordance with one or more embodiments. This disclosure provides an overview of the dynamic transportation matching system 112 with reference to FIG. 1. After providing an overview, the disclosure describes components and processes of the dynamic transportation matching system 112 in further detail with reference to subsequent figures. As used herein, the term “requestor” refers to person (or group of people) who use a computing device to submit a transportation request to a dynamic transportation matching system. A requestor may refer to a person who requests a ride or other form of transportation but who is still waiting for pickup. A requestor may also refer to a person whom a transportation vehicle has picked up and who is currently riding within the transportation vehicle to a destination location (e.g., a destination indicated by a requestor). Additionally, a requestor may refer to a person whom a transportation vehicle has dropped off at a destination location. A requestor may be associated with the requestor computing device 116. Accordingly, the term “requestor computing device” refers to a computing device associated with a requestor. Typically, a requestor computing device includes a mobile device, such as a laptop, smartphone, or tablet associated with a requestor. But the requestor computing device 116 may be any type of computing device. A requestor computing device 116 includes requestor application 118. In some embodiments, the requestor application 118 comprises a native or web-based application used for interacting with the dynamic transportation matching system 112. A requestor computing device may also contain sensors including touch sensors, cameras, ambient sensors, and identification sensors (e.g., fingerprint sensors and facial recognition). Additionally, in some instances, the dynamic transportation matching system 112 provides data packets including instructions that, when executed by the requestor computing device 116, instruct create or otherwise integrate transportation application 106 within an application or webpage. Relatedly, the term “provider” refers to a driver or other person who operates a transportation vehicle and/or who interacts with a vehicle computing device. For instance, a provider includes a person who drives a transportation vehicle along various routes to pick up and drop off requestors. In certain embodiments, the vehicle subsystem 102 is associated with a provider. However, in other embodiments, some or all of the vehicle subsystems 102 is not associated with a provider, but rather includes an autonomous transportation vehicle—that is, a self-driving vehicle that includes computer components and accompanying sensors for driving without manual input from a human operator. When a transportation vehicle is an autonomous vehicle, the transportation vehicle may include additional components not depicted in FIG. 1, such as location components, one or more sensors by which the autonomous vehicle navigates, and/or other components necessary to navigate without a provider (or with minimal interactions from a provider). As shown in FIG. 1, the environment 100 includes the dynamic transportation matching system 112 located on server(s) 110, requestor computing device 116, and vehicle subsystem 102. The dynamic transportation matching system 112 may communicate with the vehicle subsystem 102 and the requestor computing device 116 via the network 120. For example, the dynamic transportation matching system 112 communicates with the vehicle computing device 104 and the requestor computing device 116 via the network 120 to determine locations of the vehicle computing device 104 and the requestor computing device 116. Per device settings, for instance, the dynamic transportation matching system 112 may receive location coordinates from the vehicle computing device 104 and/or the requestor computing device 116. Based on the location coordinates, the dynamic transportation matching system 112 determines the geographic area in which the vehicle computing device 104 and/or the requestor computing device 116 are located. As used in this disclosure, the term “destination location” refers to a geographic location in a larger geographic area. A destination location may be an area specified by the requestor computing device as the final destination of a transportation request. For example, the requestor computing device may specify an address as the destination location. A destination location may also be the area in which a requestor is dropped off and leaves the vehicle. As used herein, “transportation request” refers to a request from one computing device. More specifically, a transportation request is a request sent by the requestor computing device that includes relevant information to enable the vehicle subsystem 102 to locate and transport thee requestor to a destination location. In at least one embodiment, a transportation request may include information such as the desired pickup location and destination location. For example, a requestor associated with requestor computing device 116 may input, via the requestor application 118, an address as a destination location and the requestor' s current location as a pickup location. The requestor application 118 may compile this information and other relevant information and send the information as a transportation request to the transportation matching system 110, which matches the transportation request to an available vehicle subsystem (such as vehicle subsystem 102). The transportation request is completed when the requestor associated is dropped off at the destination location. For example, transportation request completion may be detected by the transportation matching system 112 based on communications received from the vehicle computing device 104 and/or requestor computing device 116 indicating user input or an automatic detection that the requestor has been dropped off at the destination location. In some embodiments, the dynamic transportation matching system 112 sends a request from the requestor computing device 116 to the vehicle computing device 104 within a vehicle subsystem 102. As used herein, term “vehicle subsystem” refers to a system comprising a vehicle, computing device, and other components. For example, a vehicle subsystem includes a transportation vehicle (not shown), vehicle sensors (such as vehicle sensors 108), and a computing device associated with the vehicle or corresponding provider (such as the vehicle computing device 104). The transportation vehicle may be an automobile or other vehicle. In some embodiments, the computing device associated with the vehicle performs functions for facilitating completion of a transportation request and/or controls the operation of various functions of the vehicle subsystem. For example, when the dynamic transportation matching system 112 sends a transportation request to the vehicle subsystem 102—or queries location information from the vehicle subsystem 102—in some embodiments the dynamic transportation matching system 112 sends the transportation request or location query to the vehicle computing device 104. The vehicle computing device 104 may be associated with a human operator (or “provider”) of the vehicle subsystem 102, or may be integrated into the vehicle subsystem. Furthermore, although FIG. 1 illustrates a single vehicle computing device, in other embodiments, the vehicle subsystem 102 can include multiple computing devices associated with corresponding providers or integrated into the vehicle itself. As illustrated in FIG. 1, the environment 100 includes material detection system 114 as part of the dynamic transportation matching system 112. The material detection system 114 may communicate with the dynamic transportation matching system 112 regarding transportation requests. More specifically, the material detection system 114 may receive data from the dynamic transportation matching system 112 regarding a transportation request received from the requestor computing device 116 and matched to the vehicle subsystem 102. In some embodiments, the data indicates a status of the transportation request (e.g., whether the requestor associated with requestor computing device 116 has been picked up, if the requestor is in the vehicle, a progress of the vehicle along the requested route, and when the requestor has been dropped off at a destination location). The material detection system 114 also detects when a requestor associated with the requestor computing device 116 has left material in the vehicle of the vehicle subsystem 102. As used herein, the term “material” refers to any personal items or other matter that might be introduced into the vehicle by a requestor. For example, material may include electronics (e.g., the requestor computing device), other personal items (e.g., purse, backpack, food, and drink), bodily fluids (e.g., vomit, urine), and other matter left behind by a requestor. To illustrate, a requestor may leave a mobile device and a backpack in the vehicle at the end of a ride. The material detection system 114 may be configured to collect data from various data collection devices including vehicle sensors 108, requestor computing device 116, and vehicle computing device 104. The material detection system 114 collects data to determine whether the requestor associated with the requestor computing device 116 has left material in the vehicle. For example, material detection system 114 receives data from the data collection devices before the requestor enters the vehicle, while the requestor is in the vehicle, and/or after the requestor has left the vehicle at the destination location. Material detection system 114 may analyze the collected data to determine whether material has been left in the vehicle after the transportation request has been completed (i.e., the requestor has been dropped off at a destination location), as will be discussed in more detail below. In addition to detecting the presence of material left in a vehicle, the material detection system 114 further discerns attributes of the material left in the vehicle, based on the collected data, to determine an appropriate action to handle the material left in the vehicle. Additionally, material detection system 114 communicates with vehicle computing device 104, requestor computing device 116, and other components of the dynamic transportation matching system 112 as part of performing an appropriate action for handling the material. For example, the material detection system 114 may call or message the vehicle computing device 104, call or message the requestor computing device 116, or cause the vehicle subsystem 102 to return to the destination location where the requestor was dropped off. In some embodiments, the material detection system 114 uses an appropriate operating system as well as various server applications, such as common gateway interface (CGI) servers, JAVA servers, hypertext transport protocol (HTTP) servers, file transfer protocol (FTP) servers, database servers, etc. As illustrated, the material detection system 114 is located on the server(s) 110. However, in one or more embodiments, one or more components of the material detection system 114 may be integrated locally into the vehicle subsystem 102. In some embodiments, the vehicle subsystem includes one or more vehicle sensors 108, as shown in FIG. 1. The term, “vehicle sensors” refers to a plurality of sensors associated with the vehicle. For instance, in some embodiments, the vehicle sensors 108 collect data associated the vehicle interior. For example, the vehicle sensors 108 can include cameras, moisture sensors, audio sensors, olfactory sensors, or weight/pressure sensors associated with the vehicle subsystem 102. The vehicle sensors 108 send collected data to the dynamic transportation matching system 112 (e.g., using the transportation application 106) for analysis by the material detection system 114. For instance, vehicle subsystem 102 may send, to the material detection system 114 digital images from the vehicle interior before the vehicle picked up a requestor associated with requestor computing device 116 and after the vehicle has dropped off the requestor associated with the requestor computing device 116. As will be described in more detail below, the material detection system 114 can then analyze the data to detect the presence of material left in the vehicle by the requestor. As mentioned, the vehicle subsystem 102 may be associated with a human provider (i.e., operator) of the vehicle subsystem 102. In other embodiments, the vehicle subsystem 102 includes an autonomous or self-driving vehicle, including a computer-based navigation and driving system (e.g., controlled or facilitated by the vehicle computing device 104). Regardless of whether the vehicle subsystem 102 is human-operated or autonomous, the vehicle subsystem 102 may also include a locator device, such as a GPS device, that determines the location of the vehicle subsystem 102. As mentioned above, the vehicle subsystem 102 includes vehicle computing device 104. The vehicle computing device 104 may be separate or integrated into the vehicle itself. For example, the vehicle computing device 104 may refer to a separate mobile device, such as a laptop, smartphone, or tablet associated with the vehicle subsystem 102. But the vehicle computing device 104 may be any type of computing device. Additionally, or alternatively, the vehicle computing device 104 may be a subcomponent of a vehicle computing system. Regardless of its form, the vehicle computing device 104 may include various sensors, such as a GPS locator, an inertial measurement unit, an accelerometer, a gyroscope, a magnetometer, a Bluetooth signal sensor/antenna, and/or other sensors that collect information and data regarding the location, current state, and surroundings of the vehicle computing device 104. As further shown in FIG. 1, the vehicle computing device 104 includes transportation application 106. In some embodiments, the transportation application 106 comprises a native software application that facilitates interactions with the dynamic transportation matching system 112 (e.g., to receive transportation requests). Additionally, in some instances, the dynamic transportation matching system 112 provides data packets including instructions that, when executed by the vehicle computing device 104, create or otherwise integrate the transportation application 106 within an application or webpage. In some embodiments, the dynamic transportation matching system 112 communicates with the vehicle computing device 104 through the transportation application 106. Additionally, the transportation application 106 optionally include computer-executable instructions that, when executed by the vehicle computing device 104, cause the vehicle computing device 104 to perform certain functions. For instance, the transportation application 106 can cause the provider computing device 106 to communicate with the material detection system 114 to determine an appropriate action for handling material left in the vehicle. In certain embodiments, the dynamic transportation matching system 112 matches transportation requests with available providers. For instance, the dynamic transportation matching system 112 manages the distribution and allocation of transportation requests to the vehicle subsystem 102 based on, for example, location and availability indicators. To facilitate matching requests with transportation vehicles, the dynamic transportation matching system 112 communicates with the vehicle computing device 104 (through the transportation application 106) and with the requestor computing device 116 (through the requestor application 118). As shown in FIG. 1, the server(s) 110 may comprise one or more server devices that implement the dynamic transportation matching system 112. The server(s) 110 can also comprise a communication server or a web-hosting server. Additional details regarding the server(s) 110 will be discussed below. FIG. 2 illustrates a series of acts performed by the vehicle subsystem 102, the matching detection system 114, and the requestor computing device 116 in accordance with one or more embodiments of the features disclosed herein. While FIG. 2 illustrates a single requestor computing device 116 and a single vehicle subsystem 102, it will be understood from this disclosure that the dynamic transportation matching system 112 can similarly interact with any number of additional vehicle subsystems (or computing devices associated with a vehicle/provider) and requestor computing devices. Furthermore, while FIG. 2 illustrates a particular order or sequence for the acts depicted therein, the acts may be performed in an alternative order and may further include additional or alternative acts as well. As illustrated by sequence 200 of FIG. 2, the requestor computing device 116 sends a ride request to the dynamic transportation matching system 112, as depicted by act 202. Initially, the dynamic transportation matching system 112 receives a transportation request from requestor application 118 on the requestor computing device 116. The transportation request may include a pick up location for the ride request, a requestor identifier, a requestor computing device location, a destination location, and/or any other relevant information associated with the transportation request and/or requestor. As further illustrated in FIG. 2, the dynamic transportation matching system 112 matches the transportation request 204. To match the transportation request 204, the dynamic transportation matching system 112 identifies and assigns vehicle computing device 104 of vehicle Attorney Docket No. 204.184.229.179 19 Patent Application subsystem 102) as a match to pick up and transport the requestor associated with requestor computing device 116. In matching the vehicle computing device 104 to the received transportation request, the dynamic transportation matching system 112 utilizes information received from the vehicle computing device 104, such as the current location of the vehicle computing device 104, to assign the transportation request to the vehicle computing device 104. In some embodiments, the vehicle computing device 104 may automatically accept the received transportation request. In other embodiments, a provider associated with vehicle computing device 104 provides user input to accept the transportation request. As part of step 204, the dynamic transportation matching system 112 may receive a response indicating acceptance of the transportation request. Furthermore, the dynamic transportation matching system 112 provides information to the vehicle computing device 104 to facilitate completion of the transportation request. For example, the dynamic transportation matching system 112 may send the vehicle computing device 104 pickup location information, route information, destination location information, and user profile information. The dynamic transportation matching system 112 can monitor the location of the vehicle computing device 104 and the requestor computing device 116 and send location information to the respective other device. Thus, as the vehicle computing device 104 gets closer to pick up location, the dynamic transportation matching system may monitor the location of the vehicle computing device 104 and send the location of the requestor computing device 116 to the vehicle computing device 104. Additionally, the transportation matching system 112 can monitor the location of the vehicle computing device 104 and the requestor computing device 116 while the vehicle computing device 104 is on route to the destination location. Furthermore, in some embodiments, the requestor computing device 116 may communicate locally and directly with the vehicle computing device 104 (e.g., using Bluetooth communications), as will be explained in more detail below. At step 206 of FIG. 2, the dynamic transportation matching system 112 detects the completion of the matched transportation request. For example, dynamic transportation matching system 112 detects completion of the transportation request based on a communication received from the vehicle computing device 104 or requestor computing device 116, indicating that the requestor has been dropped off at a destination location. In some embodiments, the transportation application 106 sends the dynamic transportation matching system 112 a dropoff notification. The vehicle subsystem 102 may send the dropoff notification when the provider associated with the vehicle subsystem 102 indicates that the requestor has been dropped off. Alternatively, the vehicle computing device 104 associated with an autonomous vehicle may automatically detect that the requestor has been dropped off, and then send the indication to the dynamic transportation matching system 112. As illustrated in FIG. 2, at step 208, the material detection system 114 receives data from the vehicle subsystem 102 and the requestor computing device 116. Data from the vehicle subsystem 102 includes data collected by the vehicle sensors 108. For example, the vehicle sensors 108 may include cameras, audio sensors, pressure sensors, moisture sensors, olfactory sensors, and/or additional sensors. Data may be collected by the vehicle sensors 108 before the requestor entered the vehicle, while the requestor was in the vehicle, and/or after the requestor exited the vehicle. In some embodiments, the vehicle computing device 104 communicates locally with the vehicle sensors 108 to gather the collected data and then send the data to dynamic transportation matching system 112. The data can also include data sensed/collected by the requestor computing device 116 and vehicle computing device 104. Namely, the material detection system 114 may receive location data, motion data, communication data, interaction data, and any other suitable data from vehicle computing device 104 and requestor computing device 116 (e.g., as gathered by sensors of the vehicle computing device 104 and requestor computing device 116). For example, the vehicle computing device 104 and the requestor computing device 116 may send, to the material detection system 114, their respective geographic locations. Additionally, the vehicle computing device 104 and requestor computing device 116 may collect and send data regarding signal strength readings and communications between the vehicle computing device 104 and the requestor computing device 116. Furthermore, both the vehicle computing device 104 and the requestor computing device 116 may send motion data and interaction data to the dynamic transportation matching system 112, as discussed above. In yet further embodiments, the dynamic transportation matching system 112 receives data from other sources (e.g., additional computing devices associated with the requestor or a traveling companion of the requestor, third-party providers of weather and traffic data). As illustrated in FIG. 2, the material detection system 114 analyzes the received data 210. In step 210, material detection system 114 analyzes data received from the plurality of vehicle sensors 108, vehicle computing device 104, and requestor computing device 116. In some embodiments, the material detection system 114 analyzes the data to determine consistencies or differences between data regarding the vehicle's interior collected prior to the requestor entering the vehicle and data regarding the vehicle's interior collected after the requestor exited the vehicle. For example, the material detection system 114 compares data collected by the vehicle sensors 108 and vehicle computing device 104 before the requestor entered the vehicle with data collected by the vehicle sensors 108 and vehicle computing device 104 after the requestor left the vehicle. Additionally, the material detection system 114 may compare those two sets of data with another obtained while the requestor was in the vehicle. Based on the data comparison, the material detection system 114 may, for example, determine that differences detected occurred when the requestor entered the vehicle or during transportation of the requestor remained even after the requestor left the vehicle. For example, the material detection system 114 may analyze data from a moisture sensor that indicated that a seat in the vehicle that was dry before the requestor entered the vehicle became measurably damp while the requestor was in the vehicle, and then remained damp after the requestor left the vehicle. Thus, the material detection system 114 might determine, based on data received from the vehicle moisture sensors, that the requestor spilled fluid onto the seat. In another example embodiment, the material detection system 114 analyzes whether the requestor computing device 116 is located within a threshold distance of the vehicle computing device 104, even after the requestor has been dropped off and when the vehicle has left or is leaving the destination location. For example, after the transportation request has been completed, the dynamic transportation system 112 may determine the geographic location of the requestor computing device 116, determine the geographic location of the vehicle computing device 104, compare the geographic locations, and determine that the requestor computing device is within a threshold distance of the vehicle computing device. Similarly, the transportation matching system 112 may determine, based on signal strength between the requestor computing device and the vehicle computing device, whether the requestor computing device 116 is within a threshold distance/proximity of the vehicle computing device 104. In further embodiments, the material detection system 114 analyzes and compares motion data received from the vehicle computing device 104 and requestor computing device 116. The motion data can include accelerometer data, gyroscope data, proximity sensor data, and magnetometer data. The material detection system 114 analyzes the motion data to determine consistencies or disparities in the motion of the vehicle computing device 104 and requestor computing device 116. For instance, material detection system 114 can determine and compare the acceleration, speed, and/or rotation of the vehicle computing device 104 with the acceleration, speed, and/or rotation of the requestor computing device 116 to determine whether the two devices are moving in similar ways. Furthermore, the material detection system 114 can analyze the motion data received from the requestor computing device 116 to identify an activity/setting consistent with the motion. For example, the material detection system 114 can analyze the motion data to determine whether the motion indicates that the requestor computing device 116 is in a vehicle, is in a person's possession while walking, is being held in a person's hand, etc. In some embodiments, the material detection system 114 utilizes a trained classifier (e.g., a machine learning model trained using a training dataset of previously classified motion data) to analyze and classify the motion data as pertaining to a particular activity or setting. Further illustrated in FIG. 2, the material detection system 114 may determine that material has been left in the vehicle 212. As part of step 212, the material detection system 114 determines, based on the received data, characteristics of the vehicle interior, including whether or not material has been left in the vehicle. Additionally, the material detection system 114 may aggregate the data received in order to determine material attributes. For example, the material detection system 114 may further determine a type of the material (e.g., mobile device, bag, trash, fluid) and/or a quantity of material (e.g., how many/much of each type of material) left in the vehicle. As part of step 212, in some embodiments, the material detection system 114 determines that material has been left in the vehicle if any of the collected data indicates the presence of material in the vehicle. In further embodiments, the material detection system 114 calculates a confidence score indicating a likelihood/probability that material has been left in the vehicle. The material detection system 114 can use various methods to calculate the confidence score. For example, the material detection system 114 may consider and/or sum the number of different pieces or types of collected data that indicate material has been left in the vehicle. For example, if only one type of collected data indicates that material has been left in the vehicle, the material detection system 114 might calculate a relatively low confidence score. In contrast, if several different types of data indicate the possible presence of material left in the vehicle, the material detection system 114 might calculate a relatively high confidence score. Furthermore, in calculating the confidence score, in some embodiments, the material detection system 114 weights different types of data differently. For example, if a particular type of data has been shown to be particularly reliable in detecting the presence of material left in a vehicle, the material detection system 114 might apply a relatively higher weight to that particular type of data when calculating the confidence score than is applied to another type of data that has been shown to be less reliable in detecting the presence of material left in a vehicle. This weighting may also be dependent on the type of detected material if certain types of collected data are better and detecting the presence of one type of material than another type of material. To illustrate, while moisture sensors may be more reliable than a camera in detecting a fluid spill, they might be less reliable than a camera in detecting the presence of a personal item left on the seat. Furthermore, the material detection system 114 may use machine learning models that take the collected data as an input and output a confidence score indicating the likelihood of material left in the vehicle. As illustrated in FIG. 2, the material detection system 114 may identify and perform an action 214 for handling the material left in the vehicle (e.g., based on one or more attributes of the detected material). The material detection system 114 may perform a single or multiple actions for handling the detected material. For example, in some embodiments, material detection system 114 cancels a subsequent transportation request matched to the vehicle subsystem 102 or prevents a subsequent transportation request from being matched to the vehicle subsystem 102, as shown in step 216. By canceling/preventing subsequent transportation requests, the material detection system 114 avoids the cancelation entirely or limits the detrimental effect of the cancelation on the overall efficiency of the dynamic transportation matching system 112. Additionally, in some embodiments, the material detection system 114 initiates one or more communications 218 (e.g., phone calls, messages, and/or email) with the requestor computing device 116 or vehicle computing device 104. In instances where the material detection system 114 determines that material left in the vehicle does not include the requestor computing device 116, the material detection system 114 may initiate communication with the requestor computing device 116 to notify the requestor that something was left in the vehicle and to provide instructions for recovering the requestor's property. Additionally, the material detection system 114 might initiate a communication to the vehicle computing device 104 to inform a provider or instruct the vehicle subsystem 102 to return to the dropoff location so that the requestor can recover his/her items. In cases where the material detection system 114 determines that initiating communication with the requestor computing device 116 is ineffective (e.g., when the requestor has left the requestor computing device 116 in the vehicle or when initial attempts at communication are unsuccessful), the material detection system 114 may also initiate communication with alternative computing devices. For example, the material detection system 114 might initiate a communication with an emergency contact associated with the requestor computing device 116 (e.g., as stored in a profile for the requestor), with a companion traveling with the requestor (e.g., based on the companion being tagged in the transportation request, based on the cost of the transportation request being split with the companion, or based on communication signals received by the vehicle computing device 104 from the companion's computing device while the requestor is in the vehicle), or with a third-party system (e.g., a Public Announcement system or security system) associated with the dropoff location. Accordingly, the material detection system 114 attempts to contact the requestor indirectly through computing devices/systems other than the requestor computing device 116. The material detection system 114 may also initiate communication with an alternative computing device associated with the requestor. For example, the system may send an email to an address associated with the requestor if the system determines that the requestor left the requestor computing device 116 in the vehicle. In further embodiments, as part of performing an action 214, the material detection system 114 sends one or more notifications 220 associated with the detected material. For example, the material detection system 114 can initiate one or more push notifications to the requestor computing device 116 and/or vehicle computing device 104 notifying the requestor and/or provider that the material has been left in the vehicle. In some embodiments, the provided notifications include an indication that material has been left in the vehicle, and instructions for the vehicle subsystem 102 and/or requestor to facilitate return of the material to the requestor. In some embodiments, as part of performing step 214, the material detection system 114 dispatches the vehicle subsystem 102 to a location to facilitate handling the material left by the requestor. More specifically, the material detection system 114 may dispatch vehicle subsystem 102 (e.g., by sending instructions to the vehicle computing device 104) to the dropoff location associated with the transportation request, to a detected location of the requestor computing device 116, to a service station (e.g., to clean up the material if the material includes trash or fluids, or to store the material in a lost and found for later pickup by the requestor). To illustrate, if the detected material includes a personal item, such as a bag or purse, the material detection system 114 might dispatch the vehicle subsystem 102 to a current location of the requestor computing device to return the personal item to the requestor. In conjunction with this, the material detection system 114 might also initiate one or more communications with the requestor computing device 116 to inform the requestor of and/or provide directions to a location to pick up the personal item. As another example, if the material detection system 114 determines that the material is a spilled drink, bodily fluid, or some other material that requires cleanup, the material detection system 114 might dispatch the vehicle subsystem 102 to a service station that specializes in handling the detected material (e.g., a detail shop that can clean the vehicle). If attempts to directly return a personal item to a requestor are unsuccessful, the material detection system 114 might dispatch the vehicle subsystem 102 to a service station that serves as lost and found storage of personal items. In situations where the vehicle subsystem 102 is autonomous, the material detection system 114 might also take the vehicle subsystem 102 out of service (e.g., for cleaning) and place another vehicle into
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