Abstract: A method for performing traffic monitoring by utilizing distinct sensors is disclosed. A radar point cloud is obtained from a radar sensor and image data is obtained from an image sensor. The radar sensor and the image sensor are fixedly mounted to observe traffic. The radar sensor and the image are synchronized for managing a flow of data for the radar sensor and the image sensor. A first classifier is applied on the first dataset to generate first classifications. A second classifier is applied on the second dataset to generate second classifications. The first classifications and the second classifications from the radar sensor and the image sensor are integrated to generate a composite classification.

Abstract: A width detection system to measure a width of an object at a transit gate of a transit system is disclosed. The width detection system includes a gate paddle to control access through the transit gate, a first gate cabinet and a second gate cabinet of the transit gate separated by an aisle width, a sensor system, and a controller. The sensor system includes a primary sensor positioned at the first gate cabinet of the transit gate. The primary sensor emits a primary signal directed at the second gate cabinet and determines a primary distance of the object to the primary sensor. The controller determines the width of the object based on the primary distance and the aisle width, compares the width against a primary threshold, and actuates the gate paddle.

Abstract: A method for performing traffic monitoring by utilizing distinct sensors is disclosed. A radar point cloud is obtained from a radar sensor and image data is obtained from an image sensor. The radar sensor and the image sensor are fixedly mounted to observe traffic. The radar sensor and the image are synchronized for managing a flow of data for the radar sensor and the image sensor. A first classifier is applied on the first dataset to generate first classifications. A second classifier is applied on the second dataset to generate second classifications. The first classifications and the second classifications from the radar sensor and the image sensor are integrated to generate a composite classification.

Abstract: A fare gate in a transportation system including a barrier, a sensor, and an actuator. The actuator moves the barrier from the open position into the closed position. The sensor is mounted on the barrier and in one position captures sensor data across an aisle formed by the fare gate. A transit user in front of the barrier in another position is identified by the sensor. The transit user passes through the fare gate using the aisle. The actuator moves the barrier from a closed position to an open position to clear passage through the aisle. Using the sensor, the aisle is scanned with a movement of the barrier. The sensor is calibrated based on a predetermined point with movement of the barrier to align the sensor and the predetermined point.

Abstract: A transportation system for identifying an object using a short range radar at a transportation gate. The transportation system includes one or more short range radars and a cloud server. The radars detect the object within a predetermined distance from the transportation gate and sense the object to generate a point cloud. An identification of the object is determined based on sensed data of the object using a machine learning algorithm from the cloud server. The identification is determined based on matching the point cloud with a plurality of profiles. The plurality of profiles includes matching information for a plurality of predetermined objects. The object is selected from the plurality of predetermined objects using the matching information. An authorization for the object is determined using another machine learning algorithm. Based on the authorization, either the passage through the transportation gate is authorized or the object is flagged as unauthorized.

Abstract: A method for operating an adaptive gateline may include detecting a patron approaching a gateline. The method may include determining whether the gateline should be operated in a standard mode or in a modified mode based at least in part on data from one or more sensors. The method may include operating the gateline in the standard mode or in the modified mode based on the determination. In the modified mode a barrier of the gateline operates to provide one or both of extra time or additional space for the patron to pass through the gateline relative to the standard mode.

Abstract: A system and method for self-learning operation of gate paddles is disclosed. Opening and closing of the gate paddles requires timing and other settings to avoid injury and fare evasion. Self-learning allows a machine learning model to adapt to new data dynamically. The new data captured at a fare gate improves the machine learning model, which can be shared the other similar fare gates within a transit system so that learning disseminates.

Abstract: A method for operating an adaptive gateline may include detecting a patron approaching a gateline. The method may include determining whether the gateline should be operated in a standard mode or in a modified mode based at least in part on data from one or more sensors. The method may include operating the gateline in the standard mode or in the modified mode based on the determination. In the modified mode a barrier of the gateline operates to provide one or both of extra time or additional space for the patron to pass through the gateline relative to the standard mode.

Abstract: A transportation system for identifying an object using a short range radar at a transportation gate. The transportation system includes one or more short range radars and a cloud server. The radars detect the object within a predetermined distance from the transportation gate and sense the object to generate a point cloud. An identification of the object is determined based on sensed data of the object using a machine learning algorithm from the cloud server. The identification is determined based on matching the point cloud with a plurality of profiles. The plurality of profiles includes matching information for a plurality of predetermined objects. The object is selected from the plurality of predetermined objects using the matching information. An authorization for the object is determined using another machine learning algorithm. Based on the authorization, either the passage through the transportation gate is authorized or the object is flagged as unauthorized.

Abstract: A fare gate in a transportation system including a barrier, a sensor, and an actuator. The actuator moves the barrier from the open position into the closed position. The sensor is mounted on the barrier and in one position captures sensor data across an aisle formed by the fare gate. A transit user in front of the barrier in another position is identified by the sensor. The transit user passes through the fare gate using the aisle. The actuator moves the barrier from a closed position to an open position to clear passage through the aisle. Using the sensor, the aisle is scanned with a movement of the barrier. The sensor is calibrated based on a predetermined point with movement of the barrier to align the sensor and the predetermined point.

Abstract: A system and method for self-learning operation of gate paddles is disclosed. Opening and closing of the gate paddles requires timing and other settings to avoid injury and fare evasion. Self-learning allows a machine learning model to adapt to new data dynamically. The new data captured at a fare gate improves the machine learning model, which can be shared the other similar fare gates within a transit system so that learning disseminates.

Abstract: A method of providing adaptive transit resource allocation may include receiving journey planning information from a mobile device. The method may include generating one or more routes based on the journey planning information. The method may include providing the one or more routes and details associated with each of the routes to the mobile device. The method may include receiving a selection of one of the one or more routes from the mobile device. The method may include analyzing the selection and selected routes from a number of other mobile devices. The method may include adjusting an allocation of transit resources based on the analysis.

Abstract: A method of operating a gateline includes obtaining, at a computing device, information indicative of one or both of a current or predicted amount of throughput of transit users through the gateline and calculating, based at least in part of the information, a desired configuration of one or more fare gates in the gateline. The desired configuration is compared to a current gateline configuration. A command is sent to the gateline to adjust the current gateline configuration to match the desired configuration based on a determination that the desired configuration is different than the current gateline configuration.

Abstract: A weapon training system including a magnetic sensor system is described. The magnetic sensor system is insertable into or integrated with a round of an indirect firing weapon and includes at least one magnetic sensor and a microcontroller communicatively coupled to the at least one magnetic sensor. The microcontroller is configured to perform operations including receiving at least one proximity signal from the at least one magnetic sensor indicating a proximity of at least one magnet of at least one charge to the at least one magnetic sensor, determining, based on the at least one proximity signal, that the at least one charge is removably attached to the round, generating an output signal indicating that the at least one charge is removably attached to the round, and wirelessly transmitting the output signal to an electronic device.

Abstract: Systems, methods, and other techniques for providing dynamically responsive feedback to a transit user are disclosed. Location data regarding a plurality of locations of the transit user within a transit system may be detected by a tracking device. An intent to validate is received from the transit user. Based on the intent to validate, it is determined that a successful validation has occurred. Based on the location data, the plurality of locations are determined. Based on the plurality of locations, a location and a velocity of the transit user are determined. Instructions for a feedback signal are generated based on the location and the velocity. A feedback device positioned within the transit system is caused to output the feedback signal, indicating the successful validation.

Abstract: An overhead tracking system for tracking validation events including a plurality of validation devices that wirelessly receive an access token from a fare media device and validate the access token. The system includes an overhead tracking sensor that continuously tracks a position of each of a plurality of users passing underneath the sensor and receives an indication from at least one of the validation devices upon a user having successfully validated the access token from a fare media device associated with the user. The sensor detects when a particular one of the plurality of users has crossed into a feedback zone and sends a command to one or more remote devices based on detecting that the user has crossed into the feedback zone. The command and the remote devices are selected based on whether the user has successfully validated the access token.

Abstract: A method of operating a gateline includes obtaining, at a computing device, information indicative of one or both of a current or predicted amount of throughput of transit users through the gateline and calculating, based at least in part of the information, a desired configuration of one or more fare gates in the gateline. The desired configuration is compared to a current gateline configuration. A command is sent to the gateline to adjust the current gateline configuration to match the desired configuration based on a determination that the desired configuration is different than the current gateline configuration.

Abstract: The CAV may include one or more sensors, a communications interface, a driving control configured to be activated to cause a change in the operation of the CAV, and a processing unit communicatively coupled with the one or more sensors, the communications interface, and the driving control. The processing unit may be configured to cause the CAV to: obtain vehicle data regarding a vehicle using the one or more sensors; obtain, using the vehicle data, risk data via the communications interface, the risk data being indicative of a likelihood of an accident caused by the vehicle; determine a risk value based on the risk data regarding the vehicle, the risk value being indicative of a likelihood that the CAV may be involved in an accident; and responsive to determining the risk value is above a threshold level, activate the driving control to modify the operation of the CAV.

Abstract: An overhead tracking system for tracking validation events including a plurality of validation devices that wirelessly receive an access token from a fare media device and validate the access token. The system includes an overhead tracking sensor that continuously tracks a position of each of a plurality of users passing underneath the sensor and receives an indication from at least one of the validation devices upon a user having successfully validated the access token from a fare media device associated with the user. The sensor detects when a particular one of the plurality of users has crossed into a feedback zone and sends a command to one or more remote devices based on detecting that the user has crossed into the feedback zone. The command and the remote devices are selected based on whether the user has successfully validated the access token.

Abstract: Systems, methods, and other techniques for providing dynamically responsive feedback to a transit user are disclosed. Location data regarding a plurality of locations of the transit user within a transit system may be detected by a tracking device. An intent to validate is received from the transit user. Based on the intent to validate, it is determined that a successful validation has occurred. Based on the location data, the plurality of locations are determined. Based on the plurality of locations, a location and a velocity of the transit user are determined. Instructions for a feedback signal are generated based on the location and the velocity. A feedback device positioned within the transit system is caused to output the feedback signal, indicating the successful validation.