Environmental tracking systems and methods are disclosed. An environmental tracking system receives sensor data from the one or more sensors, such as camera(s) and Light Detection and Ranging (LIDAR) sensors. The system uses trained machine learning (ML) model(s) to detect, within the sensor data, representation(s) of at least a portion of a vehicle with a door that is at least partially open. Based on these representation(s), the system generates a boundary for the vehicle that includes the door and is sized based on the door being at least partially open. The system determines a route that avoids the boundary, for example by planning the route around the boundary or by planning to stop before intersecting with the boundary. In some examples, the sensors are sensors coupled to a second vehicle, and the second vehicle traverses the route.

Aspects of the disclosed technology encompass solutions for automatically managing autonomous vehicle (AV) operating and maintenance tasks, such as implementing an alternative operating mode or ordering replacement parts for an AV components. In some aspects, a process of the disclosed technology can include steps for receiving diagnostic data corresponding with an AV component, determining an estimated life cycle of the AV component, and determining whether to generate an action to implement an alternative operating mode or an order request for one or more replacement parts of the AV component, based on the estimated life cycle of the AV component. Systems and machine-readable media are also provided.

Disclosed herein are an autonomous vehicle and a service providing system and method using the same. The autonomous vehicle includes a navigation system setting, as a destination, a service zone adjacent to a parking lot when there is a previously registered vehicle service input through a user terminal, and setting, as a destination, the parking lot adjacent to the service zone after completion of the previously registered vehicle service, and an operation system moving the vehicle to the destination through autonomous driving. One or more of the autonomous vehicle, the user terminal, and the server may be associated with artificial intelligence, a robot, augmented reality (AR), virtual reality (VR), or the like.

The disclosure provides for a method for determining a pullover spot for a vehicle. The method includes using a computing device to detect information related to a system of the vehicle or an environment surrounding the vehicle using a sensor of a vehicle and determine a local failure of the vehicle based on the information. The computing device may then be used to determine that the vehicle should pullover before completing a current trip related to transporting a passenger or good by comparing vehicle requirements for the trip with the local failure and determine a pullover spot by identifying a first area for the vehicle to park in part based on a second area being available for a second vehicle to pick up the passenger or good. The computing device may operate the vehicle to the pullover spot and transmit a request for a second vehicle.

An autonomous vehicle (AV) system includes an AV control system that resolves unique situations encountered while operating as a ride hail provider. The AV control system includes an artificial intelligence (AI) agent programmed to receive a situation data set as an input from vehicle sensors or from another AI agent. The situation data set can include a generic representation of information describing and characterizing the circumstances and details of the current situation. The system may access a knowledge library having catalogued prior situation data sets that describe situations encountered by the AV or other vehicles in a fleet. The AV control system may search the knowledge library for a similar situation encountered by a fleet vehicle. Once a similar situation is identified, the AV control system may identify one or more remedies that were executed to handle the prior situation, and execute the remedy to address the current situation.

An on-demand predefined route automated driving vehicle automatically travels, regardless of whether a passenger is on board, along a annular-connecting predefined route which has a annular predefined route and a connecting predefined route. The in-vehicle control device of the on-demand predefined route automated driving vehicle transmits its current location to a fleet control device, and controls a drive mechanism, a braking mechanism and a travel-direction control mechanism in a manner such that the velocity V1 in a standby state is lower than the velocity V2 in an dispatch state when changing states from the standby state, which is a state where no passenger is on board and it is possible to receive an dispatch command signal, to the dispatch state, which is a state in which a vehicle selected for dispatch to a scheduled boarding location is traveling toward the scheduled boarding location on the basis of an dispatch command signal transmitted from the fleet control device in response to the use request from the user.

A health risk assessment system for estimating a health risk posed by transporting a user in a vehicle. The system includes one or more processors and a memory communicably coupled to the one or more processors and storing a health risk assessment module. The health risk assessment module includes computer-readable instructions that when executed by the one or more processors cause the one or more processors to attempt to acquire information regarding a travel history of the user. The module is also configured to, using acquired travel history information, determine a value of a first health status parameter and to compare the value of the first health status parameter to a first threshold. Responsive to the value of the first health status parameter exceeding the threshold, the module controls operation of the vehicle to implement at least one infection prevention measure.

The disclosure provides for a method for determining a pullover spot for a vehicle. The method includes using a computing device to detect information related to a system of the vehicle or an environment surrounding the vehicle using a sensor of a vehicle and determine a local failure of the vehicle based on the information. The computing device may then be used to determine that the vehicle should pullover before completing a current trip related to transporting a passenger or good by comparing vehicle requirements for the trip with the local failure and determine a pullover spot by identifying a first area for the vehicle to park in part based on a second area being available for a second vehicle to pick up the passenger or good. The computing device may operate the vehicle to the pullover spot and transmit a request for a second vehicle.

A method for controlling an autonomous vehicle is provided. While the vehicle is at a commanded destination the method may be responsive to an absence of an ingress/egress of a passenger for a predetermined period. The predetermined period may depend on whether the vehicle is in arrival mode or departure mode. The method may include commanding the vehicle to travel to a predetermined location selected to have measures of cellular-wireless signal strength that are greater than a predetermined threshold.

Examples are directed toward a system and method relating to mobile screening. For example, a mobile screening vehicle includes a passenger scanner that performs security scanning of a passenger on the mobile screening vehicle. The mobile screening vehicle also includes a verification system that verifies, consistent with the security scanning of passengers, that passengers on the mobile screening vehicle are approved to proceed to a secure area of a travel venue.