A remote driving taxi system provides a mobility service using remote driving taxis that are driven by remote drivers. Each of the remote driving taxis includes a display lamp configured to indicate whether the remote driving taxi is currently available. Management information includes use states of the remote driving taxis and assignment states between the remote driving taxis and the remote drivers. The remote driving taxi system puts on the display lamp of the remote driving taxi to which the remote driver has already been assigned and that is currently available, based on the management information. Further, the remote driving taxi system puts off the display lamp of the remote driving taxi to which the remote driver has already been assigned and that is currently unavailable, based on the management information.

A method is disclosed. A data set including: (a) identifiers of a set of incidents occurring within a defined geographic region to which at least one service provider responded during a first time period and (b) address data identifying a location within the geographic region of each said incident of the set is retrieved over a network. An instruction to generate a heat map of the incidents occurring within the geographic region during the first time period is received from a user via a user interface generated to a display device. In response to the instruction to generate the heat map, the address data is converted to GPS data. A heat map of an aerial view of the geographic region based on the GPS data is generated. The heat map is displayed to the display device in a user interface.

A computer-implemented method is provided. The method includes: obtaining a location of a vehicle driver's terminal device, a location of a first passenger's terminal device and a location of a second passenger's terminal device and a location of a destination; determining a plurality of candidate pick-up points according to the locations of the first and second passenger's terminal devices; determining at least one target pick-up point from the plurality of candidate pick-up points, in such a manner that a total time cost from the location of the vehicle driver's terminal device to the location of the destination to be minimum when the first and second passenger's terminal devices are picked up from a respective target pick-up point in the at least one target pick-up point; and determining a navigation path for the vehicle driver's terminal device based on at least a location of the at least one target pick-up point.

A mobile unit control system includes an acquisition unit configured to acquire operation information on transportation located around the traveling area of a mobile unit that a user gets on and off while the mobile unit is traveling and a setting unit configured to set the traveling route or the traveling speed of the mobile unit based on the operation information on transportation.

Aspects of the disclosure relate to computing platforms that utilize machine learning to reduce false positive/negative collision output generation. A computing platform may apply machine learning algorithms on received data to generate a collision output. In response to generating the collision output indicating a collision, the computing platform may identify a data collection location. If the data collection location is within a predetermined radius of a false positive collection location, the computing platform may modify the collision output to indicate a non-collision. If the data collection location is not within the predetermined radius, the computing platform may compute a score using telematics data and compare the score to a predetermined threshold. If the score does not exceed the predetermined threshold, the computing platform may modify the collision output to indicate a non-collision. If the score exceeds the predetermined threshold, the computing platform may affirm the collision output indicating a collision.

A method of facilitating a fleet exchange includes retrieving a fleet and retrieving a set of workers, analyzing the fleet and the set of workers using smart scheduling to generate allocations, and displaying the allocations to the workers. In another aspect, a non-transitory computer readable medium includes program instructions that when executed, cause a computer system to receive vehicle allocation request, retrieve worker information and a worker calendar, generate an allocation, and display the allocation in a display device. A computing system for facilitating fleet exchange includes one or more processors and a memory including computer executable instructions that, when executed by the one or more processors, cause the computing system to retrieve a fleet and a set of workers, analyze the fleet and the set of workers to generate allocations, and display the allocations in a respective computing device of the workers.

The technology includes communicating the current status of a self-driving vehicle to users, such as passengers within the vehicle and other users awaiting pickup. Certain information about the trip and vehicle status is communicated depending on where the passenger is sitting within the vehicle or where the person awaiting pickup is located outside the vehicle. This includes disseminating the “monologue” of a vehicle operating in an autonomous driving mode to a user via an app on the user's device (e.g., mobile phone, tablet or laptop PC, wearable, or other computing device) and/or an in-vehicle user interface. The monologue includes current status information regarding driving decisions and related operations or actions. This alerts the user as to why the vehicle is taking (or not taking) a certain action, which reduces confusion and allows the user to focus on other matters.

A delivery system in which the vehicles themselves coordinate their movements. Vehicles are assigned to groups based on proximity. Each vehicle communicates its location and route information to the other vehicles in the group. The vehicles in the group then know the positions and routes of the other vehicles in the group. When a delivery is requested, the vehicles in the group use this information to determine which vehicle should be assigned to make that delivery. As the vehicles move around, their proximity to each other changes. When a vehicle has moved away from a group, that vehicle may be removed from the group and assigned to a different group. In this manner, the vehicle coordination mechanism is a distributed task performed by all the vehicles.

A drive assistance apparatus predicts demand for vehicles in each area including a driving route, based on a demand prediction model for predicting the demand in the area. The drive assistance apparatus also predicts the frequency of occurrence of an obstacle in each of the regions obtained by dividing the area, based on a frequency model for predicting the frequency of occurrence of the obstacle in the region, and generates a driving route of the vehicle, based on the predicted demand in the area and the predicted frequency of occurrence of the obstacle.

A movement assistance device guides a user to a meeting location for meeting a vehicle. The movement assistance device calculates a first required time until the vehicle arrives at the meeting location, and a plurality of routes from the user's current location to the meeting location. The movement assistance device calculates a second required time for the user to arrive at the meeting location from the user's current location for each route. The movement assistance device then determines the route associated with the second required time as a route via which the vehicle could be met on time when a second required time is the same as or shorter than the first required time. The movement assistance device then causes the communication device to output information that indicates the route or routes determined to be the route or routes via which the vehicle could be met on time.