An electronic control device is mounted on a vehicle and executes automatic driving control using a plurality of pieces of map information. Each piece of the map information includes one or more pieces of partial data corresponding to a predetermined geographical area and being information of a predetermined attribute related to a road of the predetermined geographical area. The electronic control device includes a storage unit that stores one or more pieces of the map information, a specification unit that specifies the map information corresponding to a traveling position of the vehicle, and a control unit that determines a control method of the vehicle at a traveling position of the vehicle according to the partial data included in the map information specified by the specification unit.

A vehicle control device includes an external situation recognition unit configured to recognize a crossing person who crosses over a path of a vehicle and acquire information on the crossing person and information on an environment where the crossing person crosses, a scheduled departure time deciding unit configured to decide a scheduled departure time of the vehicle based on the information on the crossing person and the environment where the crossing person crosses when the crossing person is recognized by the external situation recognition unit, and an informing controller configured to perform a control to inform an outside of the vehicle of the scheduled departure time. The scheduled departure time deciding unit predicts a crossing completion time at which the crossing person recognized by the external situation recognition unit completes the crossing and decides the scheduled departure time based on the crossing completion time.

Vehicles in traffic are expected to communicate wirelessly, to avoid collisions and facilitate the flow of traffic. Unfortunately, in 5G and 6G, the process of finding a wireless address of a specific vehicle is slow and difficult. Disclosed is a “connectivity matrix”, an emblem that vehicles can display, showing a pattern of black and white squares that forms a unique code. Another vehicle can autonomously read the code and look up the wireless address in a tabulation. The tabulation relates each code to the relevant wireless address, and optionally other information about the vehicle. The two vehicles can then transfer messages, including emergency messages, without delay. At freeway speeds, this can save lives. A central entity maintains the tabulation, ensuring that each wireless address is associated with a unique connectivity matrix code. Roadside companies and access points can also display a connectivity matrix, promote communication with prospective customers.

Vehicles in traffic are expected to communicate wirelessly, to avoid collisions and facilitate the flow of traffic. Unfortunately, in 5G and 6G, the process of finding a wireless address of a specific vehicle is slow and difficult. Disclosed is a “connectivity matrix”, an emblem that vehicles can display, showing a pattern of black and white squares that forms a unique code. Another vehicle can autonomously read the code and look up the wireless address in a tabulation. The tabulation relates each code to the relevant wireless address, and optionally other information about the vehicle. The two vehicles can then transfer messages, including emergency messages, without delay. At freeway speeds, this can save lives. A central entity maintains the tabulation, ensuring that each wireless address is associated with a unique connectivity matrix code. Roadside companies and access points can also display a connectivity matrix, promote communication with prospective customers.

A position information acquisition system according to the present disclosure includes: a server that receives request data from a terminal and transmits information corresponding to a content of the received request data to the terminal; and a plurality of markers each representing a code that allows acquisition of the request data by a predetermined identification method. A vehicle identifies an image marker, acquires the request data, and transmits the request data to the server. When a transmission source of the received request data is the vehicle, the server transmits position information at a specific location where the image marker is installed to the vehicle regardless of the content of the request data.

A position information acquisition system according to the present disclosure includes: a server that receives request data from a terminal and transmits information corresponding to a content of the received request data to the terminal; and a plurality of markers each representing a code that allows acquisition of the request data by a predetermined identification method. A vehicle identifies an image marker, acquires the request data, and transmits the request data to the server. When a transmission source of the received request data is the vehicle, the server transmits position information at a specific location where the image marker is installed to the vehicle regardless of the content of the request data.

The method comprises, for a given route between a starting point and a destination, and for an arrival at the destination at a given desired time: a preliminary step of determining and recording a plurality of vehicle mission profiles, at least a first instant during the journey, a step of determining an instantaneous position of the vehicle at this first instant and a desired time remaining to reach the destination, a step of identifying, among the mission profiles, the mission profile(s) whose curves are closest to the desired time remaining at the instantaneous position of the vehicle, and a step of determining new driving parameters to follow a new mission profile, the new mission profile being determined on the basis of the determined mission profiles.

Vehicles in traffic cannot coordinate their actions properly in 5G and 6G without knowing the location and the wireless address of the other vehicle. GNSS signals are generally too slow and too imprecise to discern vehicles in, for example, adjacent lanes. Directional wireless beams are subject to reflections from conducting surfaces, producing chaotic signals and false locations if more than one vehicle is within the transmission beam. To provide precise localization in traffic, methods are disclosed for multiple vehicles (or other mobile devices) to acquire satellite signals simultaneously, and then analyze the data differentially, thereby canceling major uncertainties (such as propagation variations, ephemeris motion, and clock jitter), and thereby determining the relative positions precisely. Unlike prior-art “precision” positioning methods, the disclosed methods do not require averaging multiple acquisitions. On the contrary, examples show how high differential precision can be obtained without averaging, using measurements acquired at the predetermined time.

Vehicles in traffic cannot coordinate their actions properly in 5G and 6G without knowing the location and the wireless address of the other vehicle. GNSS signals are generally too slow and too imprecise to discern vehicles in, for example, adjacent lanes. Directional wireless beams are subject to reflections from conducting surfaces, producing chaotic signals and false locations if more than one vehicle is within the transmission beam. To provide precise localization in traffic, methods are disclosed for multiple vehicles (or other mobile devices) to acquire satellite signals simultaneously, and then analyze the data differentially, thereby canceling major uncertainties (such as propagation variations, ephemeris motion, and clock jitter), and thereby determining the relative positions precisely. Unlike prior-art “precision” positioning methods, the disclosed methods do not require averaging multiple acquisitions. On the contrary, examples show how high differential precision can be obtained without averaging, using measurements acquired at the predetermined time.

Route search systems, methods, and programs acquire movement paths of a plurality of users, and classify, on the basis of a plurality of characteristics of the movement paths of the plurality of users, the movement paths of each of the users into a plurality of types such that movement paths with a plurality of similar characteristics belong to a same type. The systems, methods, and programs set a cost for each of the types and each attribute of a road on the basis of the plurality of movement paths of each of the types, classify, on the basis of a plurality of characteristics of a movement path of a route searcher, the route searcher into one of the types, and search for a route on the basis of the cost which is set for the type of the route searcher.