# US 10,768,004 B2 · Travel routing selection system and methods implemented based on characterization of historical latency data > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 10,768,004 B2 - Document ID: US10768004B2 - Status: Granted - Kind: B2 - Application number: 15/882,489 - Filed: 2018-01-29 - Published: 2019-08-01 - Granted: 2020-09-08 - Earliest claimed: 2018-01-29 - Assignees: DENSO International America, Inc.; Denso Corporation - Applicants: DENSO International America, Inc.; Denso Corporation - Inventors: Haris Volos; Kenji Konishi - Web page: https://patentgrep.com/patent/US10768004B2 ## CPC - G05D 1/0217: {in accordance with energy consumption, time reduction or distance reduction criteria} - G01C 21/3453: {Special cost functions, i.e. other than distance or default speed limit of road segments} - G01C 21/3492: {employing speed data or traffic data, e.g. real-time or historical (traffic control systems for road vehicles involving transmission of navigation instructions to the vehicle G08G1/0968)} - G05D 1/0285: {using signals transmitted via a public communication network, e.g. GSM network} - G08G 1/0112: {from the vehicle, e.g. floating car data [FCD]} - G08G 1/0141: {for traffic information dissemination} - G08G 1/096816: {where the complete route is transmitted to the vehicle at once} - G08G 1/096833: {where different aspects are considered when computing the route} - H04L 41/147: for predicting network behaviour - H04L 41/5009: Determining service level performance parameters or violations of service level contracts, e.g. violations of agreed response time or mean time between failures [MTBF] - H04L 43/0852: Delays - H04L 67/12: specially adapted for proprietary or special-purpose networking environments, e.g. medical networks, sensor networks, networks in vehicles or remote metering networks - H04L 67/535: {Tracking the activity of the user (network monitoring arrangements H04L43/00; recording of computer activity G06F11/34)} - H04W 4/024: Guidance services - H04W 4/029: Location-based management or tracking services - G08G 1/0129: {for creating historical data or processing based on historical data} - G08G 1/22: {Platooning, i.e. convoy of communicating vehicles} - G05D: SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES - G01C: MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY (measuring liquid level G01F; radio navigation, determining distance or velocity by use of propagation effects, e.g. Doppler effects, propagation time, of radio waves, analogous arrangements using other waves G01S) - G08G: TRAFFIC CONTROL SYSTEMS (guiding railway traffic, ensuring the safety of railway traffic B61L; arrangement of road signs or traffic signals E01F9/00; radar or analogous systems, sonar systems, lidar systems specially adapted for traffic control G01S13/91, G01S15/88, G01S17/88; {radar or analogous systems, sonar systems, lidar systems specially adapted for anti-collision purposes G01S13/93, G01S15/93, G01S17/93}) - H04L: TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION (arrangements common to telegraphic and telephonic communication H04M) - H04W: WIRELESS COMMUNICATION NETWORKS (broadcast communication H04H; communication systems using wireless links for non-selective communication, e.g. wireless extensions H04M1/72) ## Abstract A travel route selection system is provided and includes historical latency data and travel route modules. The historical latency data module includes data and characterization modules. The data module collects historical latency data. The historical latency data are associated with transmission of signals in a network for one or more vehicle applications of a vehicle. The characterization module: obtains characteristic distributions of the historical latency data at selected locations along travel routes; based on the characteristic distributions, (i) calculates metrics along the travel routes for the vehicle, or (ii) combines the characteristic distributions to obtain an overall distribution for each of the travel routes; and based on the metrics or the overall distribution, performs a statistical process to predict latencies of the signals along each of the travel routes. The travel route module selects one of the travel routes based on the predicted latencies of the signals. ## Claims ### Claim 1 A travel route selection system comprising: a historical latency data module comprising a first data module configured to collect historical latency data, wherein the historical latency data are associated with transmission of signals in a network for one or more vehicle applications of a vehicle, and a characterization module configured to obtain characteristic distributions of the historical latency data at selected locations along a plurality of travel routes, based on the characteristic distributions, perform at least one of (i) calculating metrics along the plurality of travel routes for the vehicle, or (ii) combining the characteristic distributions to obtain an overall distribution for each of the plurality of travel routes, and based on at least one of the metrics or the overall distributions, perform a statistical process to predict latencies of the signals along each of the plurality of travel routes; and a travel route module configured to select one of the plurality of travel routes based on the predicted latencies of the signals. ### Claim 2 (depends on 1) The travel route selection system of claim 1, wherein the historical latency data are obtained from at least one of a historical latency database, a road side device, a second vehicle, a network device, or a cloud-based server. ### Claim 3 (depends on 1) The travel route selection system of claim 1, further comprising a second data module configured to collect contextual data corresponding to the historical latency data, wherein the first data module is configured to collect the historical latency data based on the contextual data, such that the historical latency data have similar corresponding contextual data. ### Claim 4 (depends on 1) The travel route selection system of claim 1, wherein: the characterization module is configured to characterize the historical latency data corresponding to distances along the plurality of travel routes; and the travel route module is configured to select the one of the plurality of travel routes based on the characterization of the historical latency data. ### Claim 5 (depends on 1) The travel route selection system of claim 1, wherein the characterization module is configured to, based on the characteristic distributions, calculate the metrics along the plurality of travel routes; and the metrics include a minimum latency, a maximum latency, and a sum of latencies. ### Claim 6 (depends on 1) The travel route selection system of claim 1, wherein the characteristic distributions include a probability distribution function or a cumulative distribution function. ### Claim 7 (depends on 1) The travel route selection system of claim 1, wherein: the travel route module is configured to select the one of the plurality of travel routes based on a score function value of metrics of the one of the plurality of travel routes and score function values of metrics of the other ones of the plurality of travel routes: and the metrics of the one of the plurality of travel routes and the metrics of the other ones of the plurality of travel routes include total distance of route, a minimum latency, a maximum latency, an amount of traffic and a cost of communication. ### Claim 8 (depends on 1) The travel route selection system of claim 1, wherein the travel route module is configured to select the one of the plurality of travel routes with a least overall latency as compared to overall latencies of the other ones of the plurality of travel routes. ### Claim 9 (depends on 1) The travel route selection system of claim 1, wherein the travel route module is configured to select the one of the plurality of travel routes based on the overall distribution of the one of the plurality of travel routes and the overall distributions of the other ones of the plurality of travel routes. ### Claim 10 (depends on 1) A vehicle system comprising: the travel route selection system of claim 1; and a vehicle control module configured to control operation of one or more vehicle devices to facilitate routing of the vehicle along the selected one of the plurality of travel routes. ### Claim 11 A method of operating a vehicle route selection system, the method comprising: collecting historical latency data associated with transmission of signals in a network for one or more vehicle applications of a vehicle; obtaining characteristic distributions of the historical latency data at selected locations along a plurality of travel routes; based on the characteristic distributions, performing at least one of (i) calculating metrics along the plurality of travel routes for the vehicle, or (ii) combining the characteristic distributions to obtain an overall distribution for each of the plurality of travel routes; based on at least one of the metrics or the overall distributions, performing a statistical process to predict latencies of the signals along each of the plurality of travel routes; and selecting one of the plurality of travel routes based on the predicted latencies of the signals. ### Claim 12 (depends on 11) The method of claim 11, wherein the historical latency data are obtained from at least one of a historical latency database, a road side device, a second vehicle, a network device, or a cloud-based server. ### Claim 13 (depends on 11) The method of claim 11, further comprising collecting contextual data corresponding to the historical latency data, wherein the historical latency data are collected based on the contextual data, such that the historical latency data have similar corresponding contextual data. ### Claim 14 (depends on 11) The method of claim 11, comprising: characterizing the historical latency data corresponding to distances along the plurality of travel routes; and selecting the one of the plurality of travel routes based on the characterization of the historical latency data. ### Claim 15 (depends on 11) The method of claim 11, comprising, based on the characteristic distributions, calculating the metrics along the plurality of travel routes for the vehicle, wherein the metrics include a minimum latency, a maximum latency, and a sum of latencies. ### Claim 16 (depends on 11) The method of claim 11, comprising, based on the characteristic distributions, calculating the metrics along the plurality of travel routes for the vehicle, wherein the metrics include a sum of latencies for a predetermined confidence level. ### Claim 17 (depends on 11) The method of claim 11, wherein the characteristic distributions include a probability distribution function or a cumulative distribution function. ### Claim 18 (depends on 11) The method of claim 11, comprising selecting the one of the plurality of travel routes based on metrics of the one of the plurality of travel routes and metrics of the other ones of the plurality of travel routes. ### Claim 19 (depends on 11) The method of claim 11, comprising selecting the one of the plurality of travel routes with a least overall latency as compared to overall latencies of the other ones of the plurality of travel routes. ### Claim 20 (depends on 11) The method of claim 11, comprising selecting the one of the plurality of travel routes based on the overall distribution of the one of the plurality of travel routes and the overall distributions of the other ones of the plurality of travel routes. ### Claim 21 (depends on 1) The travel route selection system of claim 1, wherein the characteristic distributions include latency estimates for distances along the travel routes. ### Claim 22 (depends on 1) The travel route selection system of claim 1, wherein: the characterization module is configured to use the metrics to define score function values for each of the plurality of travel routes; and each of the score function values are based on a sum of weighted minimum latency values, maximum latency values and distance values. ### Claim 23 (depends on 1) The travel route selection system of claim 1, wherein the characterization module is configured to predict the latencies of the signals along each of the plurality of travel routes using a Gaussian process.