Denso Corporation

Denso International America, Inc.

Kenji Konishi

Haris Volos

Takashi Bando

Kazuhito Takenaka

Hideaki Misawa

Yuki Shinohara

A vehicle application enabling system is provided and includes a latency characterization and prediction module and an application enable module. The latency characterization and prediction module includes: an estimate sample module configured to collect and store obtained latency estimates, where the obtained latency estimates are associated with transmission of signals in a network for one or more vehicle applications; a sample characterization module configured to characterized the obtained latency estimates; a trend module configured to determine a trend based on the characterized obtained latency estimates; a point projection module configured to generate projected latency estimates based on the trend; and a projection characterization module configured to characterize the projected latency estimates. The application enable module is configured to determine whether to enable the one or more vehicle applications based on the characterization of the projected latency estimates.

Vehicle application enabling and network routing systems implemented based on latency characterization and projection

A vehicle application enabling system is provided and includes a memory and initialization, latency evaluation, and application enable modules. The initialization module: receives a maximum network latency; sets a percentage of occurrences that the maximum network latency is not satisfied, a maximum false positive rate, and a maximum deviation value; and calculates a weighting factor based on the percentage of occurrences, maximum false positive rate and maximum deviation value. The latency evaluation module implements a latency evaluation algorithm, which includes: comparing one or more latency estimates to the maximum network latency to provide one or more samples; updating confusion matrix statistics based on the one or more samples; updating a probability threshold based on the maximum false positive rate; updating weighted observations based on the weighting factor; and determining a predicted decision based on the probability threshold. The application enable module executes the vehicle application based on the probability threshold.

Application specific connected service provision system

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.

Travel routing selection system and methods implemented based on characterization of historical latency data

A risk assessment system is provided and includes a behavior description generator, driving behavior comparator, and risk assessment modules and a transceiver. The behavior description generator module receives a set of driving features and topics corresponding to a driving behavior of a first driver in a location and under a set of driving conditions. The driving behavior comparator module: compares the set of driving features and the topics to other sets of features and topics, which correspond to driving behaviors of other drivers for the location and same or similar driving conditions as the set of driving conditions; and generates an anomaly score for the first driver based on results of the comparison. The risk assessment module calculates a risk assessment score for the driver based on the anomaly score, where the risk assessment score is indicative of a risk level of the first driver relative to the other drivers.

Risk assessment system for assessing current driver behavior relative to past behavior and behaviors of other drivers

A car sharing system includes: an IC card carried by a user and including an identification ID of the user; an in-vehicle apparatus that is mounted on a vehicle, and includes a card reading portion reading the IC card and a switch control portion performing an on-off control of a vehicle power source switch that allows traveling of a vehicle; and a management apparatus that is disposed in a reservation management center, wirelessly communicates with the in-vehicle apparatus, manages an operation status of the vehicle, and further manages reservation information. The in-vehicle apparatus reads the IC card by the card reading portion and, based on authentication of an the identification ID by collation between the identification ID, which is read, and the reservation information, executes a check-in process of the vehicle and turns on the vehicle power source switch.

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San Jose, CA, United States of America

Kenji Konishi