US 12,073,332 B2
Rest stop recommendation system
Zhenyu Shou, Milpitas, CA (US); Ziran Wang, San Jose, CA (US); Kyungtae Han, Palo Alto, CA (US); Yongkang Liu, Plano, TX (US); and Prashant Tiwari, Santa Clara, CA (US)
Assigned to Toyota Motor Engineering & Manufacturing North America, Inc., Plano, TX (US)
Filed by Toyota Motor Engineering & Manufacturing North America, Inc., Plano, TX (US)
Filed on Aug. 20, 2020, as Appl. No. 16/998,529.
Prior Publication US 2022/0058495 A1, Feb. 24, 2022
Int. Cl. G06Q 30/02 (2023.01); G01C 21/34 (2006.01); G01C 21/36 (2006.01); G06N 5/04 (2023.01); G06N 7/01 (2023.01); G06N 20/00 (2019.01); G06Q 30/0201 (2023.01); G06Q 50/14 (2012.01); G16H 50/70 (2018.01)
CPC G06N 5/04 (2013.01) [G01C 21/3492 (2013.01); G01C 21/3682 (2013.01); G06N 7/01 (2023.01); G06N 20/00 (2019.01); G06Q 30/0201 (2013.01); G16H 50/70 (2018.01); G06Q 50/14 (2013.01)] 18 Claims
OG exemplary drawing
 
6. A method of determining and providing a rest stop recommendation, comprising:
monitoring, over a period of time, driving behavior of an ego driver driving a vehicle and store information indicating the driving behavior as historical data;
determining, based at least in part on the historical data, a driver tiredness state, a continuous driving length preference, and a refueling pattern preference, wherein the determining the continuous driving length preference comprises:
extracting, from the historical data, a distribution of sequences of continuous drive time lengths before a rest;
determining a posterior distribution of the continuous drive time lengths before the rest based on Bayesian inference; and
determining the continuous driving length preference as a summation of a mean value and a standard deviation value over the distribution and the posterior distribution;
determining a time to recommend a rest stop based at least in part on the driver tiredness state, the continuous driving length preference, and the refueling pattern preference;
extracting, from a map database, a plurality of rest stops within a predetermined radius of a position of the vehicle;
determining rest stop characteristic preferences based at least in part on the historical data;
selecting one or more potential rest stops from among the plurality of rest stops based at least in part on the rest stop characteristic preferences;
presenting the one or more potential rest stops to the ego driver in a recommendation;
determining one or more routes, respectively, for the one or more potential rest stops based at least in part on the historical data;
receiving, via an input system, a selection of a route of the one or more routes; and
communicating with at least one vehicle system to perform, in an automated manner, at least a portion of a navigation of the vehicle along the route,
wherein the at least one vehicle system comprises at least one of a propulsion system, a braking system, a steering system, a throttle system, a transmission system, a signaling system, or a navigation system.