International Business Machines Corporation

Renjie Yao

Chun Ma

Jian Ding

Zhi Hu Wang

Ning Duan

Wei Shan Dong

Peng Gao

Peng Ji

Jing Chang Huang

Chang Li

Ting Yuan

Wei Sun

Jian Li

Wen Han Luo

A mechanism is provided for controlling the internal air-quality of a vehicle, including configuring a control policy that controls an internal air-quality of a vehicle and performing an action dictated by the control policy according to a window status of the vehicle.

Intelligent in-vehicle air-quality control

A mechanism is provided for controlling the internal air-quality of a vehicle, including determining a changing trend of the in-vehicle air-quality based on acquired in-vehicle sensor data and usage status of the vehicle and responsive to the determined changing trend of the in-vehicle air-quality, signaling a control system of the vehicle to control the usage status of the vehicle based on a control policy.

Embodiments are described for minimizing a wait time for a rider after sending a ride request for a vehicle. An example computer-implemented method includes receiving a ride request, the request being for travel from a starting location to a zone in a geographic region during a specified timeslot. The method further includes predicting travel demand based on a number of ride requests in the zone during the specified timeslot. The method further includes requesting transport of one or more vehicles to the zone in response to the predicted number of ride requests when the travel demand is predicted to exceed a number of vehicles in the zone during the specified timeslot.

Neural network computing systems for predicting vehicle requests

A mechanism is provided for controlling the internal air-quality of a vehicle. In-vehicle sensor data of a vehicle are acquired and the usage status of the vehicle is determined based on the acquired in-vehicle sensor data. Based on the acquired in-vehicle sensor data and the determined usage status, a changing trend of the in-vehicle air-quality is determined and responsive to the determined changing trend of the in-vehicle air-quality, a control system of the vehicle is signaled to control the usage status of the vehicle based on a control policy.

Systems and methods for obtaining vehicle operational data and driving context data from one or more monitoring systems, including converting the obtained vehicle operational data and driving context data into sequential vehicle operational feature data and sequential driving context feature data, calibrating the sequential vehicle operational feature data and the sequential driving context feature data temporally to form calibrated sequential vehicle operational feature data and calibrated sequential driving context feature data, constructing a sequence table of temporal sample points based on the calibrated sequential vehicle operational feature data and the calibrated sequential driving context feature data, feeding the sequence table into a deep neural network model for applying network learning to form a trained deep neural network model, extracting driving behavior features from the trained deep neural network model and analyzing the extracted driving behavior features to determine driving behavior characteristics of the driver.

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Beijing, China

Renjie Yao