Tusimple, Inc.

Tangome, Inc.

Yixin Yang

Zehua Huang

Yuxin Liu

Dinghua Li

Haim Vaisburd

Wei Liu

Siyuan Liu

Lei Su

Yuanyuan Wang

Shaowei Su

Jiangming Jin

Yifan Gong

Eric Setton

Xu Liu

Gregory Dorso

Yishu Lin

Disclosed are devices, systems and methods for the operational testing on autonomous vehicles. One exemplary method includes configuring a primary vehicular model with an algorithm, calculating one or more trajectories for each of one or more secondary vehicular models that exclude the algorithm, configuring the one or more secondary vehicular models with a corresponding trajectory of the one or more trajectories, generating an updated algorithm based on running a simulation of the primary vehicular model interacting with the one or more secondary vehicular models that conform to the corresponding trajectory in the simulation, and integrating the updated algorithm into an algorithmic unit of the autonomous vehicle.

Operational testing of autonomous vehicles

Techniques for analysis of autonomous vehicle operations are described. As an example, a method of autonomous vehicle operation includes storing sensor data from one or more sensors located on the autonomous vehicle into a storage medium, performing, based on at least some of the sensor data, a simulated execution of one or more programs associated with the operations of the autonomous vehicle, generating, based on the simulated execution of the one or more programs and as part of a simulation, one or more control signal values that control a simulated driving behavior of the autonomous vehicle, and providing a visual feedback of the simulated driving behavior of the autonomous vehicle on a simulated road.

Autonomous vehicle simulation system

Techniques are disclosed for performing hybrid simulation operations with an autonomous vehicle. A method of testing autonomous vehicle operations includes receiving, by a computer, a pre-configured scenario that includes one or more simulation parameters and one or more initial condition parameters, sending, to the autonomous vehicle and based on the one or more initial condition parameters, control signals that instruct the autonomous vehicle to operate at an operative condition, and in response to determining that the autonomous vehicle is operating at the operative condition, performing a simulation with the one or more simulated objects and the autonomous vehicle to test a response of the autonomous vehicle.

Hybrid simulation system for autonomous vehicles

The present disclosure provides a method, an apparatus and a system for multi-module scheduling, capable of solving the problem associated with inconsistency in data inputted to a computing module in the multi-module scheduling technique in the related art. The method includes: reading, by a master process, a pre-stored configuration file storing a directed computation graph; initializing, by the master process, states of all the nodes and connecting edges in the directed computation graph initially in computation in a current computing period; determining a node to be called based on the computation direction in the directed computation graph and the states of the nodes, the node to be called comprising a node having all of its input edges in a complete state; transmitting, to the computing module in the slave process corresponding to the node to be called, a call request of Remote Process Call (RPC) to execute the computing module; updating the state of the node and the state of each output edge of the node upon receiving a response to the call request; and proceeding with a next computing period upon determining that the states of all the nodes have been updated.

Method, apparatus, and system for multi-module scheduling

The present disclosure provides a method, an apparatus and a system for multi-module scheduling, capable of solving at least one of the problems associated with the multi-module scheduling technique in the related art, i.e., inconsistency in data inputted to a computing module, and a significant delay or low throughput in data transmission between computing modules. The method includes: reading, by a master process, a pre-stored configuration file storing a directed computation graph; initializing, by the master process, states of the nodes and connecting edges in a current computing period; determining a node to be called based on the computation direction of the directed computation graph and the states of the nodes, the node to be called comprising a node having all of its input edges in a complete state; transmitting, to the computing module in the slave process corresponding to the node to be called, a call request of Remote Process Call (RPC) to execute the computing module; updating the state of the node and the state of each output edge of the node upon receiving a response to the call request; and proceeding with a next computing period after determining that the states of all the nodes in the directed computation graph have been updated.

Method, apparatus and system for multi-module scheduling

A method for controlling error resilience in network communication is described. The method includes: determining, by a receiver-side controller, a packet gap representing a packet loss of a packet being communicated over a network; projecting, by the receiver-side controller, a retransmission time-out for at least one missing packet of the packet loss; issuing, by the receiver-side controller, a retransmission request for the at least one missing packet; if the packet gap is not filled within a first time period of the retransmission time-out, then issuing, by the receiver-side controller, at least one synchronization frame request; and selecting, by a sender-side controller, to respond to at least one of either of the retransmission request or the at least one synchronization frame request and neither of the retransmission request nor the at least one synchronization frame request.

Joint retransmission and frame synchronization for error resilience control

A system for enabling communication between devices is described. The system includes the following: a media processing information receiver configured for receiving, at a first device, media processing information associated with a second device, wherein at least one of the first and second device is a mobile device; a comparer configured for comparing the media processing information to a processing time of the at least one media processing component of the first device; a target adjustment level determiner configured for determining a target adjustment level, wherein arriving at the target adjustment level enables the first and second device to achieve a matching media processing quality level; and a media processing component adjuster coupled with the computer and configured for adjusting the at least one media processing component of the first device to meet the target adjustment level.

Controlling CPU usage to balance fast and slow devices

A method for utilizing an instrumented application in a mobile device environment. The method includes instrumenting an application to generate an instrumented application configured for use in the mobile device environment, obtaining authorization from a governing body for use of the instrumented application in the mobile device environment, and directing the instrumented application to cause a mobile device to operate according to a first setting. The first setting is invoked without requiring further authorization by the governing body.

Growing community of inventors

Beijing, China

Yixin Yang