System and method for determining a target vehicle speed

A system, comprising:

• a sensor;
• one or more processors;
• and
• physical memory storing computer-executable instructions that, as a result of being executed by the one or more processors, cause the system to:
• receive sensor data from the sensor;
• determine, based at least in part on the sensor data, a plurality of conditions associated with a driving environment of a vehicle, wherein the plurality of conditions comprise:
• a first number of additional vehicles in proximity to the vehicle and travelling in a same direction as the vehicle;
• a second number of additional vehicles in proximity to the vehicle and travelling in an opposite direction relative to the vehicle;
• and
• environmental conditions comprising one or more of a physical road condition, weather of the driving environment, or visibility;
• provide the first number of additional vehicles in the same direction, the second number of additional vehicles in the opposite direction, and the environmental conditions to a machine-learned model to produce a target speed, the machine-learned model trained using training data generated from vehicles driven by human drivers;
• determine, based at least in part on the sensor data and the target speed, a trajectory for the vehicle;
• determine whether the target speed is within a threshold amount of a previous target speed;
• and
• control the vehicle based at least in part on the trajectory and based at least in part on determining that the target speed is within the threshold amount of the previous target speed.

A non-transitory computer-readable storage medium having stored thereon executable instructions that, as a result of being executed by one or more processors of a computer system, cause the computer system to perform operations comprising:

• obtaining sensor data from one or more sensors on a vehicle;
• determining, based at least in part on the sensor data, one or more parameters representative of characteristics of an environment through which the vehicle travels, wherein the one or more parameters represent characteristics comprising:
• a first number of additional vehicles in proximity to the vehicle and travelling in a same direction as the vehicle;
• a second number of additional vehicles in proximity to the vehicle and travelling in an opposite direction relative to the vehicle;
• and
• environmental conditions comprising one or more of a physical road condition, weather of the environment, or visibility;
• determining, based at least in part on the sensor data and the one or more parameters, a target speed provided by a machine-learned model, the machine-learned model trained by:
• receiving a sample of driving data of an individual vehicle driven by a human driver;
• determining a set of the one or more parameters associated with the sample and an associated speed driven by the human driver;
• and
• inputting the associated speed, the first number of additional vehicles in the same direction, the second number of additional vehicles in the opposite direction, and the environmental conditions into the machine-learned model;
• determining, based at least in part on the sensor data and the target speed, a trajectory for the vehicle;
• and
• controlling the vehicle based at least in part on the trajectory;
• wherein the driving data includes a plurality of data samples, each sample in the plurality of data samples including a value for each parameter in the one or more parameters and an associated speed driven by a human driver.