Systems and techniques for reducing disturbance from autonomous vehicle activity
A process for mitigating potential disturbance can include obtaining at least one of wireless activity data associated with a geographic area, vehicle traffic data associated with the geographic area, and sound data associated with the geographic area; determining, based on one or more of the wireless activity data, the vehicle traffic data, and the sound data, a disturbance factor associated with the geographic area, wherein the disturbance factor indicates a likelihood of an autonomous vehicle activity disturbing one or more persons within the geographic area; and determining, based on the disturbance factor, instructions corresponding to at least one autonomous vehicle.
1 . A fleet management system comprising:
a memory; and
one or more processors coupled to the memory, the one or more processors being configured to:
obtain at least one of wireless activity data associated with a geographic area, vehicle traffic data associated with the geographic area, and sound data associated with the geographic area;
determine, based on an analysis of the wireless activity data, the vehicle traffic data, and the sound data by the one or more processors, a disturbance factor associated with the geographic area, wherein the disturbance factor is a quantitative metric which indicates a likelihood of an autonomous vehicle activity disturbing one or more persons within the geographic area;
determine, based on the disturbance factor, instructions corresponding to at least one autonomous vehicle; and
control the at least one autonomous vehicle based on the instructions.
2 . The fleet management system of claim 1 , wherein;
the wireless activity data associated with the geographic area includes at least one of Wi-Fi activity data and cellular activity data of a population which comprises the one or more persons and is located in the geographic area;
the one or more processors are configured to:
determine, based on the wireless activity data, a level of wireless activity of persons comprised in the population; and
determine the disturbance factor based on correlation between the wireless activity data and one or more of:
a density of the population in the geographic area; and
respective activity states of the persons comprised in the population.
3 . The fleet management system of claim 1 , wherein the one or more processors are further configured to:
obtain pedestrian traffic data associated with the geographic area, wherein the disturbance factor is further based on the pedestrian traffic data.
4 . The fleet management system of claim 1 , wherein the sound data associated with the geographic area includes at least one of a sound amplitude level and a sound absorbability level.
5 . The fleet management system of claim 1 , wherein the sound data associated with the geographic area is received from one or more autonomous vehicles navigating through the geographic area.
6 . The fleet management system of claim 1 , wherein the instructions corresponding to the at least one autonomous vehicle include at least one of a vehicle service instruction, a vehicle recovery instruction, a vehicle routing instruction, a vehicle passenger alert, a vehicle lighting configuration, and a vehicle audio system configuration.
7 . The fleet management system of claim 1 , wherein at least one of the wireless activity data, the vehicle traffic data, and the sound data correspond to historical data associated with the geographic area.
8 . The fleet management system of claim 1 , wherein the one or more processors are further configured to:
in response to a determination that the disturbance factor is greater than a threshold value, send a message to a passenger device associated with the at least one autonomous vehicle, wherein the message includes at least one of an alternate drop-off location, an alternate pick-up location, and a quietness notification; and
control the at least one autonomous vehicle based on a user response associated with the message.
9 . The fleet management system of claim 1 , wherein the one or more processors are further configured to:
determine an in-cabin noise level based on cabin audio data received from the at least one autonomous vehicle, wherein the disturbance factor is further based on the in-cabin noise level.
10 . The fleet management system of claim 1 , wherein the one or more processors are further configured to:
send routing instructions directing one or more autonomous vehicles to navigate through the geographic area, wherein the one or more autonomous vehicles are configured to collect at least one of the wireless activity data, the vehicle traffic data, and the sound data.
11 . The fleet management system of claim 1 , wherein the one or more processors are configured to determine the disturbance factor based on applying respective weights to the wireless activity data, the vehicle traffic data, and the sound data.
12 . A method comprising:
obtaining at least one of wireless activity data associated with a geographic area, vehicle traffic data associated with the geographic area, and sound data associated with the geographic area;
determining, based on analyzing the wireless activity data, the vehicle traffic data, and the sound data, a disturbance factor associated with the geographic area, wherein the disturbance factor is a quantitative metric which indicates a likelihood of an autonomous vehicle activity disturbing one or more persons within the geographic area;
determining, based on the disturbance factor, instructions corresponding to at least one autonomous vehicle; and
controlling the at least one autonomous vehicle based on the instructions.
13 . The method of claim 12 , wherein:
the wireless activity data associated with the geographic area includes at least one of Wi-Fi activity data and cellular activity data of a population which comprises the one or more persons and is located in the geographic area; and
the method further comprises:
determining, based on the wireless activity data, a level of wireless activity of persons comprised in the population; and
determining the disturbance factor based on correlation between the wireless activity data and one or more of:
a density of the population in the geographic area; and
respective activity states of the persons comprised in the population.
14 . The method of claim 12 , further comprising:
obtaining pedestrian traffic data associated with the geographic area, wherein the disturbance factor is further based on the pedestrian traffic data.
15 . The method of claim 12 , wherein the sound data associated with the geographic area includes at least one of a sound amplitude level and a sound absorbability level.
16 . The method of claim 12 , wherein the sound data associated with the geographic area is received from one or more autonomous vehicles navigating through the geographic area.
17 . The method of claim 12 , wherein the instructions corresponding to the at least one autonomous vehicle include at least one of a vehicle service instruction, a vehicle recovery instruction, a vehicle routing instruction, a vehicle passenger alert, a vehicle lighting configuration, and a vehicle audio system configuration.
18 . The method of claim 12 , wherein at least one of the wireless activity data, the vehicle traffic data, and the sound data correspond to historical data associated with the geographic area.
19 . The method of claim 12 , further comprising:
in response to determining that the disturbance factor is greater than a threshold value, sending a message to a passenger device associated with the at least one autonomous vehicle, wherein the message includes at least one of an alternate drop-off location, an alternate pick-up location, and a quietness notification; and
controlling the at least one autonomous vehicle based on a user response associated with the message.
20 . A non-transitory computer-readable media comprising instructions stored thereon which, when executed are configured to cause a computer or processor to:
obtain at least one of wireless activity data associated with a geographic area, vehicle traffic data associated with the geographic area, and sound data associated with the geographic area;
determine, based on an analysis of the wireless activity data, the vehicle traffic data, and the sound data by the computer or processor, a disturbance factor associated with the geographic area, wherein the disturbance factor is a quantitative metric which indicates a likelihood of an autonomous vehicle activity disturbing one or more persons within the geographic area;
determine, based on the disturbance factor, instructions corresponding to at least one autonomous vehicle; and
control the at least one autonomous vehicle based on the instructions.
21 . The non-transitory computer-readable media of claim 20 , comprising further instructions configured to cause the computer or processor to:
in response to a determination that the disturbance factor is greater than a threshold value, send a message to a passenger device associated with the at least one autonomous vehicle, wherein the message includes at least one of an alternate drop-off location, an alternate pick-up location, and a quietness notification; and
control the at least one autonomous vehicle based on a user response associated with the message.