Road condition status prediction method, device, and server, and storage medium

A road condition status prediction device, the road condition status prediction device being disposed in a server, and the road condition status prediction device comprising:

• at least one memory configured to store computer program code;
• and
• at least one processor configured to access the at least one memory and operate according to the computer program code, the computer program code comprising:
• information obtaining code configured to cause the at least one processor to obtain historical road segment information, the historical road segment information comprising road condition statuses and classification events that are used to classify the road condition statuses, and the classification events being determined based on content of the classification events;
• calculation code configured to cause the at least one processor to:
• obtain an occurrence probability of each of the classification events, based on the obtained historical road segment information;
• and
• obtain a conditional probability of each of the classification events in each of the road condition statuses, based on the obtained historical road segment information;
• and
• prediction code configured to cause the at least one processor to predict a road condition status of a road segment, based on the obtained occurrence probability of each of the classification events and the obtained conditional probability of each of the classification events in each of the road condition statuses.

A non-transitory computer-readable storage medium storing instructions that cause at least one processor to:

• obtain historical road segment information, the historical road segment information comprising road condition statuses and classification events that are used to classify the road condition statuses, and the classification events being determined based on content of the classification events;
• obtain an occurrence probability of each of the classification events, based on the obtained historical road segment information;
• obtain a conditional probability of each of the classification events in each of the road condition statuses, based on the obtained historical road segment information;
• and
• predict a road condition status of a road segment, based on the obtained occurrence probability of each of the classification events and the obtained conditional probability of each of the classification events in each of the road condition statuses.