FIG. 2 shows an exemplary IRIS sensing framework. 201: Vehicles send data collected within their sensing range to RSUs. 202: RSUs collect lane traffic information based on vehicle data on the lane; RSUs share/broadcast their collected traffic information to the vehicles within their range. 203: RSU collects road incidents information from reports of vehicles within its covering range. 204: RSU of the incident segment send incident information to the vehicle within its covering range. 205: RSUs share/broadcast their collected information of the lane within its range to the Segment TCUs. 206: RSUs collect weather information, road information, incident information from the Segment TCUs. 207/208: RSU in different segment share information with each other. 209: RSUs send incident information to the Segment TCUs. 210/211: Different segment TCUs share information with each other. 212: Information sharing between RSUs and CAVH Cloud. 213: Information sharing between Segment TCUs and CAVH Cloud.

FIG. 3 shows an exemplary IRIS prediction framework. 301: data sources comprising vehicle sensors, roadside sensors, and cloud. 302: data fusion module. 303: prediction module based on learning, statistical and empirical algorithms. 304: data output at microscopic, mesoscopic and macroscopic levels.