No abstract

A key question about cooperative vehicle longitudinal control is reactivity, which determines the future of road safety, and capacity. In adaptive cruise control (ACC), the controller adapts the speed of the vehicle to its immediate leader's speed whereas, in the cooperative version (CACC), connectivity between the platoon equipped vehicles reduces their response times. The USDoT Cooperative Automated Research Mobility Applications (CARMA) platform provides data for platooning experiments involving ACC and CACC vehicles. We measure ACC response times (mean = 2.78 seconds) larger than for human-driven cars. We study response times inside CACC platoons showing that connectivity is not always effective.

International audienceThis paper addresses the problem of travel time forecasting within a highway. Several measurements are captured describing travel times for multiple origin-destination (OD) pairs. A network model is then proposed to infer travel time between origin and destination based on a reduced number of states. The forecast strategy is based on current day and historical data. Historical data is organized into several clusters. For each cluster, a predictor is designed based on the Kalman filtering strategy. Then these predictions are fused, in a best linear unbiased estimation sense, in order to get the best prediction. The performance of the proposed method is evaluated using traffic data from the South Ring of the Grenoble city in France