Abstract
The traditional signalized intersection is no longer able to meet the increasing demands of transportation. A method combining autonomous intersection management (AIM) and connected and automated vehicles (CAVs) is suggested for solving existing traffic problems. This study proposes a control method for unsignalized intersections based on cooperative grouping, which discretizes the continuous traffic flow into a series of small-scale vehicle groups. In addition, a Petri Net model with a progressive structure is proposed, for which the time domain sequence of each group is strictly defined. To realize the global control of CAVs, the whole process of vehicle movement is decomposed into two processes: <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">i</i> ) adjustment on branches and <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">ii</i> ) coordination in the junction. All grouping conditions in the junction are clearly defined, and time windows are used for the discrete traffic flow modeling. Furthermore, a cooperative adaptive cruise control (CACC) model with bifurcations is proposed for grouping and following the control of vehicles on each branch. Simulation results show that vehicles are automatically grouped according to their initial positions, and no collision occurs during the whole process. Applied with the proposed method, the traffic capacity of a four-branch intersection exceeds 10000 veh/h under ideal conditions. The vehicles run more smoothly and show a better fuel economy than the other two methods.
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