Abstract: A test method for a variable speed limit (VSL) strategy in a mixed traffic flow considering driver compliance is provided. A road scenario is built, and multiple mixed traffic flows formed by human-driven vehicles (HDVs) and connected and automated vehicles (CAVs) are set, which vary in CAV penetration rate. The VSL strategy is established, and a speed limit of an upstream of the bottleneck area is calculated based on the VSL strategy. A HDV compliance is established, and in combination with the speed limit, the HDV drivers are classified, and a proportion of the HDV drivers in individual types in the road scenario is determined. Based on a traffic flow scenario in which the HDV drivers and CAV drivers are located, indicator data reflecting traffic capacity is calculated. A test system for performing the test method is further provided.

Abstract: A smooth cooperative lane change control method for multi-connected and autonomous vehicles (CAVs), including: acquiring vehicle information of a lane-changing vehicle M and four surrounding vehicles A, B, C and D; constructing uncontrolled-vehicle and controlled-vehicle motion state prediction models; according to the motion state prediction models, predicting motion states of the lane-changing vehicle M, and the vehicles A, B, C and D; constructing an upper-layer optimization model to calculate an optimal control value and an optimized motion state of the lane-changing vehicle M and an optimal control value of the vehicle A; constructing a lower-layer optimization model to calculate an optimal control value of the vehicle D; and controlling the lane-changing vehicle M, the vehicle A and the vehicle D to run according to a corresponding optimal control value.

Abstract: A control method of mixed traffic flow on freeway ramp based on controllable connected and autonomous vehicles (CAVs) is provided. A ramp is divided into a normal driving section, a vehicle platoon formation section and an accelerating and merging section. A vehicle platoon is formed by a leading CAV and human-driven vehicles (HDVs). Time interval [tmin, tmax] for the vehicle platoon to completely reach the merging point S is calculated. CAVs on the main lane and ramp are cooperatively controlled, and a merging gap is reserved for the ramp vehicle platoon. The vehicle platoon is allowed to accelerate and merge into the main lane. By means of the Internet-of-Vehicle (IoV) technology, the traffic situation on the main lane and downstream merging zone can be obtained in advance, and speeds of the CAVs are cooperatively controlled to lead the ramp vehicles to safely merge into the main lane.

Abstract: A smooth cooperative lane change control method for multi-connected and autonomous vehicles (CAVs), including: acquiring vehicle information of a lane-changing vehicle M and four surrounding vehicles A, B, C and D; constructing uncontrolled-vehicle and controlled-vehicle motion state prediction models; according to the motion state prediction models, predicting motion states of the lane-changing vehicle M, and the vehicles A, B, C and D; constructing an upper-layer optimization model to calculate an optimal control value and an optimized motion state of the lane-changing vehicle M and an optimal control value of the vehicle A; constructing a lower-layer optimization model to calculate an optimal control value of the vehicle D; and controlling the lane-changing vehicle M, the vehicle A and the vehicle D to run according to a corresponding optimal control value.

Abstract: Provided is a method for berth allocation of a multiline bus station and speed guidance of buses. The intelligent control center sorts all buses between the current station and the previous station to form the BusNumber table, and performs speed guidance for all buses in the BusNumber table. Whether the guided bus can pass through the signalized intersection is determined. The buses that cannot pass through the signalized intersection are guided by acceleration, and those that cannot pass through the signalized intersection by acceleration guidance method update their speeds based on the phase state of signal light, so as to pass through the signalized intersection without stopping in most cases. All buses are conducted through speed guidance methods, and the berths are allocated for all the buses under different conditions.

Abstract: Provided is a method for berth allocation of a multiline bus station and speed guidance of buses. The intelligent control center sorts all buses between the current station and the previous station to form the BusNumber table, and performs speed guidance for all buses in the BusNumber table. Whether the guided bus can pass through the signalized intersection is determined. The buses that cannot pass through the signalized intersection are guided by acceleration, and those that cannot pass through the signalized intersection by acceleration guidance method update their speeds based on the phase state of signal light, so as to pass through the signalized intersection without stopping in most cases. All buses are conducted through speed guidance methods, and the berths are allocated for all the buses under different conditions.