Kaidi Yang

Multi-scale perimeter control approach in a connected-vehicle environment

Abstract: This paper proposes a novel approach to integrate optimal control of perimeter intersections (i.e. to minimize local delay) into the perimeter control scheme (i.e. to optimize traffic performance at the network level). This is a complex control problem rarely explored in the literature. In particular, modeling the interaction between the network level control and the local level control has not been fully considered. Utilizing the Macroscopic Fundamental Diagram (MFD) as the traffic performance indicator, we formulate a dynamic system model, and design a Model Predictive Control (MPC) based controller coupling two competing control objectives and optimizing the performance at the local and the network level as a whole. To solve this highly non-linear optimization problem, we employ an approximation framework, enabling the optimal solution of this large-scale problem to be feasible and efficient. Numerical analysis shows that by applying the proposed controller, the protected network can operate around the desired state as expressed by the MFD, while the total delay at the perimeter is minimized as well. Moreover, the paper sheds light on the robustness of the proposed controller. This multi-scale hybrid controller is further extended to a stochastic MPC scheme, where connected vehicles (CV) serve as the only data source. Hence, low penetration rates of CVs lead to strong noises in the controller. This is a first attempt to develop a network-level traffic control methodology by using the emerging CV technology. We consider the stochasticity in traffic state estimation and the shape of the MFD. Simulation analysis demonstrates the robustness of the proposed stochastic controller, showing that efficient controllers can indeed be designed with this newly-spread vehicle technology even in the absence of other data collection schemes (e.g. loop detectors).

Implementing transit signal priority in a connected vehicle environment with and without bus stops

ABSTRACT Connected vehicles give more precise and detailed information on vehicle movements, thus can be beneficial to provide priority to public transportation. This paper proposes a transit signal priority algorithm using connected vehicle information for multimodal traffic control. The algorithm can also be adapted to scenarios with near-side or far-side bus stops. Moreover, it can minimize either signal delay or schedule delay for buses while minimizing additional car delays. Simulation is conducted for different volume to capacity ratios, bus arrivals, bus occupancies, and penetration rates. Results show that this algorithm successfully reduces the total passenger delay. It is also shown that this algorithm is not sensitive to the assumed bus passenger occupancy, nor the estimation of bus dwell time, hence does not require accurate information on these parameters. Overall, this algorithm seems rather promising as it significantly reduces the delay of buses with minimal increase to the delay of cars in the conflicting approach.

Continuous and Discrete-Time Optimal Controls for an Isolated Signalized Intersection

A classical control problem for an isolated oversaturated intersection is revisited with a focus on the optimal control policy to minimize total delay. The difference and connection between existing continuous-time planning models and recently proposed discrete-time planning models are studied. A gradient descent algorithm is proposed to convert the optimal control plan of the continuous-time model to the plan of the discrete-time model in many cases. Analytic proof and numerical tests for the algorithm are also presented. The findings shed light on the links between two kinds of models.

A Transit Signal Priority Algorithm under Connected Vehicle Environment

Transit signal priority is a cost-effective way to improve transit operations and reliability. Connected vehicles provide more precise and detailed information on vehicle movements, thus can be beneficial for transit signal priority. This paper proposes a transit signal priority algorithm using connected vehicle information. Simulation is conducted for different total flow, bus arrivals, bus occupancy and penetration rates. Results show that this algorithm successfully reduces the total passenger delay. It is also shown that this algorithm is not sensitive to the assumed occupancy, hence does not require accurate information on bus occupancy. Additionally, this algorithm significantly reduces the delay of buses with minimal increase to the delay of cars in the conflicting approach.