01660279

Component

High level of detail renders microscopic traffic models impractical for control purposes and local control schemes cannot coordinate actions over the whole city. Thus, development of efficient modeling and control methods for large-scale urban road networks is an important research challenge. Providing a unimodal, low-scatter, and demand-insensitive relationship between vehicle accumulation and travel production inside an urban region, the macroscopic fundamental diagram (MFD) of urban traffic has been developed into a powerful modeling tool for building aggregated,low-complexity dynamic urban network models suitable for real-time traffic management. Alleviating congestion via manipulation of traffic flows or assignment of vehicles to specific paths has a great potential in achieving efficient network usage. Motivated by this fact, this paper proposes a hierarchical traffic management scheme that combines a network-level regional route guidance model predictive control (MPC) scheme with a region-level subregional path assignment mechanism. The route guidance MPC optimizes network performance based on actuation via regional split ratios, whereas the path assignment mechanism recommends paths for vehicles to follow, realizing the regional split ratios sent by the MPC in order to achieve said performance. Simulation results in a detailed 49 subregion model indicates potential of the proposed scheme in achieving coordination and efficient use of network capacity, leading to increased mobility

This paper was sponsored by TRB committee AHB45 Standing Committee on Traffic Flow Theory and Characteristics.

18-03326

English

17p

2018

Transportation Research Board 97th Annual Meeting

Digital/other

Figures; References

Mathematical prediction; Networks; Physical distribution; Routes and routing; Simulation; Traffic models; Urban areas

Macroscopic fundamental diagrams

Highways; Operations and Traffic Management

Transportation Research Board Annual Meeting 2018 Paper #18-03326

TRIS, TRB, ATRI

Jan 8 2018 10:49AM