01593862

Component

When the traffic state becomes oversaturated, intersections are not immune to congestion. It is necessary to understand the traffic dynamic of the signalized arterial network to determine proper signal control plans. A number of elaborate arterial traffic flow models, which were deductively derived to describe the complex interactions between traffic state evolution and key control parameters, have been applied to provide relatively accurate predictions. Model-based proactive control systems can adjust signal timing plans in real time to handle fluctuations and congestion-based predicted traffic states. A particular simplified control design pursued in various past studies is based on store-and-forward modeling (SFM). This paper presents a new methodology for optimizing the signal timing controls of an oversaturated corridor based on an enhanced SFM model and a multi-objective technique. The multi-objective model seeks to find trade-offs between maximizing throughput and minimizing the average queue ratio. An adaptive control simulation platform is developed using a full-scale signal simulator, ASC/3, in a microscopic traffic model VISSIM. A case study of a 7.4-kilometer arterial corridor reveals that (1) the Pareto frontier can provide more appropriate alternatives under particular situations, and (2) the proposed model is promising for use in the design of arterial signals, especially under congested, high demand traffic conditions, as compared to traditional actuated signal control.

This paper was sponsored by TRB committee AHB25 Standing Committee on Traffic Signal Systems. Alternate title: Multiobjective Signal Optimization with Embedded Enhanced Store-and-Forward Model for Oversaturated Corridor

01584066

16-3704

English

18p

2016

Transportation Research Board 95th Annual Meeting

Digital/other

Figures; References; Tables

Arterial highways; Case studies; Optimization; Signalization; Traffic congestion; Traffic flow

VISSIM (Computer model)

Highways; Operations and Traffic Management

Transportation Research Board Annual Meeting 2016 Paper #16-3704

TRIS, TRB, ATRI

Jan 12 2016 5:37PM