01049638

Component

https://doi.org/10.3141/2035-17

http://scholar.google.com....+Li&publication_year=2007

Traffic signal timing would be a trivial undertaking if demand were constant and uniform. Once stochastic factors and demand fluctuation are taken into consideration, however, the optimization of signal timing becomes challenging, if not impossible, even for an isolated, fixed-time signal. To answer the question of whether a longer cycle—more than 150 s, for example—or a shorter one—less than 60 s, for example—is better under fluctuating demand conditions, a probabilistic approach is employed to study minimal average delay by the use of mathematical formulations and Monte Carlo simulations. The idea is to select a cycle length that is small enough to ensure low delay, and hence level of service, but can provide adequate capacity to handle most of the fluctuating demand conditions. A five-step framework is presented for carrying out the analyses, which are demonstrated with a hypothetical example. Subsequent sensitivity analyses, level-of-service assessment, and cycle failure rate estimation were conducted on the basis of random demand and are presented here. Conclusions of the study include the following: (a) introduction of a fluctuating demand level increases the average delay in general, (b) longer cycle lengths do not yield optimal delay results, and (c) with extremely short cycle lengths, delay is usually high because of a lack of capacity and hence frequent cycle failures are guaranteed. A major contribution of this study is a proposed framework for optimizing cycle length under stochastic inter- and intracycle demand levels based on the expectation function of delay. When deployed, this framework can aid traffic engineers in choosing the desirable cycle length for minimal delay or for any reasonable level-of-service requirements.

01091263

English

pp 150-157

2007

Transportation Research Record: Journal of the Transportation Research Board

9780309104623

Print

Figures (5) ; References (15) ; Tables (3)

Highway capacity; Level of service; Monte Carlo method; Optimization; Traffic delays; Traffic engineering; Traffic flow; Traffic signal cycle; Traffic signal timing

Traffic capacity (Intersections)

Highways; Operations and Traffic Management; I73: Traffic Control

TRIS, TRB, ATRI

Feb 8 2007 7:07PM

• Active Signal Priority for Light Rail Transit at Grade Crossings
• Advance Preempt with Gate-Down Confirmation: Solution for Preempt Trap
• Application of Diamond Interchange Control Strategies at Closely Spaced Intersections
• Data-Driven Algorithms for Real-Time Adaptive Tuning of Offsets in Coordinated Traffic Signal Systems
• Effectiveness of Alternative Detector Configurations for Option Zone Protection on High-Speed Approaches to Traffic Signals
• Empirical Observations of Dynamic Dilemma Zones at Signalized Intersections
• Evaluating Effects of Toll Strategies on Route Diversion and Travel Times for Origin–Destination Pairs in a Regional Transportation Network
• Evaluation of Adaptive Maximum Feature in Actuated Traffic Controller: Hardware-in-the-Loop Simulation
• Event-Based Data Collection for Generating Actuated Controller Performance Measures
• Feasibility of Traffic Simulation for Decision Support in Real-Time Regional Traffic Management
• Foundation for Jointly Determining Passage Time and Detection Zone Length with Stop Bar Presence Detection
• Implementation of Lane-by-Lane Detection at Actuated Controlled Intersections
• Input–Output and Hybrid Techniques for Real-Time Prediction of Delay and Maximum Queue Length at Signalized Intersections
• Methodology to Assess Traffic Signal Transition Strategies for Exit Preemption Control
• Modeling Traffic Signal Operations with Precedence Graphs
• Models for Quantitative Assessment of Video Detection System Impacts on Signalized Intersection Operations
• Opening the New Woodrow Wilson Memorial Bridge: Planning and Implementing a Major Traffic Switch
• Performance Analysis of Coordinated Traffic Signals During Transition
• Recasting Dilemma Zone Design as a Marginal Cost-Benefit Problem
• Risk Analysis to Account for Uncertainty in Benefit–Cost Evaluations of Intelligent Transportation Systems
• Traffic Operations for Hurricane Evacuation
• VisSim-Based Genetic Algorithm Optimization of Signal Timings