Integration of Dynamic Traffic Assignment with Real-Time Traffic Adaptive Control System

1998 ◽  
Vol 1644 (1) ◽  
pp. 150-156 ◽  
Author(s):  
Nathan H. Gartner ◽  
Chronis Stamatiadis
Keyword(s):  
Adaptive Control ◽  
Control System ◽  
Real Time ◽  
Traffic Assignment ◽  
Dynamic Traffic Assignment ◽  
Transportation Systems ◽  
Signal Control ◽  
Adaptive Control System ◽  
Dynamic Traffic ◽  
Real Time Traffic

Intelligent transportation systems (ITS) are being designed to provide real-time control and route guidance to motorists to optimize traffic network performance. Current research and development efforts consist of a dynamic traffic assignment capability that can predict future traffic conditions and a real-time traffic adaptive control system (RT-TRACS) for generation of signal control strategies. Although these models are intimately connected, so far they have developed independently of one another. A framework is presented here for integrating the two models into a combined system with a practical approach for realizing it. First the static case involving the interaction between travelers (demand) and transportation facilities (supply) under recurrent conditions is discussed. This model is applicable in the design and planning of transportation systems management actions. The framework is then extended to the quasi-dynamic and the dynamic cases, which involve incorporation of advanced ITS technologies in the form of advanced traffic management systems and advanced traveler information systems. An innovative application of this framework to advanced traffic-adaptive signal control is presented using the hierarchic structure of RT-TRACS.

Real-Time Traffic Flow Pattern Matching to Improve Predictive Performance of Online Simulation-Based Dynamic Traffic Assignment

2019 ◽  
Vol 2673 (9) ◽  
pp. 23-33
Author(s):  
Haleh Ale-Ahmad ◽  
Hani S. Mahmassani ◽  
Eunhye Kim ◽  
Marija Ostojic
Keyword(s):  
Real Time ◽  
Pattern Matching ◽  
Traffic Assignment ◽  
Dynamic Traffic Assignment ◽  
Predictive Performance ◽  
Dynamic Traffic ◽  
Time Pattern ◽  
Real Time Traffic ◽  
Simulation Based ◽  
Soft Matching

In real-time simulation-based dynamic traffic assignment, selection of the most suitable demand from the library of demands calibrated offline improves the accuracy of the prediction. In the era of data explosion, relying on contextual and rule-based pattern matching logic does not seem sufficient. A rolling horizon scheme for real-time pattern matching is introduced using two pattern matching frameworks. The hard matching algorithm chooses the closest pattern at each evaluation interval, while soft matching calculates the probability of being a match for each pattern. To make sure the pattern switch does not happen because of short-lived interruptions in traffic conditions, a persistency index is introduced. The results show that the number of switches in hard matching is bigger than soft matching but the error of real-time matching for both cases is low. The importance of the results is twofold: First, any observation that is not similar to only one pattern in the library can be mimicked using multiple available patterns; second, more advanced algorithms can match the patterns existing in the library, without any contextual logics for pattern matching.

ACS-Lite Algorithmic Architecture: Applying Adaptive Control System Technology to Closed-Loop Traffic Signal Control Systems

2003 ◽  
Vol 1856 (1) ◽  
pp. 175-184 ◽  
Author(s):  
Felipe Luyanda ◽  
Douglas Gettman ◽  
Larry Head ◽  
Steven Shelby ◽  
Darcy Bullock ◽  
...  
Keyword(s):  
Adaptive Control ◽  
Control System ◽  
Control Systems ◽  
Closed Loop ◽  
Signal Control ◽  
Traffic Signal Control ◽  
Adaptive Control System ◽  
Traffic Conditions ◽  
Run Time ◽  
Traffic Signal Control Systems

ACS-Lite is being developed by FHWA to be a cost-effective solution for applying adaptive control system (ACS) technology to current, state-of-the-practice closed-loop traffic signal control systems. This effort is intended to make ACS technology accessible to many jurisdictions without the upgrade and maintenance costs required to implement ACS systems that provide optimized signal timings on a second-by-second basis. The ACS-Lite system includes three major algorithmic components: a time-of-day (TOD) tuner, a run-time refiner, and a transition manager. The TOD tuner maintains plan parameters (cycle, splits, and offsets) as the long-term traffic conditions change. The run-time refiner modifies the cycle, splits, and offsets of the plan that is currently running based on observation of traffic conditions that are outside the normal bounds of conditions this plan is designed to handle. The run-time refiner also determines the best time to transition from the current plan to the next plan in the schedule, or, like a traffic-responsive system, it might transition to a plan that is not scheduled next in the sequence. The transition manager selects from the transition methods built in to the local controllers to balance the time spent out of coordination with the delay and congestion that is potentially caused by getting back into step as quickly as possible. These components of the ACS-Lite algorithm architecture are described and the similarities and differences of ACS-Lite with state-of-the-art and state-of-the-practice adaptive control algorithms are discussed. Closed-loop control system characteristics are summarized to give the context in which ACS-Lite is intended to operate.

Sign in / Sign up

Export Citation Format

Share Document