01516666

Component

https://doi.org/10.3141/2466-12

The route choice system and the traffic control system (TCS) constitute two major approaches to mitigating congestion in urban road networks. The interaction between signal control and route choice is considered from a narrower route choice system perspective, with the focus on route choice models for operational purposes. The goal is to analyze the relative performance of alternative route choice models as different assumptions are made about the type of TCS in use. To this end, an agent-based framework for formulating different route choice models is defined, and this framework is integrated with a microscopic traffic simulation environment. Within the framework, each agent’s memory is updated repeatedly (daily) to reflect available prior individual and social experience, and then a route is chosen by a probabilistic sequential decision-making process. Several previously developed route choice models from the literature are implemented with the framework, and their performance, along with some additional hybrid models that are suggested by the modeling framework, is evaluated on two simulated real-world systems: a 32-intersection road network in Pittsburgh, Pennsylvania, running with a SYNCHRO-generated coordinated timing plan and the same road network running with the scalable urban traffic control (SURTRAC) adaptive TCS. The results show that specific route choice models perform differentially when applied in conventional and adaptive traffic control settings and that better overall network performance for all route choice models is achieved in the adaptive control setting. This unified framework also makes it possible to analyze the performance impact of route choice model components and to formulate better-performing hybrid models.

01557688

14-2100

English

pp 105–113

2014

Transportation Research Record: Journal of the Transportation Research Board

9780309295581

Print

Figures (4) ; References (35) ; Tables (1)

Adaptive control; Highway traffic control systems; Route choice; Traffic congestion; Traffic signal control systems; Traffic simulation; Urban areas

Agent based models

Pittsburgh (Pennsylvania)

Highways; Operations and Traffic Management; Planning and Forecasting; I72: Traffic and Transport Planning; I73: Traffic Control

TRIS, TRB, ATRI

Jan 27 2014 2:44PM

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