Ilsoo Yun

Application of Microscopic Simulation Model Calibration and Validation Procedure: Case Study of Coordinated Actuated Signal System

In the application of microscopic simulation models, the importance of model calibration and validation cannot be overemphasized. A recent study proposed a systematic approach for conducting a simulation model calibration and validation procedure on the basis of experimental design and optimization and applied it to an isolated intersection with a VISSIM simulation model. The present study further evaluates the previously developed simulation model calibration and validation procedure by applying it to an urban arterial network consisting of 12 coordinated actuated signalized intersections. Both VISSIM and CORSIM simulation models were used. Travel time was used for the calibration measure, and maximum queue length was used for the validation measure. Study results showed that calibrated and validated simulation models were able to represent field conditions adequately, whereas default parameter-based models could not. As such, the previously developed simulation model calibration and validation procedure...

Stochastic Optimization for Sustainable Traffic Signal Control

ABSTRACT The primary research focus of traffic signal control systems has been the development of traffic signal timing plans minimizing vehicular delay and stops. Very little is known if such a strategy would be optimal for a sustainable traffic signal control system minimizing emission and fuel consumption. This paper presents a development of a sustainable traffic signal control system and speed management framework consisting of a microscopic simulation model, a microscopic fuel consumption and emission model, and a genetic algorithm – based optimizer. Based on an implementation of the proposed framework on a case study network, it was found that the proposed framework was very effective in minimizing fuel consumption and emission with moderate trade-offs in delay and stops.

Cumulative Travel-Time Responsive Real-Time Intersection Control Algorithm in the Connected Vehicle Environment

This paper presents a cumulative travel-time responsive (CTR) real-time intersection control algorithm that takes full advantage of connected vehicles (CVs). The potential benefits of the proposed CTR algorithm under varying imperfect CV market penetration rates and traffic congestion conditions were investigated. The core of the CTR algorithm is based on a stochastic state estimation technique utilizing Kalman filtering that is used in estimating the cumulative travel times under imperfect market penetration rates at every update interval. Comprehensive simulation experiments covering varying volume-to-capacity ratios and imperfect market penetration rates were performed at a hypothetical isolated intersection with two through lanes and a single left-turn lane at each approach. At 100% market penetration, the CTR algorithm improved the total delay time and average speed of the intersection by 34 and 36%, respectively, compared to an optimized actuated control. It was found that at least 30% market penetration rates are needed to realize the benefits of the CTR algorithm.

Enhancement of time of day based traffic signal control

A majority of urban traffic signal systems including coordinated actuated signals deploy multiple signal timing plans to account for traffic demand changes over time during a day (i.e., off peak, morning peak, mid day, evening peak, and night). A recent study proposed a data driven methodology that develops such time of day (TOD) break points using a clustering algorithm. One disadvantage of such statistical approaches was that they often produce clusters with few data points (i.e., infeasible time-of-day interval). This paper presents an enhancement of data driven methodology that determines optimal break points for TOD traffic signal control. In order to overcome such drawback, a genetic algorithm based clustering is proposed and evaluated through the performance of actual timing plan under microscopic simulation program, SIMTRAFFIC. The study results indicate that the proposed method can eliminate infeasible TOD intervals and its TOD-based timing plan produced comparable performances to those existing TOD intervals.

Application of stochastic optimization method for an urban corridor

This paper presents a stochastic traffic signal optimization method that consists of the CORSIM microscopic traffic simulation model and a heuristic optimizer. For the heuristic optimizer, the performance of three widely used optimization methods (i.e., genetic algorithm, simulated annealing and OptQuest Engine) was compared using a real world test corridor with 12 signalized intersections in Fairfax, Virginia, USA. The performance of the proposed stochastic optimization method was compared with an existing signal timing optimization program, SYNCHRO, under microscopic simulation environment. The results indicated that the genetic algorithm-based optimization method outperforms the SYNCHRO program as well as the other stochastic optimization methods in the optimization of traffic signal timings for the test corridor

Estimation of dynamic origin destination matrix: a genetic algorithm approach

Dynamic origin-destination (O-D) matrix estimation is one of the key components in the deployment of microscopic traffic simulation based real-time traffic predictions and estimations. Various theoretical methods have been proposed and tested via relatively small-scale networks. Very few practical studies have attempted to evaluate the performance of dynamic O-D matrix estimation methods for large-scale networks. This is because practical applications have not yet adopted dynamic O-D matrix estimation method, in part, due to the complexity and time requirements of advanced methods. This paper investigates the application of dynamic O-D matrix estimation methods for a large-scale network using a genetic algorithm (GA). The performance of GA-based method was compared with that of the QUEENSOD method using a microscopic traffic simulation program, PARAMICS. The evaluation results indicate that the GA-based method outperforms the QUEENSOD method.

Study of the Effect of the Point-to-Point Speed Enforcement System Using a Comparison-Group Method

In order to reduce traffic accidents at long road sections involving high risks of traffic accidents, including tunnels, bridges or curves, the National Police Agency have decided a tentative installation and operation of an automated point-to-point speed enforcement system based on cameras at January, 2007. The first system was established at the direction to Kangreung of Dunnae Tunnel at December, 2007. Currently, the automated point-to-point speed enforcement system operates at 11 sections including eight sections on expressways and three sections on national highways. However, there have been few researches on the effects of the system upon the reduction of traffic accidents in a scientific way. To this end, this research effort was initiated to evaluate the effect of the automated point-to-point speed enforcement system on traffic safety by comparing the number of traffic accidents before and after the installation of the system using a comparison-group(C-G) method. Three-year-long traffic accident data for the expressways were collected in order to evaluate the system. As a result, the installation of the system was found to reduce traffic accidents by 49.97% in average.

Evaluation of Microscopic Simulation Tools for Coordinated Signal System Deployment

With the advances in the computational technology, microscopic traffic simulation models have become more realistic than ever, for example, 3D animations. They have been widely adopted as decision-supporting tools on various traffic operation and management studies. However, very few studies analyzed pros and cons of these models. At times, a microscopic simulation program is selected only because it was available for the engineers at the time of study. In practice, model selection has not been well exercised mainly due to the lack of available literature and experience. This paper presents a quick overview of four microscopic traffic simulation models and evaluates their performances using a case study of modeling a coordinated signal system. Models studied in this paper are CORSIM, Paramics, SIMTRAFFIC, and VISSIM. In order to provide reference performance measures for various traffic signal settings including pretimed and actuated controls, SYNCHRO program is utilized.

Comparative evaluation of heuristic optimization methods in urban arterial network optimization

Heuristic optimization methods have been widely applied in the engineering applications that are known to be extremely difficult to find an optimal solution using traditional mathematical approaches. Examples of such optimizations in transportation problems includes: congestion pricing, dynamic traffic assignment, developing traffic signal timing plans, etc. Studies have shown mixed results on the performances of various heuristic optimization methods. Obviously, the performance depends largely on the nature of problems, complexity of solution space, etc. This paper presents an evaluation of a few selected heuristic optimization methods (genetic algorithm (GA), harmony search (HS), and OptQuest) applied to solving a transportation optimization problem of an urban arterial network. The study results showed that the control parameters in GA and HS significantly affected the performance, and with properly determined parameters, GA outperformed HS and OptQuest. In addition, the best control parameters in GA and HS are robust to increased traffic conditions.

Feasibility assessment of ITS deployment analysis system (IDAS) for ITS evaluations

This study investigated the feasibility of utilizing the ITS deployment analysis system (IDAS) program version 2.2 as a tool for evaluating intelligent transport systems (ITS) deployment plans. First, an online survey was conducted among MPO staffs in the US to understand the usage and the issues of the IDAS program for the ITS deployment plan evaluation. Second, case studies were carried out to examine the benefits of deploying several popular ITS options. The case studies of Hampton Roads area and a simple network with six selected ITS options identified three issues: (i) overestimation of ITS option benefits when the benefits are estimated from travel time savings, (ii) incorrect interpolation on travel time reliability rates for non-integer V/C ratios, and (iii) insensitive cost savings for combined ITS options.