Wonho Suh

EFFECT OF SKIP-STOP POLICY ON A KOREAN SUBWAY SYSTEM

An express subway system is planned for the Seoul, Korea, metropolitan area. Many problems are involved in operating an express subway system, such as installation of siding track and scheduling of passing locations and times for different headways. A skip-stop system can be considered as an alternative to express subway service. With a given origin-destination (O-D) demand matrix, distances between stations, headways, and maximum link speeds, the total time saving of a skip-stop schedule that satisfies safety conditions is predicted. In a field study, the time saving effects based on O-D data for Line 5 in Seoul, Korea, were simulated. From the simulation using C language, the peak-hour waiting time increased by 43.8% to 56.3%, but the travel time decreased by 10.8% to 12.9%, compared with the existing system. Waiting time was only 6.9% to 11.6% of the total system travel time—the total system time decreased by 7.1% to 7.8% and, in the maximum case, up to 9.8%. The skip-stop system can be advantageous to the existing system without constructing additional facilities. When the express line is installed, time saving effects and additional construction costs of the three systems (all-stop system, skip-stop system, and express line with siding track) could be compared.

An investigation of real-time dynamic data driven transportation simulation

Widespread deployment of sensors in roadways and vehicles is creating new challenges in effectively exploiting the wealth of real-time transportation system data. However, the precision of the real-time data varies depending on the level of data aggregation. For example, minute-by-minute data are more precise than hourly average data. This paper explores the ability to create an accurate estimate of the evolving state of transportation systems using real-time roadway data aggregated at various update intervals. It is found that simulation based on inflow data aggregated over a short time interval is capable of providing a superior representation of the real world over longer aggregate intervals. However, the perceived improvements are minimal under congested conditions and most pronounced under un-congested conditions. In addition, outflow constraints should be considered during congested flow periods, otherwise significant deviation from the real world performance may arise

A Probe-Vehicle-Based Evaluation of Adaptive Traffic Signal Control

In 2005, the Cobb County Department of Transportation, Cobb County, GA, conducted an adaptive signal control pilot study implementing the Sydney Coordinated Adaptive Traffic System (SCATS) on 15 intersections. This paper presents the results of a before-and-after probe-vehicle-based operational comparison of optimized time-of-day (i.e., before control) and SCATS (i.e., after control) traffic control system performance. The focus of this operational analysis is the typical operating performance during the weekday peak, weekday off-peak, and weekend travel periods. Travel time data were collected using Global-Positioning-System (GPS)-equipped test vehicles. The results showed that both systems provided good performance, whereas neither the before time-of-day or after SCATS is clearly dominant, except on Cumberland Parkway, where SCATS control consistently provides equivalent or superior performance to that of the time-of-day control.

Ad hoc distributed simulation for transportation system monitoring and near-term prediction

Abstract The widespread deployment of sensors, computers, and communications in vehicles and roadways is creating new challenges and opportunities to effectively exploit the wealth of real-time data and information that is now becoming increasingly available. In this paper the authors capitalize on these rapid technological advancements using a technique termed on-line ad hoc distributed simulation. This approach utilizes a dynamic collection of autonomous simulations interacting with each other and with real-time data in a continuously running, distributed, real-time simulation environment. Within the ad hoc distributed simulation approach a rollback-based time synchronization method is used to allow the simulations to adapt to unanticipated changes in traffic and to changes in predictions produced by other simulations. The proposed approach is tested on a transportation network with different geographical distributions of client locations and randomized network partitioning under different traffic demand scenarios. The results demonstrate that the proposed approach has the ability to share complex traffic data among participating vehicles and process the data in an effective way to provide drivers/system monitoring with near-term traffic predictions.

Ad Hoc Distributed Dynamic Data-Driven Simulations of Surface Transportation Systems

An ad hoc distributed dynamic data-driven simulation is a collection of autonomous online simulations brought together to model an operational system. They offer the potential of increased accuracy, responsiveness, and robustness compared to centralized approaches. They differ from conventional distributed simulations in that they are created bottom-up rather than top-down. They combine concepts from conventional distributed simulations and replicated trials, raising new issues in data management and synchronization. In this article, the ad hoc simulation approach and an optimistic synchronization algorithm are proposed. A prototype coupling in-vehicle transportation simulation is evaluated and shown to yield results comparable to a traditional replicated experiment for the tested scenarios. Experiences applying this concept to a commercial transportation simulator in an emergency scenario are described.

Modeling pedestrian crossing activities in an urban environment using microscopic traffic simulation

Microscopic traffic simulation tools are increasingly being employed as an integral part of modeling vehicular traffic and pedestrian activity. However, the complexity of pedestrians’ behaviors and their interactions with the various components of the traffic network is commonly under-represented in simulation models, resulting in potentially misleading analyses. This paper explores modeling pedestrians at the microscopic level, attempting to replicate observed pedestrian behavior at a crosswalk in Midtown Atlanta, GA. The VISSIM® simulation tool, with pedestrian movement based on the Social Force Model by Helbing and Molnár (Social Force Model for pedestrian dynamics. Phys Rev E 1995; 51: 4282-4286), is utilized. Comparative results of field observations and the microscopic modeling of the same vehicle and pedestrian activity are presented. A primary observation is that, for the intersection studied, only a small percentage of pedestrians appear to comply with the pedestrian signal indication, with the vast majority of pedestrians exhibiting gap-seeking behavior, crossing when a gap is available, regardless of the signal indication. This results in potentially significant over-estimates of wait time if high pedestrian signal compliance rates are assumed. A second notable observation is that the pedestrian crossing behavior is strongly related to the cross-street traffic queue clearance time and subsequent traffic flow. Capturing this interaction significantly enhances the models’ ability to reflect the observed field performance.

A case for real-time calibration of data-driven microscopic traffic simulation tools

Despite recent technological advancements in alleviating roadway congestion, there is still a considerable amount of time and fuel wasted by travelers. In searching for solutions to mitigate congestion, a number of research efforts have been geared toward developing simulation tools to provide real-time performance measures. One of the challenges of such tools is that the underlying simulation model does not always adequately reflect field conditions outside of the time period for which it was calibrated. In this paper, this is highlighted when calibrating a model for two different periods. During this exercise, 1000 model replicates were generated to explore the sensitivity of potential calibration parameter values. From this analysis only one replicate was found to be adequately calibrated for both periods. This paper suggests that a real-time calibration algorithm should be included in online, data-driven microscopic traffic simulation tools.

Tablet-Based Traffic Counting Application Designed to Minimize Human Error

Basic traffic counts are among the key elements in transportation planning and forecasting. As emerging data collection technologies proliferate, the availability of traffic count data will expand by orders of magnitude. However, availability of data does not always guarantee data accuracy, and it is essential that observed data are compared with ground truth data. Little research or guidance is available that ensures the quality of ground truth data with which the count results of automated technologies can be compared. To address the issue of ground truth data based on manual counts, a manual traffic counting application was developed for an Android tablet. Unlike other manual count applications, this application allows data collectors to replay and toggle through the video in supervisory mode to review and correct counts made in the first pass. For system verification, the review function of the application was used to count and recount freeway traffic in videos from the Atlanta, Georgia, metropolitan area. Initial counts and reviewed counts were compared, and improvements in count accuracy were assessed. The results indicated the benefit of the review process and suggested that this application could minimize human error and provide more accurate ground truth traffic count data for use in transportation planning applications and for model verification.

Ad Hoc Distributed Simulation of Surface Transportation Systems

Current research in applying the Dynamic Data Driven Application Systems (DDDAS) concept to monitor and manage surface transportation systems in day-to-day and emergency scenarios is described. This work is focused in four, tightly coupled areas. First, a novel approach to predicting future system states termed ad hoc distributed simulations has been developed and is under investigation. Second, on-line simulation models that can incorporate real-time data and perform rollback operations for optimistic ad hoc distributed simulations are being developed and configured with data corresponding to the Atlanta metropolitan area. Third, research in the analysis of real-time data is being used to define approaches for transportation system data collection that can drive distributed on-line simulations. Finally, research in data dissemination approaches is examining effective means to distribute information in mobile distributed systems to support the ad hoc distributed simulation concept.

On the Resilience of Ad Hoc Distributed Simulation of Surface Transportation Systems with Unreliable Communications

The Dynamic Data Driven Application Systems (DDDAS) concept is examined in the context of monitoring and managing surface transportation systems in day-to-day and emergency scenarios. An approach to predicting future system states termed ad hoc distributed simulations is described. This approach uses on-line distributed simulation models that can incorporate real-time data and utilizes rollback operations to update state predictions as new information becomes available. This paper focuses on examining the reliability of ad hoc distributed simulations in mobile computing environments, and specifically, assessing the accuracy of future state predictions in the face of unreliable communications.