Felipe Castrillon

Stochastic Extension of Newell's Three-Detector Method

A stochastic extension of Newells three-detector method is presented. The method predicts the traffic states at an intermediate location given boundary data from downstream and upstream detectors. The method presented takes into account day-to-day variations in the arrivals, sensor detection errors, and variability in the fundamental diagram parameters. The output is the probabilistic distribution of predicted cumulative counts, which can be used to obtain confidence bounds on any traffic variable. The method is tested with empirical data.

Comparison of Modeling Approaches for Imputation of Video Detection Data in Intelligent Transportation Systems

Gaps in real-time and archived traffic data are common and can be attributed to several factors, such as sensor failures and data communications interruptions. Regardless of the cause of the missing data, these gaps often must be filled with reliable and accurate estimates before the data can be used for planning, operations, or congestion-mitigation purposes. This research compared different methods for imputing missing values in video detection system data, including historical averages, simple linear regression, multiple linear regression, spatial averages, and Newells simplified kinematic wave model. The study used the fundamental relationship between speed and flow in filtering the data for quality control. A sensitivity analysis tested the response of different methods to factors such as the size of training data set and time-of-day adjustments to the algorithms. The results indicated that the time of day and volume adjustment factors had a nontrivial impact on the accuracy of the outputs. Despite significant errors in the base data set, the Newell algorithm performed on a par with the other methods in terms of bias and mean absolute percentage, but the more simple factoring methods provided comparable results and were easier to implement.

I-85 High-Occupancy Toll Lane’s Impact on Commuter Bus and Vanpool Occupancy in Atlanta, Georgia

In October 2011, Atlanta, Georgia, opened its first high-occupancy toll (HOT) lanes, which were converted from high-occupancy vehicle (HOV) lanes. In partnership with the Georgia Department of Transportation, the Georgia Institute of Technology established a research team to assess changes in vehicle throughput, vehicle occupancy, and passenger throughput associated with the I-85 HOV-to-HOT lane conversion. For the assessment of these measures, commuter bus ridership, which carries a significant portion of ridership, could not be collected through the applied efforts to collect field data. Moreover, the effects of ridership and vehicle throughput on vanpools, which also use the managed lanes, are unknown. The purpose of this research was to estimate the change in vehicle and person throughput of alternative modes before and after the HOV-to-HOT lane conversion. The results indicate that person throughput remained relatively stable for commuter buses, even with an increase in vehicle throughput. The vehicle throughput of vanpools was not substantial and increased slightly after the conversion. The commuter bus results were unexpected, as ridership was expected to increase because of the related travel time saving and reliability. Behavioral research is needed to understand the underlying effects of ridership to separate the underlying effects from external factors such as gas prices, travel times, employment, and others.

Impact of buses on the macroscopic fundamental diagram of homogeneous arterial corridors

ABSTRACT This paper proposes a modification of the method of cuts to estimate the effect of bus operations on the macroscopic fundamental diagram of long arterial corridors with uniform signal parameters and block lengths. It is found that the impact of buses can be adequately captured by the theory of moving bottlenecks using only the bus average free-flow speed. This speed considers the effects of signals and stops but not traffic conditions and therefore can be calculated endogenously. A formulation is developed to approximate the bus average free-flow speed as a function of bus operational parameters. We also found that buses produce an additional capacity restriction that is similar to the ‘short block’ on networks without buses and that can severely reduce corridor capacity. The proposed method is validated with numerical approximations of the corresponding kinematic wave problem.