Authors: Mark Franz and Gang-Len Chang
Conference: 90th TRB Annual Meeting in 2011
The Maryland State Highway Administration has started a pilot program to evaluate the effectiveness of an automated speed enforcement system in work zones. Three sites were selected to measure the spatial and temporal effect of automated speed enforcement on motorists’ speeding behavior. In addition to comparing the temporal changes and spatial evolution of mean and 85 percentile speeds, the spatial and temporal change in percentages of three motorist populations, conservative, normal and aggressive drivers, were considered. A total of five datasets were analyzed. For the two data sets that compared the before versus during analysis periods, the enforcement period displayed a general reduction in aggressive motorists while creating a more stable spatial speeding distribution through the work zone. Two of the three data sets comparing the during versus after enforcement periods showed that motorists may learn where enforcement is taking place and adjust their speeds accordingly. This effect was evident even after the enforcement period. Lastly, one dataset displayed increased speeds and less stable spatial speeding patters during the enforcement period, suggesting the need for further investigation of this data set.
Authors: Zichuan Li and Gang-Len Chang
Conference: TRB 2010 Annual Meeting, January 13, 2010
This study presents an arterial signal optimization model that is capable of capturing the queue blockage between intersection lane groups during oversaturated conditions. The proposed model is grounded on the original cell transmission concept proposed by Daganzo, but enhanced with a new diverging cell for formulating the complex interactions of queue spillback between left-turn and through traffic flows. With the embedded formulations for forward wave, backward wave, and the horizontal queue, the proposed arterial signal optimization model can yield effective signal plans for both saturated and under-saturated intersections. To evaluate the performance of the proposed model, this study has conducted extensive simulation experiments with a segment of Georgia Avenue connected directly to Capital Beltway in Maryland. The analysis results in comparison with the signal plans from TRANSYT-7F (Release 10) have demonstrated the promising properties of the proposed model.
Authors: Ning Yang and Yue Liu
Conference: The 15th World Congress on Intelligent Transport Systems, New York, 2008
In this paper, we develop a simulation optimization procedure for optimizing the urban arterial traffic signal timings including a bunch of sequential intersections. The system performance is estimated via a stochastic discrete-event meso-scopic traffic simulator, and a gradient-based search algorithm on stochastic approximation is applied to give the optimal signal timings. Simultaneous perturbation analysis is used to derive both left-hand and right-hand gradient estimators of the system performance with respect to the cycle lengths, green splits, and green offsets for those intersections within the arterial. Numerical experiments show that the meso-scopic traffic simulator provides reasonable system performance in much less running time if properly calibrated, compared with a widely-used commercial traffic microscopic simulation program CORSIM. In particular, for all scenarios designed, the optimizer converges to optimal signal timing plans which significantly increase the system performance.
Authors: Yue Liu, Gang-Len Chang, Jie Yu, Yuanyuan Hou, and Saed Rahwanji
Conference: The 11th International IEEE Conference on Intelligent Transportation System, October 2008 in Beijing, China
This paper presents a macroscopic model of traffic able to replicate the key features occurring at signalized intersections. Different from the previous link or movement based traffic flow models, the proposed model considers explicitly queue accumulation and dissipation at the lane-group level, in order to facilitate modeling the discharging process for shared lanes. In particular, the proposed model also accounts for the blocking effects between different lane groups due to intersection geometric constraints or improper signal settings, which offer potentials for it to be integrated with optimal control models. The performance of the proposed model applied to a real-world intersection under different demand levels appears to be computer-efficient and convincing when validated by a calibrated microscopic simulation program, VISSIM.
Authors: Yue Liu, Gang-Len Chang, and Jie Yu
Conference: the 11th International IEEE Conference on Intelligent Transportation System, October 2008 in Beijing, China
This paper presents the investigation results of driver behavioral patterns during a yellow phase, based on field observations of 1123 drivers at six signalized intersections of high accident frequency in Maryland. By classifying drivers at each intersection into aggressive pass, conservative stop, and normal groups based on their responses (i.e., stop or pass) and their distances to the stop line when the signal turns yellow, the statistical tests with the ordered-probit model clearly indicate the impacts of some critical factors on a driver’s decision. Such factors include: average traffic flow speeds, traffic volume rate, the green split, the number of through and crossing lanes in the target approach, signal coordination, the difference between individual vehicle’s approaching speed and average traffic flow speeds, individual driver’s gender, age, and talking over cell phone or not, individual vehicle’s type and model, and etc. The analysis results offer the basis for assessing the safety conditions at hazardous intersections, and for design of contra measures
Authors: Yue Liu, Gang-Len Chang, Ruihua Tao, Thonas Hicks and Eric Tabacek
Conference: 2008′ TRB Annual Meeting
This paper presents the investigation results of driver behavioral patterns during a yellow phase, based on field observations of 1123 drivers using a specially-designed system at six signalized intersections of high accident frequency in Maryland. By classifying drivers at each intersection into aggressive pass, conservative stop, and normal groups based on their responses (i.e., stop or pass) and their distances to the stop line when the signal turns yellow, the statistical tests with the ordered-probit model clearly indicates the impacts of some critical factors on a driver’s decision. Such factors include: average traffic flow speeds, traffic volume rate, the green split, the number of through and crossing lanes in the target approach, signal coordination, the difference between individual vehicle’s approaching speed and average traffic flow speeds, individual driver’s gender, age, and talking over cell phone or not, individual vehicle’s type and model, and etc. The analysis results offer the basis for assessing the safety conditions at hazardous intersections, and for design of contra measures.
Authors: Xiaorong Lai, Jonathan Reid, Saed Rahwanji and Gang-Len Chang
Conference: 2007′ World Congress on ITS, Beijing in China
This paper presents the framework and major functions of an integrated program for unconventional arterial intersection design. The proposed program features its integration of a build-in knowledge base and the interactive analysis tools, which aims to provide a better understanding and convenient evaluation of all unconventional intersection types. Various factors, related to traffic analysis, safety concerns, cost estimation, and pedestrian impacts can be included in the evaluation framework through user-friendly interfaces. A case study is presented to show the applicability of the proposed system with respect to the selection and design of unconventional intersections under userspecified scenarios.
Authors: Yue Liu, Gang-Len Chang, Xiaorong Lai and Ying Liu
Conference: 2007′ World Congress on ITS, Beijing in China
Evacuating large municipal areas during emergencies and disasters in an efficient manner is one of the critical concerns faced by emergency management agencies. This study has developed a corridor-based evacuation planning system for Washington D.C. to design and evaluate various traffic control strategies. The proposed system divides the entire study area into different evacuation corridors, and employs its optimization module along with an embedded macroscopic simulator to generate both signal timings and routing strategies for each corridor in the evacuation area.
Authors: Ying Liu, Xiaorong Lai, Gang-Len Chang
Conference: the 2006 IEEE International Conference on Networking, Sensing and Control, 2006
One popular class of approaches to estimate freeway corridor travel time is based on measured or estimated speed data from roadside detectors. In most estimation practices, using either simulated or actual data, detectors are assumed to evenly distribute with a close spacing of around half mile. Unfortunately, this detector location scheme will be too costly for most freeway corridors under limited budget. To contend with this issue, this paper examines some widely used estimation algorithms under various traffic conditions with different detector spacing, and then proposes a set of strategies for locating detectors. Numerical results, based on traffic conditions on I-70 corridor of Maryland, have demonstrated the promising properties of our proposed strategies under recurrent congestion pattern.
Authors: Ying Liu, Nan Zou, and Gang-len Chang
Conference: the 2005 IEEE International Conference on Intelligent Transportation Systems
The consecutive hurricane attacks to US coastline have drawn significant attentions to evacuation operations related issues. To better prepare the state of Maryland for potential hurricanes, this study presents an emergency evacuation system that integrates both optimization and microscopic simulation methods. The optimization module applies a two-level process to generate the preliminary optimal control plans, which is based on a revised cell transmission formulation for large-scale network applications. Using the optimized results as the initial input, the simulation module takes into account various operational constraints and driver responses that are difficult to be captured realistically with mathematical formulations. The proposed system also features its flexibility for potential users to adjust the optimized plans in both the planning phase and real-time operations based on the results of simulation evaluation. The case study with the data from Ocean City, Maryland during hurricane attacks has demonstrated the potential of the proposed system for evacuation of traffic flows in large-scale networks within a given time window.