Authors: Yue Liu, Gang-Len Chang, and Jie Yu
Journal: ASCE Journal of Transportation Engineering
Abstract:
This paper presents the analysis results of driver responses during a yellow phase, based on field observations of 1123 drivers collected with a specially-designed system from six signalized intersections of high crash frequency in Maryland. By classifying drivers into aggressive, conservative, and normal groups based on their responses (i.e., stop or pass) and the distances to the stop line when the signal turns yellow, the statistical tests with the ordered-probit model clearly indicate some critical factors and their impacts on a driver’s decision at intersections. 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 a vehicle’s approaching speed and the average traffic flow speeds, a driver’s gender, age, talking over cell phone or not, a vehicle’s type and model, and etc. The research findings for this study offer the basis for responsible agencies to identify underlying factors contributing to aggressive maneuvers at signalized intersections which often cause traffic crashes, and to develop improvement strategies, such as customized driver education and intelligent safety protection systems.

Download (TEENG-666.pdf)

Authors: Jie Yu, Yue, Liu, and Gang-Len Chang
Journal: Journal of Transportation Engineering ASCE
Abstract:
This paper presents a comprehensive model for ranking candidate location plans of multiple urban transit hubs, which can effectively capture various aspects of concerns in the transit hub location planning process, including the overall efficiency of the transit network, the transfer intensity, the proximity to major passenger generators/attractors, the effectiveness of hub service coverage, the compatibility with land use restrictions, and the adaptability to future developable transit concepts. Grounded on an Analytical Hierarchy Process (AHP)-based framework integrated with the fuzzy logic, the proposed model offers the strengths to effectively determine the weights for multiple evaluation criteria, and to synthesize the final score of each candidate plan for comparison. Results from a case study in Suzhou Industrial Park, China reveal that the proposed model offers some promising properties for transportation planners to use in planning of transit hub locations. Comparative studies with respect to different evaluation criteria has further demonstrated the effectiveness of the proposed model in capturing the impacts of different criteria on the decision making process.

Download (TEENG-688.pdf)

Authors: Yue, Liu and Gang-Len Chang
Journal: Transportation Research Part C， 2010
Abstract:
This paper presents an arterial signal optimization model that features its effectiveness on: (1) explicitly modeling physical queue evolution on arterial links by lane-group to account for shared-lane traffic interactions; and (2) capturing the dynamic interactions of spillback queues among lane groups and between neighboring intersections due to high demand, geometric constraints, or signal settings. Depending on the detected traffic patterns, one can select the control objective to be either minimizing the total travel time or maximizing the total throughput over the target area. The solution procedures developed with the Genetic Algorithm (GA) have been tested with an example arterial of four intersections under different demand scenarios. Extensive experimental analyses in comparison with results from TRANSYT-7F (version 8) reveal that the proposed model and solution method are quite promising for use in design of arterial signals, especially under congested, high demand traffic conditions.

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Authors:Yongjie Lin, Xianfeng Yang, Gang-Len Chang, and Nan Zou
Journal: Transportation Research Record: Journal of the Transportation Research Board, No. 2356, 2013
Abstract:
This paper presents a transit signal priority (TSP) model designed to consider the benefits both to bus riders and to intersection passenger car users. The proposed strategy, which is mainly for headway-based bus operations, offers the responsible agency a reliable way to determine the optimal green extension or red truncation duration in response to multiple bus priority requests from different routes. The control objective is to minimize bus passenger waiting time at the downstream bus stop while ensuring that the delays for all passengers are not increased. In tests that used field data from Jinan, China, the proposed strategy showed promise in reducing bus passenger waiting time and total intersection delay. Further exploration with simulation experiments for sensitivity analysis found that TSP is most effective if the ratio between bus and passenger volumes exceeds a threshold of 2%.

Download (Transit-Priority-Strategies-for-Multiple-Routes-Under-Headway-Based-Operations.pdf)