Authors: Xin Zhang and Gang-Len Chang
Journal: Journal of Intelligent Transportation Systems: Technology, Planning, and Operations 2014
Abstract: In most metropolitan areas, an emergency evacuation may require a potentially large number of pedestrians to walk some distance to access their passenger cars or resort to transit systems. In this process, the massive number of pedestrians may place a tremendous burden on vehicles in the roadway network, especially at critical intersections. Thus, the effective road enforcement of the vehicle and pedestrian flows and the proper coordination between these two flows at critical intersections during a multi-modal evacuation process is a critical issue in evacuation planning. This article presents an integrated linear model for the design of optimized flow plans for massive mixed pedestrian–vehicle flows within an evacuation zone. The optimized flow can also be used to generate signal timing plans at critical intersections. In addition, the linear nature of the model can circumvent the computational burden to apply in large-scale networks. An illustrating example of the evacuation around the M&T Bank Stadium in downtown Baltimore, MD, is presented and used to demonstrate the model’s capability to address the complex interactions between vehicle and pedestrian flows within an evacuation zone. Results of simulation experiments verify the applicability of our model to a real-world scenario and further indicate that accounting for such conflicting movements will yield more reliable estimation of an evacuation’s required clearance time.
Authors: Yang (Carl) Lu, Xianfeng Yang, and Gang-Len Chang
Journal: Transportation Research Record 2014
Abstract: Although average effective vehicle length (AEVL) has been recognized as one of the most popular methods for detecting data errors, how to set proper thresholds so as to prevent false alarms and missed detections remains a challenging ongoing issue. This study proposed a sequential screening algorithm that employed multiple comparisons with the best statistics to compare concurrently the estimated AEVLs between lanes and stations for assessment of the data quality of a target detector. With both the temporal and spatial information, the proposed method can reliably generate a confidence interval and determine whether the target detector is malfunctioning or in need of calibration. The proposed algorithm was tested with 2 weeks of detector data from Ocean City, Maryland. The analysis results demonstrate the effectiveness of the proposed sequential screening algorithm and its potential for field applications.
Download (Algorithm-for-Detector-Error-Screening-on-Basis-of-Temporal-and-Spatial-Information.pdf)
Authors: Xin Zhang and Gang-Len Chang
Journal: Journal of Public Transportation, Vol. 17, No. 3, 2014
Abstract: This paper develops a decision-support model for transit-based evacuation planning occurring in metropolitan areas. The model consists of two modules executed in a sequential manner: the first deals with determining pick-up locations from candidate locations based on the spatial distribution of the evacuees, and the second plans for the route and schedule for each transit vehicle based on vehicle availability and evacuee demand pattern. An overlapping clustering algorithm is first adopted in allocating the demands to several nearby clusters. Then, an optimization model is proposed to allocate available buses from the depots to transport the assembled evacuees between the pick-up locations and different safety destinations and public shelters. A numerical example based on the city of Baltimore demonstrates the applicability of the proposed model and the advantages compared to state-of-the-art models with overly strict and unrealistic assumptions.
Download (A-Transit-Based-Evacuation-Model-for-Metropolitan-Areas.pdf)
Authors: Chien-Lun Lan and Gang-Len Chang
Journal: IEEE Transactions on Intelligent Transportation Systems 2014
Abstract: In response to the need for designing signal plans for congested intersections caused by heavy scooter–vehicle mixed flows, this paper presents our formulated model for optimizing both the cycle length and signal timings for isolated intersections. The proposed model accounts for the interactions between scooter and vehicle flows and reflects the maneuverability of scooters in the queue formation and discharging process. The robustness of the proposed formulations has been evaluated with field data and laboratory experiments. The signal optimization model, grounded on such formulations for scooter–vehicle mixed flows, has also been implemented at an intersection and assessed with a rigorous before-and-after field analysis. Our research concludes that incorporating the unique properties of scooter flows is essential for design and development of effective signal control strategies to contend with recurrent congestion caused by heavy mixed scooter–vehicle flows.