Macroscopic Approach for Optimizing Road Space Allocation of Bus Lanes in Multimodal Urban Networks Through Simulation Analysis

Author(s):  
Nan Zheng ◽  
Takao Dantsuji ◽  
Pengfei Wang ◽  
Nikolas Geroliminis

Although multimodality has been widely studied in the literature, planning and operating bus lanes in congested urban city centers are still challenging topics for researchers and policy makers. Most existing approaches lack quantitative methods for estimating the impact of bus lanes or for optimizing the operation of bus lanes at a system level. This paper proposes a novel optimization approach for allocating road space to bus lanes in cities. The approach determines the optimal space share between the modes in service and allocates the bus lanes by integrating strategies that lead to less total travel cost. By relying on recent advances in network-level traffic flow modeling, namely, the multimodal macroscopic fundamental diagram (mMFD), the approach captures multimodal traffic dynamics and travel costs by mode. The impact of a bus lane on mode usage is taken into account to aggregated mode shift phenomena under changes in layout of dedicated bus lanes. Simulation was performed in a Swiss city network to test the proposed optimization approach. The research found that ( a) the mMFD could be properly integrated to decide for road space optimization of large-scale multimodal urban networks, ( b) an optimal and efficient space share minimized the total travel cost for all users, and ( c) the best strategy for the studied network was to implement the allocated space on the connected links on a corridor rather than to assign them sparsely to the links that are heavily congested.

2020 ◽  
Vol 1 ◽  
Author(s):  
Gabriel Tilg ◽  
Zain Ul Abedin ◽  
Sasan Amini ◽  
Fritz Busch

The three-dimensional passenger macroscopic fundamental diagram (pMFD) describes the relation of the network accumulation of public transport and private vehicles, and the passenger production. It allows for modeling the multi-modal traffic dynamics in urban networks and deriving innovative performance indicators. This paper integrates this concept into a multi-modal transport system design framework formulated as a simulation-based optimization problem. In doing so, we consider the competition for limited road space and the operational characteristics, such as congestion occurrences, at the strategic design level. We evaluate the proposed framework in a case study for the Sioux Falls network. Thereby, we deliver a proof of concept, and show that the proposed methodology indeed designs a transport system which benefits the overall system's performance. This paper further advances the integration of sequential model-based optimization techniques, macroscopic traffic flow concepts, and traffic simulation to design multi-modal transport systems. This supports transport planners and local authorities in composing efficient and robust transport networks.


2018 ◽  
Vol 33 (3) ◽  
Author(s):  
Patrick Renihan ◽  
Brian Noonan

This article reports a study of rural school principals’ assessment leadership roles and the impact of rural context on their work. The study involved three focus groups of principals serving small rural schools of varied size and grade configuration in three systems. Principals viewed assessment as a matter of teacher accountability and as a focus for the school professional team. They saw themselves as teachers first, stressing their importance as sources of teacher support, serving a ‘buffer role,’ ameliorating external constraints to effective assessment and learning. Bureaucratic environments and trappings of large-scale assessment were seen to be incompatible with the familial nature of rural professional contexts. Other constraints were the logistical challenges of small student populations, higher instances of multi-graded classrooms, and the absence of grade-alike professional interaction. Conversely, smallness enabled professional interaction and transformational leadership. Finally, the quality of system-level support emerged as a critical catalyst for assessment leadership at the school level.  


2016 ◽  
Author(s):  
Thurston Herricks ◽  
David J. Dilworth ◽  
Fred D. Mast ◽  
Song Li ◽  
Jennifer J. Smith ◽  
...  

ABSTRACTCell growth is a complex phenotype widely used in systems biology to gauge the impact of genetic and environmental perturbations. Due to the magnitude of genome-wide studies, resolution is often sacrificed in favor of throughput, creating a demand for scalable, time-resolved, quantitative methods of growth assessment. We present ODELAY (One-cell Doubling Evaluation by Living Arrays of Yeast), an automated and scalable growth analysis platform. High measurement density and single cell resolution provide a powerful tool for large-scale multiparameter growth analysis based on the modeling of microcolony expansion on solid media. Pioneered in yeast but applicable to other colony forming organisms, ODELAY extracts the three key growth parameters (lag time, doubling time, and carrying capacity) that define microcolony expansion from single cells, simultaneously permitting the assessment of population heterogeneity. The utility of ODELAY is illustrated using yeast mutants, revealing a spectrum of phenotypes arising from single and combinatorial growth parameter perturbations.


Author(s):  
Chongxuan Huang ◽  
Nan Zheng ◽  
Jun Zhang

This paper investigates traffic dynamics in bimodal urban networks utilizing the macroscopic fundamental diagram (MFD) and the three-dimensional macroscopic fundamental diagram (3D-MFD), which are network-level traffic flow modeling tools. Although the existence and the properties of the MFD have been extensively analyzed with field data in literature, few empirical studies examine these features of the 3D-MFDs for large-scale networks. For this work, GPS data for cars and buses running in the network of Shenzhen city in China are available for analysis and this offers a great opportunity for the investigation. Interestingly, both MFD and 3D-MFD dynamics are reflected in the data. Network partition is performed to reduce the hysteresis on the MFD and the network is split into two regions for further analysis. Then the investigation focuses on the MFD relationship for buses only. The average passenger occupancy is estimated and incorporated to generate a passenger MFD (pMFD) for buses. Moreover, bus operation on dedicated bus lanes is analyzed. Having understood traffic dynamics of cars, buses, and passengers respectively, the 3D-MFDs which illustrate the joint influence of car and bus accumulations on the global network-level traffic performance are presented. Given the scatter plot of the 3D-MFDs for the two partitioned regions, analytical approximations are provided, fitting by exponential functions. These results are promising, as they confirm the traffic features that were found from simulation-based studies in previous work.


2012 ◽  
Vol 7 (4) ◽  
pp. 122 ◽  
Author(s):  
Stephanie J. Schulte

Objectives – The purpose of this review is to examine the development of embedded librarianship, its multiple meanings, and activities in practice. The review will also report on published outcomes and future research needs of embedded librarian programs. Methods – A search of current literature was conducted and summarized searching PubMed, CINAHL, Library, Information Science & Technology Abstracts (EBSCO), Academic Search Complete, and ERIC (EBSCO) through August 23, 2012. Articles were selected for inclusion in the review if they reported research findings related to embedded librarianship, if they provided unique case reports about embedded librarian programs, or if they provided substantive editorial comments on the topic. Relevant study findings were assessed for quality and presented in tabular and narrative form. Results – Currently, there is disparity in how embedded librarianship is being defined and used in common practice, ranging from embedding an online component into a single course to full physical and cultural integration into an academic college or business unit of an organization. Activities of embedded librarians include creating course integrated instruction modules for either face-to-face or online courses, providing in depth research assistance to students or faculty, and co-locating within colleges or customer units via office hours for a few hours to all hours per week. Several case reports exist in the recent literature. Few high quality research studies reporting outcomes of librarians or library programs labeled as embedded exist at this point. Some evidence suggests that embedded librarians are effective with regards to student learning of information literacy objectives. Surveys suggest that both students and faculty appreciate embedded librarian services. Conclusion – Most published accounts discuss librarians embedding content and ready access to services in an online course management system. A few notable cases describe the physical and cultural integration of librarians into the library user environs. Future research using valid quantitative methods is needed to explore the impact of large scale, customized, embedded programs.


2010 ◽  
Vol 26 (04) ◽  
pp. 273-289 ◽  
Author(s):  
N. Vlahopoulos ◽  
C. G. Hart

A multidisciplinary design optimization (MDO) framework is used for a conceptual submarine design study. Four discipline-level performances—internal deck area, powering, maneuvering, and structural analysis—are optimized simultaneously. The four discipline-level optimizations are driven by a system level optimization that minimizes the manufacturing cost while at the same time coordinates the exchange of information and the interaction among the discipline-level optimizations. Thus, the interaction among individual optimizations is captured along with the impact of the physical characteristics of the design on the manufacturing cost. A geometric model for the internal deck area of a submarine is created, and resistance, structural design, and maneuvering models are adapted from theoretical information available in the literature. These models are employed as simulation drivers in the discipline-level optimizations. Commercial cost-estimating software is leveraged to create a sophisticated, automated affordability model for the fabrication of a submarine pressure hull at the system level. First, each one of the four discipline optimizations and also the cost-related top level optimization are performed independently. As expected, five different design configurations result, one from each analysis. These results represent the "best" solution from each individual discipline optimization, and they are used as reference for comparison with the MDO solution. The deck area, resistance, structural, maneuvering, and affordability models are then synthesized into a multidisciplinary optimization statement reflecting a conceptual submarine design problem. The results from this coordinated MDO capture the interaction among disciplines and demonstrate the value that the MDO system offers in consolidating the results to a single design that improves the discipline-level objective functions while at the same time produces the highest possible improvement at the system level.


2020 ◽  
Vol 20 (1) ◽  
Author(s):  
Chun-Hung Cheng ◽  
Yong-Hong Kuo ◽  
Ziye Zhou

Abstract Background An effective approach to containing epidemic outbreaks (e.g., COVID-19) is targeted immunization, which involves identifying “super spreaders” who play a key role in spreading disease over human contact networks. The ultimate goal of targeted immunization and other disease control strategies is to minimize the impact of outbreaks. It shares similarity with the famous influence maximization problem studied in the field of social network analysis, whose objective is to identify a group of influential individuals to maximize the influence spread over social networks. This study aims to establish the equivalence of the two problems and develop an effective methodology for targeted immunization through the use of influence maximization. Methods We present a concise formulation of the targeted immunization problem and show its equivalence to the influence maximization problem under the framework of the Linear Threshold diffusion model. Thus the influence maximization problem, as well as the targeted immunization problem, can be solved by an optimization approach. A Benders’ decomposition algorithm is developed to solve the optimization problem for effective solutions. Results A comprehensive computational study is conducted to evaluate the performance and scalability of the optimization approach on real-world large-scale networks. Computational results show that our proposed approaches achieve more effective solutions compared to existing methods. Conclusions We show the equivalence of the outbreak minimization and influence maximization problems and present a concise formulation for the influence maximization problem under the Linear Threshold diffusion model. A tradeoff between computational effectiveness and computational efficiency is illustrated. Our results suggest that the capability of determining the optimal group of individuals for immunization is particularly crucial for the containment of infectious disease outbreaks within a small network. Finally, our proposed methodology not only determines the optimal solutions for target immunization, but can also aid policymakers in determining the right level of immunization coverage.


2017 ◽  
Vol 2612 (1) ◽  
pp. 132-140
Author(s):  
Mahmoud R. Halfawy

The current state of the practice in bridge management highlights a growing need to develop scalable optimization software tools to support the development of truly optimal bridge improvement programs and ensure that limited financial resources are optimally allocated. The heuristic project selection approaches employed in today’s bridge management systems are not capable of generating optimal programs. Agencies that rely on suboptimal programs may inadvertently direct a significant portion of their budget to the wrong projects, leading to an increase in maintenance backlogs and overall system risk levels. The subjective project selection criteria may also hinder the ability to quantify project benefits or justify projects to funding agencies and stakeholders. This paper presents a novel dynamic programming–based multiobjective optimization approach that is capable of generating global optimal network-level, long-range bridge improvement programs. The algorithm considers three objectives: the minimization of system-level risk, the maximization of system-level condition, and the minimization of life-cycle costs, subject to agency-defined constraints and planning scenarios. The algorithm efficiently explores the enormous search space to find optimal project lists for each year in the planning horizon under any given scenario. Alternative planning scenarios are defined to quantify the impact of different investment levels on system-level performance metrics and to determine the investment required to achieve the desired performance and risk targets.


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