scholarly journals Modeling the α-max capacity of transportation networks: a single-level mathematical programming formulation

2021 ◽  
Author(s):  
Zhaoqi Zang ◽  
Xiangdong Xu ◽  
Anthony Chen ◽  
Chao Yang
Keyword(s):  
Mathematical Programming ◽  
Travel Time ◽  
Large Scale ◽  
Transportation Network ◽  
Network Capacity ◽  
Solution Algorithm ◽  
Single Level ◽  
Capacity Model ◽  
Proposed Model ◽  
The Impact

AbstractNetwork capacity, defined as the largest sum of origin–destination (O–D) flows that can be accommodated by the network based on link performance function and traffic equilibrium assignment, is a critical indicator of network-wide performance assessment in transportation planning and management. The typical modeling rationale of estimating network capacity is to formulate it as a mathematical programming (MP), and there are two main approaches: single-level MP formulation and bi-level programming (BLP) formulation. Although single-level MP is readily solvable, it treats the transportation network as a physical network without considering level of service (LOS). Albeit BLP explicitly models the capacity and link LOS, solving BLP in large-scale networks is challenging due to its non-convexity. Moreover, the inconsideration of trip LOS makes the existing models difficult to differentiate network capacity under various traffic states and to capture the impact of emerging trip-oriented technologies. Therefore, this paper proposes the α-max capacity model to estimate the maximum network capacity under trip or O–D LOS requirement α. The proposed model improves the existing models on three aspects: (a) it considers trip LOS, which can flexibly estimate the network capacity ranging from zero to the physical capacity including reserve, practical and ultimate capacities; (b) trip LOS can intuitively reflect users’ maximum acceptable O–D travel time or planners’ requirement of O–D travel time; and (c) it is a convex and tractable single-level MP. For practical use, we develop a modified gradient projection solution algorithm with soft constraint technique, and provide methods to obtain discrete trip LOS and network capacity under representative traffic states. Numerical examples are presented to demonstrate the features of the proposed model as well as the solution algorithm.

scholarly journals Estimating the Capacity of Urban Transportation Networks with an Improved Sensitivity Based Method

2015 ◽  
Vol 2015 ◽  
pp. 1-13 ◽  
Author(s):  
Muqing Du ◽  
Xiaowei Jiang ◽  
Lin Cheng
Keyword(s):  
Sensitivity Analysis ◽  
Large Scale ◽  
Transportation Network ◽  
Network Capacity ◽  
Combined Model ◽  
Practical Applications ◽  
Large Scale Problems ◽  
Capacity Model ◽  
High Efficient ◽  
Equilibrium Constraint

The throughput of a given transportation network is always of interest to the traffic administrative department, so as to evaluate the benefit of the transportation construction or expansion project before its implementation. The model of the transportation network capacity formulated as a mathematic programming with equilibrium constraint (MPEC) well defines this problem. For practical applications, a modified sensitivity analysis based (SAB) method is developed to estimate the solution of this bilevel model. The high-efficient origin-based (OB) algorithm is extended for the precise solution of the combined model which is integrated in the network capacity model. The sensitivity analysis approach is also modified to simplify the inversion of the Jacobian matrix in large-scale problems. The solution produced in every iteration of SAB is restrained to be feasible to guarantee the success of the heuristic search. From the numerical experiments, the accuracy of the derivatives for the linear approximation could significantly affect the converging of the SAB method. The results also show that the proposed method could obtain good suboptimal solutions from different starting points in the test examples.

Definition and Evaluation Modeling of Transportation Network Layout Adaptability

2011 ◽  
Vol 71-78 ◽  
pp. 3938-3941 ◽  
Author(s):  
Jie Gao ◽  
Mei Xiang Wu ◽  
Chen Qiang Yin
Keyword(s):  
Heuristic Algorithm ◽  
Coefficient Of Variation ◽  
Large Scale ◽  
Transportation Networks ◽  
Transportation Network ◽  
Optimization Methods ◽  
Network Capacity ◽  
Network Layout ◽  
Proposed Model ◽  
Coordination Degree

According to the reliability theories and the characteristics of transportation networks, the layout adaptability is defined as the coupling and coordination degree of transportation network capacity and demand firstly. Then a layout adaptability model is built adopting the optimization methods, degree of layout adaptability index and coefficient of variation are used to evaluate the adaptability of scale and distribution respectively. Meanwhile, the heuristic algorithm suitable for large scale is designed to solve the proposed model. At last, a numerical example and its results are provided to demonstrate the validity of the proposed model and algorithm.

scholarly journals Analytical Model for Travel Time-Based BPR Function with Demand Fluctuation and Capacity Degradation

2019 ◽  
Vol 2019 ◽  
pp. 1-13
Author(s):  
Junjie Zhang ◽  
Miaomiao Liu ◽  
Bin Zhou
Keyword(s):  
Travel Time ◽  
Transportation Network ◽  
Empirical Studies ◽  
Network Capacity ◽  
Stochastic Network ◽  
Traffic Demand ◽  
Proposed Model ◽  
Capacity Degradation ◽  
Sensitivity Analysis Method ◽  
Demand Sensitivity

This study presents a stochastic model based on the link performance function of the Bureau of Public Roads to assess the reliability of travel time in the transportation network. Empirical studies have verified that the variability of travel time can be ascribed to demand fluctuation and the degradation of the capacity of the stochastic network. The mean-variance approach in previous research presented the budget model of travel time, with the capacity of the stochastic network and elastic demand as the sources of uncertainty of travel time. Previous research was devoted to the study of estimation of travel time considering a single factor or a factor independent of these two sources. Meanwhile, this study introduces the current degeneration coefficient of capacity (CDC) and the density distribution function of road section saturation (DDFS) with simultaneous network capacity and traffic demand. Sensitivity analysis method for the parameters of the proposed model is investigated theoretically using the sensitivity model of traffic capacity degradation. Results of case analysis show that the DDFS and CDC have an effect on the decision of travelers regarding the choice of route. The empirical analysis also illustrates the effectiveness of the computational approach and the proposed model.

scholarly journals MODELING AND ESTIMATING THE CAPACITY OF URBAN TRANSPORTATION NETWORK WITH RAPID TRANSIT

Transport ◽  
2014 ◽  
Vol 29 (2) ◽  
pp. 165-174 ◽  
Author(s):  
Lin Cheng ◽  
Muqing Du ◽  
Xiaowei Jiang ◽  
Hesham Rakha
Keyword(s):  
Travel Behavior ◽  
Travel Demand ◽  
Transportation Network ◽  
Urban Transportation ◽  
Network Capacity ◽  
Rapid Transit ◽  
Demand Model ◽  
Trip Distribution ◽  
Capacity Model ◽  
The Impact

To study the impact of the rapid transit on the capacity of current urban transportation system, a two-mode network capacity model, including the travel modes of automobile and transit, is developed based on the well-known road network capacity model. It considers that the travel demand accompanying with the regional development will increase in a variable manner on the trip distribution, of which the travel behavior is represented using the combined model split/trip distribution/traffic assignment model. Additionally, the choices of the travel routes, trip destinations and travel modes are formulated as a hierarchical logit model. Using this combined travel demand model in the lower level, the network capacity problem is formulated as a bi-level programming problem. The latest technique of sensitivity analysis is employed for the solution of the bi-level problem in a heuristic search. Numerical computations are demonstrated on an example network, and the before-and-after comparisons of building the new transit lines on the integrated transportation network are shown by the results.

Network Design for Shipping Service of Large-Scale Intermodal Liners

2012 ◽  
Vol 2269 (1) ◽  
pp. 42-50 ◽  
Author(s):  
Qiang Meng ◽  
Shuaian Wang ◽  
Zhiyuan Liu
Keyword(s):  
Network Design ◽  
Large Scale ◽  
Programming Model ◽  
Transportation Network ◽  
Liner Shipping ◽  
Maritime Transportation ◽  
Mixed Integer ◽  
Hub And Spoke ◽  
Shipping Company ◽  
Proposed Model

A model was developed for network design of a shipping service for large-scale intermodal liners that captured essential practical issues, including consistency with current services, slot purchasing, inland and maritime transportation, multiple-type containers, and origin-to-destination transit time. The model used a liner shipping hub-and-spoke network to facilitate laden container routing from one port to another. Laden container routing in the inland transportation network was combined with the maritime network by defining a set of candidate export and import ports. Empty container flow is described on the basis of path flow and leg flow in the inland and maritime networks, respectively. The problem of network design for shipping service of an intermodal liner was formulated as a mixed-integer linear programming model. The proposed model was used to design the shipping services for a global liner shipping company.

Impact of Major Road Supply on Individual Travel Time Expenditure: An Exploration with a 30-Year Variation of Infrastructure and Travel

2018 ◽  
Vol 2672 (3) ◽  
pp. 56-68
Author(s):  
Ryosuke Abe ◽  
Kay W. Axhausen
Keyword(s):  
Travel Time ◽  
Large Scale ◽  
Travel Demand ◽  
Road Traffic ◽  
Land Development ◽  
Transportation Infrastructure ◽  
Major Road ◽  
Birth Cohorts ◽  
Data Set ◽  
The Impact

This study estimates the impact of major road supply on individual travel time expenditures (TTEs) using data that cover 30-year variations in transportation infrastructure and travel behavior. The impacts of the supply of road and rail infrastructure are estimated with a data set that combines records of large-scale household travel surveys in the Tokyo metropolitan area conducted in 1978, 1988, 1998, and 2008. Linear and Tobit models of individual TTEs are estimated by following the behavior of birth cohorts over the 30-year period. The models incorporate the changes in transportation infrastructure, measured as lane kilometers of two levels of major road stock and vehicle kilometers of urban rail service. The results show significant negative effects of lane kilometers for higher-level and lower-level major roads on the TTEs for all travel purposes and for commuting, after controlling for socioeconomic backgrounds and generations of individuals. This study discusses that, in Tokyo, the estimated effect is more likely to reflect the effect of a major road network per se on individual TTEs than the (indirect) effect of major road supply on individual TTEs working through land development activities (i.e., induced car travel demand). For example, the caveat is that actual road investment decisions still need to consider the induced component of road traffic in addition to the (direct) effect that is estimated in this study.

scholarly journals Network Fundamental Diagram Based Routing of Vehicle Fleets in Dynamic Traffic Simulations

2020 ◽  
Author(s):  
Florian Dandl ◽  
Gabriel Tilg ◽  
Majid Rostami-Shahrbabaki ◽  
Klaus Bogenberger
Keyword(s):  
Travel Time ◽  
Transportation Network ◽  
Time Factor ◽  
Travel Times ◽  
Dynamic Traffic ◽  
Fundamental Diagram ◽  
Trade Off ◽  
On Demand ◽  
Network Fundamental Diagram ◽  
The Impact

The growing popularity of mobility-on-demand fleets increases the importance to understand the impact of mobility-on-demand fleets on transportation networks and how to regulate them. For this purpose, transportation network simulations are required to contain corresponding routing methods. We study the trade-off between computational efficiency and routing accuracy of different approaches to routing fleets in a dynamic network simulation with endogenous edge travel times: a computationally cheap but less accurate Network Fundamental Diagram (NFD) based method and a more typical Dynamic Traffic Assignment (DTA) based method. The NFD-based approach models network dynamics with a network travel time factor that is determined by the current average network speed and scales free-flow travel times. We analyze the different computational costs of the approaches in a case study for 10,000 origin-destination (OD) pairs in a network of the city of Munich, Germany that reveals speedup factors in the range of 100. The trade-off for this is less accurate travel time estimations for individual OD pairs. Results indicate that the NFD-based approach overestimates the DTA-based travel times, especially when the network is congested. Adjusting the network travel time factor based on pre-processed DTA results, the NFD-based routing approach represents a computationally very efficient methodology that also captures traffic dynamics in an aggregated way.

scholarly journals A Security Assessment Model for Electrical Power Grid SCADA System

2019 ◽  
Vol 8 (12S2) ◽  
pp. 763-773
Keyword(s):  
Vulnerability Assessment ◽  
Cyber Security ◽  
Large Scale ◽  
Critical Infrastructure ◽  
Security Analysis ◽  
Assessment Model ◽  
Primary Concern ◽  
Scada System ◽  
Proposed Model ◽  
The Impact

Due to the wide application of SCADA systems in national critical infrastructure, their cyber security issues and vulnerabilities have been a primary concern; whereas, the impact and consequences of cyber-attacks to these systems have the potential to result in catastrophic consequences in the physical domain. Therefore, estimating possible attack impacts and identifying system vulnerabilities are major concern in SCADA management and operations. However, it is quite difficult to plan, execute and review vulnerability analysis in critical infrastructure systems as well as in industrial control systems (such as SCADA system) due to its complexity, large-scale and heterogeneity. Consequently, a consistent domain-specific conceptual model is required to establish a generic framework for cyber security analysis to examine and investigate security threats on cyber-physical systems, the role of the entities within the system as well as system operations. The main contribution of this work is to present a multi-facets model to support cyber security analysis practices such as penetration testing, vulnerability assessment and risk analysis. The proposed model presents a common insight among different SCADA configurations, implementations and the employed protocols to handle its complexity, heterogeneous and scale. To demonstrate the usability as a proof of concept and applicability of the proposed model, the paper also presents an example illustrating how the proposed model can be employed to carry out security vulnerability assessment.

scholarly journals A Descriptive Analysis on the Impact of COVID-19 Lockdowns on Road Traffic Incidents in Sydney, Australia

2021 ◽  
Vol 18 (21) ◽  
pp. 11701
Author(s):  
Sai Chand ◽  
Ernest Yee ◽  
Abdulmajeed Alsultan ◽  
Vinayak V. Dixit
Keyword(s):  
Large Scale ◽  
Road Traffic ◽  
Transportation Network ◽  
Sustainable Transportation ◽  
Traffic Incidents ◽  
Traffic Incident ◽  
Incident Duration ◽  
The Mean ◽  
The Impact ◽  
Sydney Australia

COVID-19 has had tremendous effects worldwide, resulting in large-scale death and upheaval. An abundance of studies have shown that traffic patterns have changed worldwide as working from home has become dominant, with many facilities, restaurants and retail services being closed due to the lockdown orders. With regards to road safety, there have been several studies on the reduction in fatalities and crash frequencies and increase in crash severity during the lockdown period. However, no scientific evidence has been reported on the impact of COVID-19 lockdowns on traffic incident duration, a key metric for crash management. It is also unclear from the existing literature whether the impacts on traffic incidents are consistent across multiple lockdowns. This paper analyses the impact of two different COVID-19 lockdowns in Sydney, Australia, on traffic incident duration and frequency. During the first (31 March–28 April 2020) and second (26 June–31 August 2021) lockdowns, the number of incidents fell by 50% and 60%, respectively, in comparison to the same periods in 2018 and 2019. The proportion of incidents involving towing increased significantly during both lockdowns. The mean duration of crashes increased by 16% during the first lockdown, but the change was less significant during the subsequent lockdown. Crashes involving diversions, emergency services and towing saw an increase in the mean duration by 67%, 16%, and 47%, respectively, during the first lockdown. However, this was not reflected in the 2021 data, with only major crashes seeing a significant increase, i.e., by 58%. There was also a noticeable shift in the location of incidents, with more incidents recorded in suburban areas, away from the central business area. Our findings suggest drastic changes in incident characteristics, and these changes should be considered by policymakers in promoting a safer and more sustainable transportation network in the future.

scholarly journals Improving Bus Operations through Integrated Dynamic Holding Control and Schedule Optimization

2018 ◽  
Vol 2018 ◽  
pp. 1-18 ◽  
Author(s):  
Shuozhi Liu ◽  
Xia Luo ◽  
Peter J. Jin
Keyword(s):  
Numerical Simulation ◽  
Travel Time ◽  
Optimal Choice ◽  
Fleet Size ◽  
Slack Time ◽  
Proposed Model ◽  
Average Travel Time ◽  
Bus Bunching ◽  
Bus Services ◽  
The Impact

Bus bunching can lead to unreliable bus services if not controlled properly. Passengers will suffer from the uncertainty of travel time and the excessive waiting time. Existing dynamic holding strategies to address bus bunching have two major limitations. First, existing models often rely on large slack time to ensure the validity of the underlying model. Such large slack time can significantly reduce the bus operation efficiency by increasing the overall route travel times. Second, the existing holding strategies rarely consider the impact on the schedule planning. Undesirable results such as bus overloading issues arise when the bus fleet size is limited. This paper explores analytically the relationship between the slack time and the effect of holding control. The optimal slack time determined based on the derived relationship is found to be ten times smaller than in previous models based on numerical simulation results. An optimization model is developed with passenger-orient objective function in terms of travel cost and constraints such as fleet size limit, layover time at terminals, and other schedule planning factors. The optimal choice of control stops, control parameters, and slack time can be achieved by solving the optimization. The proposed model is validated with a case study established based on field data collected from Chengdu, China. The numerical simulation uses the field passenger demand, bus average travel time, travel time variance of road segments, and signal timings. Results show that the proposed model significantly reduce passengers average travel time compared with existing methods.

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