Cordon- or Link-Based Pricing: Environment-Oriented Toll Design Models Development and Application

This study focuses on an environment-friendly toll design problem, where an acceptable road network performance is promised. First, a Traffic Performance Index (TPI)-based evaluation method is developed to help identify the optimal congestion level and the management target of a transportation system. Second, environment-oriented cordon- and link-based road toll design models are respectively proposed through the use of bi-level programming. Both upper-level submodel objectives are to minimize gross revenue (the total collected toll minus the emissions treatment cost) under different pricing strategies. Both lower-level submodels quantify the user equilibrium (UE) condition under elastic demand. Moreover, the TPI-related constraints for the management requirements of the network performance are incorporated into the bi-level programming modeling framework, which can lead to 0–1 mixed integer bi-level nonlinear programming for toll design problems. Accordingly, a genetic algorithm-based heuristic searching method is proposed for the two pricing models. The proposed cordon- and link-based pricing models were then applied to a real-world road network in Beijing, China. The effects of the toll schemes generated from the two models were compared in terms of emissions reduction and congestion mitigation. In this study, it was indicated that a higher total collected toll may lead to more emissions and related treatment costs. Tradeoffs existed between the toll scheme, emissions reduction, and congestion mitigation.

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A Multistage Multiobjective Model for Emergency Evacuation Considering ATIS

Mathematical Problems in Engineering ◽

10.1155/2016/8291950 ◽

2016 ◽

Vol 2016 ◽

pp. 1-8 ◽

Cited By ~ 1

Author(s):

Ming-Hua Zeng ◽

Ke-Jun Long ◽

Zi-Wen Ling ◽

Xi-Yan Huang

Keyword(s):

Travel Time ◽

Road Network ◽

Network Performance ◽

Programming Model ◽

Choice Model ◽

Compliance Rate ◽

Emergency Evacuation ◽

User Equilibrium ◽

Stochastic User Equilibrium ◽

Traffic Demand

The impacts of advanced traveler information system’s (ATIS’s) penetration and compliance rates on network performances during hybrid traffic emergency evacuation are investigated in a degraded road network. Before traffic incident a Path-Size Logit (PSL) route choice model is integrated with constraints on the level of service (LOS) of traffic to formulate a bilevel programming model. It aims at minimizing traffic demand in road network which may locally deteriorate the LOS. The lower level is a PSL-stochastic user equilibrium model for multiple classes of users. During the ongoing incident, a multiobjective multiuser-class stochastic optimization model is established with the objectives of maximizing evacuation reliability and minimizing expected network travel time. Furthermore, computations and analyses are completed for five designated scenarios including a method proposed in previous literature. The results show that the evacuation reliability and different kinds of total expected travel time costs regularly increase with emergency traffic’s ATIS compliance rate and decrease with general traffic’s ATIS penetration rate. The research will help improve transport network performance when considering ATIS’s effect on hybrid traffic.

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Resilience-Based Optimization of Postdisaster Restoration Strategy for Road Networks

Journal of Advanced Transportation ◽

10.1155/2021/8871876 ◽

2021 ◽

Vol 2021 ◽

pp. 1-15

Author(s):

Xinhua Mao ◽

Jibiao Zhou ◽

Changwei Yuan ◽

Dan Liu

Keyword(s):

Travel Time ◽

Road Network ◽

Network Performance ◽

Network Flows ◽

Programming Model ◽

Mixed Integer ◽

Total System ◽

Network Resilience ◽

The Road ◽

Restoration Strategies

This work proposes a framework for the optimization of postdisaster road network restoration strategies from a perspective of resilience. The network performance is evaluated by the total system travel time (TSTT). After the implementation of a postdisaster restoration schedule, the network flows in a certain period of days are on a disequilibrium state; thus, a link-based day-to-day traffic assignment model is employed to compute TSTT and simulate the traffic evolution. Two indicators are developed to assess the road network resilience, i.e., the resilience of performance loss and the resilience of recovery rapidity. The former is calculated based on TSTT, and the latter is computed according to the restoration makespan. Then, we formulate the restoration optimization problem as a resilience-based bi-objective mixed integer programming model aiming to maximize the network resilience. Due to the NP-hardness of the model, a genetic algorithm is developed to solve the model. Finally, a case study is conducted to demonstrate the effectiveness of the proposed method. The effects of key parameters including the number of work crews, travelers’ sensitivity to travel time, availability of budget, and decision makers’ preference on the values of the two objectives are investigated as well.

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Enhancing Road Network Resilience by Considering the Performance Loss and Asset Value

Sustainability ◽

10.3390/su10114188 ◽

2018 ◽

Vol 10 (11) ◽

pp. 4188 ◽

Cited By ~ 1

Author(s):

Myungsik Do ◽

Hoyong Jung

Keyword(s):

Road Network ◽

Network Performance ◽

Evaluation Method ◽

Critical Path ◽

Regional Scale ◽

The Road ◽

Performance Loss ◽

Asset Value ◽

Total Travel Time ◽

Infrastructure Performance

In this study, we focus on resilience as the ability of specific infrastructure systems at the regional scale to absorb the shocks of extreme events, such as earthquakes. The occurrence of a disaster such as an earthquake leads to a rapid decrease in infrastructure performance. In the case of road networks, performance might refer to the number of drivers using the road within a certain period of time. The objective of this study is to propose a quantitative evaluation method to analyze road network performance (or performance loss) when natural disasters occur. Furthermore, we use cluster analysis and consider the performance loss and asset value in an attempt to propose a method to determine the critical path that should be prioritized for maintenance. This study aimed at analyzing hazard resilience from the network aspect through a scenario analysis depending on damage recovery after disaster occurrence. This study compared the hazard resilience speed to recover existing performance according to the scenario for damage recovery targeting the selected road network. It was found that the total increase in the utility (e.g., total travel time saved) gradually diminished as the restoration cost increased.

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Consistency Between Convergence of Dynamic Assignment and Stochasticity of Microsimulation: Implication for Number of Runs

Transportation Research Record Journal of the Transportation Research Board ◽

10.3141/2667-09 ◽

2017 ◽

Vol 2667 (1) ◽

pp. 88-95

Author(s):

Neeraj Saxena ◽

Vinayak V. Dixit ◽

S. Travis Waller

Keyword(s):

Network Performance ◽

Dynamic Network ◽

Computation Time ◽

User Equilibrium ◽

Medium Size ◽

Modeling Framework ◽

Network Characteristics ◽

Dynamic Assignment ◽

Minimum Number ◽

Valid Estimate

Dynamic transportation models route vehicles by using the principles of dynamic user equilibrium. These models include a dynamic network loading (DNL) module that is used to evaluate link costs. However, an element of stochasticity creeps into the modeling framework when the analytical dynamic assignment (DA) procedure is used along with a stochastic microscopic DNL. A methodologically correct way of approaching this problem is by solving the entire DA with a microscopic DNL (DA-microDNL) model until convergence for a given random seed and then repeating the process with different seed values. This paper proposes an approach to determine the minimum number of replications of the DA-microDNL model to determine a statistically valid estimate of the measure of effectiveness (MOE). The approach was tested on a small and medium-size network having different demand and network characteristics. Results show that running the integrated DA-microDNL framework for a minimum number of replications provides a statistically significant MOE at much lower computation time. The consistent estimates obtained by using this approach would provide robust information to transportation planners and practitioners in evaluating the impacts of several policy decisions on network performance.

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AN APPROXIMATE RELIABILITY EVALUATION METHOD FOR IMPROVING TRANSPORTATION NETWORK PERFORMANCE

Transport ◽

10.3846/transport.2010.24 ◽

2010 ◽

Vol 25 (2) ◽

pp. 193-202 ◽

Cited By ~ 6

Author(s):

Afshin Shariat-Mohaymany ◽

Mohsen Babaei

Keyword(s):

Resource Allocation ◽

Network Performance ◽

Evaluation Method ◽

Programming Model ◽

Network Reliability ◽

Transportation Network ◽

Random Variables ◽

Network Connectivity ◽

Mixed Integer ◽

Nonlinear Programming Model

Considering the importance of maintaining network performance at desired levels under uncertainty, network reliability, as a new approach to assessing the performance of degradable urban transportation networks, has become increasingly developed in two recent decades. In this paper, a method for optimizing resource allocation to meet the required levels of transportation network reliability is proposed. The worked out method consists of two stages: at stage one, a method for computing the reliability of network connectivity based on the reliability of computing arc performance with an assumption that capacities are random variables for each arc is presented. These random variables are assumed to be conformed to especial probability density functions which can be modified through investing to improve the performance reliability of the arcs. At stage two, a mixed integer nonlinear programming model is developed to optimize resource allocation in the network. Numerical results are also provided in a simple network to demonstrate the capability of the employed method.

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Optimizing capacity of signalized road network with reversible lanes

Transport ◽

10.3846/16484142.2014.994227 ◽

2015 ◽

Vol 33 (1) ◽

pp. 1-11 ◽

Cited By ~ 6

Author(s):

Jian Wang ◽

Wei Deng

Keyword(s):

Traffic Flow ◽

Road Network ◽

Flow Direction ◽

Network Capacity ◽

User Equilibrium ◽

Network Design Problem ◽

Mixed Integer ◽

Mixed Network ◽

Level Problem ◽

Upper Level

This paper studies the network capacity problem on signalized road network with reversible lanes. A Mixed Network Design Problem (MDNP) is formulated to describe the problem where the upper-level problem is a mixed integer non-linear program designed to maximize the network capacity by optimizing the input parameters (e.g. the signal splits, circles, reassigned number of lanes and O–D demands), while the lower-level problem is the common Deterministic User Equilibrium (DUE) assignment problem formulated to model the drivers’ route choices. According to whether one way strategy is permitted in practice, two strategies for implementing reversible roadway are considered. In the first strategy, not all lanes are reversible and the reversible roadways always hold its ability to accommodate the two-way traffic flow. In the second strategy, one-way road is allowed, which means that all the lanes are reversible and could be assigned to one flow direction if the traffic flow in both directions is severally unsymmetrical. Genetic Algorithm (GA) is detailedly presented to solve the bi-level network capacity problem. The application of the proposed method on a numerical example denotes that Strategy 2 can make more use of the physical capacity of key links (signal controlled links), thus, the corresponding network capacity outperforms it is of Strategy 1 considerably.

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Quanto Pricing beyond Black–Scholes

Journal of Risk and Financial Management ◽

10.3390/jrfm14030136 ◽

2021 ◽

Vol 14 (3) ◽

pp. 136

Author(s):

Holger Fink ◽

Stefan Mittnik

Keyword(s):

Option Pricing ◽

Goodness Of Fit ◽

Calibration Procedure ◽

Barrier Options ◽

Pricing Models ◽

Modeling Framework ◽

Double Barrier ◽

Parameter Stability ◽

Comprehensive Data ◽

Black Scholes

Since their introduction, quanto options have steadily gained popularity. Matching Black–Scholes-type pricing models and, more recently, a fat-tailed, normal tempered stable variant have been established. The objective here is to empirically assess the adequacy of quanto-option pricing models. The validation of quanto-pricing models has been a challenge so far, due to the lack of comprehensive data records of exchange-traded quanto transactions. To overcome this, we make use of exchange-traded structured products. After deriving prices for composite options in the existing modeling framework, we propose a new calibration procedure, carry out extensive analyses of parameter stability and assess the goodness of fit for plain vanilla and exotic double-barrier options.

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