An aggregate demand model for domestic airlines

An econometric model is estimated for the aggregate demand of an airline. The demand is expressed in terms of airline network structure, operating characteristics and firm-specific variables. A number of model formulations with different combinations of explanatory variables are estimated using the two-stage least-square procedure. The results suggest that the airline aggregate demand is elastic with respect to yield, and inelastic with respect to both network size and hub dominance. Some implications regarding airline network expansion and hubbing are discussed.     

An aggregate demand model for air passenger traffic in the hub-and-spoke network

In this paper, we build an aggregate demand model for air passenger traffic in a hub-and-spoke network. This model considers the roles of airline service variables such as service frequency, aircraft size, ticket price, flight distance, and number of spokes in the network. It also takes into account the influence of local passengers and social-economic and demographic conditions in the spoke and hub metropolitan areas. The hub airport capacity, which has a significant impact on service quality in the hub airport and in the whole hub-and-spoke network, is also taken into consideration.Our demand model reveals that airlines can attract more connecting passengers in a hub-and-spoke network by increasing service frequency than by increasing aircraft size in the same percentage. Our research confirms the importance of local service to connecting passengers, and finds that, interestingly, airlines’ services in the first flight leg are more important to attract passengers than those in the second flight segment. Based on data in this study, we also find that a 1% reduction of ticket price will bring about 0.9% more connecting passengers, and a 1% increase of airport acceptance rate can bring about 0.35% more connecting passengers in the network, with all else equal. These findings are helpful for airlines to understand the effects of changing their services, and also useful for us to quantify the benefits of hub airport expansion projects.At the end of this paper, we give an example as an application to demonstrate how the developed demand model could be used to valuate passengers’ direct benefit from airport capacity expansion.     

An aggregate demand model for intercity passenger travel in Sri Lanka

Inspite of the inherent weaknesses in aggregate demand models, they continue to be used in everyday applications, especially in developing countries. The largely data intensive disaggregate model preclude its application in many cases. This paper attempts the formulation and calibration of an aggregate total demand model for estimating inter-district passenger travel by public transport in Sri Lanka. In its process, an investigation is made of the common problems in the aggregate approach while examining possible remedial measures to improve the accuracy and (hence) the usability of the aggregate model. It is argued that commonly used variables and functional forms are inappropriate for making accurate estimates in developing countries. Consequently, the model calibration is shown to incorporate variables representing urbanisation, under-development, transfers, a mode-abstract cost function and intrinsic features. The necessity for functional form for each variable to be based on behavioral assumptions that are tested using the Box-Cox transformation for ensuring the best fit of the data is also observed. Although, the model form was calibrated for Sri Lanka, the model is generalised in order for its applications to other countries as well as, both, inter-district and intercity travel demand estimation.     

An aggregate approach to model evacuee behavior for no-notice evacuation operations

This study proposes an aggregate approach to model evacuee behavior in the context of no-notice evacuation operations. It develops aggregate behavior models for evacuation decision and evacuation route choice to support information-based control for the real-time stage-based routing of individuals in the affected areas. The models employ the mixed logit structure to account for the heterogeneity across the evacuees. In addition, due to the subjectivity involved in the perception and interpretation of the ambient situation and the information received, relevant fuzzy logic variables are incorporated within the mixed logit structure to capture these characteristics. Evacuation can entail emergent behavioral processes as the problem is characterized by a potential threat from the extreme event, time pressure, and herding mentality. Simulation experiments are conducted for a hypothetical terror attack to analyze the models’ ability to capture the evacuation-related behavior at an aggregate level. The results illustrate the value of using a mixed logit structure when heterogeneity is pronounced. They further highlight the benefits of incorporating fuzzy logic to enhance the prediction accuracy in the presence of subjective and linguistic elements in the problem.     

有轨陡坡斜井有关施工能力的探讨

文章通过乌鞘岭隧道13#斜井有轨陡坡斜井施工的实际情况,对有轨陡坡斜井施工能力进行了分析,并对有关问题进行了探讨,以供同行参考.     

A regional railroad network optimization model for coal transportation

A regional railroad network is presented to evaluate the system's response to increased coal traffic. An optimal, multimodal, coal-shipping pattern is developed for the study region to minimize total costs and to efficiently use the existing network. A two-stage, general model allocates resources among demands and then assigns flows to the network according to efficiency criteria. The model is sufficiently general to permit modification for specific needs, assumptions and data. Government agencies and industries can apply the model in resource allocation decisions and transportation policy analysis.     

Development of a differential route share model for railroad freight traffic

This paper summarizes work undertaken towards development and calibration of a model to predict the distribution of rail freight traffic among competing routes. The model is designed for use in analyzing the traffic effects of changes in the level-of-service on selected rail lines. The model predicts route shares based on the overall network configuration of each railroad participating in a given market. The model selects feasible routes, discards those routes which appear to be too circuitous or costly, and then assigns traffic to the remaining routes in accordance with several network characteristics. It is designed to be sensitive to level-of-service changes, and to simulate the response of shippers and railroads to a competitive environment. A multiple route-finding algorithm was used to find possible routes based on the number of railroads operating at the originating and terminating end of a market. Multiple routes were determined and matched with observed traffic flows from the ICC One-Percent Waybill Sample. Physical network characteristics for each route, including distance, junction frequency, and “impedance,” were calculated from the network model and were correlated with the traffic share observed on each route in the market. A two-stage model was developed to find feasible routes from the set of possible routes and to allocate traffic to feasible routes based on levels-of-service. The model was calibrated on 9,793 routes from 1,199 markets with twenty or more carloads from the 1977 One-Percent Carload Waybill Sample. Model calibration supported the hypothesis that network route characteristics did indeed influence shipper choice of route, and that a normative model could be used to assess relative attractiveness of routes under various railroad corporate ownership restructuring scenarios.     

A comment on W. Wei and M. Hansen’s benefit estimation in “An aggregate demand model for air passenger traffic in the hub-and-spoke network”

This comment analyzes the demand model and method used by W. Wei and M. Hansen for computing the benefits of an airport capacity extension. The log-linear specification and coefficients of the demand function imply that the airport extension’s positive effect on demand decreases with the volume of traffic and associated congestion. If this unlikely result is accepted, the surplus method used by Wei and Hansen underestimates the users’ investment benefit. The note argues that the marginal willingness to pay for a capacity extension should rather increase with congestion. If this is the case, the method used by Wei and Hansen could actually overestimates the benefit.A better specification would rather allow for a function concave to the origin in order to account for capacity constraints, and also set a maximum finite price. Above all, a fair evaluation of the users’ benefit should be based on a function which explicitly includes a variable, or function of variables, that permits an estimation of the users’ cost of congestion.     

Parameter estimation for the peak traffic model

In a previous article a model was developed for predicting the temporal distribution of peak traffic demand, and the model is sensitive to the determining cost parameters whose values were not known. These costs are the cost to late and early arrivals at work and the cost to delays in the system while travelling. In this paper, using the method of least squares, representative values for these cost parameters are estimated for both the Southbound and Northbound traffic using the Sydney Harbour Bridge during the morning peak period. The resulting estimates show that a traveller tends to attach much higher cost to delays than to earliness or lateness to work; although the relative cost he attaches to lateness is higher than he attaches to earliness.     

An agent-based multimodal simulation model for capacity planning of a cross-border transit facility

Cross-border transit facilities constitute major public investment, and thus must serve the long-term needs of the communities, such as providing access to schools and businesses, contributing to a shared regional culture and lifestyle, fostering international trade, and supporting jobs for the region’s residents. Numerous studies have been conducted to evaluate the economic implications of vehicular flow delays at border crossings, however none of the studies focused on assessing cross-border flow of bus passengers and pedestrians. Since pedestrians are considered to be autonomous, intelligent, and perceptive, it is a challenging task to predict pedestrian movement and behavior in comparison to vehicular flows which follow a specific set of traffic rules. This paper presents a multiagent based multimodal simulation model to evaluate the capacity and performance of a cross-border transit facility. The significance of this research is the use of dynamic mode choice functionality in the model, which allows an individual person to make instantaneous choices between available modes of transportation. The scope of interest of the paper is limited to simulating access interface, circulation areas, ancillary and processing facilities. The developed model was calibrated to ensure realistic performance, and validated against specific performance criteria such as throughput per processing facility. In order to demonstrate the applicability of the developed simulation model, capacity and operational planning of a pedestrian transit facility was performed. The relative performance of alternative design or configuration was evaluated using the level of service criteria. Lastly, the effectiveness of each proposed capacity or operational improvement strategy was compared to the “do-nothing” scenario.     

An integrated model system and policy evaluation tool for maximizing mobility under environmental capacity constraints: A case study in Dalian City,China

This paper presents an integrated model system for mobility maximization based on a quantified specification of environmental capacity, and evaluates policy interaction and effectiveness by simulating a number of policy scenarios. The system is designed to specify the maximum level of car ownership and number of trips by private and public modes subject to an environmental capacity constraint defined as the frontier emission under maximum system efficiency. Four types of hypothetical policies (population change, urban sprawl, land-use pattern and network improvement) are designed and the effects of 13 policy scenarios are simulated using data of Dalian City, China. Results reveal that the integrated model system reacts sensitively to policy interventions. The urban sprawl reflected in a changing residential distribution from central to suburban areas is most instrumental from the perspective of pollution alleviation. If the goal is to simultaneously reduce emissions while accommodating mobility, two combinational policy scenarios outperform all others.     

An aircraft performance model implementation for the estimation of global and regional commercial aviation fuel burn and emissions

Estimates of global aviation fuel burn and emissions are currently nearly 10 years out of date. Here, the development of the Aircraft Performance Model Implementation (APMI) software which is used to update global commercial aviation fuel burn and emissions estimates is described. The results from APMI are compared with published estimates obtained using the US Federal Aviation Administration’s System for Assessing Aviation’s Global Emissions (SAGE) for the year 2006. The number of global departures modelled with the APMI software is 8% lower compared with SAGE and reflects the difference between their commercial air traffic statistics data sources. The mission fuel burn, CO₂ and H₂O estimates from APMI are approximately 20% lower than those predicted by SAGE for 2006 while the estimate for the total global aircraft SO_x emissions is approximately 40% lower. The estimates for the emissions of CO, HC and NO_x are 10%, 140% and 30% higher than those predicted by SAGE respectively. The reasons for these differences are discussed in detail.     

On the estimation of the multinomial probit model

Multinomial Probit provides, perhaps, the most satisfactory form of discrete choice model based on the framework of utility maximization. It has clear advantages over more commonly used alternatives, such as the multinomial logit model, although its use involves more computational effort. This paper discusses the problems both of calculating the multinomial probit choice functions and in estimating the model parameters. Four techniques for calculating the choice functions are reviewed with regard to their comparative accuracy, computational requirements and applicability. With regard to model estimation different calibration methods are reviewed and a simulation based algoirthm is presented and tested.     

Testing the dogit model with aggregate time-series and cross-sectional travel data

This paper compares dogit and logit specifications of market share models, taking into account the possibility that conclusions might depend on transformations of the explanatory variables of these models. Parameter estimates are obtained both for a time-series urban transit mode of payment model and for a cross-sectional intercity mode choice model. It is demonstrated, using current maximum likelihood techniques extended to take multiple-order autocorrelation of the residuals into account, that the dogit specification is at least equal to, and sometimes clearly superior to, the logit specification irrespective of transformations of explanatory variables.     

An analytical method for aircraft collision risk estimation

Transportation system safety is difficult to assess, particularly when examining future systems that are unlike existing systems. The absence of consensus concerning safety metrics and associated mathematical techniques inhibits implementation of improvements. One method for assessing safety was recently applied to assess new air traffic control procedures. The method contains several steps, including use of a collision risk model. The model uses probability theory to assess collision risk between aircraft due to random deviations from course. Techniques that recognize human monitoring and intervention to avoid collisions must be combined with the model to obtain absolute values of risk. Examples of model application are presented, together with a discussion of model limitations and use.     

Telemetric system for monitoring and automation of railroad networks

This paper describes a new method of real-time train monitoring based on the ZigBee/IEEE 802.15.4 protocol. The system consists of a mobile device embedded in the moving train which transmits parameter signals that are being measured by a base unit with the help of routers. When applied, the technique monitors and controls vehicles operating on permanent routes, making a real-time evaluation of their performance and location, and allowing an effective planning of trains. It consists of a low cost, low power consumption and safe modular technology capable of monitoring many different variables simultaneously.     

Enhancing intelligent agent collaboration for flow optimization of railroad traffic

Intelligent agents have successfully solved the train pathing problem on a small portion of railroad network [Tsen, 1995, Ph.D. Thesis, Carnegie Mellon University, USA]. As the railroad network grows, it is imperative that the agents collaborate to operate as efficiently as possible. In this paper, the authors demonstrate a collaboration protocol based on a conditional measure of agent effectiveness. Because agent effectiveness is not directly measurable, a suitable metric for agent effectiveness is introduced. Where typically agents run with uniform frequency, the collaboration protocol schedules the agents with a frequency proportional to their expected effectiveness. This protocol introduced a 10-fold improvement in the agent efficiency when tested with a simulation program on a portion of the Burlington Northern railroad.     

Validation of the Rakha-Pasumarthy-Adjerid car-following model for vehicle fuel consumption and emission estimation applications

The Rakha-Pasumarthy-Adjerid (RPA) car-following model has been demonstrated to successfully replicate empirical driver car-following behavior. However, the validity of this model for fuel consumption and emission (FC/EM) estimation has yet to be studied. This paper attempts to address this research need by analyzing the applicability of the model for FC/EM estimation and comparing its performance to other state-of-practice car-following models; namely, the Gipps, Fritzsche and Wiedemann models. Naturalistic empirical data are employed to generate ground truth car-following events. The model-generated second-by-second Vehicle Specific Power (VSP) distributions for each car-following event are then compared to the empirical distributions. The study demonstrates that the generation of realistic VSP distributions is critical in producing accurate FC/EM estimates and that the RPA model outperforms the other three models in producing realistic vehicle trajectory VSP distributions and robust FC/EM estimates. This study also reveals that the acceleration behavior within a car-following model is one of the major contributors to producing realistic VSP distributions. The study further demonstrates that the use of trip-aggregated results may produce erroneous conclusions given that second-by-second errors may cancel each other out, and that lower VSP distribution errors occasionally result in greater bias in FC/EM estimates given the large deviation of the distribution at high VSP levels. Finally, the results of the study demonstrate the validity of the INTEGRATION micro-simulator, given that it employs the RPA car-following model, in generating realistic VSP distributions, and thus in estimating fuel consumption and emission levels.     

Reserve capacity model based on variable demand for land-use development control

In this paper, the concept of reserve capacity has been extended to zone level to measure the land-use development potentiality of each trip generation zone. Bi-level programing models are proposed to determine the signal setting of individual intersections for maximizing possible increase in total travel demand and the corresponding reserve capacity for each zone. The change of the origin–destination pattern with the variation of upper level decision variables is presented through the combined distribution/assignment model under user equilibrium conditions. Both singly constrained and doubly constrained combined models are considered for different trip purposes and data information. Furthermore, we have introduced the continuous network design problem by increasing road capacity and examined its effect on the land-use development potentiality of trip generation zone. A numerical example is presented to illustrate the application of the models and how a genetic algorithm is applied to solve the problem.