Combined Trip Distribution Research Articles

Оцінка пропускної спроможності міської дорожньої мережі з урахуванням пропозиції паркування

In order to improve the estimation of network capacity for a given urban road system, it is assumed that the impact of destination parking management strategies should be considered in the network capacity estimation model. This study presents an extended road network capacity model that takes into account both the number of parking spaces and parking rates in each traffic zone. The network capacity model is formulated as a two-level programming problem with maximizing the total trip generation at the upper level and the combined trip distribution and traffic assignment (CTDTA) problem at the lower level. In order to reasonably characterize the impact of parking pricing and parking delays due to congestion, the CTDTA model involves two classes of travel demand. An efficient and practical algorithm for solving the two-level network capacity model is presented. Numerical experiments show the advantages of the proposed model and demonstrate the impact of parking supply and pricing on the results of road network capacity assessment.

Assessing Urban Road Network Capacity considering Parking Supply and Parking Pricing

To enhance the assessment of the network capacity for a given urban road system, the effects of the parking management strategies at destination areas are supposed to be considered in the network capacity assessment model. This study provides an extended road network capacity model which takes into consideration both the parking supply and parking pricing at each traffic zone. The network capacity model is formulated as a bilevel programming problem, with the maximization of total trip generation in the upper level and the combined trip distribution and traffic assignment (CTDTA) problem in the lower level. To reasonably characterize the impacts of the parking pricing and parking delay due to the congestion effect, two classes of travel demand are involved in the CTDTA model. An efficient and practical algorithm is provided for the solution of the bilevel network capacity model. Numerical experiments show the advantages of the proposed model and also demonstrate the effect of the parking supply and parking pricing on the assessment results of the road network capacity.

Traffic Impact Analysis for Proposed Construction in Warangal City

Traffic congestion is reaching intolerable levels in many cities in both developed and developing countries. New building developments are cited as one of the major causes of congestion in the cities. The uncontrolled growth of these developments adversely affects the quality of life and aggravates environmental and safety problems. Generally, it is seen that the new constructions are initiated and developed without giving due consideration to the ability of the existing transportation facilities to handle the additional traffic. Though the demand and supply characteristics of a transportation system must complement each other, it is not practically feasible to increase the supply infinitely to meet the demand. Hence, it is evident that Traffic Impact Analysis plays an important role in managing and reducing the uncontrolled development and its negative impacts on transportation system, environment and economy. A traffic impact analysis is an engineering study which assesses the adequacy of the existing or future transportation infrastructure to accommodate additional trips generated by a proposed development, redevelopment or land rezoning. The purpose of a traffic impact analysis review is to assess potential traffic impacts, identify acceptable mitigation strategic plan for the transportation requirement of future development, and maintain a balance between land use and quality of transportation services. An attempt has been made in this study to carry out traffic impact analysis for a proposed development in Warangal city. In this work, trip rate for the proposed development is computed on the basis of trip rates of similar existing developments. Combined Trip distribution and Assignment has been carried out using Traffic count based distribution model. Future condition Analysis has been done and appropriate mitigation measures are suggested.

Network Equilibrium Model with Dogit and Nested Logit Structures

This paper develops a combined equilibrium model for the simultaneous prediction of trip distribution, mode choice, and trip assignment. Trip distribution is formulated as a dogit model to take into account travel behavior of compulsory (work) and discretionary (nonwork) trips. Mode choice is given by a two-level nested logit model to avoid the independence from irrelevant alternatives restriction. Trip assignment is based on Wardrop's user-equilibrium principle. The log sums of the mode choice model were computed and fed back into the trip distribution step. Under this iterative process, destination choice of discretionary trips would respond to changing travel cost conditions occurring in mode choice and trip assignment steps, whereas destination choice of compulsory trips would remain fixed in the study time period. The proposed combined trip distribution, mode choice, and trip assignment (CDMA) model was reformulated as an equivalent convex programming problem with linear constraints and applied empirically to a county-level network in New Jersey. The results indicate that the CDMA model is better than the commonly used logit combined model in reproducing the observed link flows, origin–destination (O-D) trip flows, and O-D trip flows by mode.

Post-earthquake modelling of transportation networks

Transportation networks are critical civil infrastructures susceptible to natural hazards such as earthquakes. It is essential to understand and model the travel demand in emergency situation when considering measures to secure traffic function immediately after the earthquake and to restore the performance of transportation networks. Post-earthquake travel demand is complicated, and the changes of traffic pattern after the event are often coupled with the physical damage of transportation infrastructures. This study develops a scenario-based methodology to model the performance of post-earthquake transportation systems by extending the combined trip distribution and assignment model. Several general assumptions are made on post-earthquake travel behaviour and emergency traffic management measures. The proposed methodology is demonstrated with the Sioux-Falls road network and results are presented. The findings suggest that such scenario-based integrated methodology can capture the post-earthquake travel characteristics and is capable to provide more reasonable results than conventional transportation modelling approaches. The methodology can be used to model the emergency demand and post-earthquake performance of transportation systems. It is helpful to aid traffic planners and emergency managers in evaluating their contingency traffic plans and making decisions in emergency management.

An Application of Combined Model for Tehran Metropolitan Area Incorporating Captive Travel Behavior

To overcome deficiencies of the sequential transportation planning approach, this research applies a Combined Trip Distribution and Assignment Model (CTDAM) for the simultaneous prediction. The proposed combined model can itself be reformulated as an Equivalent Minimization Problem (EMP). When applying the Evans algorithm to the EMP, the CTDAM is expected to be usable in a realistic application. The objective of this research is to compare the conventional sequential procedure and CTDAM by applying both models to a large urban transportation network for captive trip purposes. Several evaluation measures were utilized to compare the results and confirm that the proposed model can efficiently satisfy several convergence criterions. It became clear that the User Equilibrium (UE) assignment in the proposed model can be obtained relatively swifter than the Sequential Model (SM) and can be efficiently used in large transportation networks. Furthermore, the comparing results point out the performance of the CTDAM is significantly better than SM.

An Application of Combined Model for Tehran Metropolitan Area Incorporating Captive Travel Behavior

To overcome deficiencies of the sequential transportation planning approach, this research applies a Combined Trip Distribution and Assignment Model (CTDAM) for the simultaneous prediction. The proposed combined model can itself be reformulated as an Equivalent Minimization Problem (EMP). When applying the Evans algorithm to the EMP, the CTDAM is expected to be usable in a realistic application. The objective of this research is to compare the conventional sequential procedure and CTDAM by applying both models to a large urban transportation network for captive trip purposes. Several evaluation measures were utilized to compare the results and confirm that the proposed model can efficiently satisfy several convergence criterions. It became clear that the User Equilibrium (UE) assignment in the proposed model can be obtained relatively swifter than the Sequential Model (SM) and can be efficiently used in large transportation networks. Furthermore, the comparing results point out the performance of the CTDAM is significantly better than SM.

An improved origin-based algorithm for solving the combined distribution and assignment problem

Abstract This paper is to further study the origin-based (OB) algorithm for solving the combined distribution and assignment (CDA) problem, where the trip distribution follows a gravity model and the traffic assignment is a user-equilibrium model. Recently, the OB algorithm has shown to be superior to the Frank–Wolfe (FW) algorithm for the traffic assignment (TA) problem and better than the Evans’ algorithm for the CDA problem in both computational time and solution accuracy. In this paper, a modified origin–destination (OD) flow update strategy proposed by Huang and Lam [Huang, H.J., Lam, W.H.K., 1992. Modified Evans’ algorithms for solving the combined trip distribution and assignment problem. Transportation Research B 26 (4), 325–337] for CDA with the Evans’ algorithm is adopted to improve the OB algorithm for solving the CDA problem. Convergence proof of the improved OB algorithm is provided along with some preliminary computational results to demonstrate the effect of the modified OD flow update strategy embedded in the OB algorithm.

AN INTEGRATED MODELING FRAMEWORK FOR ENVIRONMENTALLY EFFICIENT CAR OWNERSHIP AND TRIP BALANCE

Urban transport emissions generated by automobile trips are greatly responsible for atmospheric pollution in both developed and developing countries. To match the long-term target of sustainable development, it seems to be important to specify the feasible level of car ownership and travel demand from environmental considerations. This research intends to propose an integrated modeling framework for optimal construction of a comprehensive transportation system by taking into consideration environmental constraints. The modeling system is actually a combination of multiple essential models and illustrated by using a bi-level programming approach. In the upper level, the maximization of both total car ownership and total number of trips by private and public travel modes is set as the objective function and as the constraints, the total emission levels at all the zones are set to not exceed the relating environmental capacities. Maximizing the total trips by private and public travel modes allows policy makers to take into account trip balance to meet both the mobility levels required by travelers and the environmentally friendly transportation system goals. The lower level problem is a combined trip distribution and assignment model incorporating traveler's route choice behavior. A logit-type aggregate modal split model is established to connect the two level problems. In terms of the solution method for the integrated model, a genetic algorithm is applied. A case study is conducted using road network data and person-trip (PT) data collected in Dalian city, China. The analysis results showed that the amount of environmentally efficient car ownership and number of trips by different travel modes could be obtained simultaneously when considering the zonal control of environmental capacity within the framework of the proposed integrated model. The observed car ownership in zones could be increased or decreased towards the macroscopic optimization objective with zonal limit of emissions.

Meta‐Optimization Using Cellular Automata with Application to the Combined Trip Distribution and Assignment System Optimal Problem

In this paper, meta‐optimization and cellular automata have been introduced as a modeling environment for solving large‐scale and complex transportation problems. A constrained system optimum combined trip distribution and assignment problem was selected to demonstrate the applicability of the cellular automata approach over classical mixed integer formulation. A mathematical formulation for the selected problem has been developed and a methodology for applying cellular automata has been presented. A numerical example network was used to illustrate the potential for using cellular automata as a modeling environment for solving optimization problems.

Modeling urban taxi services in congested road networks with elastic demand

This paper extends the simple network model of urban taxi services proposed by Yang and Wong (Yang, H., Wong, S.C., 1998. Transportation Research B 32, 235–246). The extensions include incorporation of congestion effects, customer demand elasticity, reformulation of the model and development of a new solution algorithm. Instead of the previous characterization of pure taxi movements in a network by a system of nonlinear equations, a two-level model formulation is proposed for taxi movements in congested road networks. The bi-level problem is a combined network equilibrium model that describes simultaneous movements of vacant and occupied taxis as well as normal traffic in a user-optimal manner for given total customer generation from each origin and total customer attraction to each destination. The upper-level problem is a set of linear and nonlinear equations ensuring that the relation between taxi and customer-waiting times and the relation between customer demand and taxi supply are satisfied. The lower-level problem can be solved by the conventional multi-class combined trip distribution and assignment algorithm, whereas the upper-level problem is solved by a Newtonian algorithm with line search. A numerical example is presented to illustrate the proposed model and algorithm and demonstrate the characteristics of the taxi services in congested road networks.

Network Equilibrium Model of Employment Location and Travel Choices

A network equilibrium model for the simultaneous prediction of employment location, trip distribution, mode choice, and trip assignment is developed. The employment location choice was given by a simplified form of Putman’s employment allocation model. The trip distribution and mode choice were formulated as a nested logit model. Trip assignment was based on Wardrop’s “user-optimized” principle. The proposed combined employment location, trip distribution, mode choice, and assignment model can itself be reformulated as an equivalent minimization problem (EMP) so that the equilibrium conditions on the network and the location and travel demand functions can be derived as the Kuhn-Tucker conditions of the EMP. Under mild assumptions on the demand and link cost functions, the EMP is a convex programming problem with linear constraints, a great advantage from the computational aspect. In addition, a unique solution of the EMP exists that is equivalent to the proposed combined model. When applying the Evans algorithm to the equilibrium problem, the model is expected to be usable in a realistic application at a reasonable cost and within a reasonable time period. Several areas for further extensions of the model are also discussed.

Mathematical Programming Formulation of Combined Transportation and Land Use Model

A mathematical programming model of combined trip distribution, equilibrium network assignment, and residential location choice is presented. The model is developed on the basis of Wardrop’s user equilibrium principle and the random utility theory. A traveler’s route choice behavior is assumed to follow the user-optimized principle, whereas the residential location choice behavior is captured by the random utility theory. The simultaneous choice of travel routes and residential location is based on the assumption that each individual tries to minimize his or her travel cost and maximize his or her living utility. On the basis of this assumption the choice of travel routes is determined by using a user equilibrium assignment model and the choice of residential location is quantified by using a multinomial logit model. After defining the system equations of the combined model, the model is reformulated as a mathematical programming problem so that the characteristics of the combined model can be explored clearly and the model can be solved efficiently. After the properties of the model are analyzed the process of using the gradient search technique with a maximum-likelihood criterion to calibrate the model and by using the Evans algorithm to solve the optimization problem is presented. Furthermore, the model application procedure is also clearly defined.

Comparison of results of two models of transportation demand in Hong Kong: CDAM and a version of microTRIPS

CDAM is a new computer program for solving the combined trip distribution and assignment model for multiple user classes, which enables transport planners to estimate consistent Origin-Destination (O-D) matrices and equilibrium traffic flows simultaneously if the trip production and attraction of each user class at zone centroids are available. This paper reports an application of CDAM to the central Kowloon study area in Hong Kong. The coefficients of the model related to the components of generalized costs are calibrated on 1986 travel data. A comparison of results of CDAM and a version of MicroTRIPS models of transportation demand in Hong Kong are presented. Finally, some conclusions are drawn and the advantage of the CDAM are discussed.

A combined trip distribution and assignment model for multiple user classes

This paper presents a combined trip distribution and assignment model with multiple user classes, in which the trip productions at origins and trip attractions at destinations for each mode are available. In this model, the entropy-type (or gravity-type) trip distribution submodel is incorporated with the user equilibrium assignment problem for multiclass-user transportation networks. The original unsymmetrical link cost functions can be converted to symmetric forms by a ‘normalization’ procedure, and hence an equivalent convex mathematical programming model is formulated. Two different algorithms based on the Frank-Wolfe's and Evans', respectively are developed and their computational results on test networks are reported. This model is appropriate to be used on congested and multi-modal road networks in which the link travel time is similar for all traffic.

Calibration of the combined trip distribution and assignment model for multiple user classes

A combined trip distribution and assignment model for multiple user classes has been formulated by Lam and Huang (1992). We discuss here its calibration and show how to choose a suitable set of model parameters by using supplementary information. We show that each of the quantities—the mean trip cost or the entropy or the integral network cost, in the general cases—can be used individually to determine the model parameters, but the entropy would be the best choice. An algorithm is developed to obtain the parameters by using the entropy and has been tested on an example network. The relationships between the three quantities with respect to the parameters are also investigated by analyzing results of the example. However, the observed data for calculating the three quantities are usually not available or are costly to obtain. Other techniques of estimating the parameters by using alternative travel information which may be available or easy to obtain, such as partial observed Origin-Destination flows and traffic counts, are described, and a random calibration method is presented in this paper.

Modified Evans' algorithms for solving the combined trip distribution and assignment problem

Horowitz (1989) proposed a modification of Evans' algorithm for solving the combined trip distribution and assignment model with a reduction in computational time and memory, but without proof of convergence. It is shown here that his modified algorithm does not always converge to the optimal solution; in fact, it may fail in two of the total of seven possible cases. In these two cases either the iterative scheme falls into a deadlock or the new feasible solution is worse than the old one. On this basis another modified algorithm which first identifies the cases and then solves them by Horowitz's modification or Evans' original approach is presented. This new algorithm always converges to the correct solution and needs less computational time than Evans' method, but slightly more than Horowitz's modification. Computational results of the three algorithms on test networks are reported and their effectiveness compared.

A Model For Combined Trip Distribution And Traffic Assignment

The transportation planning process is usually carried out in a number of stages such as trip generation, trip distribution, modal split and traffic assignment. The aim of this study is to derive m...

An Optimal Land Use Design Model with Traffic Congestion

Given a transportation network, a land use design model is formulated as a two level system optimizing problem. The master problem allocates land use activities in zones so that the sum of the total development cost of land use and total transportation cost would be minimized. The sub problem gives a traffic flow equilibrium through combined trip distribution and assignment procedure. Taking into consideration traffic congestion, travel cost between each origin and destination pair is endogeneously determined. Consequently land use allocation, trip distribution and assignment process are consistent in the model. The meaning of the problem is stated from the view point of game theory, especially the Stackelberg game whose players are the planner and the network user. Heuristic solution procedure is proposed using MAP algorithm. A numerical example is executed for a simple and hypothetical zoning and transportation network. Some extensions of the model is briefly discussed.

A study of the spatial distribution of transportation‐an alternative approach and evaluation

Abstract This study intends to investigate a calibration procedure for a proposed combined trip generation and distribution model which is based on the concept of accessibility. Apart from the proofs of the existence and uniqueness of the solution, the computation efficiency is evaluated by using Cesario's data (1). The calibration procedure is further tested with empirical data which is obtained from an actual transportation survey carried out in Kaohsiung City of Taiwan, the Republic of China.