scholarly journals Modelling the Effects of Parking Charge and Supply Policy Using System Dynamics Method

2017 ◽  
Vol 2017 ◽  
pp. 1-10 ◽  
Author(s):  
Zhenyu Mei ◽  
Qifeng Lou ◽  
Wei Zhang ◽  
Lihui Zhang ◽  
Fei Shi
Keyword(s):  
System Dynamics ◽  
Choice Model ◽  
Evaluation Model ◽  
Travel Cost ◽  
Travel Mode ◽  
Travel Choice ◽  
Supply Policy ◽  
Proposed Model ◽  
Traffic Speed ◽  
Business District

Reasonable parking charge and supply policy are essential for the regular operation of the traffic in city center. This paper develops an evaluation model for parking policies using system dynamics. A quantitative study is conducted to examine the effects of parking charge and supply policy on traffic speed. The model, which is composed of three interrelated subsystems, first summarizes the travel cost of each travel mode and then calibrates the travel choice model through the travel mode subsystem. Finally, the subsystem that evaluates the state of traffic forecasts future car speed based on bureau of public roads (BPR) function and generates new travel cost until the entire model reaches a steady state. The accuracy of the model is verified in Hangzhou Wulin business district. The related error of predicted speed is only 2.2%. The results indicate that the regular pattern of traffic speed and parking charge can be illustrated using the proposed model based on system dynamics, and the model infers that reducing the parking supply in core area will increase its congestion level and, under certain parking supply conditions, there exists an interval of possible pricing at which the service reaches a level that is fairly stable.

scholarly journals Choice Model and Influencing Factor Analysis of Travel Mode for Migrant Workers: Case Study in Xi’an, China

2015 ◽  
Vol 2015 ◽  
pp. 1-9 ◽  
Author(s):  
Hong Chen ◽  
Zuo-xian Gan ◽  
Yu-ting He
Keyword(s):  
Influencing Factors ◽  
Migrant Workers ◽  
Choice Model ◽  
Mode Choice ◽  
Influencing Factor ◽  
Travel Mode ◽  
Factors Affecting ◽  
Travel Choice ◽  
Travel Mode Choice ◽  
Set Up

Based on the basic theory and methods of disaggregate choice model, the influencing factors in travel mode choice for migrant workers are analyzed, according to 1366 data samples of Xi’an migrant workers. Walking, bus, subway, and taxi are taken as the alternative parts of travel modes for migrant workers, and a multinomial logit (MNL) model of travel mode for migrant workers is set up. The validity of the model is verified by the hit rate, and the hit rates of four travel modes are all greater than 80%. Finally, the influence of different factors affecting the choice of travel mode is analyzed in detail, and the inelasticity of each factor is analyzed with the elasticity theory. Influencing factors such as age, education level, and monthly gross income have significant impact on travel choice mode for migrant workers. The elasticity values of education degree are greater than 1, indicating that it on the travel mode choice is of elasticity, while the elasticity values of gender, industry distribution, and travel purpose are less than 1, indicating that these factors on travel mode choice are of inelasticity.

scholarly journals A Multi-Modal Route Choice Model with Ridesharing and Public Transit

2018 ◽  
Vol 10 (11) ◽  
pp. 4275 ◽  
Author(s):  
Meng Li ◽  
Guowei Hua ◽  
Haijun Huang
Keyword(s):  
Public Transit ◽  
Choice Model ◽  
Route Choice ◽  
Smart Phone ◽  
Travel Cost ◽  
Payment Systems ◽  
Key Factors ◽  
Main Road ◽  
Proposed Model ◽  
Modal Route

With the extensive use of smart-phone applications and online payment systems, more travelers choose to participate in ridesharing activities. In this paper, a multi-modal route choice model is proposed by incorporating ridesharing and public transit in a single-origin-destination (OD)-pair network. Due to the presence of ridesharing, travelers not only choose routes (including main road and side road), but also decide travel modes (including solo driver, ridesharing driver, ridesharing passenger, and transit passenger) to minimize travelers’ generalized travel cost (not their actual travel cost due to the existence of car capacity constraints). The proposed model is expressed as an equivalent complementarity problem. Finally, the impacts of key factors on ridesharing behavior in numerical examples are discussed. The equilibrium results show that passengers’ rewards and toll charge of solo drivers on main road significantly affect the travelers’ route and mode choice behavior, and an increase of passengers’ rewards (toll) motivates (forces) more travelers to take environmentally friendly travel modes.

scholarly journals Impact of Capacity Drop on Commuting Systems under Uncertainty

2018 ◽  
Vol 2018 ◽  
pp. 1-15 ◽  
Author(s):  
Wenwei Zhang ◽  
Hui Zhao ◽  
Rui Jiang
Keyword(s):  
Traffic Congestion ◽  
Travel Cost ◽  
Peak Period ◽  
Travel Choice ◽  
Dispersion Degree ◽  
Proposed Model ◽  
The Mean ◽  
Capacity Drop ◽  
The Impact ◽  
The Relationship

This paper analyzes the impact of capacity drop on commuters’ travel choice behaviors under uncertainty. For clarity, we assume that the capacity drop is triggered by the queue forming at the bottleneck under the hypercongestion circumstances, and the stochasticity of the drop could not be neglected. Considering the uncertainty of travel time, we establish a bottleneck model with commuters choosing their departure time according to the mean travel cost. From the proposed model, analytical solutions are achieved and therefore several properties are presented, including monotonicity of travel cost and departure rate, and the relationship between dispersion degree and length of peak period. To alleviate traffic congestion at the bottleneck and avoid capacity drop, we design a time-varying toll scheme and a step toll scheme. Evolution of queue length in equilibrium is discussed based on the Laih model. Numerical examples are also presented to demonstrate the established model and the effectiveness of the proposed toll schemes.

scholarly journals A Bayesian Network Model on the Public Bicycle Choice Behavior of Residents: A Case Study of Xi’an

2017 ◽  
Vol 2017 ◽  
pp. 1-13 ◽  
Author(s):  
Qiuping Wang ◽  
Hao Sun ◽  
Qi Zhang
Keyword(s):  
Bayesian Network ◽  
Network Model ◽  
Expert Knowledge ◽  
Choice Model ◽  
Mode Choice ◽  
Bayesian Network Model ◽  
Travel Mode ◽  
The Public ◽  
Proposed Model ◽  
Travel Mode Choice

In order to study the main factors affecting the behaviors that city residents make regarding public bicycle choice and to further study the public bicycle user’s personal characteristics and travel characteristics, a travel mode choice model based on a Bayesian network was established. Taking residents of Xi’an as the research object, a K2 algorithm combined with mutual information and expert knowledge was proposed for Bayesian network structure learning. The Bayesian estimation method was used to estimate the parameters of the network, and a Bayesian network model was established to reflect the interactions among the public bicycle choice behaviors along with other major factors. The K-fold cross-validation method was used to validate the model performance, and the hit rate of each travel mode was more than 80%, indicating the precision of the proposed model. Experimental results also present the higher classification accuracy of the proposed model. Therefore, it may be concluded that the resident travel mode choice may be accurately predicted according to the Bayesian network model proposed in our study. Additionally, this model may be employed to analyze and discuss changes in the resident public bicycle choice and to note that they may possibly be influenced by different travelers’ characteristics and trip characteristics.

A Heteroscedastic Polarized Logit Model to Investigate the Competition of Bicycle for the Bikeable Trips with the Other Modes

2018 ◽  
Vol 2672 (49) ◽  
pp. 58-68
Author(s):  
Khandker Nurul Habib
Keyword(s):  
Choice Model ◽  
National Capital Region ◽  
Travel Mode ◽  
Household Travel Survey ◽  
Market Shares ◽  
Proposed Model ◽  
National Capital ◽  
Mode Share ◽  
Household Travel ◽  
Low Sensitivity

The paper proposes a new discrete choice model, named the Heteroscedastic Polarized Logit (HPL) to investigate choice contexts with one or more alternatives with remarkably low market shares. The proposed model is used to investigate the factors influencing the choice of a bicycle as a travel mode in the National Capital Region (NCR) of Canada. Data from the latest household travel survey of the NCR are used to investigate the mode choices of bikeable trips. Bikeable trips are defined as trips with lengths shorter than 16 km as this is the observed maximum limit of a bicycle trip in the dataset. A large dataset with over 40,000 trip records is used for empirical investigation where the bicycle has the lowest mode share of 3%. The HPL model clearly shows its appropriateness and superiority over comparable models in such a context. The choice to walk is found to be more sensitive to trip length than the choice to cycle, yet walking is found to have three times larger market share than that of cycling. Similarly, motorized modes are found to have low sensitivity to travel time and other impedances and have larger market shares. Women and students are found not to prefer the bicycle as a travel mode. Cycling infrastructure is seen to be effective in increasing the choice of the bicycle as a travel mode, but it also becomes clear that additional soft policy initiatives would be necessary to increase the popularity of cycling among young people, students, and women.

scholarly journals Mode Choice Modelling Between Bus and Train Under the New Normal Condition

2021 ◽  
Vol 004 (01) ◽  
pp. 084-092
Author(s):  
Willy Kriswardhana ◽  
Akhmad Hasanuddin ◽  
Daud Muntsari
Keyword(s):  
Normal Condition ◽  
Large Scale ◽  
Choice Model ◽  
Stated Preference ◽  
Mode Choice ◽  
Travel Cost ◽  
Travel Mode ◽  
New Normal ◽  
Social Distancing ◽  
Travel Mode Choice

The passenger movements were limited by the government policies that made new system decisions, namely large-scale social distancing policies. However, over time several regions in Indonesia have begun to end large-scale social distancing called new normal. The new normal condition has undoubtedly changed the pattern of mode choice of the passenger. Little attention has been paid to the travel mode choice under the new normal condition. Therefore, this study aims to understand the travel mode choice model of train and bus, especially in the new normal era. The primary data was collected using the stated preference online-based survey. This study performed a Binomial-Logit-Difference model. From the modelling result, 89% of the passenger will choose the bus if the train's travel fare is IDR 160,000 higher. The probability value will be equal when the ticket fare of the bus is IDR 25,000 higher than train’s travel cost. It indicates that people choose the bus mode because of the travel cost factor. Directions for the future study are presented

THE DEVELOPMENT OF THE MATHEMATICAL MODEL OF PREDICTING THE INDICATORS OF ACCREDITATION OF TECHNICAL UNIVERSITIES IN THE RUSSIAN FEDERATION

2017 ◽  
pp. 27-38
Author(s):  
Olga Mikhaylovna Tikhonova ◽  
Alexander Fedorovich Rezchikov ◽  
Vladimir Andreevich Ivashchenko ◽  
Vadim Alekseevich Kushnikov
Keyword(s):  
Mathematical Model ◽  
System Dynamics ◽  
Regression Model ◽  
Oriented Graph ◽  
Real Data ◽  
Educational Process ◽  
Proposed Model ◽  
Linear Differential ◽  
The University ◽  
The Mathematical Model

The paper presents the system of predicting the indicators of accreditation of technical universities based on J. Forrester mechanism of system dynamics. According to analysis of cause-and-effect relationships between selected variables of the system (indicators of accreditation of the university) there was built the oriented graph. The complex of mathematical models developed to control the quality of training engineers in Russian higher educational institutions is based on this graph. The article presents an algorithm for constructing a model using one of the simulated variables as an example. The model is a system of non-linear differential equations, the modelling characteristics of the educational process being determined according to the solution of this system. The proposed algorithm for calculating these indicators is based on the system dynamics model and the regression model. The mathematical model is constructed on the basis of the model of system dynamics, which is further tested for compliance with real data using the regression model. The regression model is built on the available statistical data accumulated during the period of the university's work. The proposed approach is aimed at solving complex problems of managing the educational process in universities. The structure of the proposed model repeats the structure of cause-effect relationships in the system, and also provides the person responsible for managing quality control with the ability to quickly and adequately assess the performance of the system.

A system dynamics model for routing and scheduling of cross-dock and transportation in reverse logistics network of perishable goods

2021 ◽  
pp. 1-17
Author(s):  
Pezhman Abbasi Tavallali ◽  
Mohammad Reza Feylizadeh ◽  
Atefeh Amindoust
Keyword(s):  
System Dynamics ◽  
Reverse Logistics ◽  
Logistics Network ◽  
Routing And Scheduling ◽  
Perishable Goods ◽  
Decision Variables ◽  
Proposed Model ◽  
Reverse Logistics Network ◽  
The Cross ◽  
Space Requirements

Cross-dock is defined as the practice of unloading goods from incoming vehicles and loading them directly into outbound vehicles. Cross-docking can simplify supply chains and help them to deliver goods to the market more swiftly and efficiently by removing or minimizing warehousing costs, space requirements, and use of inventory. Regarding the lifetime of perishable goods, their routing and scheduling in the cross-dock and transportation are of great importance. This study aims to analyze the scheduling and routing of cross-dock and transportation by System Dynamics (SD) modeling to design a reverse logistics network for the perishable goods. For this purpose, the relations between the selected variables are first specified, followed by assessing and examining the proposed model. Finally, four scenarios are developed to determine the optimal values of decision variables. The results indicate the most influencing factors on reaching the optimal status is the minimum distance between the cross-dock and destination, rather than increasing the number of manufactories.

scholarly journals Research on the Evaluation Model of Urban Tourism Management Efficiency with Uncertain Linguistic Information

2014 ◽  
Vol 2014 ◽  
pp. 1-4 ◽  
Author(s):  
Song-Mao Wang ◽  
Liang-Yan Fang ◽  
Feng Deng
Keyword(s):  
Decision Making ◽  
Evaluation Model ◽  
Multiple Attribute Decision Making ◽  
Urban Tourism ◽  
Weighted Averaging ◽  
Linguistic Information ◽  
Management Efficiency ◽  
Tourism Management ◽  
Proposed Model ◽  
Multiple Attribute

We investigate the multiple attribute decision making problems for evaluating the urban tourism management efficiency with uncertain linguistic information. We utilize the uncertain linguistic weighted averaging (ULWA) operator to aggregate the uncertain linguistic information corresponding to each alternative and get the overall value of the alternatives and, then rank the alternatives and select the most desirable one(s). Finally, a numerical example for evaluating the urban tourism management efficiency with uncertain linguistic information is used to illustrate the proposed model.

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