Chengdu Bus Group Case Study

1Low-Carbon Technology and Economy Research Center, Sichuan University, Chengdu 610064, China
2Uncertainty Decision-Making Laboratory, Sichuan University, Chengdu 610064, China

Copyright © 2012 Jiuping Xu et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

The idea of the “garden city” was developed theoretically to offer solutions to serious city development problems such as traffic congestion, population, and environmental pollution, among which the transportation is considered the most important. The question is how to develop balanced transportation in a garden city. Transportation is a complex system, particularly in a garden city. Therefore, we establish a new approach named the transportation multiobjective optimization system dynamics  (SD-MOP) model, which firstly calculates the optimal proportion of different transport means with an MOP approach and then applies them to the dynamic transportation system to analyze the results and analyze the influence on the whole system using different transportation means variation. In this paper, we take Chengdu as an example, one of the few cities in the world declared as building a garden city, and then develop some recommendations about world modern garden city transportation system development.

1. Introduction

It is generally recognized that cities are experiencing huge change in terms of their development and mobility patterns, while transportation, and  will continue to plays, a critical role in city development [1–3]. Energy consumption is one of the most severe transportation problems. IEA [4] argues that transport plays an important role in addressing the challenges of climate change mitigation as it consumes nearly half of global oil and contributes 25% of total fossil fuel combustion-related CO2 emissions of the world, and road transport is responsible for about 75% of the emissions from the transport sector. Petri et al. [5] compare the development of transport and energy use with a focus on CO2 emissions and suggest a more sustainable passenger transport system. Dominic [6] examines recent temporal and spatial trends and forecasts in energy consumption, energy efficiency, and energy costs in the transport sector across Europe. Meanwhile, land use, health effects, employment, population growth, and transport alternatives are all considered as related to the transportation problems. Frank [7] focused on land use, noting that, with different land uses, traffic designs need to be different. Messenger and Ewing [8] think that employment, the balance of living space, ownership, and the public transport service level affect people’s transport choice. Martin [9] investigates the association between means of transportation to work and overweight and obesity. In this paper, transportation structure is our main concern to the research. Transportation structure is the proportion of traffic amount carried by different transport means in extent of time and space. As the transportation structure directly influences resource allocation, a reasonable urban transportation structure can contribute to the rational use of resources and ensure a well-functioning system [10]. Although these studies have contributed a lot to transportation, we feel that all of the studies had not analyzed the transportation in a systematic and dynamic way. Thus, this paper seeks to further research in solving transportation problem and differs from its predecessors and we hope to introduce completely and accurately new viewpoints and models and research.

China is the largest developing country in the world. With rapid process of industrialization and urbanization, China has maintained an extensive growth in economic development while the deficiency of transportation began to emerge and became an urgent problem for us to deal with. Traffic congestion exists widely in metropolitan [11] capacity excess or overload caused by road passenger volume [12], which has already led to problems such as environmental pollution, lack of rational planning [13], economic intervention, and greenhouse gas emission excess [14]. Steps need to be taken to prevent the situation from deteriorating, otherwise, in return, this may hinder the development of the world modern garden city.

The “garden city” was first proposed by Howard [15] in the late 19th century, which came into being with the overcrowded, pollution, and epidemic spreading problems. It focuses on the coalition of city and countryside in essence and, later, makes some city planning about city scale, layout and structure, population density, and green belt [16]. A garden city is designed for health, life, and industry; it contains both rural and urban areas and has a strictly controlled city scale. It is the farmlands and towns around the central cities that control the expanding of urban land without limit. The garden city can ensure every resident to be close to nature and surrounded by self-sufficient farmland; especially in an ideal garden city, the land belongs to the public and under the responsibility of a professional committee. Therefore, the world modern garden city has its own features that differ from the ordinary city. Firstly, the form and pattern of garden city are multicenter, networking, and clustered in development along with being humanized in urban spatial structure. Secondly, harmonious nature and society: there are two kinds of harmony which refer to the strengthening of ecology and environment, social welfare, and wellbeing. Thirdly, the development path: the city aims to modern service industry and headquarters economy as the core, for the direction of high-tech industry, based on the powerful modern manufacturing industry and agriculture, all of which projects to be an internationally regional hub and central city on the basis of to be western and national central city. Fourthly, land use layout and transportation: it is the decentralized layout that is put into use in garden city, while in ordinary city, the public buildings are always arranged in concentrated form.

To realize the construction of world modern garden city, transportation should play its due role in it and act as a stimulus to promote it. As for the transportation in garden city, we think it is the traffic arteries that connect the central city with peripheral group city, with the agricultural land scattered around it, which finally realize the garden city. And the key way to build a world modern garden city is to promote the modernized and intellectualized transportation, that is, to make the linking of the urban and rural areas come true. In garden city, environmental and faster high-speed railway is the best choice to create the traffic circle in connecting between cities. In order to construct garden city, the transportation should match the development of garden city, and, in turn, the garden city will surely promote the transportation construction. Therefore, a strategy is needed to balance transportation system development and garden city construction, as transportation is an essential element of its success. Since regional transportation system is constantly changing, it is necessary to find a dynamic simulation method. System dynamics (SD) approaches as a modeling tool to provide a flexible way of building simulation models from causal loop or stock and flow diagrams. Therefore, to reflect the dynamic characteristics of garden city transportation system, the SD approach is the main methodology used in this paper, combined with multiobjective optimization (MOP) for its effectiveness.

The aim of this paper is to propose a system dynamics and multiobjective programming integrated support model to predict and adjust transport structure for the modern garden city in the world. The remainder of this paper is structured as follows. Section 2 describes the general system and solution approach problem. Section 3 develops a detailed garden city transportation system based on the SD-MOP model. In Section 4, Chengdu in China is discussed as a case study. Finally, we present some conclusions and proposals for the development of the transportation system in Chengdu and other garden cities in the world.

2. Problem Description

In this Section, a description of the problem is discussed, then a general framework to address the given problem is proposed. We give a basic background for our study.

2.1. System Description

It is of great significance to analyze logical urban transportation system in Chengdu, because it can assist in the development and management of the transportation plan and has a practical significance in helping relieving city traffic congestion [17]. Transport structure is an important factor in the whole system; a reasonable logic transport structure is a part of city planning and the adjustment of industrial structure, meanwhile, it guarantees minimum time waste, costs, and environment pollution.

As has been mentioned, an urban transportation system is a complex system and is especially important in the development of the garden city. With population, transport means, transport congestion, transport demand, and vehicle travel time are emerging as concerns in transportation system analysis. These elements are highly interrelated, but they are not the only factors that affect the system, there is also social, economic, political, environmental, and technical factors [17]. From previous research [18, 19], we assume that the garden city transportation system consists of five subsystems: the economic subsystem, the environmental subsystem, the traffic congestion subsystem, the policy management subsystem, and the traffic mode subsystem. The whole system is constantly changing and has an interrelationship with each other. Figure 1 shows the relationships between them. With economic development, there are more travel demand and transport choices or modes, and if not managed properly, they will lead to traffic congestion, which can result in environmental pollution, and, in turn, impacts the economy. However, through manual intervention, policy management can be used to control these effects when necessary.

Figure 1: The subsystems of garden city transportation system.

2.2. Method Design

System dynamics (SD) is a simulation technology that studies complex systems based on feedback control theory. It establishes synthetical models using system structures, the relation of consequent to antecedent and feedback loops, and, further, to find the solution to system performance using simulations. SD has been applied to a number of studies, not only the social sciences field, but also the agricultural practices [20], environmental issues [21], and economic controls [22] and has proven to be especially appropriate for modeling problems. Meanwhile, a number of system dynamics (SD) approaches have been used to do transportation modeling [23, 24], which give us successful examples for our research. SD can be used to forecast the trends in the next ten years by using certain parameters, but cannot be used to estimate exact levels reliably [25–27]. Therefore, while a system dynamics method is used as the main approach, we introduce multiobjective programming in the system dynamics model to develop an integrated model, which we call a system dynamics multiobjective programming model (SD-MOP), for the solution. The SD-MOP model not only provide better understanding of complex problems but also have considered the multiple objectives and also involve expert opinions in the decision. A general framework of the modeling process is shown in Figure 2. In a garden city transportation system decision process, a thorough analysis of the decision problem is conducted. Then, using the system dynamics (SD) approach, a causal loop diagram and detailed flow diagram are established. We run a series of MOPs to get the optimum value of those sensitive variables, and place these values into the SD model for simulation. Based on results of the SD-MOP integrated approach, different policy experiments are compared to choose the best route. If we are not satisfied with the result of the simulation, we can adjust the MOP models to yield better results; otherwise, the decision process is ended.

Figure 2: The general framework of the modeling process.

2.3. Basic Assumption

The basic assumptions of a garden city transportation system are as follows.(1)The main environmental pollution emissions we consider are CO2, excluding the exhausted gas from motorcycles.(2)We consider private cars, buses, taxis, and rail as the four main transportation means that directly influence transportation congestion and ignore others such as bicycles, pedestrians, and others.(3)The influence of employment is ignored in the whole system so the employment is ignored.(4)We use gross domestic product (GDP) to measure the economic development.(5)The purpose of this study is to promote coordinated economic development, environmental protection, policy management, and population through the optimization of transportation construction and structure.

2.4. Index System

The transportation system is one of the most complex systems in modern city. Similarly, the analysis of transportation has been a vital element in world modern garden city. Factors analysis is an effective way to understand the structure and function of a system well. According to the subsystems of garden city transportation system (Figure 1) and the characteristic of world modern garden city, we analyze the subdivision of each subsystem by selecting variables and influential factors synthetically based on the relative theoretical basis and the existing and our own research foundation, in principle of integrality, objectivity, scientificity, nonlinearity, practicality, and availability. Here, we list the main variables and influential factors of this model in Table 1 (variables and symbols in garden city transportation system). In order to facilitate our research and establish a mathematical model, we sort them according to the symbol of the name.

Table 1: Variables and symbols in garden city transportation system.

3. Modelling

Referring to the system description for garden city transportation structures, we construct a corresponding model. Firstly, the system dynamics general model is constructed. Secondly, a model is established, and the system dynamics model based on multiobjective optimization (SD-MOP) is developed. Finally, the model simulation method is analyzed.

3.1. System Dynamics Model

This Section is divided into two parts for a particular description of the modeling; firstly, the cause-effect relationship diagram, and, secondly, the stock and flow diagram, both of which are the two main steps when using system dynamics.

3.1.1. Cause-Effect Relationship Diagram

The SD model for the present study is developed for a transportation system. There are many variables in the subsystems occupying important positions in the system; thus, we build the cause-effect relationship diagram (see Figure 3) by incorporating the various features associated with the system. In this Figure, the arrows denote the cause-and-effect relationships and the plus and minus signs denote the positive and negative effects, respectively. The main feedback loops are given below:

Figure 3: The cause-effect relationship diagram of garden city transportation system.

(1)economic development total number of vehicles transportation congestion environmental pollution economic development;(2)population trip demand total trips transportation congestion economic development urban population;(3)economic development infrastructure investment road investment road capacity transportation congestion economic development;(4)policy management economic development environmental pollution policy intervention.
3.1.2. Stock and Flow Diagram

The causal relationship diagram emphasizes the feedback structure of the system, which, however, can never be comprehensive. We need to convert the causal relationship diagram into the stock and flow diagram that emphasizes the physical structure of the model, which tends to be more detailed than the causal loop diagram [28], to force us to think more specifically about the system structure. Figure 4 gives a detailed description, with the main formula as follows.

Figure 4: The stock and flow diagram of garden city transportation system.

Through system dynamics modeling, we can get the first-order differential equations. The change rate of the turnover of bus, the , is dependent on the stock of the turnover of bus , and there exists the basic stock , which is subject to factors of transport planning, demand volume, and so on; besides, it would be effected by functioning time , which regularly means one year: Similarly, the differential equations of the turnover of the taxi, railway, and private car are Through the previous analysis, we get the main part of the links in the garden city transport system:

Till now, we obtained the turnover of bus , similarly, the turnover of taxi, railway, and private car can be also described as , , and , and the traffic intensity can be formulated as the following: Further, where it can indicated that the irrational structure of transportation can increase the environmental pollution and ultimately decrease the development of economy to a certain extent. Meanwhile,

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