Multi-scale and multi-modal network topology model

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Urban transportation development in China

Over the past decades, China, as a notable emerging country, has gone through a course of rocketing socio-economic development. This leads to the constant growth of urban transportation system. Nevertheless, before the eighties the urban transportation development in China was directed to the goods transportation. As a result, the improvement of the levels of urban transportation management and planning did not incorporate with the urban transportation development. The reason behind this trend relied in the fact was that the goods transportation was important for industrial products, as before the eighties industrial development of the Chinese cities was considered crucially important to urban industrialization. Moreover, the development of urban public transportation was neglected due to a low mobility demand of people. After the eighties, with a growing trend to urbanization and modernization in China, opportunities for passenger transportation are raised. For example, in 1980 the city of Wuhan had about 35000 motor vehicles, of which 49 percent were goods vehicles, but in 1998 with a total number of nearly 284000 motor vehicles, the proportion of goods vehicles was only 20 percent (Statistics Bureau of Wuhan, 1999). Furthermore, the urban road networks of Chinese cities are rapidly sprawling, as the advances in motor vehicles and infrastructure construction materials incorporate with a great growth of the urban mobility demand since the middle of the 1980s. In the city of Shanghai, for instance, the length of highways increased threefold to over 10000 kilometres from 1990 to 2006 (Statistics Bureau of Shanghai, 2007).

Trip characteristics in the big cities of Chinana

The urban transportation development makes a great impact on the change of the urban transportation modal split (i.e., urban trip characteristics) in the Chinese cities. Table 2.2 reveals an example of the transportation modal split estimates in some large cities between the mid-eighties and the early nineties. All selected cities have more than one million inhabitants. Although a direct comparison of the cities is less practical because of the different years of survey, it is realistic to extract some basic features in the period between the mid-eighties and the early nineties. In this period, one obvious feature was that the bicycle played an important role in all trips, i.e., over 30 percent of all trips, and even over 60 percent in some cities. Walking was a popular mode, especially with a trip rate of over 30 percent in the cities of Shanghai, Chengdu and Guangzhou. Also, the public transportation was quite important in the cities, particularly with trip rates of over 20 percent in Beijing, Shanghai, and Guangzhou. Another interesting characteristic was that, due to a low ownership, there were no indications of the use of private cars in this period.

Issues of urban transportation development in China

The soaring growth of the number of private cars has led to many traffic problems including traffic congestion, traffic safety and air pollution in the large cities of China. For example, in the city of Beijing, average peak-hour vehicle speeds on the arterial roads between the Second and the Third Ring Roads have declined from 45 km per hour in 1994, to 33 in 1995, 20 in 1996, 12 in 2003, and less than 10 in 2005 (Beijing Research Centre for Transportation Development, 2006). Congestion is spreading severely beyond the Third and Fourth Ring Roads and along the major radial arterial roads. In the city of Shanghai, vehicle speeds are found to be less than 20 km per hour on most of the 29 major roads, and as low as 15 km per hour on night of them in 2004 (Shanghai Institute of Transportation Planning, 2004). Peak-hour vehicle speeds on the city centre roads were just between 9 an 18 km per hour. Moreover, traffic safety has become a serious traffic issue in China. In the city of Shenzhen, for instance, traffic accidents have been the top killer in 2001 (Shenzhen Daily, 2005). In China, the amount of carbon monoxide and hydrocarbons from auto emissions accounted for 79 percent of the total in urban areas nationwide in 2005 (World Bank, 2006). These traffic problems present a critical issue: Whether the urban transportation development will suffer severe decline if the cities were to increase its urban automobile ownership and usage to the Western level. This implies that it is necessary to build an effective public transportation system which can provide numerous enough capacity to meet the urban mobility demand. This usually involves high-level transportation data management and network planning, and high-quality information services, to attract travellers to use the public transportation mode instead of the private car mode.
Although the public transportation development is dropped behind the development of private car mode in China, the number of public transit vehicle per capital has had a rapid growth since the 1990s. For example, public transit vehicle numbers per million populations in Beijing, Shanghai, and Guangzhou in 2007 averaged 1581, as compared to 711 in 1995. In addition, these three cities have a significant higher capacity rail component as a part of their public transit vehicle number. For example, in the city of Shanghai, there were 829 rail cars in 2006, according a report released the Statistics Bureau of Shanghai in 2007. However, the average occupancy per public transportation vehicle in the big cities of China is also high. In 1995, the figure has reached 53 persons per vehicle on average, as compared to 14 and 20 in the US and western European in the same period (Kenworthy and Laube, 2001). This is consistent with the crowded situation in buses in most lager cities of China. Average peak-hour speed of public transportation vehicle was just 10 km per hour in Chinese mega cities in 2005 (Chinese Construction Ministry, 2005). This speed is less than the technical speed (12 km per hour) of a bicycle. The poor public transit supply and service make a negative impact on public transportation use, which consists of “captive-riders”, not “choice-riders”. Choice-riders are transit users who could drive if they wished to. Captive-riders are transit users who use transit because they do not have access to an automobile for variety of reasons. Such captive riders will all too readily switch to cars as their growing incomes. This allows them to escape the crowded conditions and slow and unreliable services of public transport systems based mainly on buses. This is needed to promote the efficiency and quality of the public transportation system in the cities of China. This entails a necessary task to explore and study the information-based means applied to transportation data management, network planning and information services.

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Guangzhou transportation sGuangzhou transportation systemsystems

The continuous growth of urban mobility demand has led to a wider gap between public transportation supply and demand in the large cities of China, particularly in the city of Guangzhou. This massive imbalance has changed the patterns of the urban transportation modes and travel behaviours. As a result, a number of policies and factors are pushing its transportation system to greater reliance on public transportation modes and private car modes. The city of Guangzhou has developed a large multi-modal transportation network composed of streets, bus and metro transit networks. The network system generates many travel behaviours whose analysis could reflect the way the city and the dwellers interact with.

The city of Guangzhou

The city of Guangzhou is one of the main transportation hubs of South China (Figure 2.1). Figure 2.2 illustrates the large administrative area that comprises ten urban districts (i.e., Tianhe, Baiyun, Huanpu, Haizhu, Liwan, Yuexiu, Huadu, Luogang, Panyu and Nansha) and two suburban counties (i.e. Conghua and Zengcheng), with a total urban area of 7434,40 square kilometres (Statistics Bureau of Guangzhou, 2007). Amongst the districts, Liwan are Yuexiu are the historically downtown centres of the city, where the Guangzhou municipal and Guangdong provincial governments and many academic institutions locate. Tianhe is the new downtown centre, and is now attracting a lot of commercial activities. Other districts, such as Huanpu, Bainyun and Haizhou, surround these historical and current downtown centres to form the « core » of the city.

Needs to Guangzhou transportation development

The change of the travel behaviours in the city of Guangzhou implies that the attraction of public transportation modes is declining. More trips tend to shift from non-motorized modes to cars and motorcycles. As a result, the growth of public transportation ridership is dropped from 10 to 3 percent per year after 2002. This presents the needs to deal with the poor public transportation provisions. One need is to balance the investment in the transportation development. In the city of Guangzhou, compared to the investments for improving the service level of urban road systems, the investments of urban public transportation are low for highly improving the performance of the systems (Kenworthy and Hu, 2002). Therefore, the policy should be changed to balance investment in new high capacity road infrastructure with investment in improving the service level of the public transportation systems, or even to prioritize the public transportation systems above road investment. Besides the change of the investment policy, it is also needed to employ appropriate information-based means to evaluate the criteria to a multi-modal transportation network. In short, the implementation of information technology applications presents an important topic, which is to maintain the high-quality accessibility to, connectivity of, and spatiality of the multi-modal transportation network, taking into account the quality of public transportation services. This implies that a transportation information system needs to be developed to promote the data management, representation, planning, routing and pre-trip guidance of multi-modal transportation network.

Table of contents :

Chapter 1
1.1 Context of the research
1.2 Research motivation
1.3 Research objective
1.4 Outline of the thesis
Chapter 2
2.1 Review of urban transportation development
2.1.1 Urban transportation systems
2.1.2 Urban transportation development
2.2 Urban transportation development in China
2.2.1 Trip characteristics in the big cities of China
2.2.2 Issues of urban transportation development in China
2.2.3 Guangzhou transportation systems
2.3 Integration of GIS and transportation systems
2.3.1 GIS for transportation
2.3.2 Users’ needs and transportation GIS applications
2.3.3 Current GIS-T applications in the city of Guangzhou
2.3.4 Towards a multi-modal and multi-scale transportation GIS
2.4 Transportation GIS data modelling approach
2.4.1 Transportation data representation
2.4.2 Current multi-modal transportation GIS data models
2.4.3 UML-based GIS data modelling
2.5 GIS-T development and routing application
2.5.1 Transportation GIS development
2.5.2 Transportation GIS routing application
2.6 Discussion
2.6.1 Application requirement
2.6.2 Related work
Chapter 3
3.1 Modelling process
3.2 Conceptual object model
3.2.1 Transportation object
3.2.2 Temporal relationship definitions
3.2.3 Event and evolution
3.3 Multi-scale and multi-modal network topology model
3.3.1 Bus line network
3.3.2 Metro line network
3.3.3 Urban street networks
3.3.4 Walking links network
3.3.5 Multi-scale data modelling and representations
3.4 Multi-modal and multi-criteria routing
3.4.1 Data structure to multi-modal routing
3.4.2 Travel costs in multi-modal routing
3.4.2 Multi-modal and multi-criteria routing model
3.5 Conclusion
Chapter 4
4.1 Study area: the centre of Tianhe District
4.2 A GIS-T prototype applied to the study area
4.3 Transportation data management and representation
4.4 Transportation data analysis and evaluation
4.4.1 Data Query
4.4.2 Shortest path finding
4.4.3 Service coverage
4.4.4 Multi-modal trip planning
4.4.5 Transportation network data analysis
4.6 Discussion
Chapter 5
5.1 Research purpose
5.2 Contribution
5.3 Further research


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