Exploring the future Electric Vehicle market and its impacts with an agent-based spatial integrated framework: A case study of Beijing, China

This paper investigates the potential expansion and impacts of Electric Vehicle (EV) market in Beijing, China at the micro level with an agent-based integrated urban model (SelfSim-EV), considering the interactions, feedbacks and dynamics found in the complex urban system. Specifically, a calibrated and validated SelfSim-EV Beijing model was firstly used to simulate how the EV market might expand in the context of urban evolution from 2016 to 2020, based on which the potential impacts of EV market expansion on the environment, power grid system and transportation infrastructures were assessed at the multiple resolutions. The results suggest that 1) the adoption rate of Battery Electric Vehicle (BEV) increases over the period, whereas the rate of Plug-in Hybrid Electric Vehicle (PHEV) almost remains the same; Furthermore, the so-called neighbour effects appear to influence the uptake of BEVs, based on the spatial analyses of the residential locations of BEV owners; 2) the EV market expansion could eventually benefit the environment, as evident from the slight decrease in the amounts of HC, CO and CO2 emissions after 2017; 3) Charging demand accounting for around 4% of total residential electricity demand in 2020 may put slight pressure on the power grid system; 4) the EV market expansion could influence several EV-related transport facilities, including parking lots, refuelling stations, and charging posts at parking lots, in terms of quantity, layout and usage. These results are expected to be useful for different EV-related stakeholders, such as local authorities and manufacturers, to shape polices and invest in technologies and infrastructures for EVs

The role of the license plate lottery policy in the adoption of Electric Vehicles: A case study of Beijing

Policy is an influential factor to the purchase and usage of Electric Vehicles (EVs). This paper is focused on the license plate lottery policy, a typical vehicle purchase restriction in Beijing, China. An agent-based spatial integrated urban model, SelfSim-EV, is employed to investigate how the policy may influence the uptake of EVs over time at the individual level. Two types of “what-if” scenario were set up to explore how the methods to allocate the vehicle purchase permits and the number of permits might influence the EV market expansion from 2016 to 2020. The results suggested that 1) both the allocation methods and the number of purchase permits could heavily influence the uptake of EVs and further its impacts on vehicular emissions, energy consumption and urban infrastructures; 2) compared to the baseline, both scenarios got significantly different spatial distributions of vehicle owners, transport facilities, vehicular emissions and charging demand at the multiple resolutions; 3) SelfSim-EV was found as a useful tool to quantify the nonlinear relationships between the increase of EV purchasers and the demand for transport facilities and electricity, and also to capture some unexpected results coming out from the interactions in the complex dynamic urban system

The effects of infrastructure investment on economic development in China, with specific focus on High-Speed Railways

Relevant studies about the relationship between transport and economic development is not a new research area. Many advocates and policy makers believe that investment in transport projects can stimulate the economy in different ways. However, the impact of transportation projects on economic development is still very difficult to measure due to the underlying complexity of this topic. This is precisely the focus and contribution of this thesis. From the 1990s, the Chinese government started to plan the national High Speed Railway (HSR) development to alleviate the pressure on the conventional railway system. The first well-known HSR (‘Jing-Jin” railway) was introduced in 2008 to connect Beijing and Tianjin. Ever since then, a massive and rapid development of HSR has been introduced in various places of China, providing many scholars a unique opportunity to evaluate national scale transport investment. This thesis aims to analyze the impact of such remarkable HSR development in China from different perspectives. HSR can certainly change the spatial pattern of China due to its advantages in efficiency, comfortability and sustainability. The transport gap between the coastal line area and inland of China might be significantly reduced due to the shrinkage of time-space map caused by the provision of HSR services. Therefore, this thesis discusses the impact of HSR, from spatial perspective, by developing an accessibility measure index based on railway timetable data and then evaluating the accessibility changes for each prefecture-level city. From the macroeconomic perspective, utilizing the results from accessibility measure index to a production function model, this thesis produces significant results in terms of changing the accessibility level on economic growth, accounting for spatial interrelationships between prefecture level cities. On the other hand, this thesis also develops a micro founded agent-based model to analyze the causal relationship between HSR and economic development, and empirically verify the results from the microeconomic perspective. Based on the empirical investigations in this thesis, HSR should be treated as a ‘necessary’ but not ‘sufficient’ condition for economic development. In addition, knowing its potential in terms of its impact on economic growth, it is beneficial to many stakeholders