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Xia Li
Beijing Institute of Technology

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Article
Published: 05 September 2019 in Transportation
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Coupling activity-based models with dynamic traffic assignment appears to form a promising approach to investigating travel demand. However, such an integrated framework is generally time-consuming, especially for large-scale scenarios. This paper attempts to improve the performance of these kinds of integrated frameworks through some simple adjustments using MATSim as an example. We focus on two specific areas of the model—replanning and time stepping. In the first case we adjust the scoring system for agents to use in assessing their travel plans to include only agents with low plan scores, rather than selecting agents at random, as is the case in the current model. Secondly, we vary the model time step to account for network loading in the execution module of MATSim. The city of Baoding, China is used as a case study. The performance of the proposed methods was assessed through comparison between the improved and original MATSim, calibrated using Cadyts. The results suggest that the first solution can significantly decrease the computing time at the cost of slight increase of model error, but the second solution makes the improved MATSim outperform the original one, both in terms of computing time and model accuracy; Integrating all new proposed methods takes still less computing time and obtains relatively accurate outcomes, compared with those only incorporating one new method.

ACS Style

Chengxiang Zhuge; Mike Bithell; Chunfu Shao; Xia Li; Jian Gao. An improvement in MATSim computing time for large-scale travel behaviour microsimulation. Transportation 2019, 48, 193 -214.

AMA Style

Chengxiang Zhuge, Mike Bithell, Chunfu Shao, Xia Li, Jian Gao. An improvement in MATSim computing time for large-scale travel behaviour microsimulation. Transportation. 2019; 48 (1):193-214.

Chicago/Turabian Style

Chengxiang Zhuge; Mike Bithell; Chunfu Shao; Xia Li; Jian Gao. 2019. "An improvement in MATSim computing time for large-scale travel behaviour microsimulation." Transportation 48, no. 1: 193-214.

Journal article
Published: 09 August 2019 in Energies
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An empirical study of the parking behaviour of Conventional Vehicles (CVs), Battery Electric Vehicles (BEVs), and Plug-in Hybrid Electric Vehicles (PHEVs) was carried out with the data collected in a paper-based questionnaire survey in Beijing, China. The study investigated the factors that might influence the parking behaviour, with a focus on the maximum acceptable time of walking from parking lot to trip destination, parking fee, the availability of charging posts, the state of charge of EVs and the range anxiety of BEVs. Several Multinomial Logit (MNL) models were developed to explore the relationships between individual attributes and parking choices. The results suggest that (1) the maximum acceptable walking time generally increases with the rise in the amount of saving for parking fee; (2) the availability of charging posts does not influence the maximum acceptable walking time when PHEVs and BEVs have sufficient charge, but the percentage of people willing to walk longer than eight minutes increases from around 35% to 46% when PHEVs are in a low stage of charge; (3) more than half of BEV drivers want the driving range of their vehicles to be one and a half times the driving distance before they depart, given the distance is 50 km. Based on the empirical findings above, a conceptual framework was proposed to explicitly simulate the parking behaviour of both CVs and EVs using agent-based modelling.

ACS Style

Chengxiang Zhuge; Chunfu Shao; Xia Li; Shao; Li. Empirical Analysis of Parking Behaviour of Conventional and Electric Vehicles for Parking Modelling: A Case Study of Beijing, China. Energies 2019, 12, 3073 .

AMA Style

Chengxiang Zhuge, Chunfu Shao, Xia Li, Shao, Li. Empirical Analysis of Parking Behaviour of Conventional and Electric Vehicles for Parking Modelling: A Case Study of Beijing, China. Energies. 2019; 12 (16):3073.

Chicago/Turabian Style

Chengxiang Zhuge; Chunfu Shao; Xia Li; Shao; Li. 2019. "Empirical Analysis of Parking Behaviour of Conventional and Electric Vehicles for Parking Modelling: A Case Study of Beijing, China." Energies 12, no. 16: 3073.

Journal article
Published: 16 July 2019 in Sustainability
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A comparative study is carried out to investigate the differences among conventional vehicles (CVs), battery electric vehicles (BEVs) and plug-in hybrid electric vehicles (PHEVs) in the maximum acceptable time of diverting to a refuelling station, maximum acceptable time of queueing at a refuelling station, refuelling modes and desirable electric driving ranges, using Beijing, China, as a case study. Here, several multinomial logit (MNL) models are developed to relate the diverting and waiting times to individual attributes. The results suggest that, (1) the diverting time roughly follows a normal distribution for both CVs and electric vehicles (EVs), but the difference between them is slight; (2) EVs tend to bear longer waiting time above 10 min; (3) the MNL models indicate that income and the level of education tend to be more statistically significant to both the diverting and waiting times; (4) the most preferred driving ranges obtained for BEVs and PHEVs are both around 50 km, indicating that EV drivers may just prefer to charge for a specific time ranging from 8 to 10 min. Finally, ways to apply the empirical findings in planning refuelling and charging stations are discussed with specific examples.

ACS Style

Chengxiang Zhuge; Chunfu Shao; Xia Li. A Comparative Study of En Route Refuelling Behaviours of Conventional and Electric Vehicles in Beijing, China. Sustainability 2019, 11, 3869 .

AMA Style

Chengxiang Zhuge, Chunfu Shao, Xia Li. A Comparative Study of En Route Refuelling Behaviours of Conventional and Electric Vehicles in Beijing, China. Sustainability. 2019; 11 (14):3869.

Chicago/Turabian Style

Chengxiang Zhuge; Chunfu Shao; Xia Li. 2019. "A Comparative Study of En Route Refuelling Behaviours of Conventional and Electric Vehicles in Beijing, China." Sustainability 11, no. 14: 3869.

Transportation engineering
Published: 30 December 2016 in KSCE Journal of Civil Engineering
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Population synthesis is extensively required by a number of micro-simulation models in transportation. A heuristic-based population synthesis method called Pop-H was proposed to overcome the following two limitations that received less attention. The first limitation is that one target marginal distribution can be well met by various sets of household weights that can be used to generate different sets of population and thus it is a problem that which set of household weights is the real one. Secondly, the population synthesis is commonly viewed as an optimization problem, and minimizing the Mean Absolute Percentage Error of control variables is generally used as the objective function. The Standard Deviation of control variables is also crucial in some cases, which, however receives scant attention. In response to these two limitations, the heuristic-based population synthesis method works in the following way: the Pop-H algorithm starts with the initial set of household weights derived from a sample data and calculates the final set of household weights by iteratively adjusting the initial set in a defined way with the objective function taking into account both Mean Absolute Percentage Error and Standard Deviation of control variables. Finally, the medium-sized city of Baoding, China was used as the case study. The sensitivity test was firstly done to examine four key parameters of the Pop-H algorithm, and then the algorithm was applied to create the population for the whole city.

ACS Style

Chengxiang Zhuge; Xia Li; Chia-An Ku; Jian Gao; Hui Zhang. A heuristic-based population synthesis method for micro-simulation in transportation. KSCE Journal of Civil Engineering 2016, 21, 2373 -2383.

AMA Style

Chengxiang Zhuge, Xia Li, Chia-An Ku, Jian Gao, Hui Zhang. A heuristic-based population synthesis method for micro-simulation in transportation. KSCE Journal of Civil Engineering. 2016; 21 (6):2373-2383.

Chicago/Turabian Style

Chengxiang Zhuge; Xia Li; Chia-An Ku; Jian Gao; Hui Zhang. 2016. "A heuristic-based population synthesis method for micro-simulation in transportation." KSCE Journal of Civil Engineering 21, no. 6: 2373-2383.

Conference paper
Published: 29 June 2016 in CICTP 2016
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Method based on fuzzy mathematics in combination with principal component analysis (FUZZY-PCA) can be used on evaluation of unmanned ground vehicles in U-turn environment. Relative membership degree is applied to make all indicators normalized and standardized after establishing index system of U-turn behavior, and using PCA method to compare all the teams with their evaluation index, which can obtain the final value matrix, and easily collate the results. The ranking of applying the method to the evaluation of “Future Challenge 2012” of the four unmanned ground vehicles is in agreement with the ranking of referee group. This kind of method is valuable for evaluation of unmanned ground vehicles’ behavior both in U-turn and other environment.

ACS Style

Yun-Hui Li; Ya-Nan Zhao; Li Gao; Fang Dong; Li Feng; Xia Li. Evaluation of the U-Turn Behavior of Unmanned Ground Vehicles Based on the FUZZY-PCA Method. CICTP 2016 2016, 1704 -1713.

AMA Style

Yun-Hui Li, Ya-Nan Zhao, Li Gao, Fang Dong, Li Feng, Xia Li. Evaluation of the U-Turn Behavior of Unmanned Ground Vehicles Based on the FUZZY-PCA Method. CICTP 2016. 2016; ():1704-1713.

Chicago/Turabian Style

Yun-Hui Li; Ya-Nan Zhao; Li Gao; Fang Dong; Li Feng; Xia Li. 2016. "Evaluation of the U-Turn Behavior of Unmanned Ground Vehicles Based on the FUZZY-PCA Method." CICTP 2016 , no. : 1704-1713.