@article{PCOVID19202301,

title = {Assessing the Impacts of Stay-in-Place Policy of COVID-19 Pandemic during the Chinese Spring Festival: A Stated Preference Approach},

author = {Xiaofeng Pan and Tao Feng and Yanyi Chen},

url = {https://downloads.hindawi.com/journals/jat/2023/9662990.pdf},

doi = {https://doi.org/10.1155/2023/9662990},

year  = {2023},

date = {2023-01-17},

urldate = {2023-01-17},

journal = {Journal of Advanced Transportation},

volume = {2023},

number = {9662990},

abstract = {This paper aims to investigate Chinese people’s willingness to stay in the city where they work when the Spring Festival meets the COVID-19 pandemic. Specifically, a stated choice experiment about intercity travel including three homecoming trips (i.e., trips carried by conventional railway, high-speed railways, and private car) and the option “stay in place” was designed. Respondents were requested to choose the most preferred alternative in the context of the current situation of the COVID-19 pandemic and relevant policies. Based on the data collected from 800 respondents, a latent class mixed logit model was developed and estimated to capture the potential correlations within alternatives and respondents and the preference heterogeneity between respondents. Two latent classes were identified, one of which paid more attention to epidemic prevention policies while the other cared more about the characteristics of homecoming trips. Results show that people’s willingness to stay in the city of work is largely dependent on epidemic prevention policies in their hometowns and decisions of social network members.

},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{ZHU2023,

title = {An information model for highway operational risk management based on the IFC-Brick schema},

author = {Bencheng Zhu and Fujin Hou and Tao Feng and Tao Li and Cancan Song},

url = {https://www.sciencedirect.com/science/article/pii/S2046043022001046},

doi = {https://doi.org/10.1016/j.ijtst.2022.12.004},

issn = {2046-0430},

year  = {2023},

date = {2023-01-01},

journal = {International Journal of Transportation Science and Technology},

abstract = {With the development of highways, new technologies should be continuously introduced to improve highway traffic safety. Digital twin (DT) has been an emerging field of research in recent years. To develop a digital twin management system, a data model is essential. In the field of highway operational risk management (HORM), however, the development of data models is still in its infancy. Motivated by the concept of linked data, in this paper, we attempt to propose an information model for HORM. The main achievements of this paper include data architecture, identification and classification code methods, data interaction method, and the developed system. Based on data needs analysis, the highway information model architecture for risk management is defined as five layers: basic highway products, traffic sensors and equipment, traffic rules, traffic flow, and weather. Furthermore, according to the concepts of semantic data, these five layers can be classified into three categories: highway product data, topology data, and sensor data. Although the Industry Foundation Classes (IFC) standard and Brick schema were first proposed and applied in the building domain, some of their entities and relationships can also be applied to highways. To this end, we defined some new classes, a specific ontology, and an integrated framework for HORM. Finally, a case study was carried out. Applying such information model to highways has broad potential. It changes the file-based exchange method to the data-based one, which can promote highway data exchange and applications. The proposed information model could be of great significance for HORM.},

keywords = {Digital Twin, Highway, IFC-Brick, Information Model, Operational Risk Management},

pubstate = {published},

tppubtype = {article}

}

@article{YAN2023103585,

title = {A model of household shared parking decisions incorporating equity-seeking household dynamics and leadership personality traits},

author = {Qianqian Yan and Tao Feng and Harry Timmermans},

url = {https://www.sciencedirect.com/science/article/pii/S0965856423000058},

doi = {https://doi.org/10.1016/j.tra.2023.103585},

issn = {0965-8564},

year  = {2023},

date = {2023-01-01},

journal = {Transportation Research Part A: Policy and Practice},

volume = {169},

pages = {103585},

abstract = {Shared parking is viewed increasingly important as a way to alleviate parking problems in urban areas. To maximize the effect of shared parking initiatives, it is critical to understand the decision of households to share private parking spaces. Current models of household decision-making fail to adequately address equity seeking/avoiding household dynamics, which may negatively affect model validity. In this study, a model, which overcomes this theoretical concern, is introduced and estimated to understand the household shared parking participation decision. Specifically, the concept of leadership personality is used, jointly with individual and household characteristics, to specify the decision weight of each spouse of a couple. A choice experiment, in which individual members of couples first answer the choice questions individually and independently, and then jointly complete the choice questions, is designed to estimate the model. Estimation results, based on data collected in Qingdao, China, support the proposed model. Results show that intra-household interactions influence the households’ shared parking participation decision and that households favor alternatives that provide higher equality. Age, leadership personality, household structure, and household financial management are significantly related to household member decision weights.},

keywords = {Household decision-making, Intra-household interaction, Leadership personality, Shared parking},

pubstate = {published},

tppubtype = {article}

}

@article{Zhang2023,

title = {Association rules and prediction of transportation mode choice: Application to national travel survey data},

author = {Jiajia Zhang and Tao Feng and Harry J. P. Timmermans and Zhengkui Lin},

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85149871014&doi=10.1016%2fj.trc.2023.104086&partnerID=40&md5=eb1a8d77d53861b16c1a4c1b421b0ef9},

doi = {10.1016/j.trc.2023.104086},

issn = {0968090X},

year  = {2023},

date = {2023-01-01},

journal = {Transportation Research Part C: Emerging Technologies},

volume = {150},

publisher = {Elsevier Ltd},

abstract = {Predicting transportation mode choice is a classic challenge of travel behavior research. Over the years, different theoretical concepts and modeling approaches have been applied. This paper elaborates the application of class association rules (CARs) and examines their predictive performance using data extracted from the 2015 National Dutch Travel Survey. To solve the problem how to activate rules that have high confidence but low support, the information gain (IG) concept is introduced in the model building process. The modeling process in this study first involves extracting frequent items from the data using the FP-Growth algorithm and deriving CARs from these frequent items. Next, the IG statistic is used to construct a novel model (named CARIG), which consists of a set of decision rules that formally represent behavioral scripts, for predicting individuals’ transportation mode choice. The performance of CARIG is compared with the performance of conventional class-based association rules (CBA), decision trees (DT), a convolutional neural network (CNN) and a logistic regression (LR) model. In addition, a 10-fold cross validation test using a grid search parameter optimization method is conducted to validate the proposed approach. The results show that the proposed method is promising in predicting transportation mode choices observed in the national travel survey data. © 2023 Elsevier Ltd},

note = {Cited by: 0},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Wu2023,

title = {Uncovering the spatiotemporal impacts of built environment on traffic carbon emissions using multi-source big data},

author = {Jishi Wu and Peng Jia and Tao Feng and Haijiang Li and Haibo Kuang and Junyi Zhang},

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85149753704&doi=10.1016%2fj.landusepol.2023.106621&partnerID=40&md5=7e2bd842748fc814c1130a305a79b385},

doi = {10.1016/j.landusepol.2023.106621},

issn = {02648377},

year  = {2023},

date = {2023-01-01},

journal = {Land Use Policy},

volume = {129},

publisher = {Elsevier Ltd},

abstract = {Understanding and predicting urban traffic carbon emissions constitute an urgent agenda in research and policy decision-making. Since the exhausted emissions vary in time and different urban settings, assessing the spatiotemporal distribution of carbon emissions is fundamentally important for land use planning. This paper attempts to identify the spatial and temporal heterogeneity of the impacts of land use and built environment on urban traffic carbon emissions. A spatial standard deviational ellipse (SDE) model and a geographically and temporally weighted regression (GTWR) model were developed to explore the spatiotemporal dependency of traffic carbon emissions on land use and built environment factors and applied to the core urban zones of Dalian, China. Results show the center of gravity of traffic carbon emissions have a footprint characterized by a shift to the southeast first and then to the northwest, with weekday and weekend performance being consistent. Compared to other periods, emissions are spatially agglomerated during internal hours (9:00–15:59), especially during weekdays. Land use and built environment factors affect carbon emissions differently across space and time whereas the effects of residential population density, employment density, medical, road network density on weekdays are larger than that on weekends. Furthermore, we found that increasing land use mix leads to a greater negative impact on weekday emissions. This supplements the important role of mixed land use planning in decarbonization. Based on the findings, we propose various policy interventions to support the development of carbon neutral cities. © 2023 Elsevier Ltd},

note = {Cited by: 0},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{rs15082075,

title = {Driving Mechanism of Differentiation in Urban Thermal Environment during Rapid Urbanization},

author = {Yifeng Ji and You Peng and Zhitao Li and Jiang Li and Shaobo Liu and Xiaoxi Cai and Yicheng Yin and Tao Feng},

url = {https://www.mdpi.com/2072-4292/15/8/2075},

doi = {10.3390/rs15082075},

issn = {2072-4292},

year  = {2023},

date = {2023-01-01},

journal = {Remote Sensing},

volume = {15},

number = {8},

abstract = {To achieve sustainable urban development, it is essential to gain insight into the spatial and temporal differentiation characteristics and the driving mechanisms of the urban thermal environment (UTE). As urbanization continues to accelerate, human activity and landscape configuration and composition interact to complicate the UTE. However, the differences in UTE-driven mechanisms at different stages of urbanization remain unclear. In this study, the UTE of Shenyang was measured quantitatively by using the land surface temperature (LST). The spatial and temporal differentiation characteristics were chronologically studied using the standard deviation ellipse (SDE) and hotspot analysis (Getis-Ord Gi*). Then, the relationship between human activities, landscape composition and landscape configuration and LST was explored in a hierarchical manner by applying the geographical detector. The results show that the UTE in Shenyang continues to deteriorate with rapid urbanization, with significant spatial and temporal differentiation characteristics. The class-level landscape configuration is more important than that at the landscape level when studying UTE-driven mechanisms. At the class level, the increased area and abundance of cropland can effectively reduce LST, while those of impervious surfaces can increase LST. At the landscape level, LST is mainly influenced by landscape composition and human activities. Due to rapid urbanization, the nonlinear relationship between most drivers and LST shifts to near-linear. In the later stage of urbanization, more attention needs to be paid to the effect of the interaction of drivers on LST. At the class level, the interaction between landscape configuration indices for impervious surfaces, cropland and water significantly influenced LST. At the landscape level, the interactions among the normalized difference building index (NDBI) and other selected factors are significant. The findings of this study can contribute to the development of urban planning strategies to optimize the UTE for different stages of urbanization.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{HAN2023113035,

title = {Research on the influence of courtyard space layout on building microclimate and its optimal design},

author = {Jie Han and Xinyue Li and Beiyu Li and Wei Yang and Wei Yin and You Peng and Tao Feng},

url = {https://www.sciencedirect.com/science/article/pii/S0378778823002657},

doi = {https://doi.org/10.1016/j.enbuild.2023.113035},

issn = {0378-7788},

year  = {2023},

date = {2023-01-01},

journal = {Energy and Buildings},

volume = {289},

pages = {113035},

abstract = {The inner courtyard is an important transition space for mass exchange and heat transfer between the internal space of courtyard buildings and the external environment. A good layout of courtyard space is conducive to building energy efficiency and human thermal comfort. In the paper, we analyze the impacts of different design schemes of the spatial layout on the microclimate of inner courtyard space using field measurements and numerical simulation methods. The analysis of the measured data presents the main meteorological factors affecting the thermal comfort of the courtyard. The magnitude of the effects is ranked as air temperature, total solar radiation intensity, near-surface air flow rate, and relative humidity. Results of the ENVI-met simulation show that changing the cover of different underlying surface types leads to different microclimate regulation effects in the sense that the temperature and relative humidity in summer drops up to 3.53 °C and 15.59%, respectively and in winter increase up to 3.97 °C and 37.21%, respectively. This paper proposes that lawn ground, marble ground, water surface and landscape tree coverage of 25%, 25%, 50% and 75%, respectively, are suitable design schemes for the inner courtyard space of library.},

keywords = {Adaptive thermal comfort, Courtyard space, ENVI-met, Patio microclimate},

pubstate = {published},

tppubtype = {article}

}

@article{XIA2023109284,

title = {Research on safety and efficiency warranted vessel scheduling in unidirectional multi-junction waterways of port waters},

author = {Zicheng Xia and Tao Feng and Zijian Guo and Ying Jiang and Wenyuan Wang},

url = {https://www.sciencedirect.com/science/article/pii/S036083522300308X},

doi = {https://doi.org/10.1016/j.cie.2023.109284},

issn = {0360-8352},

year  = {2023},

date = {2023-01-01},

journal = {Computers & Industrial Engineering},

pages = {109284},

abstract = {Traffic management in port waters is a complicated task considering vessels with various characteristics and the specific layout of waterways. Optimal management is needed to reduce vessel waiting time and guarantee adequate safety, which in turn could enhance port competitiveness, and is conducive to port development. In this paper, a key collision avoidance point precomputation model is proposed to assess the safety level of each vessel scheduling plan and the consequent efficiency in unidirectional multi-junction waterways of port waters. An integrated vessel scheduling approach (IVSA) is proposed and developed to obtain the safety-enabled optimal vessel scheduling with the purpose to minimize the total delay under the premise of adequate safety. A series of experiments has been conducted by employing data of an empirical port in northern China. It is found that, in addition to improving traffic environment and reducing unnecessary behavior of vessels, IVSA could substantially reduce the total delay, from 6.04% to 27.75%. Result of this research can provide a guidance for port seaside management under complex situations and provide the decision-making support for the assessment of vessel traffic on future port waterway expansion.},

keywords = {Diversity speed, Traffic scheduling, Unidirectional multi-junction waterway, Vessel safety},

pubstate = {published},

tppubtype = {article}

}

@article{YUE2023104640,

title = {Classification and Determinants of High-Speed Rail Stations Using Multi-Source Data: A Case Study in Jiangsu Province, China},

author = {Yifan Yue and Jun Chen and Tao Feng and Xinwei Ma and Wei Wang and Hua Bai},

url = {https://www.sciencedirect.com/science/article/pii/S2210670723002512},

doi = {https://doi.org/10.1016/j.scs.2023.104640},

issn = {2210-6707},

year  = {2023},

date = {2023-01-01},

journal = {Sustainable Cities and Society},

pages = {104640},

abstract = {High-speed rail (HSR) stations play a vital role in the HSR system. HSR stations not only facilitate the accessibility of interregional transportation but also stimulate population movements across various cities in China. HSR stations in different cities can vary greatly, and an efficient HSR system requires an in-depth understanding of the interrelations between the related influential factors and spatiotemporal passenger flow patterns of different HSR stations. This study adopts a new scheme for clustering HSR stations based on passengers' arrival and departure time series using mobile phone data in Jiangsu, China. To this end, 71 HSR stations are clustered into 3 classes and the spatiotemporal characteristics of passenger flow at different stations are compared. Finally, a geographically weighted multinomial logit model (GWMNL) is built to explore the influence of the built environment, socioeconomic indicators, and HSR station attributes on the classification results of HSR stations related to the time-varying characteristics of passenger flow. The model results show that the number of entertainment POIs, population, population density, area, GDP and building area are significantly associated with the classification results of HSR stations. Additionally, for HSR stations under the same classification result, these variables also have different effects on them in the geographical dimension. According to these findings, quantitative analysis of the linkages between the passenger flow patterns at different HSR stations and the impacting factors would offer implications for planners and policymakers in HSR station planning and associated urban development.},

keywords = {Built environment, Geographically Weighted Multinomial Logit Model, High-Speed Rail Station, Influential factors, Mobile Phone Data},

pubstate = {published},

tppubtype = {article}

}

@article{nokey,

title = {Demand Prediction and Optimal Allocation of Shared Bikes Around Urban Rail Transit Stations},

author = {Liang Yu and Tao Feng and Tie Li and Lei Cheng},

url = {https://link.springer.com/content/pdf/10.1007/s40864-022-00183-w.pdf?pdf=button},

doi = {https://doi.org/10.1007/s40864-022-00183-w},

year  = {2022},

date = {2022-12-13},

journal = {Urban Transit Rail},

abstract = {The imbalance between the supply and demand of shared bikes is prominent in many urban rail transit stations, which urgently requires an efficient vehicle deployment strategy. In this paper, we propose an integrated model to optimize the deployment of shared bikes around urban rail transit stations, incorporating a seasonal autoregressive integrated moving average with long short-term memory (SARIMA-LSTM) hybrid model that is used to predict the heterogeneous demand for shared bikes in space and time. The shared bike deployment strategy was formulated based on the actual deployment process and under the principle of cost minimization involving labor and transportation. The model is applied using the big data of shared bikes in Xicheng District, Beijing. Results show that the SARIMA-LSTM hybrid model has great advantages in predicting the demand for shared bikes. The proposed allocation strategy provides a new way to solve the imbalance challenge between the supply and demand of shared bikes and contributes to the development of a sustainable transportation system.},

keywords = {Big data, Bike sharing, Machine learning, Transit},

pubstate = {published},

tppubtype = {article}

}

@article{nokey,

title = {A novel reliable path planning approach for multimodal networks based on a two-factor bound convergence algorithm},

author = {Wentao Yu and Huijun Sun and Tao Feng and Ying Lv and Xin Guo and Guangyu Xin},

url = {https://www.worldscientific.com/doi/epdf/10.1142/S0217984922500075},

doi = {https://doi.org/10.1142/S0217984922500075},

year  = {2022},

date = {2022-08-22},

journal = {Modern Physics Letters B},

abstract = {Due to the influence of diverse factors, travel time is highly uncertain. Travelers are eager to find the most reliable path in multimodal networks to reduce the penalty caused by late arrival. However, the research considering the traveler preferences in multimodal transportation networks to solve the reliable path problem with given budgets is limited. Thus, we propose two multimodal reliable path models to find personalized and reliable paths. First, we build a multimodal network based on smart card data to incorporate the multimodal transfers between public and private transportation and solve corresponding parking issues effectively. Next, we build a multimodal time-reliable path model to find time-reliable paths. Further, considering traveler preferences, we design a multimodal utility-reliable path model to find personalized and reliable paths. A novel two-factor reliability bound convergence algorithm is developed to solve the proposed models and proved for its theoretical feasibility. Finally, a real-world case study is used to verify the effectiveness and efficiency of the proposed models and algorithm.},

keywords = {Bound convergence algorithm, Multimodal network, Path planning},

pubstate = {published},

tppubtype = {article}

}

@article{@FrontiersPublicHealthPengFeng,

title = {Analysis of students' positive emotions around the green space in the university campus during the COVID-19 pandemic in China},

author = {Shaobo Liu and Yifeng Ji and Jiang Li and You Peng and Zhitao Li and Wenbo Lai and Tao Feng},

url = {https://doi.org/10.3389/fpubh.2022.888295},

doi = {doi.org/10.3389/fpubh.2022.888295},

year  = {2022},

date = {2022-08-09},

urldate = {2022-08-09},

journal = {Frontiers in Public Health},

abstract = {Green space around the university campus is of paramount importance for emotional and psychological restorations in students. Positive emotions in students can be aroused when immersed in green space and naturalness. However, to what extent can perceived naturalness influence students' positive emotion remains unclear, especially in the context of COVID-19 countermeasures. This study, therefore, attempts to investigate in-depth the nature and strength of the relationships between students' positive emotion and their perceived naturalness, place attachment, and landscape preference, which are potentially varying across universities in different social and environmental contexts and different restrictions policies regarding the COVID-19 pandemic. A course of questionnaire-based surveys was administered on two university campuses in Heilongjiang and Hunan Provinces, China, resulting in 474 effective samples. Structural equation modeling was used to explore the hypothetical conceptual framework of latent variables and the indicators. The findings indicate that the higher students' perceived naturalness results in greater positive emotion. Students' perceived naturalness in green spaces of campus has a positive effect on their place attachment and landscape preference. Moreover, the difference between mediate effects of place attachment and landscape preference were addressed, which verifies the contextual influences.},

keywords = {COVID-19, Health},

pubstate = {published},

tppubtype = {article}

}

@article{Chen2022,

title = {Examine the Prediction Error of Ride-Hailing Travel Demands with Various Ignored Sparse Demand Effects},

author = {Zhiju Chen and Kai Liu and Tao Feng},

url = {https://www.hindawi.com/journals/jat/2022/7690309/},

doi = {https://doi.org/10.1155/2022/7690309},

year  = {2022},

date = {2022-04-12},

journal = {Journal of Advanced Transportation},

volume = {2022},

abstract = {The accurate short-term travel demand predictions of ride-hailing orders can promote the optimal dispatching of vehicles in space and time, which is the crucial issue to achieve sustainable development of such dynamic demand-responsive service. The sparse demands are always ignored in the previous models, and the uncertainties in the spatiotemporal distribution of the predictions induced by setting subjective thresholds are rarely explored. This paper attempts to fill this gap and examine the spatiotemporal sparsity effect on ride-hailing travel demand prediction by using Didi Chuxing order data recorded in Chengdu, China. To obtain the spatiotemporal characteristics of the travel demand, three hexagon-based deep learning models (H-CNN-LSTM, H-CNN-GRU, and H-ConvLSTM) are compared by setting various threshold values. The results show that the H-ConvLSTM model has better prediction performance than the others due to its ability to simultaneously capture spatiotemporal features, especially in areas with a high proportion of sparse demands. We found that increasing the minimum demand threshold to delete more sparse data improves the overall prediction accuracy to a certain extent, but the spatiotemporal coverage of the data is also significantly reduced. Results of this study could guide traffic operations in providing better travel services for different regions.},

keywords = {Ride hailing, Travel demand},

pubstate = {published},

tppubtype = {article}

}

@article{40c9feae3bd0408b805b8e9538654c6e,

title = {Role of latent factors and public policies in travel decisions under COVID-19 pandemic: Findings of a hybrid choice model},

author = {Chao Chen and Tao Feng and Xiaoning Gu},

url = {https://www.sciencedirect.com/science/article/pii/S2210670721008660},

doi = {10.1016/j.scs.2021.103601},

issn = {2210-6707},

year  = {2022},

date = {2022-03-01},

urldate = {2022-03-01},

journal = {Sustainable Cities and Society},

volume = {78},

publisher = {Elsevier},

abstract = {Policy measures to control the spread of COVID-19 imposed by different countries have a devastating impact on people's travel behaviors. Differing from the normal situation where general concerns on travel time and cost determine the travel choices, the uncertainty underlying behavior change in the case of a pandemic might be largely attributed to the latent aspects, i.e., social responsibility, risk perception, attitudes, which could diminish the effects of main attributes on travel decisions. Therefore, this paper examines the effects of COVID-19 related policies on individuals' travel choices influenced by the latent aspects. A stated choice experiment was designed to collect people's responses under policy measures to various transportation modes. Results of a hybrid choice model show that COVID-19 related policies significantly affect individuals' transportation mode choice decisions during pandemic situations. The attributes, like travel time and travel cost, which significantly impact travel behavior in normal situations, become less relevant. Moreover, the travel preferences during the pandemic are significantly associated with latent factors of social responsibility, fear of infection, perceived risk, and travel anxiety. In general, public transportation is identified as an insecure alternative compared with other private modes, and people who are more socially responsible tend to travel less during the pandemic. Outcomes of this study could be of value to policymakers and public health emergencies, e.g., government authorities to utilize such knowledge in providing social support for these COVID-19 countermeasures and designing customized policies for specific population groups.},

keywords = {COVID-19 pandemic, Latent factors, Public transport},

pubstate = {published},

tppubtype = {article}

}

@article{cd8c66995497429ba47116d41341c4f0,

title = {Investigating the effectiveness of COVID-19 pandemic countermeasures on the use of public transport: A case study of The Netherlands},

author = {Chao Chen and Tao Feng and Xiaoning Gu and Baozhen Yao},

url = {https://www.sciencedirect.com/science/article/pii/S0967070X22000051},

doi = {10.1016/j.tranpol.2022.01.005},

issn = {0967-070X},

year  = {2022},

date = {2022-03-01},

urldate = {2022-03-01},

journal = {Transport Policy},

volume = {117},

pages = {98--107},

publisher = {Elsevier},

abstract = {During the COVID-19 pandemic, public transport in many cities faces dramatic reduction of passenger demand. Various countermeasures such as social distancing and in-vehicle disinfection have been implemented to reduce the potential risks concerning infection, the effectiveness in promoting the use of public transport however remains unclear. Unlike the usual situation where time and cost are the main factors affecting travel decisions, the uncertainty hiding behind the behavior change of public transport users in a pandemic might be greatly affected by the control measures and the perception of people. This paper therefore aims to examine the effects of COVID-19 related countermeasures implemented in public transport on individuals' travel decisions. We explore the extent to which do policy countermeasures influence different groups of people on the use of public transport. An error component latent class choice model was estimated using the data collected in the Netherlands. Results show that the restrictions policy lifted by the Dutch central government have significant effect on individuals' transportation mode choice decision during the pandemic. The related measures adopted by the public transport sector, by contrast, present different effects on different people. The older and highly educated people are more susceptible to enforcement measures, whereas young and single Dutch citizens are more accessible to non-compulsory measures. Moreover, compared with other private modes, public transport is generally identified as a riskier option, and the average willingness to travel descends. Findings of this study are helpful for the authorities in designing and promoting effective policies in the context of pandemics.},

keywords = {COVID-19 pandemic, Error component latent class choice model, Public transport, Taste variation, Travel behavior},

pubstate = {published},

tppubtype = {article}

}

@article{LIU2022108,

title = {A route analysis of metro-bikeshare users using smart card data},

author = {Yang Liu and Yanjie Ji and Tao Feng and Zhuangbin Shi},

url = {https://www.sciencedirect.com/science/article/pii/S2214367X21000880},

doi = {https://doi.org/10.1016/j.tbs.2021.09.006},

issn = {2214-367X},

year  = {2022},

date = {2022-01-01},

journal = {Travel Behaviour and Society},

volume = {26},

pages = {108-120},

abstract = {Few studies have analyzed individuals’ travel route characteristics in the integrated metro and bikeshare network. Taking Nanjing, China, as a case study, this paper analyzes the combined travel route of metro-bikeshare users based on three-week metro- and shared bike smart card data. The smart card data provides both boarding/borrowing and alighting/returning location and time, which makes it possible to trace each combined mode user’s actual metro routes. By assuming that the bike routes are the shortest paths between a specific OD pair from smart card records, we extract the combined metro-bikeshare travel routes of each user by using a metro route reconstruction method. The results show that over 60% of the metro-bikeshare users, most of whom are youth adults (18–35 years old), only occasionally use this mode. Further, the spatial and temporal characteristics of the combined metro-bikeshare travel routes are analyzed visually across different age groups. We find that most of the combined metro-bikeshare routes concentrated on Metro Line 2 with different cycling access/egress routes; however, the routes mostly travelled by different age groups are significantly different. Young adults are mainly distributed in suburban and exurban areas. Adults are more likely to be metro-bikeshare commuters, with travel routes usually passing through the central area of the city. Besides, the routes mostly travelled by the elderly are longer than those by other groups, and highly coincide with the routes mostly travelled by adults during the rush hours. Finally, relevant policy implementations are proposed in conjunction with metro-bikeshare users’ travel route characteristics.},

keywords = {Metro-bikeshare integration, Smart card data, Spatiotemporal patterns, Travel route},

pubstate = {published},

tppubtype = {article}

}

@article{LIU2022103215,

title = {Robust charging strategies for electric bus fleets under energy consumption uncertainty},

author = {Kai Liu and Hong Gao and Yang Wang and Tao Feng and Cheng Li},

url = {https://www.sciencedirect.com/science/article/pii/S1361920922000451},

doi = {https://doi.org/10.1016/j.trd.2022.103215},

issn = {1361-9209},

year  = {2022},

date = {2022-01-01},

journal = {Transportation Research Part D: Transport and Environment},

volume = {104},

pages = {103215},

abstract = {Charging management has a profound impact on the reliability and safety of electric bus (EB) services. However, the actual charging operation of EB fleets is a critical challenge due to uncertain energy consumption, limited charging resources and other factors. A deterministic model and a robust model with a probability-free uncertainty set are proposed and compared. The power is optimized via rational allocation of charging resources, where the uncertainty of energy consumption is addressed to achieve the dual goals of reducing charging expenses and improving system robustness. A column generation algorithm is designed to solve the optimization issue. The experimental results show that the obtained robust charging strategies can achieve up to 97.88% utilization of charging resources at low electricity prices. Moreover, the robust model can effectively prevent low electric quantity and delayed departure issues for EBs caused by the uncertainty of energy consumption.},

keywords = {Battery performance, Column generation, Damage prevention, Energy consumption uncertainty, Robust optimization},

pubstate = {published},

tppubtype = {article}

}

@article{GU2022108409,

title = {The prediction of potential risk path in railway traffic events},

author = {Shuang Gu and Keping Li and Tao Feng and Dongyang Yan and Yanyan Liu},

url = {https://www.sciencedirect.com/science/article/pii/S0951832022000813},

doi = {https://doi.org/10.1016/j.ress.2022.108409},

issn = {0951-8320},

year  = {2022},

date = {2022-01-01},

journal = {Reliability Engineering & System Safety},

volume = {222},

pages = {108409},

abstract = {In railway traffic operation, the prediction of risk path is one of the important issues because it can ensure the potential consequences are effectively mitigated and controlled to prevent the domino effect. However, it is quite difficult to mine the potential information and investigate the complex dependency in failure text data, which makes the prediction of potential risk path challenging. In this paper, we propose a new network-based risk prediction model to investigate the propagation path of potential risk and reduce the risk of cascade failures. Three kinds of information hidden in network connections are considered: local structural information, global structural information and attribute information. The model uses the keyword extraction method of text data for data preprocessing. The breadth-first search-based algorithm is improved to identify the meta-paths. The co-occurrence matrix and the association matrix are considered to play a role in the model. In order to verify the feasibility and advantages of the model, we use a dataset consisting of traffic events in Beijing subway as a case study. Results of the comparative analysis show that the proposed model not only can effectively predict the potential risk path, but also provides the best results in terms of ROC, AUC and Precision.},

keywords = {Network-based model, Potential path, Railway traffic event, Risk prediction},

pubstate = {published},

tppubtype = {article}

}

@article{10.3389/fpubh.2022.861456,

title = {Analysis of Urban Built Environment Impacts on Outdoor Physical Activities—A Case Study in China},

author = {Bo Li and Qiuhong Liu and Tong Wang and He He and You Peng and Tao Feng},

url = {https://www.frontiersin.org/article/10.3389/fpubh.2022.861456},

doi = {10.3389/fpubh.2022.861456},

issn = {2296-2565},

year  = {2022},

date = {2022-01-01},

urldate = {2022-01-01},

journal = {Frontiers in Public Health},

volume = {10},

abstract = {Outdoor physical activities can promote public health and they are largely influenced by the built environment in different urban settings. Understanding the association between outdoor physical activities and the built environment is important for promoting a high quality of life. Existing studies typically focus on one type of outdoor activity using interview-based small samples and are often lack of systematic understanding of the activities' intensity and frequency. In this study, we intend to gain deeper insight into how the built environment influences physical activities using the data extracted from individual's wearables and other open data sources for integrated analysis. Multi-linear regression with logarithm transformation is applied to perform the analysis using the data from Changsha, China. We found that built environment impacts on outdoor physical activities in Changsha are not always consistent with similar studies' results in other cities. The most effective measures to promote outdoor physical activities are the provision of good arterial and secondary road networks, community parks, among others in Changsha. The results shed light on future urban planning practices in terms of promoting public health."},

keywords = {Built environment, Health, Physical Activity},

pubstate = {published},

tppubtype = {article}

}

@article{ZHANG2022103385,

title = {Customizing the promotion strategies of integrated air-bus service based on passenger satisfaction},

author = {Jiyang Zhang and Min Yang and Junyi Ji and Tao Feng and Yalong Yuan and Enhui Chen and Lichao Wang},

url = {https://www.sciencedirect.com/science/article/pii/S1361920922002139},

doi = {https://doi.org/10.1016/j.trd.2022.103385},

issn = {1361-9209},

year  = {2022},

date = {2022-01-01},

journal = {Transportation Research Part D: Transport and Environment},

volume = {109},

pages = {103385},

abstract = {The integrated air-bus service expands the catchment area and alleviates congestion of regional airports. To gain further insights into the unexplored potential attributes of the integrated service that generate passenger satisfaction, this paper utilizes a two-stage analysis approach to identify the key promotion factors for passengers from different constituents. Based on the survey data collected in Nanjing Lukou International Airport, this paper 1) uses k-means clustering to categorize respondents into four groups. 2) Combines the gradient boosting decision tree and impact asymmetry analysis to identify the attributes that have nonlinear influences on the overall service satisfaction for each group respectively. Results suggest that the timetable of the airport bus is critical for all passenger groups. Interestingly, there are noticeable differences in passenger satisfaction with the accessibility, cost affordability, comfort, reliability, and integration of the integrated service, providing the basis for customizing service promotion strategies among different passenger groups and airports.},

keywords = {Clustering analysis, Gradient Boosting Decision Tree, Impact-asymmetry analysis, Integrated air-bus services, Passenger satisfaction, Service promotion},

pubstate = {published},

tppubtype = {article}

}

@article{YAN2022,

title = {Private owners’ propensity to engage in shared parking schemes under uncertainty: comparison of alternate hybrid expected utility-regret-rejoice choice models},

author = {Qianqian Yan and Tao Feng and Harry Timmermans},

url = {https://www.sciencedirect.com/science/article/pii/S1942786722005094},

doi = {https://doi.org/10.1080/19427867.2022.2088568},

issn = {1942-7867},

year  = {2022},

date = {2022-01-01},

journal = {Transportation Letters},

abstract = {ABSTRACT 

To develop effective strategies for the supply of shared parking and study various theoretical choice models under uncertainty, this paper investigates private parking space owners’ propensity to engage in shared parking schemes using a stated choice experiment that involves an uncertain key attribute. A hybrid expected utility-regret model incorporating rejoice is specified to explore the participation behavior. Equivalent models considering the perception of attribute differences are also estimated. Results show that socio-demographic characteristics, social influence, government’s role, media attention, platform fee, and revenues are all important factors explaining private parking owners’ propensity to engage in shared parking schemes. Besides, the model incorporating all these components, including the emotions of regret and rejoice and the perception of attribute differences, yields the best results. These findings could help promote the policy development toward increasing people’s engagement in shared parking.},

keywords = {hybrid expected utility-regret-rejoice models, owners, perception, propensity, Shared parking},

pubstate = {published},

tppubtype = {article}

}

@article{YUAN2022533,

title = {Heterogeneity in the transfer time of air-rail intermodal passengers based on ticket booking data},

author = {Yalong Yuan and Min Yang and Tao Feng and Yafeng Ma and Yifeng Ren and Xinpei Ruan},

url = {https://www.sciencedirect.com/science/article/pii/S0965856422002580},

doi = {https://doi.org/10.1016/j.tra.2022.09.022},

issn = {0965-8564},

year  = {2022},

date = {2022-01-01},

journal = {Transportation Research Part A: Policy and Practice},

volume = {165},

pages = {533-552},

abstract = {Transfer constitutes the weakest link in air-rail integrated services (ARISs). Air-rail passengers face problems such as long transfer times, complex transfer processes and poor transfer experiences, which seriously reduces ARIS competitiveness. The transfer time, as the most direct and objective measurement of transfer behavior, is important in ARIS planning, construction and operation. This paper aims to analyze the influence of transfer time on the use of ARIS using ticket booking data. The air-rail intermodal passengers are classified into three groups according to the social demographical attributes and trip characteristics using a latent class clustering model, namely passengers departing on weekdays for medium- or long-distance trips, passengers departing on weekdays for medium- or short-distance trips and passengers departing during weekends for medium- or long-distance trips. After that, a generalized ordered logistic regression (GOL) model is employed to identify the key factors influencing the transfer behavior of these three passenger groups. The results indicate that ticket-related attributes have the greatest impact on passenger transfer behavior, followed by transfer-related attributes, and operation-related attributes have the least impact. The effects of operation- and transfer-related attributes on transfer behavior among the different passenger groups are similar, but the ticket price, travel distance and travel time impose distinct effects on transfer behavior in the different passenger groups. Finally, some relevant recommendations to improve the ARIS are discussed.},

keywords = {Air-rail integrated service (ARIS), Air-rail passenger, Passenger heterogeneity, Ticket booking data, Transfer time},

pubstate = {published},

tppubtype = {article}

}

@article{doi:10.1080/23249935.2022.2138628,

title = {Attitudes, personality traits and private parking space owners’ willingness to engage in shared parking schemes: a hybrid prospect theoretic model},

author = {Qianqian Yan and Tao Feng and Harry Timmermans},

url = {https://doi.org/10.1080/23249935.2022.2138628},

doi = {10.1080/23249935.2022.2138628},

year  = {2022},

date = {2022-01-01},

journal = {Transportmetrica A: Transport Science},

volume = {0},

number = {0},

pages = {1-29},

publisher = {Taylor & Francis},

abstract = {ABSTRACTTo develop effective strategies for the supply of shared parking, the present study investigates factors influencing the willingness of private parking space owners to engage in shared parking. Apart from the attributes of shared parking options, unobserved latent variables measuring attitudes and personality traits, are assumed to play a role in the decision-making process. This study estimates a hybrid prospect theoretic model to investigate the willingness of parking space owners to share their parking space. The latent variables include personality traits and attitudes that are incorporated into a prospect theoretic choice model. Non-linear effects of the latent variables and the interaction effects between personality traits and attitudes are examined. Results indicate that non-linear effects and interactions significantly improve the overall explanatory power of the model. The research findings may help in developing shared parking policies and informing companies and governments how to promote shared parking schemes.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{LIU2022460,

title = {Understanding the route choice behaviour of metro-bikeshare users},

author = {Yang Liu and Tao Feng and Zhuangbin Shi and Mingwei He},

url = {https://www.sciencedirect.com/science/article/pii/S0965856422002890},

doi = {https://doi.org/10.1016/j.tra.2022.11.006},

issn = {0965-8564},

year  = {2022},

date = {2022-01-01},

journal = {Transportation Research Part A: Policy and Practice},

volume = {166},

pages = {460-475},

abstract = {Understanding the determinants of the route choice behaviour on a multi-modal transit network of metro and shared bike is important to improve personalized multimodal travel services. This paper attempts to analyse the route choice behaviour of metro-bikeshare users considering passengers’ socio-economic attributes and perceived congestion which is approximated by load status. An abstract integrated metro-bikeshare network (IMBN) is built with virtual nodes by aggregating shared bike stations within the walkable distance and abstract routes by aggregating optional paths for each OD pair. Using the metro- and shared bike smart- card data from Nanjing, China, the route sets of metro-bikeshare users were extracted from the IMBN. A multinomial Logit model (MNL) was then applied to investigate the determinants of route choice behaviour for two types of users, namely “return-enter” and “exit-lease”, respectively. The results show that the models with the load status attributes have a better performance than the models without these attributes. We found the sensitivity of “exit-lease” users to the train crowding is significantly greater than that of the “return-enter” users. “Return-enter” users have a higher perception of out-of-vehicle travel time (OVTT) than that of in-vehicle travel time (IVT), while the “exit-lease” users have the opposite perception. Besides, the change rate of shared bike inventory, departure time and whether he or she is a regular user also have a significant impact on route choice behaviour. The findings can help policymakers and system operators to improve the services and the efficiency of the multimodal transportation system.},

keywords = {Metro-bikeshare integration, Multinomial logit model, Route choice, Smart card data},

pubstate = {published},

tppubtype = {article}

}

@article{c8074a50b1504dc9bbb68a3a8a592d14,

title = {Improved imputation of rule sets in class association rule modeling: application to transportation mode choice},

author = {Jiajia Zhang and Tao Feng and Harry Timmermans and Zhengkui Lin},

doi = {10.1007/s11116-021-10238-9},

issn = {0049-4488},

year  = {2021},

date = {2021-11-26},

journal = {Transportation},

volume = {XX},

number = {X},

publisher = {Springer},

abstract = {Predicting transportation mode choice is a critical component of forecasting travel demand. Recently, machine learning methods have become increasingly more popular in predicting transportation mode choice. Class association rules (CARs) have been applied to transportation mode choice, but the application of the imputed rules for prediction remains a long-standing challenge. Based on CARs, this paper proposes a new rule merging approach, called CARM, to improve predictive accuracy. In the suggested approach, first, CARs are imputed from the frequent pattern tree (FP-tree) based on the frequent pattern growth (FP-growth) algorithm. Next, the rules are pruned based on the concept of pessimistic error rate. Finally, the rules are merged to form new rules without increasing predictive error. Using the 2015 Dutch National Travel Survey, the performance of suggested model is compared with the performance of CARIG that uses the information gain statistic to generate new rules, class-based association rules (CBA), decision trees (DT) and the multinomial logit (MNL) model. In addition, the proposed model is assessed using a ten-fold cross validation test. The results show that the accuracy of the proposed model is 91.1%, which outperforms CARIG, CBA, DT and the MNL model.},

note = {Funding Information: This work was supported by China Scholarship Council.},

keywords = {Class association rules, FP-tree, Rule merging, Transportation mode choice},

pubstate = {published},

tppubtype = {article}

}

@article{@ZHANG2021URBANCOMPUTATION,

title = {“What should be computed” for supporting post-pandemic recovery policy making? A life-oriented perspective},

author = {Junyi Zhang and Tao Feng and Jing Kang and Shuangjin Li and Rui Liu and Shuang Ma and Baoxin Zhai and Runsen Zhang and Hongxiang Ding and Taoxing Zhu },

url = {https://link.springer.com/content/pdf/10.1007/s43762-021-00025-8.pdf},

doi = {doi.org/10.1007/s43762-021-00025-8},

year  = {2021},

date = {2021-11-19},

urldate = {2021-11-19},

journal = {Computational Urban Science },

volume = {1},

number = {24},

pages = {1-16},

abstract = {The COVID-19 pandemic has caused various impacts on people’s lives, while changes in people’s lives have shown mixed effects on mitigating the spread of the SARS-CoV-2 virus. Understanding how to capture such two-way interactions is crucial, not only to control the pandemic but also to support post-pandemic urban recovery policies. As suggested by the life-oriented approach, the above interactions exist with respect to a variety of life domains, which form a complex behavior system. Through a review of the literature, this paper first points out inconsistent evidence about behavioral factors affecting the spread of COVID-19, and then argues that existing studies on the impacts of COVID-19 on people’s lives have ignored behavioral co-changes in multiple life domains. Furthermore, selected uncertain trends of people’s lives for the post-pandemic recovery are described. Finally, this paper concludes with a summary about “what should be computed?” in Computational Urban Science with respect to how to catch up with delays in the SDGs caused by the COVID-19 pandemic, how to address digital divides and dilemmas of e-society, how to capture behavioral co-changes during the post-pandemic recovery process, and how to better manage post-pandemic recovery policymaking processes.},

keywords = {Computation, COVID-19 pandemic},

pubstate = {published},

tppubtype = {article}

}

@article{WOS:000703846700010,

title = {Examining the spatial-temporal relationship between urban built  environment and taxi ridership: Results of a semi-parametric GWPR model},

author = {Chao Chen and Tao Feng and Chuan Ding and Bin Yu and Baozhen Yao},

url = {https://www.sciencedirect.com/science/article/pii/S0966692321002258},

doi = {10.1016/j.jtrangeo.2021.103172},

issn = {0966-6923},

year  = {2021},

date = {2021-10-01},

urldate = {2021-10-01},

journal = {JOURNAL OF TRANSPORT GEOGRAPHY},

volume = {96},

abstract = {With the advance of intelligent transportation systems (ITSs) and data 

 acquisition systems (DASs), it becomes possible in recent to explore the 

 determinants of urban taxi ridership using multi-source heterogeneous 

 data. This paper aims to use floating car data, points-of-interests 

 (POIs) data and housing-price data to assess the influence of the built 

 environment on taxi ridership. Within a scale of 0.5 km grid, critical 

 indicators related to the economic aspect, intermodal connection, and 

 land use factors were obtained using the multi-source data in Shanghai. 

 To capture the spatial and temporal heterogeneity, Semi-parametric 

 Geographically Weighted Poisson Regression (SGWPR) models are built over 

 different time dimensions. It is found that SGWPR models result in 

 higher goodness-of-fit than the generalized linear models. More 

 importantly, the results show the impacts of built environment factors 

 on taxi demand are highly heterogeneous, positive or negative in 

 different city areas, reflected in the significant temporal variations 

 of the effects. Overall, these findings suggest that the built 

 environment factors have significant impacts on urban taxi demand, and 

 the spatial context should not be ignored. Findings in this paper are 

 expected to help better understand the relationship between urban taxi 

 demand and built environment factors, improving the service level of the 

 urban taxi system, and offering valuable insights into future urban and 

 transportation planning.},

keywords = {Big data, Geography},

pubstate = {published},

tppubtype = {article}

}

@article{WOS:000690513900001,

title = {Students' Intention of Visiting Urban Green Spaces after the COVID-19  Lockdown in China},

author = {Jiayi Liu and Zhikai Peng and Xiaoxi Cai and You Peng and Jiang Li and Tao Feng},

url = {https://www.mdpi.com/1229054},

doi = {10.3390/ijerph18168601},

year  = {2021},

date = {2021-08-01},

urldate = {2021-08-01},

journal = {INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH},

volume = {18},

number = {16},

abstract = {This study addresses students' perceptions of using urban green spaces 

 (UGSs) after the easing of COVID-19 lockdown in China. We questioned 

 whether they are still mindful of the risks from the outdoor gathering, 

 or conversely, starting to learn the restoration benefits from the green 

 spaces. Online self-reported surveys were distributed to the Chinese 

 students aging from 14 to 30 who study in Hunan and Jiangsu Provinces, 

 China. We finally obtained 608 complete and valid questionnaire forms 

 from all participants. Their intentions of visiting UGSs were 

 investigated based on the extended theory of planned behavior model. 

 Structural equation modeling was employed to test the hypothesized 

 psychological model. The results have shown good estimation performance 

 on risk perception and perceived knowledge to explain the variances in 

 their attitudes, social norms, and perceived behavior control. Among 

 these three endogenous variables, the perceived behavior control owns 

 the greatest and positive influence on the behavioral intention, 

 inferring that controllability is crucial for students to make decisions 

 of visiting green spaces in a post-pandemic context.},

keywords = {COVID-19 pandemic, Green space, Student},

pubstate = {published},

tppubtype = {article}

}

@article{WOS:000682934900007,

title = {Analyzing heterogeneity in passenger satisfaction, loyalty, and  complaints with air-rail integrated services},

author = {Yalong Yuan and Min Yang and Tao Feng and Soora Rasouli and Xinpei Ruan and Xinyu Wang and Yu Li},

url = {https://www.sciencedirect.com/science/article/pii/S1361920921002480},

doi = {10.1016/j.trd.2021.102950},

issn = {1361-9209},

year  = {2021},

date = {2021-08-01},

urldate = {2021-08-01},

journal = {TRANSPORTATION RESEARCH PART D-TRANSPORT AND ENVIRONMENT},

volume = {97},

abstract = {To increase the understanding of passenger choice of air-rail integrated 

 services (ARIS), the present paper a) analyzes the profile of intermodal 

 passengers by classifying them based on their socioeconomic and travel 

 characteristics and (b) uncovers any heterogeneity in passenger 

 satisfaction with ARIS among different passenger groups. Through 

 collecting 1,345 passenger satisfaction questionnaires about ARIS, 

 surveyed in Shijiazhuang, China, we first apply latent class clustering 

 to classify passengers into three groups. Then, the key factors 

 affecting passenger satisfaction and its subsequent effect on loyalty 

 and complaints are identified using a partial least squares structural 

 equation model. Finally, path heterogeneities in different passenger 

 groups are explored using a multi-group analysis. The results show that 

 the three passenger groups attach similar importance to ticket services, 

 reliability, accessibility and comfort, while some noticeable 

 differences in perception are identified in personalized services, 

 information services, and connectivity.},

keywords = {Air-Rail, Heterogeneity},

pubstate = {published},

tppubtype = {article}

}

@article{ijgi10110758,

title = {A Data-Based Bi-Objective Approach to Explore the Accessibility of Multimodal Public Transport Networks},

author = {Wentao Yu and Huijun Sun and Tao Feng and Jianjun Wu and Ying Lv and Guangyu Xin},

url = {https://www.mdpi.com/2220-9964/10/11/758},

doi = {10.3390/ijgi10110758},

issn = {2220-9964},

year  = {2021},

date = {2021-01-01},

urldate = {2021-01-01},

journal = {ISPRS International Journal of Geo-Information},

volume = {10},

number = {11},

abstract = {One of the top concerns for travelers when choosing public transportation is whether they can reach their destination in limited time and monetary cost on the basis of ensured reliability. However, the existing literature shows no studies on how to evaluate bi-objective multimodal accessibility under travel time uncertainty. In order to fill this research gap, this paper creates a multimodal super network based on smart card data in which the transfers among taxi, bus, and subway modes are developed and applied. Next, we propose a two-stage opportunity accessibility model to calculate bi-objective multimodal accessibility under travel time uncertainty. Then we propose a multimodal reliability path finding model and a reliability boundary convergence algorithm to solve this problem. Finally, we conduct a large-scale real-world case study. It is found that the impedance heterogeneity between different modes is significant, and multimodal travel has better accessibility than a unimodal one. Although multimodal accessibility decreases as the reliability increases, the advantage of multimodal over unimodal accessibility increases with reliability, and it can be improved up to 14.61% by multimodal transfers. This model can effectively guide traffic management departments to improve traffic accessibility in terms of time and cost and advise commuters to choose living places.},

keywords = {Bilevel, Multimodal},

pubstate = {published},

tppubtype = {article}

}

@article{Peng2021,

title = {Heterogeneity in outdoor comfort assessment in urban public spaces},

author = {Y. Peng and T. Feng and H. J. P. Timmermans},

doi = {10.1016/j.scitotenv.2021.147941},

issn = {18791026},

year  = {2021},

date = {2021-01-01},

journal = {Science of the Total Environment},

volume = {790},

abstract = {The assessment of outdoor comfort can provide valuable insights into the quality of urban public spaces. Rational indices based on the heat-balance model have been extensively used for assessing thermal comfort in various outdoor environments for a long time. However, a growing body of literature is arguing the theoretical limitations of rational indices, including the lack of contextual considerations and the non-consideration of the active role of human being. Furthermore, the well-documented inconsistency in previous investigations suggests individuals' heterogeneous thermal expectations, preferences and adaptations typically depend on person-related and place-related contexts. Nevertheless, the study of heterogeneity in comfort assessment remains fragmentary. In an attempt to incorporate heterogeneity into a comprehensive conceptual framework of outdoor comfort, this study develops a latent class path model based on empirical data of 701 respondents from Eindhoven, the Netherlands. We identified two latent classes associated with different causal structures underlying the assessment of outdoor comfort. Meanwhile, the membership of latent classes is identified based on respondents' socio-demographic and behavioral covariates. The results show that, with respect to the influence on comfort assessment, the exogenous and endogenous variables are varying in effectiveness and strength between the two latent classes. Latent class 1 assesses the outdoor comfort mainly based on thermal sensation and expectations of thermal and wind conditions, whereas latent class 2 comprehensively considered both thermal and non-thermal influences, especially, the psychological acceptability and need satisfaction of outdoor activity. Our findings suggest that, in addition to the expanded framework of outdoor comfort study, understanding the heterogeneity in respondents' comfort perception is needed to comprehensively address the approaches to archive the comfortable urban public spaces in design, planning and management practices.},

keywords = {Heterogeneity, Latent class path model, Outdoor comfort, Urban public space},

pubstate = {published},

tppubtype = {article}

}

@article{Yuan2021,

title = {Analyzing heterogeneity in passenger satisfaction, loyalty, and complaints with air-rail integrated services},

author = {Y. Yuan and M. Yang and T. Feng and S. Rasouli and X. Ruan and X. Wang and Y. Li},

doi = {10.1016/j.trd.2021.102950},

issn = {13619209},

year  = {2021},

date = {2021-01-01},

journal = {Transportation Research Part D: Transport and Environment},

volume = {97},

abstract = {To increase the understanding of passenger choice of air-rail integrated services (ARIS), the present paper a) analyzes the profile of intermodal passengers by classifying them based on their socioeconomic and travel characteristics and (b) uncovers any heterogeneity in passenger satisfaction with ARIS among different passenger groups. Through collecting 1,345 passenger satisfaction questionnaires about ARIS, surveyed in Shijiazhuang, China, we first apply latent class clustering to classify passengers into three groups. Then, the key factors affecting passenger satisfaction and its subsequent effect on loyalty and complaints are identified using a partial least squares structural equation model. Finally, path heterogeneities in different passenger groups are explored using a multi-group analysis. The results show that the three passenger groups attach similar importance to ticket services, reliability, accessibility and comfort, while some noticeable differences in perception are identified in personalized services, information services, and connectivity.},

keywords = {Air-rail integrated services, Heterogeneity, Latent class clustering, Multi-group analysis, Passenger loyalty, Passenger satisfaction},

pubstate = {published},

tppubtype = {article}

}

@article{Jiang2021,

title = {Ground access behaviour of air-rail passengers: A case study of Dalian ARIS},

author = {Y. Jiang and S. Yu and W. Guan and S. Gao and T. Feng},

doi = {10.1016/j.tbs.2021.03.006},

issn = {2214367X},

year  = {2021},

date = {2021-01-01},

journal = {Travel Behaviour and Society},

volume = {24},

abstract = {Passenger ground access behaviour greatly impacts the promotion and development of air-rail integrated service (ARIS). However, little is known about people's actual choice behaviours with combined ARIS alternatives. To further understand the decision mechanisms of air-rail passengers, this paper specifically analyses the ground access behaviour of ARIS passengers and identifies key influential factors at the fostering stage when the air and rail services are not integrated. We first introduce the development of ARIS in China, including types of air-rail network synchronization, their development stages and the structure of the total ground access time. Using revealed preference panel data from ARIS passengers at Dalian Airport, a mixed multinomial logit model with unbalanced panel data was estimated while considering group characteristics and the random distribution of the total local dwelling time. It is found that passengers tend to make choices about ARIS alternatives from the perspective of ground access time and not from a perspective of high-speed scheduling. Passengers generally prefer to maintain a longer safety margin time when choosing ARIS alternatives.},

keywords = {Air-rail integrated service (ARIS), Dalian Zhoushuizi International Airport, Ground access behaviour, Unbalanced panel data mixed multinomial logit mode},

pubstate = {published},

tppubtype = {article}

}

@article{Tian2021,

title = {Using autonomous vehicles or shared cars? Results of a stated choice experiment},

author = {Z. Tian and T. Feng and H. J. P. Timmermans and B. Yao},

doi = {10.1016/j.trc.2021.103117},

issn = {0968090X},

year  = {2021},

date = {2021-01-01},

journal = {Transportation Research Part C: Emerging Technologies},

volume = {128},

abstract = {With the development of vehicle automation and sharing economy, a mix of human-driven and autonomous vehicles can be expected in the next few decades, which means the conventional vehicles, carsharing, autonomous vehicles (AV) and shared AVs will coexist, affecting the way of travel. AVs, especially combined with shared use, may contribute to reduce or solve some of the present most intractable urban problems such as traffic congestion, crashes and wasted use of urban spaces. Given the emerging trend of new mobility options, understanding the decision of people in owning a private human-driven vehicle or private AV versus using a shared AV or joining car sharing would have important indications for policy makers to reduce car ownership in general. Therefore, this paper is devoted to gain insight into individuals’ propensity for purchasing an autonomous vehicle or using shared (autonomous) cars. Based on the data collected using a stated choice experiment, we estimated a random parameter error component model to identify the possible heterogeneity between individuals in the preference and possible correlations between various mobility alternatives. Results show substantial heterogeneity exists among individuals in their preferences. People in general prefer to keep their current car or buy an AV rather than to use shared cars, and shared AVs are more favorable than the traditional car sharing. Regarding the shared AVs, people are not only concerned about the operational costs and hourly rate, but also vehicle availability and access time. Moreover, younger people are more willing to accept these new mobility options.},

keywords = {Autonomous vehicles, Car sharing, Shared autonomous vehicles, Sharing economy},

pubstate = {published},

tppubtype = {article}

}

@article{Gu2021,

title = {The effects of life course events on car ownership and sustainable mobility tools adoption decisions: Results of an error component random parameter logit model},

author = {G. Gu and T. Feng and C. Zhong and X. Cai and J. Li},

doi = {10.3390/su13126816},

issn = {20711050},

year  = {2021},

date = {2021-01-01},

journal = {Sustainability (Switzerland)},

volume = {13},

issue = {12},

abstract = {Life course events can change household travel demand dramatically. Recent studies of car ownership have examined the impacts of life course events on the purchasing, replacing, and disposing of cars. However, with the increasing diversification of mobility tools, changing the fleet size is not the only option to adapt to the change caused by life course events. People have various options with the development of sustainable mobility tools including electric car, electric bike, and car sharing. In order to determine the impacts of life course events on car ownership and the decision of mobility tool type, a stated choice experiment was conducted. The experiment also investigated how the attributes of mobility tools related to the acceptance of them. Based on existing literature, we identified the attributes of mobility tools and several life course events which are considered to be influential in car ownership decision and new types of mobility tools choice. The error component random parameter logit model was estimated. The heterogeneity across people on current car and specific mobility tools are considered. The results indicate people incline not to sell their current car when they choose an electric bike or shared car. Regarding the life course events, baby birth increases the probability to purchase an additional car, while it decreases the probability to purchase an electric bike or joining a car sharing scheme. Moreover, the estimation of error components implies that there is unobserved heterogeneity across respondents on the sustainable mobility tools choice and the decision on household’s current car.},

keywords = {Car ownership, Car sharing, Electric car, Error component model, Life course events},

pubstate = {published},

tppubtype = {article}

}

@article{nokey,

title = {Integrated weather effects on e-cycling in daily commuting: A longitudinal evaluation of weather effects on e-cycling in the Netherlands},

author = {J. Kruijf and P. Waerden and T. Feng and L. Böcker and D. Lierop and D. Ettema and M. Dijst},

doi = {10.1016/j.tra.2021.04.003},

issn = {09658564},

year  = {2021},

date = {2021-01-01},

journal = {Transportation Research Part A: Policy and Practice},

volume = {148},

abstract = {While in many regions the conventional bicycle has already been regarded as an environmentally friendly and healthy alternative to the car for daily commuting, societal and policy agendas are also increasingly promoting e-bike adoption. Adding to recent research on e-bike safety, satisfaction with travel and behavioral change, this paper reports on the impact of weather circumstances on the use of the e-bike in daily commuting in an e-cycling incentive program in the province of Noord-Brabant, the Netherlands. The impact of this incentive program was analyzed using a longitudinal design, and it combined travel patterns that were derived from individuals’ GPS data over nine months, hourly observed meteorological data, and questionnaires on intended behavior and sociodemographic characteristics. The findings suggest that the presence of snow and ice, total precipitation, and high windspeed negatively affected the choice of commuting to work by e-bike, in this decreasing order of impact. Although the overall impact of air temperature on e-cycling was positive, the likeliness to commute by e-bike decreased at higher air temperatures. E-cycling under specific weather conditions was more likely if participants’ intention to e-cycle under such weather conditions was stronger. Our study indicates that the benefits of the e-bike in daily commuting are underestimated in relation to adverse weather conditions. Respondents from households with one car only, therefore, have fewer alternatives in poor weather conditions: for these individuals, only total precipitation and the presence of relatively low air temperature impact e-cycling. In addition, reported gender and high wind speeds might have been expected to influence participation in e-cycling.},

keywords = {Behavior change, E-bike, E-cycling, GPS-data, Weather conditions},

pubstate = {published},

tppubtype = {article}

}

@article{Yuan2021b,

title = {Heterogeneity in passenger satisfaction with air-rail integration services: Results of a finite mixture partial least squares model},

author = {Y. Yuan and M. Yang and T. Feng and S. Rasouli and D. Li and X. Ruan},

doi = {10.1016/j.tra.2021.03.003},

issn = {09658564},

year  = {2021},

date = {2021-01-01},

journal = {Transportation Research Part A: Policy and Practice},

volume = {147},

abstract = {Air-rail integration services (ARIS) are a promising solution for intermodal travel, but they also offer challenges such as trip complexity and uncertainty that may negatively impact passenger satisfaction. This paper addresses the quality evaluation of ARIS with a twofold purpose, specifically, (1) to explore the causal relationships between the psychological and behavioral variables of passengers and (2) to identify different passenger groups for precise service improvements. The relationships among passenger expectations, perceived quality, perceived value, satisfaction, complaints and loyalty are hypothesized and analyzed by using a passenger satisfaction index (PSI) model based on a representative sample of 1,345 intermodal passengers at Shijiazhuang Zhengding International Airport (SJW). Next, a finite mixture partial least squares (FIMIX-PLS) technique is applied to explore the heterogeneity. The results suggest that perceived quality, perceived value and passenger expectations have a positive effect on passenger satisfaction, which, in turn, influences passenger loyalty and complaints. Moreover, three passenger segments are found, namely, “perceived value and expectation-oriented passengers”, “perceived quality-oriented passengers”, and “satisfied loyal-conscious passengers”. Interestingly, an overall similarity in the perceived quality among the three passenger segments is observed with the importance-performance map analysis (IPMA) method. Nevertheless, some noticeable differences in the psychological-behavioral relationships of the three passenger segments are identified. Finally, managerial implications are discussed.},

keywords = {Air-rail integration services (ARIS), Finite mixture partial least squares (FIMIX-PLS), Importance-performance map analysis (IPMA), Intermodal passenger, Passenger satisfaction index (PSI)},

pubstate = {published},

tppubtype = {article}

}

@article{Gu2021b,

title = {Modeling dynamics in household car ownership over life courses: a latent class competing risks model},

author = {G. Gu and T. Feng and D. Yang and H. Timmermans},

doi = {10.1007/s11116-019-10078-8},

issn = {15729435},

year  = {2021},

date = {2021-01-01},

journal = {Transportation},

volume = {48},

issue = {2},

abstract = {This study presents a latent class competing risks model to examine the influence of socio-demographics and life course events on car transaction behaviour. The types of car transaction and interval times between car transactions events are incorporated in a competing risk model. To capture unobserved behavioural heterogeneity across the population, the model classifies households into different segments. Results estimated based on retrospective survey data show significant heterogeneity exist in household car ownership decisions. The covariates are found to have different effects on car ownership decisions between different classes. Households in the class labelled “Young households without a car” are more sensitive to life course events related to household composition. Households labelled as “middle-aged and aged households with car(s)” are more sensitive to life course events related to job and house locations.},

keywords = {Car ownership, Heterogeneity, Latent class competing risks model, Life events},

pubstate = {published},

tppubtype = {article}

}

@article{Yang2021,

title = {Bikeway provision and bicycle commuting: City-level empirical findings from the US},

author = {Q. Yang and J. Cai and T. Feng and Z. Liu and H. Timmermans},

doi = {10.3390/su13063113},

issn = {20711050},

year  = {2021},

date = {2021-01-01},

journal = {Sustainability (Switzerland)},

volume = {13},

issue = {6},

abstract = {The growing worldwide awareness of the significant benefits of bicycling as an urban transport mode has aroused great interest in exploring the role that bikeways play in promoting utilitarian bicycling. However, few studies assess the contribution of citywide bikeway provision with the inclusion of all facility types and differentiation of facility utilities. This study provides new evidence by evaluating the collective effects of bikeway kilometers per square kilometer, bikeway kilometers per 10,000 population, and low-stress bikeway proportion on the bicycle-commuting share in 28 US cities between 2005 and 2017. Using linear panel regression models, we found that the expansion of citywide bikeway infrastructure positively influences the share of commute trips by bicycle. The results also indicated that the proportion of low-stress bikeways has a stronger impact on the bicycling-to-work share than bikeway kilometers per 10,000 population, while the impact of bikeway kilometers per square kilometer ranks last. These findings may aid policy makers and planners in formulating sound city-level bikeway policies favoring sustainable urban transportation scenarios.},

keywords = {Bicycling to work, City level, Collective effects, Panel analysis, Provision of bikeway infrastructure},

pubstate = {published},

tppubtype = {article}

}

@article{Li2021,

title = {Built environment and early infection of COVID-19 in urban districts: A case study of Huangzhou},

author = {B. Li and Y. Peng and H. He and M. Wang and T. Feng},

doi = {10.1016/j.scs.2020.102685},

issn = {22106707},

year  = {2021},

date = {2021-01-01},

urldate = {2021-01-01},

journal = {Sustainable Cities and Society},

volume = {66},

abstract = {Since COVID-19 spread rapidly worldwide, many countries have experienced significant growth in the number of confirmed cases and deaths. Earlier studies have examined various factors that may contribute to the contagion rate of COVID-19, such as air pollution, smoking, humidity, and temperature. As there is a lack of studies at the neighborhood-level detailing the spatial settings of built environment attributes, this study explored the variations in the size of the COVID-19 confirmed case clusters across the urban district Huangzhou in the city of Huanggang. Clusters of infectious cases in the initial outbreak of COVID-19 were identified geographically through GIS methods. The hypothetic relationships between built environment attributes and clusters of COVID-19 cases have been investigated with the structural equation model. The results show the statistically significant direct and indirect influences of commercial vitality and transportation infrastructure on the number of confirmed cases in an infectious cluster. The clues ch inducing a high risk of contagions have been evidenced and provided for the decision-making practice responding to the initial stage of possible severe epidemics, indicating that the local public health authorities should implement sufficient measures and adopt effective interventions in the areas and places with a high probability of crowded residents.},

keywords = {Built environment, Commercial prosperity, COVID-19, DBSCAN, GIS, Medical service, SEM, Transportation infrastructure},

pubstate = {published},

tppubtype = {article}

}

@article{Peng2021b,

title = {Assessing comfort in urban public spaces: A structural equation model involving environmental attitude and perception},

author = {Y. Peng and Z. Peng and T. Feng and C. Zhong and W. Wang},

doi = {10.3390/ijerph18031287},

issn = {16604601},

year  = {2021},

date = {2021-01-01},

journal = {International Journal of Environmental Research and Public Health},

volume = {18},

issue = {3},

abstract = {The research of comfort in urban public spaces has become increasingly important for improving environmental quality and encouraging people spend more time in outdoor activities. Among numerous approaches to understand comfort perception, the rational indices based on heat balance theory have prevailed to guide the research and practice in urban planning, design, and management. The limitations of a solely rational index-based approach reveal the necessity for a more comprehensive understanding of comfort by considering a wider range of influential factors from both individual and environmental perspectives during the assessing process. This study conceptualizes individuals’ comfort in urban public spaces as a latent construct, which is mea-sured by indicators regarding perceptions on multifarious meteorological variables. The conceptual framework has been introduced involving hypothetical relationships among individuals’ comfort, attitudes, and environmental perceptions in urban public spaces. A series of field work including microclimate measurements and questionnaire-based surveys were carried out in two public squares in Changsha, China. Based on the dataset derived from 372 questionnaires and related meteorological measurements, this paper examines the relationships between the physical microclimatic variables, individuals’ socio-demographical characteristics and environmental attitudes and perceptions, and outdoor comfort assessment. The estimation results of the structural equation model quantitatively verified the conceptual framework at large, as many hypothetical relationships are identified, which indicates the importance of individuals’ role and the psychological factors in modeling comfort per-ception. This approach improves the understanding of comfort assessment, contributes to improving the quality of urban environment and the practices of urban planning and management.},

keywords = {Environmental attitude, Environmental perception, Outdoor comfort, Structural equation model, Urban public space},

pubstate = {published},

tppubtype = {article}

}