Research Output

@article{Zhang2018,

title = {A review of urban energy systems at building cluster level incorporating renewable-energy-source (RES) envelope solutions},

author = {X. Zhang and M. Lovati and I. Vigna and J. Widén and M. Han and C. Gal and T. Feng},

doi = {10.1016/j.apenergy.2018.09.041},

issn = {03062619},

year  = {2018},

date = {2018-01-01},

journal = {Applied Energy},

volume = {230},

abstract = {The emergence of renewable-energy-source (RES) envelope solutions, building retrofit requirements and advanced energy technologies brought about challenges to the existing paradigm of urban energy systems. It is envisioned that the building cluster approach—that can maximize the synergies of RES harvesting, building performance, and distributed energy management—will deliver the breakthrough to these challenges. Thus, this paper aims to critically review urban energy systems at the cluster level that incorporate building integrated RES solutions. We begin with defining cluster approach and the associated boundaries. Several factors influencing energy planning at cluster scale are identified, while the most important ones are discussed in detail. The closely reviewed factors include RES envelope solutions, solar energy potential, density of buildings, energy demand, integrated cluster-scale energy systems and energy hub. The examined categories of RES envelope solutions are (i) the solar power, (ii) the solar thermal and (iii) the energy-efficient ones, out of which solar energy is the most prevalent RES. As a result, methods assessing the solar energy potentials of building envelopes are reviewed in detail. Building density and the associated energy use are also identified as key factors since they affect the type and the energy harvesting potentials of RES envelopes. Modelling techniques for building energy demand at cluster level and their coupling with complex integrated energy systems or an energy hub are reviewed in a comprehensive way. In addition, the paper discusses control and operational methods as well as related optimization algorithms for the energy hub concept. Based on the findings of the review, we put forward a matrix of recommendations for cluster-level energy system simulations aiming to maximize the direct and indirect benefits of RES envelope solutions. By reviewing key factors and modelling approaches for characterizing RES-envelope-solutions-based urban energy systems at cluster level, this paper hopes to foster the transition towards more sustainable urban energy systems.},

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@article{Wu2018,

title = {Comparative Analysis on Propagation Effects of Flight Delays: A Case Study of China Airlines},

author = {W. Wu and C. -L. Wu and T. Feng and H. Zhang and S. Qiu},

doi = {10.1155/2018/5236798},

issn = {20423195},

year  = {2018},

date = {2018-01-01},

journal = {Journal of Advanced Transportation},

volume = {2018},

abstract = {This paper aims to capture the interdependency among the sequence of flight delays due to airline operations in airports, weather, and air traffic control conditions. A copula function is used to determine the distribution of delay sequence and examine the propagation effects. Using the actual data sourced from an airline in Asia Pacific region, it is found that flight delays could propagate to downstream airports/airlines, where the strength of delays was decreased, passed on, or increased. Considering the possible effects of increased delays under air traffic control or airline factors, scenarios that adjust flight schedules with additional buffer time were created and analyzed. Results show that, by adding buffer time efficiently, flight schedules can become more reliable.},

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}

@article{Feng2018,

title = {Measurement and evaluation of transport network performance: a data driven approach},

author = {T Feng and Q Han},

doi = {10.11175/easts.12.580},

issn = {1881-1124},

year  = {2018},

date = {2018-01-01},

journal = {Journal of the Eastern Asia Society for Transportation Studies},

volume = {12},

pages = {580-597},

abstract = {This paper attempts to propose a method to measure and evaluate the network performance by identifying regions with serious mismatch problems between travel demand and transport network services. Performance measures that include temporal, spatial and travel time reliability are generated from travel information in the form of GPS data. Results show that the proposed approach produces better and more accurate results than the ones in the literature. The results of standard deviation and coefficient variation of the identified regions based on the variation of average speed, travel time, and the amount of trips yield a higher reliability for the proposed approach.},

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}

@article{Yao2018,

title = {Machine learning in automotive industry},

author = {Baozhen Yao and Tao Feng},

doi = {10.1177/1687814018805787},

issn = {1687-8140},

year  = {2018},

date = {2018-01-01},

journal = {Advances in Mechanical Engineering},

volume = {10},

issue = {10},

pages = {1-2},

publisher = {SAGE Publications Ltd},

abstract = {Not available.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Jiang2017,

title = {A gap-theoretical path model of residential satisfaction and intention to move house applied to renovated historical blocks in two Chinese cities},

author = {W. Jiang and T. Feng and H. Timmermans and H. Li},

doi = {10.1016/j.cities.2017.06.021},

issn = {02642751},

year  = {2017},

date = {2017-01-01},

journal = {Cities},

volume = {71},

abstract = {Using data from eight historical blocks in two selected Chinese cities, this article presents the results of a path model, which captures both the direct and indirect relationships between social-demographics, residential satisfaction and intention to move. Using a gap theoretical framework, results of the path analysis suggest that the intention to move house is significantly and negatively affected by residential satisfaction. In turn, residential satisfaction is significantly influenced by the gap between aspired and actual housing and environmental attributes, proportional to aspiration level. Additionally, the intention to move house and the residential gap are influenced by a set of physical and social-demographical profiles. Residents who rent a house have a lower intention to move, while people living in historical blocks that are at the early renovation stage have a higher propensity to move. Among the various social demographical variables, age is found to be the most influential one, showing that older inhabitants have a lower intention to move house than younger inhabitants.},

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}

@article{Lu2017,

title = {An integrated Markov decision process and nested logit consumer response model of air ticket pricing},

author = {J. Lu and T. Feng and H. Timmermans and Z. Yang},

doi = {10.1080/23249935.2017.1306727},

issn = {23249943},

year  = {2017},

date = {2017-01-01},

journal = {Transportmetrica A: Transport Science},

volume = {13},

issue = {6},

abstract = {The paper attempts to propose an optimal air ticket pricing model during the booking horizon by taking into account passengers' purchasing behavior of air tickets. A Markov decision process incorporating a nested logit consumer response model is established to modeling the dynamic pricing process. The proposed model is estimated and applied using the data collected in a multi-airport region with competition in China. Results indicate that, by considering air ticket purchasing behavior, air ticket price can be set dynamically and optically in response to the changes in exogenous factors which are not controlled by airlines.},

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}

@article{Jiang2017b,

title = {Evolution trends of the network structure of Spring Airlines in China: A temporal and spatial analysis},

author = {Y. Jiang and B. Yao and L. Wang and T. Feng and L. Kong},

doi = {10.1016/j.jairtraman.2016.12.009},

issn = {09696997},

year  = {2017},

date = {2017-01-01},

journal = {Journal of Air Transport Management},

volume = {60},

abstract = {Both the sustainable development of China's economy and the deregulation of the China air transport market have acted as a spur for the halting development of low-cost carriers (LCCs) in China. To analyze the development trends of LCCs' network in China, this paper took Spring Airlines, the only LCC in China as an example. First, the winter flight plans of Spring Airlines from 2005 to 2013 were collected. Secondly, the development trends of air transport network of Spring Airlines were explored with methods of mathematical statistics and social network analysis. Additionally, the development trends were analyzed from the levels of navigable cities, air routes and air transport networks. The results show that although Spring Airlines actively launched air routes between tourist cities with non-class I airports, its network has been transformed from a star structure into a complex one with multi-hubs. The development process of the Spring Airlines network can be separated into three stages. In addition, the problems and evolution trends of its network are discussed further.},

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}

@article{Feng2016,

title = {Comparison of advanced imputation algorithms for detection of transportation mode and activity episode using GPS data},

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

doi = {10.1080/03081060.2015.1127540},

issn = {10290354},

year  = {2016},

date = {2016-01-01},

journal = {Transportation Planning and Technology},

volume = {39},

issue = {2},

abstract = {Global Positioning System (GPS) technologies have been increasingly considered as an alternative to traditional travel survey methods to collect activity-travel data. Algorithms applied to extract activity-travel patterns vary from informal ad-hoc decision rules to advanced machine learning methods and have different accuracy. This paper systematically compares the relative performance of different algorithms for the detection of transportation modes and activity episodes. In particular, naive Bayesian, Bayesian network, logistic regression, multilayer perceptron, support vector machine, decision table, and C4.5 algorithms are selected and compared for the same data according to their overall error rates and hit ratios. Results show that the Bayesian network has a better performance than the other algorithms in terms of the percentage correctly identified instances and Kappa values for both the training data and test data, in the sense that the Bayesian network is relatively efficient and generalizable in the context of GPS data imputation.},

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@article{Feng2015,

title = {Detecting activity type from gps traces using spatial and temporal information},

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

url = {https://journals.open.tudelft.nl/ejtir/article/view/3103},

doi = {10.18757/ejtir.2015.15.4.3103},

issn = {15677141},

year  = {2015},

date = {2015-01-01},

urldate = {2015-01-01},

journal = {European Journal of Transport and Infrastructure Research},

volume = {15},

issue = {4},

abstract = {Detecting activity types from GPS traces has been important topic in travel surveys. Compared to inferring transport mode, existing methods are still relatively inaccurate in detecting activity types due to the simplicity of their assumptions and/or lack of background information. To reduce this gap, this paper reports the results of an endeavour to infer activity type by incorporating both spatial information and aggregated temporal information. Three machine learning algorithms, Bayesian belief network, decision tree and random forest, are used to investigate the performance of these approaches in detecting activity types. The test is based on GPS traces and prompted recall data, collected in the Rijnmond region, The Netherlands. Results show that the random forest model has the highest accuracy. The model incorporating spatial and temporal information can predict activity types with an accuracy of 96.8% for the used dataset. These findings are expected to benefit research on the use of GPS technology to collect activity-travel diary data.},

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@article{Wang2015,

title = {Research on urban road congestion pricing strategy considering carbon dioxide emissions},

author = {Y. Wang and Z. Peng and K. Wang and X. Song and B. Yao and T. Feng},

doi = {10.3390/su70810534},

issn = {20711050},

year  = {2015},

date = {2015-01-01},

journal = {Sustainability (Switzerland)},

volume = {7},

issue = {8},

abstract = {Congestion pricing strategy has been recognized as an effective countermeasure in the practical field of urban traffic congestion mitigation. In this paper, a bi-level programming model considering carbon dioxide emission is proposed to mitigate traffic congestion and reduce carbon dioxide emissions. The objective function of the upper level model is to minimize the sum of travel costs and the carbon dioxide emissions costs. The lower level is a multi-modal transportation network equilibrium model. To solve the model, the method of successive averages (MSA) and the shuffled frog leaping algorithm (SFLA) are introduced. The proposed method and algorithm are tested through the numerical example. The results show that the proposed congestion pricing strategy can mitigate traffic congestion and reduce carbon emissions effectively.},

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}

@article{Feng2015c,

title = {Enhanced imputation of GPS traces forcing full or partial consistency in activity-travel sequences : comparison of algorithms},

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

doi = {10.3141/2430-03},

issn = {0361-1981},

year  = {2015},

date = {2015-01-01},

journal = {Transportation Research Record},

volume = {2430},

pages = {20-27},

publisher = {US National Research Council},

abstract = {Imputation of activity-travel sequences from global positioning system (GPS) data is dominantly based on epoch-level characteristic and land use data. This study shows that the accuracy of GPS data imputation can be improved by enforcing consistencies in transportation mode use across the day. In particular, this paper proposes a new algorithm to reduce misclassification error in imputed activity-travel diaries. The suggested algorithm identifies a hierarchical set of tours and superimposes logically consistent transportation modes at the tour-level. Three different methods, which keep some degree of consistency while allowing different transportation modes within a tour, are examined. Method I identifies the most probable transportation mode for each trip episode separately, and then compares the modes across all segments of the tour. Method II selects the most probable mode across the whole travel episode. Method III selects the most likely main mode in the intermediate portion of a tour as the mode in all trip segments. All methods impute transportation mode based on the highest number of epochs for which the predicted probability of that mode is highest. The algorithm was examined using GPS data recently collected in the Netherlands. Results show that the new algorithm significantly improves imputation accuracy of transportation modes. The enhanced algorithm, which partly relaxes the strict assumption of consistency, yields results even closer to reality.},

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}

@article{Feng2014,

title = {Superimposing activity–travel sequence conditions on GPS data imputation},

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

doi = {10.1080/17489725.2014.977361},

issn = {17489733},

year  = {2014},

date = {2014-01-01},

journal = {Journal of Location Based Services},

volume = {8},

issue = {4},

abstract = {Applications of new technology in travel surveys have demonstrated the possibility to obtain good quality activity data than traditional survey methods. However, the quality of the imputation diary data highly depends on the predictability of data processing algorithms, which are not fully ready yet. Narrowing the gap between imputation results and true activity–travel patterns is necessary to improve the ease of data confirmation in prompted recall surveys and develop fully automatic data imputation systems. This paper proposes an algorithm to decrease the discrepancies between imputed activity–travel diary and the so-called ground truth. Based on the activity–travel pattern obtained using a Bayesian belief network model, the algorithm takes into account the consistency of the full activity–travel pattern within a day in the sense that the activity–travel sequence is represented in terms of a hierarchical set of tours, and the transportation modes within a tour are logically consistent. We explore three different approaches based on the frequency at the trip/tour level and imputation probability at the epoch level, for each transportation mode. Results obtained based on the test using GPS data in the Netherlands show that the new algorithm significantly improves the imputation accuracy of transportation modes compared with an algorithm that does superimpose these pattern constraints.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Feng2014c,

title = {Multicriteria evaluation on accessibility-based transportation equity in road network design problem},

author = {T. Feng and J. Zhang},

doi = {10.1002/atr.1202},

issn = {20423195},

year  = {2014},

date = {2014-01-01},

journal = {Journal of Advanced Transportation},

volume = {48},

issue = {6},

abstract = {This paper investigates the performance of accessibility-based equity measurements in transportation and proposes a multiobjective optimization model to simulate the trade-offs between equity maximization and cost minimization of network construction. The equity is defined as the spatial distribution of accessibilities across zone areas. Six representative indicators were formulated, including GINI coefficient, Theil index, mean log deviation, relative mean deviation, coefficient of variation, and Atkinson index, and incorporated into an equity maximization model to evaluate the performance sensitivity. A bilevel multiobjective optimization model was proposed to obtain the Pareto-optimal solutions for link capacity enhancement in a stochastic road network design problem. A numerical analysis using the Sioux Falls data was implemented. Results verified that the equity indicators are quite sensitive to the pattern of network scenarios in the sense that the level of equity varies according to the amount of overall capacity enhancement as well as the assignment of improved link segments. The suggested multiobjective model that enables representing the Pareto-optimal solutions can provide multiple options in the decision making of road network design.},

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@article{Feng2014d,

title = {Trade-offs between mobility and equity maximization under environmental capacity constraints: A case study of an integrated multi-objective model},

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

doi = {10.1016/j.trc.2014.03.012},

issn = {0968090X},

year  = {2014},

date = {2014-01-01},

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

volume = {43},

abstract = {This paper investigates the performance of a policy decision tool proposed for multi-objective decision under different policy interventions. This tool deals with the trade-off between mobility and equity maximization under environmental capacity constraints. Two system objectives, maximization of mobility and equity, are formulated in terms of the sum of total car ownership and number of trips, and the differences in accessibility between zones. Environmental capacities are based on production efficiency theory in which the frontier emission under maximum system efficiency is taken as environmental capacity. To examine the performance of the proposed model, three types of hypothetical policies (network improvement, population increase and urban sprawl) are formulated. Effects are simulated using data pertaining to Dalian City, China. Results show that the proposed model is capable of representing the trade-offs between mobility and equity based on different policy interventions. Compared with two extreme cases with the single objective of mobility maximization or equity maximization, the Pareto-optimal solutions provide more interesting practical options for decision makers. Taking the solution based on the maximum equity as an example, the policy of urban sprawl yields the most significant improvement in both emission and accessibility of the three scenarios. © 2014 Elsevier Ltd.},

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@article{Feng2014e,

title = {Superimposing activity–travel sequence conditions on GPS data imputation},

author = {Tao Feng and Harry J. p. Timmermans},

doi = {10.1080/17489725.2014.977361},

issn = {1748-9725},

year  = {2014},

date = {2014-01-01},

journal = {Journal of Location Based Services},

volume = {8},

issue = {4},

pages = {256-267},

publisher = {Taylor and Francis Ltd.},

abstract = {Applications of new technology in travel surveys have demonstrated the possibility to obtain good quality activity data than traditional survey methods. However, the quality of the imputation diary data highly depends on the predictability of data processing algorithms, which are not fully ready yet. Narrowing the gap between imputation results and true activity–travel patterns is necessary to improve the ease of data confirmation in prompted recall surveys and develop fully automatic data imputation systems. This paper proposes an algorithm to decrease the discrepancies between imputed activity–travel diary and the so-called ground truth. Based on the activity–travel pattern obtained using a Bayesian belief network model, the algorithm takes into account the consistency of the full activity–travel pattern within a day in the sense that the activity–travel sequence is represented in terms of a hierarchical set of tours, and the transportation modes within a tour are logically consistent. We explore three different approaches based on the frequency at the trip/tour level and imputation probability at the epoch level, for each transportation mode. Results obtained based on the test using GPS data in the Netherlands show that the new algorithm significantly improves the imputation accuracy of transportation modes compared with an algorithm that does superimpose these pattern constraints.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Feng2014f,

title = {Extracting activity-travel diaries from GPS data: towards integrated semi-automatic imputation},

author = {Tao Feng and Harry J. p. Timmermans},

doi = {10.1016/j.proenv.2014.11.018},

issn = {1878-0296},

year  = {2014},

date = {2014-01-01},

journal = {Procedia Environmental Sciences},

volume = {22},

pages = {178-185},

note = {12th International Conference on Design & Decision Support Systems in Architecture and Urban Planning (DDSS 2014)<br/>, DDSS 2014 ; Conference date: 25-08-2014 Through 27-08-2014},

keywords = {},

pubstate = {published},

tppubtype = {article}

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@article{Feng2013,

title = {Capturing preference heterogeneity of truck drivers' route choice behavior with context effects using a latent class model},

author = {T. Feng and T. Arentze and H. Timmermans},

doi = {10.18757/ejtir.2013.13.4.3004},

issn = {15677141},

year  = {2013},

date = {2013-01-01},

journal = {European Journal of Transport and Infrastructure Research},

volume = {13},

issue = {4},

abstract = {This paper investigates heterogeneity in truck drivers' route choice preferences. A latent class model is estimated to identify heterogeneous segments of drivers. A stated choice experiment designed for identifying route choice behavior of truck drivers provides the data for model estimation. The effects of road pricing and environmental bonus are examined considering context dependency. Results reveal that size of truck is a significant segmentation variable of preferences for route attributes. Drivers of light trucks care more about congestion than drivers of heavy trucks, and are highly sensitive to road pricing and slightly sensitive to a road bonus. Drivers of heavy trucks are more sensitive to road category and urban area than drivers of light trucks, and are insensitive to bonus and slightly sensitive to pricing.},

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@article{Feng2013b,

title = {Transportation mode recognition using GPS and accelerometer data},

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

doi = {10.1016/j.trc.2013.09.014},

issn = {0968090X},

year  = {2013},

date = {2013-01-01},

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

volume = {37},

abstract = {Potential advantages of global positioning systems (GPS) in collecting travel behavior data have been discussed in several publications and evidenced in many recent studies. Most applications depend on GPS information only. However, transportation mode detection that relies only on GPS information may be erroneous due to variance in device performance and settings, and the environment in which measurements are made. Accelerometers, being used mainly for identifying peoples' physical activities, may offer new opportunities as these devices record data independent of exterior contexts. The purpose of this paper is therefore to examine the merits of employing accelerometer data in combination with GPS data in transportation mode identification. Three approaches (GPS data only, accelerometer data only and a combination of both accelerometer and GPS data) are examined. A Bayesian Belief Network model is used to infer transportation modes and activity episodes simultaneously. Results show that the use of accelerometer data can make a substantial contribution to successful imputation of transportation mode. The accelerometer only approach outperforms the GPS only approach in terms of the predictive accuracy. The approach which combines GPS and accelerometer data yields the best performance. © 2013 Elsevier Ltd.},

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pubstate = {published},

tppubtype = {article}

}

@article{Feng2013e,

title = {Map matching of GPS data with bayesian belief networks},

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

issn = {1881-1124},

year  = {2013},

date = {2013-01-01},

journal = {Journal of the Eastern Asia Society for Transportation Studies},

volume = {10},

pages = {100-112},

abstract = {This paper proposes a map matching algorithm using Bayesian belief network for GPS traces to generate the spatial-temporal information of individuals. The algorithm incorporates the road network topology, distance from trace nodes to road segments, the angle between two lines, direction difference, accuracy of measured GPS log point, and position of roads. The GPS data collected in the Eindhoven region, The Netherlands, was used to examine the performance of this algorithm. Results based on a small sample show that the algorithm has a good performance in both processing efficiency and prediction accuracy of correctly identified instances. Even with a small sample, the overall prediction accuracy reaches 87.02%.},

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pubstate = {published},

tppubtype = {article}

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@article{Arentze2012,

title = {Context-dependent influence of road attributes and pricing policies on route choice behavior of truck drivers: Results of a conjoint choice experiment},

author = {T. Arentze and T. Feng and H. Timmermans and J. Robroeks},

doi = {10.1007/s11116-012-9391-z},

issn = {15729435},

year  = {2012},

date = {2012-01-01},

journal = {Transportation},

volume = {39},

issue = {6},

abstract = {In this paper, we report the results of a stated choice experiment, which was conducted to examine truck drivers' route choice behavior. Of particular interest are the questions (i) what is the relative importance of road accessibility considerations via-a-vis traditional factors influencing route choice behavior, (ii) what are the influences of particular personal and situational variables on the evaluation of route attributes, (iii) how sensitive are truck drivers for possible pricing policies, and (iv) is there a difference in impact if environmental concerns are framed as a bonus or as a pricing instrument. The main findings indicate that road accessibility characteristics have a substantial impact on route preferences which is of the same order of magnitude as variation in travel times. This suggests that provision of adequate travel information in itself can be an effective instrument to prevent negative externalities of good transport associated with shortest routes. Furthermore, the results indicate that truck drivers/route planners when choosing a route are relatively sensitive to road pricing schemes and rather insensitive to environmental bonuses. © 2012 The Author(s).},

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}