Research Output

@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.},

keywords = {Accessibility-based equity, Car ownership, Environmental capacity, Mobility, Policy decision making},

pubstate = {published},

tppubtype = {article}

}

@article{Feng2010b,

title = {An integrated model system and policy evaluation tool for maximizing mobility under environmental capacity constraints: A case study in Dalian City, China},

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

doi = {10.1016/j.trd.2010.03.001},

issn = {13619209},

year  = {2010},

date = {2010-01-01},

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

volume = {15},

issue = {5},

abstract = {This paper presents an integrated model system for mobility maximization based on a quantified specification of environmental capacity, and evaluates policy interaction and effectiveness by simulating a number of policy scenarios. The system is designed to specify the maximum level of car ownership and number of trips by private and public modes subject to an environmental capacity constraint defined as the frontier emission under maximum system efficiency. Four types of hypothetical policies (population change, urban sprawl, land-use pattern and network improvement) are designed and the effects of 13 policy scenarios are simulated using data of Dalian City, China. Results reveal that the integrated model system reacts sensitively to policy interventions. The urban sprawl reflected in a changing residential distribution from central to suburban areas is most instrumental from the perspective of pollution alleviation. If the goal is to simultaneously reduce emissions while accommodating mobility, two combinational policy scenarios outperform all others. © 2010 Elsevier Ltd.},

keywords = {Environmental capacity, Integrated model, Mobility maximization, Policy evaluation},

pubstate = {published},

tppubtype = {article}

}

@article{Feng2008,

title = {An integrated modeling framework for environmentally efficient car ownership and trip balance},

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

doi = {10.1016/S0386-1112(14)60212-0},

issn = {03861112},

year  = {2008},

date = {2008-01-01},

journal = {IATSS Research},

volume = {32},

issue = {2},

abstract = {Urban transport emissions generated by automobile trips are greatly responsible for atmospheric pollution in both developed and developing countries. To match the long-term target of sustainable development, it seems to be important to specify the feasible level of car ownership and travel demand from environmental considerations. This research intends to propose an integrated modeling framework for optimal construction of a comprehensive transportation system by taking into consideration environmental constraints. The modeling system is actually a combination of multiple essential models and illustrated by using a bi-level programming approach. In the upper level, the maximization of both total car ownership and total number of trips by private and public travel modes is set as the objective function and as the constraints, the total emission levels at all the zones are set to not exceed the relating environmental capacities. Maximizing the total trips by private and public travel modes allows policy makers to take into account trip balance to meet both the mobility levels required by travelers and the environmentally friendly transportation system goals. The lower level problem is a combined trip distribution and assignment model incorporating traveler's route choice behavior. A logit-type aggregate modal split model is established to connect the two level problems. In terms of the solution method for the integrated model, a genetic algorithm is applied. A case study is conducted using road network data and person-trip (PT) data collected in Dalian city, China. The analysis results showed that the amount of environmentally efficient car ownership and number of trips by different travel modes could be obtained simultaneously when considering the zonal control of environmental capacity within the framework of the proposed integrated model. The observed car ownership in zones could be increased or decreased towards the macroscopic optimization objective with zonal limit of emissions. © 2008 International Association of Traffic and Safety Sciences.},

keywords = {Bi-level programming, Car ownership, Environmental capacity, Genetic algorithm, Integrated model, Trip balance},

pubstate = {published},

tppubtype = {article}

}