2021
Gu, G.; Feng, T.; Zhong, C.; Cai, X.; Li, J.
In: Sustainability (Switzerland), vol. 13, iss. 12, 2021, ISSN: 20711050.
Abstract | Links | BibTeX | Tags: Car ownership, Car sharing, Electric car, Error component model, Life course events
@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}
}
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.
Gu, G.; Feng, T.; Yang, D.; Timmermans, H.
Modeling dynamics in household car ownership over life courses: a latent class competing risks model Journal Article
In: Transportation, vol. 48, iss. 2, 2021, ISSN: 15729435.
Abstract | Links | BibTeX | Tags: Car ownership, Heterogeneity, Latent class competing risks model, Life events
@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}
}
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.
2014
Feng, T.; Timmermans, H. J. P.
In: Transportation Research Part C: Emerging Technologies, vol. 43, 2014, ISSN: 0968090X.
Abstract | Links | BibTeX | Tags: Accessibility-based equity, Car ownership, Environmental capacity, Mobility, Policy decision making
@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}
}
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.
2008
Feng, T.; Zhang, J.; Fujiwara, A.
An integrated modeling framework for environmentally efficient car ownership and trip balance Journal Article
In: IATSS Research, vol. 32, iss. 2, 2008, ISSN: 03861112.
Abstract | Links | BibTeX | Tags: Bi-level programming, Car ownership, Environmental capacity, Genetic algorithm, Integrated model, Trip balance
@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}
}
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.
2006
Yang, Z. -Z.; Miao, G. -Q.; Feng, T.
Forecast on maximum car ownership with constraint of environmental capacity in urban Journal Article
In: Zhongguo Gonglu Xuebao/China Journal of Highway and Transport, vol. 19, iss. 6, 2006, ISSN: 10017372.
Abstract | BibTeX | Tags: Bi-level programming model, Car ownership, Sensitivity analysis, Traffic engineering, Traffic environmental capacity, Traffic volume assignment
@article{Yang2006,
title = {Forecast on maximum car ownership with constraint of environmental capacity in urban},
author = {Z. -Z. Yang and G. -Q. Miao and T. Feng},
issn = {10017372},
year = {2006},
date = {2006-01-01},
journal = {Zhongguo Gonglu Xuebao/China Journal of Highway and Transport},
volume = {19},
issue = {6},
abstract = {A model which is a bi-level optimal problem and can forecast the maximum car ownership in urban with constraint of urban environmental capacity was developed. The upper level maximizes the car ownership subjected to the environmental capacity constraint, where the objective function is the maximum of the sum of zonal car population and constraints are environmental capacities on all links. The lower level assigns the OD traffic on road network with user equilibrium method, which simulates the behaviors of traveller path selection and forecasts distribution and running characteristics of traffic demand on road network. In order to realize the feedback between the two levels and solve two optimization problem simultaneously, an algorithm based on sensitivity analysis was developed and a numerical test was used to verify the effectiveness of model and algorithm.},
keywords = {Bi-level programming model, Car ownership, Sensitivity analysis, Traffic engineering, Traffic environmental capacity, Traffic volume assignment},
pubstate = {published},
tppubtype = {article}
}
A model which is a bi-level optimal problem and can forecast the maximum car ownership in urban with constraint of urban environmental capacity was developed. The upper level maximizes the car ownership subjected to the environmental capacity constraint, where the objective function is the maximum of the sum of zonal car population and constraints are environmental capacities on all links. The lower level assigns the OD traffic on road network with user equilibrium method, which simulates the behaviors of traveller path selection and forecasts distribution and running characteristics of traffic demand on road network. In order to realize the feedback between the two levels and solve two optimization problem simultaneously, an algorithm based on sensitivity analysis was developed and a numerical test was used to verify the effectiveness of model and algorithm.