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1228 KiB

Open AccessArticle

Factors Influencing the Behavioural Intention towards Full Electric Vehicles: An Empirical Study in Macau

by Ivan K. W. Lai, Yide Liu, Xinbo Sun, Hao Zhang and Weiwei Xu

Sustainability 2015, 7(9), 12564-12585; https://doi.org/10.3390/su70912564 - 11 Sep 2015

Cited by 106 | Viewed by 17118

This study examines the factors that influence individual intentions towards the adoption of full electric vehicles. A sample including 308 respondents was collected on the streets of Macau. The collected data were analysed by confirmatory factor analysis and structural equation modelling. The results [...] Read more.

This study examines the factors that influence individual intentions towards the adoption of full electric vehicles. A sample including 308 respondents was collected on the streets of Macau. The collected data were analysed by confirmatory factor analysis and structural equation modelling. The results demonstrate that environmental concerns and the perception of environmental policy are antecedent factors of the perception of full electric vehicles, which influences the behavioural intention to purchase full electric vehicles. This study also finds that the perception of economic benefit is one of the key factors influencing the adoption of full electric vehicles. Vehicle operators seek economic benefits from future long-term fuel savings, high energy efficiency, and cheap electricity. Thus, a government striving to promote low-carbon transportation needs to scale up its efforts to enhance citizens’ environmental concerns and to establish proper environmental policy as well as to provide long-term financial and strategic support for electric vehicles. Full article

(This article belongs to the Special Issue Carbon reduction strategies and methods in transportation)

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2685 KiB

Open AccessArticle

Performance Comparison of Reservation Based and Instant Access One-Way Car Sharing Service through Discrete Event Simulation

by Ganjar Alfian, Jongtae Rhee, Yong-Shin Kang and Byungun Yoon

Sustainability 2015, 7(9), 12465-12489; https://doi.org/10.3390/su70912465 - 11 Sep 2015

Cited by 34 | Viewed by 7050

Abstract

A car sharing service has been highlighted as a new urban transport alternative for an environmentally friendly economy. As the demand for the service from customers increases, car sharing operators need to introduce a new service such as a one-way option that will [...] Read more.

A car sharing service has been highlighted as a new urban transport alternative for an environmentally friendly economy. As the demand for the service from customers increases, car sharing operators need to introduce a new service such as a one-way option that will allow customers to return the car to different stations. Due to the complexity of the one-way system, it needs to be managed and optimized for real cases. This paper focuses on developing a simulation model in order to help operators evaluate the performance of the one-way service. In addition, this research demonstrates a strategy for an open one-way service that can increase revenue and customer satisfaction. A real case dataset is used for investigation to find the best result from the simulation. The result showed that the total number of cars, number of one-way reservations and station size have an impact on one-way performance. Thus, company profit and customer satisfaction can be maximized by optimizing these factors. Full article

(This article belongs to the Special Issue Carbon reduction strategies and methods in transportation)

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946 KiB

Open AccessArticle

Evaluation Framework for Alternative Fuel Vehicles: Sustainable Development Perspective

by Dong-Shang Chang, Sheng-Hung Chen, Chia-Wei Hsu, Allen H. Hu and Gwo-Hshiung Tzeng

Sustainability 2015, 7(9), 11570-11594; https://doi.org/10.3390/su70911570 - 25 Aug 2015

Cited by 29 | Viewed by 6423

Abstract

Road transport accounts for 72.06% of total transport CO₂, which is considered a cause of climate change. At present, the use of alternative fuels has become a pressing issue and a significant number of automakers and scholars have devoted themselves to [...] Read more.

Road transport accounts for 72.06% of total transport CO₂, which is considered a cause of climate change. At present, the use of alternative fuels has become a pressing issue and a significant number of automakers and scholars have devoted themselves to the study and subsequent development of alternative fuel vehicles (AFVs). The evaluation of AFVs should consider not only air pollution reduction and fuel efficiency but also AFV sustainability. In general, the field of sustainable development is subdivided into three areas: economic, environmental, and social. On the basis of the sustainable development perspective, this study presents an evaluation framework for AFVs by using the DEMATEL-based analytical network process. The results reveal that the five most important criteria are price, added value, user acceptance, reduction of hazardous substances, and dematerialization. Price is the most important criterion because it can improve the popularity of AFVs and affect other criteria, including user acceptance. Additional, the energy usage criterion is expected to significantly affect the sustainable development of AFVs. These results should be seriously considered by automakers and governments in developing AFVs. Full article

(This article belongs to the Special Issue Carbon reduction strategies and methods in transportation)

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820 KiB

Open AccessArticle

Quantitative Decision Making Model for Carbon Reduction in Road Construction Projects Using Green Technologies

by Woosik Jang, Hyun-Woo You and Seung Heon Han

Sustainability 2015, 7(8), 11240-11259; https://doi.org/10.3390/su70811240 - 17 Aug 2015

Cited by 14 | Viewed by 6728

Abstract

Numerous countries have established policies for reducing greenhouse gas emissions and have suggested goals pertaining to these reductions. To reach the target reduction amounts, studies on the reduction of carbon emissions have been conducted with regard to all stages and processes in construction [...] Read more.

Numerous countries have established policies for reducing greenhouse gas emissions and have suggested goals pertaining to these reductions. To reach the target reduction amounts, studies on the reduction of carbon emissions have been conducted with regard to all stages and processes in construction projects. According to a study on carbon emissions, the carbon emissions generated during the construction stage of road projects account for approximately 76 to 86% of the total carbon emissions, far exceeding the other stages, such as maintenance or demolition. Therefore, this study aims to develop a quantitative decision making model that supports the application of green technologies (GTs) to reduce carbon emissions during the construction stage of road construction projects. First, the authors selected environmental soundness, economic feasibility and constructability as the key assessment indices for evaluating 20 GTs. Second, a fuzzy set/qualitative comparative analysis (FS/QCA) was used to establish an objective decision-making model for the assessment of both the quantitative and qualitative characteristics of the key indices. To support the developed model, an expert survey was performed to assess the applicability of each GT from a practical perspective, which was verified with a case study using two additional GTs. The proposed model is expected to support practitioners in the application of suitable GTs to road projects and reduce carbon emissions, resulting in better decision making during road construction projects. Full article

(This article belongs to the Special Issue Carbon reduction strategies and methods in transportation)

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1599 KiB

Open AccessArticle

Optimization of the Waterbus Operation Plan Considering Carbon Emissions: The Case of Zhoushan City

by Juying Wang, Feng Guan, Ting Li, Can Wang, Qianqian Han and Bin Yu

Sustainability 2015, 7(8), 10976-10993; https://doi.org/10.3390/su70810976 - 11 Aug 2015

Cited by 3 | Viewed by 5240

Abstract

Recently, as more people are concerned with the issues around environment protection, research about how to reduce carbon emissions has drawn increasing attention. Encouraging public transportation is an effective measure to reduce carbon emissions. However, overland public transportation does less to lower carbon [...] Read more.

Recently, as more people are concerned with the issues around environment protection, research about how to reduce carbon emissions has drawn increasing attention. Encouraging public transportation is an effective measure to reduce carbon emissions. However, overland public transportation does less to lower carbon because of the gradually increasing pressure of the urban road traffic. Therefore, the waterbus along the coast becomes a new direction of the urban public transport development. In order to optimize the operation plan of the waterbus, a bi-level model considering carbon emissions is proposed in this paper. In the upper-level model, a multiple objective model is established, which considers both the interests of the passengers and the operator while considering the carbon emissions. The lower-level model is a traffic model split by using a Nested Logit model. A NSGA-II (Non-dominated Sorting Genetic Algorithm-II) algorithm is proposed to solve the model. Finally, the city of Zhoushan is chosen as an example to prove the feasibility of the model and the algorithm. The result shows that the proposed model for waterbus operation optimization can efficiently reduce transportation carbon emissions and satisfy passenger demand at the same time. Full article

(This article belongs to the Special Issue Carbon reduction strategies and methods in transportation)

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865 KiB

Open AccessArticle

Research on Urban Road Congestion Pricing Strategy Considering Carbon Dioxide Emissions

by Yitian Wang, Zixuan Peng, Keming Wang, Xiaolin Song, Baozhen Yao and Tao Feng

Sustainability 2015, 7(8), 10534-10553; https://doi.org/10.3390/su70810534 - 6 Aug 2015

Cited by 20 | Viewed by 6017

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 [...] Read more.

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. Full article

(This article belongs to the Special Issue Carbon reduction strategies and methods in transportation)

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1541 KiB

Open AccessArticle

Dependence of Parking Pricing on Land Use and Time of Day

by Fang Zong, Yanan He and Yixin Yuan

Sustainability 2015, 7(7), 9587-9607; https://doi.org/10.3390/su7079587 - 17 Jul 2015

Cited by 16 | Viewed by 6069

Abstract

A key strategy of sustainable transportation, parking pricing can directly contribute to decreased greenhouse gas emissions and air pollution. This paper describes an optimal structure of parking rates in terms of parking locations and time of day. A two-level parking model based on [...] Read more.

A key strategy of sustainable transportation, parking pricing can directly contribute to decreased greenhouse gas emissions and air pollution. This paper describes an optimal structure of parking rates in terms of parking locations and time of day. A two-level parking model based on game theory is established using parking survey data collected in Beijing in 2014. The model was estimated based on Stackelberg game and the Nash equilibrium. Using the two-level parking model, the optimal structure of parking rates for inside/outside business zones and during peak/off-peak hours was calculated. In addition, the relationship between the government (which represents the public benefit) and car users, as well as the relationships among car users in the parking system were investigated. The results indicate that equilibrium among all of the agents in the parking system can be obtained using the proposed parking rate structure. The findings provide a better understanding of parking behavior, and the two-level parking model presented in the paper can be used to determine the optimal parking rate to balance the temporal and spatial distribution of parking demand in urban areas. This research helps reduce car use and the parking-related cruising time and thus contributes to the reduction of carbon emissions and air pollution. Full article

(This article belongs to the Special Issue Carbon reduction strategies and methods in transportation)

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191 KiB

Open AccessArticle

Integrating Regret Psychology to Travel Mode Choice for a Transit-Oriented Evacuation Strategy

by Shi An, Ze Wang and Jianxun Cui

Sustainability 2015, 7(7), 8116-8131; https://doi.org/10.3390/su7078116 - 24 Jun 2015

Cited by 12 | Viewed by 4994

Abstract

Facing the potential dangers from sudden disasters in urban cities, emergency administrators have to make an appropriate evacuation plan to mitigate negative consequences. However, little attention has been paid to evacuee real decision psychology when developing a strategy. The aim of this paper [...] Read more.

Facing the potential dangers from sudden disasters in urban cities, emergency administrators have to make an appropriate evacuation plan to mitigate negative consequences. However, little attention has been paid to evacuee real decision psychology when developing a strategy. The aim of this paper is to analyze evacuee mode choice behavior considering regret aversion psychology during evacuation. First, the utility-based and regret-based models are formulated to obtain evacuees’ preferences on travel mode choice, respectively. According to the data collected from the stated preference (SP) survey on evacuee mode choice, the estimation results show that the regret-based model performs better than the utility model. Moreover, based on the estimates from behavioral analysis, the elasticities of evacuee mode choices are calculated, and transit strategy simulation is undertaken to investigate the influence on evacuee mode switching from private automobile to public transit. The results are expected to help emergency administrators to make a transit-oriented strategy for a sustainable evacuation plan, especially for the benefit of carless people. Full article

(This article belongs to the Special Issue Carbon reduction strategies and methods in transportation)

1169 KiB

Open AccessArticle

Urban Freight Truck Routing under Stochastic Congestion and Emission Considerations

by Taesung Hwang and Yanfeng Ouyang

Sustainability 2015, 7(6), 6610-6625; https://doi.org/10.3390/su7066610 - 26 May 2015

Cited by 28 | Viewed by 7031

Abstract

Freight trucks are known to be a major source of air pollutants as well as greenhouse gas emissions in U.S. metropolitan areas, and they have significant effects on air quality and global climate change. Emissions from freight trucks during their deliveries should be [...] Read more.

Freight trucks are known to be a major source of air pollutants as well as greenhouse gas emissions in U.S. metropolitan areas, and they have significant effects on air quality and global climate change. Emissions from freight trucks during their deliveries should be considered by the trucking service sector when they make routing decisions. This study proposes a model that incorporates total delivery time, various emissions including CO₂, VOC, NO_X, and PM from freight truck activities, and a penalty for late or early arrival into the total cost objective of a stochastic shortest path problem. We focus on urban transportation networks in which random congestion states on each link follows an independent probability distribution. Our model finds the best truck routing on a given network so as to minimize the expected total cost. This problem is formulated into a mathematical model, and two solution algorithms including a dynamic programming approach and a deterministic shortest path heuristic are proposed. Numerical examples show that the proposed approach performs very well even for the large-size U.S. urban networks. Full article

(This article belongs to the Special Issue Carbon reduction strategies and methods in transportation)

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