Showing papers in "Transportation Research Part D-transport and Environment in 2018"

A review of consumer preferences of and interactions with electric vehicle charging infrastructure

Abstract: This paper presents a literature review of studies that investigate infrastructure needs to support the market introduction of plug-in electric vehicles (PEVs). It focuses on literature relating to consumer preferences for charging infrastructure, and how consumers interact with and use this infrastructure. This includes studies that use questionnaire surveys, interviews, modelling, GPS data from vehicles, and data from electric vehicle charging equipment. These studies indicate that the most important location for PEV charging is at home, followed by work, and then public locations. Studies have found that more effort is needed to ensure consumers have easy access to PEV charging and that charging at home, work, or public locations should not be free of cost. Research indicates that PEV charging will not impact electricity grids on the short term, however charging may need to be managed when the vehicles are deployed in greater numbers. In some areas of study the literature is not sufficiently mature to draw any conclusions from. More research is especially needed to determine how much infrastructure is needed to support the roll out of PEVs. This paper ends with policy implications and suggests avenues of future research.

Fast charging infrastructure for electric vehicles: Today’s situation and future needs

Abstract: Potential users of plug-in electric vehicles often ask for public charging facilities before buying vehicles. Furthermore, the speed of public charging is often expected to be similar to conventional refueling. For this reason, research on and political interest in public charging focus more and more on fast charging options with higher power rates, yet estimates for future needs are rare. This paper tries to fill this gap by analyzing current charging behavior from a large charging data set from Sweden and Norway and take the findings to calibrate a queuing model for future fast charging infrastructure needs. We find that the ratio of battery electric vehicles to public fast charging points can be similar to other alternative fuels in the future (close to one fast charging point per 1000 vehicles for high power rates of 150 kW). In addition, the surplus on the electricity prices for payoff is only 0.05–0.15 €/kWh per charging point. However, charging infrastructure needs highly depend on battery sizes and power rates that are both likely to increase in the future.

A military airport location selection by AHP integrated PROMETHEE and VIKOR methods

Abstract: This paper presents a location selection problem for a military airport using multiple criteria decision making methods. A real-world decision problem is presented and the decision criteria to evaluate alternative locations are specified. The objective is to identify the best location among candidate locations. Nine main criteria and thirty-three sub-criteria are identified by taking into account not only requirements for a military airport such as climate, geography, infrastructure, security, and transportation but also its environmental and social effects. The criteria weights are determined using AHP. Ranking and selection processes of four alternatives are carried out using PROMETHEE and VIKOR methods. Furthermore, the results of PROMETHEE and VIKOR methods are compared with the results of COPRAS, MAIRCA and MABAC methods. All methods suggest the same alternative as the best and produce the same results on the rankings of the location alternatives. One-way sensitivity analysis is carried out on the main criteria weights for all methods. Statistically significant correlations are observed between the rankings of the methods. Therefore, it is concluded that PROMETHEE, VIKOR, COPRAS, MAIRCA and MABAC methods can be successfully used for location selection problems and in general, for other types of multi-criteria decision problems with finite number of alternatives.

Forecasting electricity demand of electric vehicles by analyzing consumers’ charging patterns

Abstract: The spread of electric vehicles (EVs) and their increasing demand for electricity has placed a greater burden on electricity generation and the power grid. In particular, the problem of whether to expand the electricity power stations and distribution facilities due to the construction of EV charging stations is emerging as an immediate issue. To effectively meet the demand for additional electricity while ensuring the stability of the power grid, there is a need to accurately predict the charging demands for EVs. Therefore, this study estimates the changes in electricity charging demand based on consumer preferences for EVs, charging time of day, and types of electric vehicle supply equipment (EVSE) and elucidates the matters to be considered for constructing EV infrastructure. The results show that consumers mainly preferred charging during the evening. However, when we considered different types of EVSEs (public and private) in the analysis, people preferred to charge at public EVSEs during the day. During peak load time, people tended to prefer charging using fast public EVSEs, which shows that consumers considered the tradeoffs between the full charge time and the price for charging. Based on these findings, this study provides key political implications for policy makers to consider in taking preemptive measures to adjust the electricity supply infrastructure.

Impacts of replacement of engine powered vehicles by electric vehicles on energy consumption and CO 2 emissions

Abstract: This paper evaluates the impacts on energy consumption and carbon dioxide (CO2) emissions from the introduction of electric vehicles into a smart grid, as a case study. The AVL Cruise software was used to simulate two vehicles, one electric and the other engine-powered, both operating under the New European Driving Cycle (NEDC), in order to calculate carbon dioxide (CO2) emissions, fuel consumption and energy efficiency. Available carbon dioxide data from electric power generation in Brazil were used for comparison with the simulated results. In addition, scenarios of gradual introduction of electric vehicles in a taxi fleet operating with a smart grid system in Sete Lagoas city, MG, Brazil, were made to evaluate their impacts. The results demonstrate that CO2 emissions from the electric vehicle fleet can be from 10 to 26 times lower than that of the engine-powered vehicle fleet. In addition, the scenarios indicate that even with high factors of CO2 emissions from energy generation, significant reductions of annual emissions are obtained with the introduction of electric vehicles in the fleet.

A review of EVs charging: From the perspective of energy optimization, optimization approaches, and charging techniques

Abstract: Introduction of electric vehicles (EVs) or plug-in electric vehicles (PEVs) in the road transportation can significantly reduce the carbon emission. Hence, the demand of EVs is likely to increase in the near future. Large penetration of EVs will also ultimately result into high loads on the existing power grids. The controlled charging of EVs can have a significant impact on the power grid load, voltage, frequency, and power losses. In this paper, we have provided a comprehensive review of various energy optimization approaches used for EVs charging. Energy optimization approaches used for EVs not only enhance the battery life but also contribute in regulating the voltage and frequency. During EVs charging, various objective functions such as supporting the renewable energy sources, minimization of the peak load, energy cost, and maximization of the aggregator profit have also been studied from optimization perspectives. The controlled and an optimized EVs charging enhances the performance of EVs batteries and conserves the energy in the system by minimizing the load and power losses. The different EVs charging approaches such as centralized and distributed suited for different objective functions have also been studied and compared with respect to various optimization approaches.

Analyzing spatiotemporal traffic line source emissions based on massive didi online car-hailing service data

Abstract: Nowadays, the massive car-hailing data has become a popular source for analyzing traffic operation and road congestion status, which unfortunately has seldom been extended to capture detailed on-road traffic emissions. This study aims to investigate the relationship between road traffic emissions and the related built environment factors, as well as land uses. The Computer Program to Calculate Emissions from Road Transport (COPERT) model from European Environment Agency (EEA) was introduced to estimate the 24-h NOx emission pattern of road segments with the parameters extracted from Didi massive trajectory data. Then, the temporal Fuzzy C-Means (FCM) Clustering was used to classify road segments based on the 24-h emission rates, while Geographical Detector and MORAN’s I were introduced to verify the impact of built environment on line source emissions and the similarity of emissions generated from the nearby road segments. As a result, the spatial autoregressive moving average (SARMA) regression model was incorporated to assess the impact of selected built environment factors on the road segment emission rate based on the probabilistic results from FCM. It was found that short road length, being close to city center, high density of bus stations, more ramps nearby and high proportion of residential or commercial land would substantially increase the emission rate. Finally, the 24-h atmospheric NO2 concentrations were obtained from the environmental monitor stations, to calculate the time variational trend by comparing with the line source traffic emissions, which to some extent explains the contribution of on-road traffic to the overall atmospheric pollution. Result of this study could guide urban planning, so as to avoid transportation related built environment attributes which may contribute to serious atmospheric environment pollutions.

Identifying the unique challenges of installing cold ironing at small and medium ports – The case of aberdeen

Abstract: Emissions from shipping contribute significantly to both climate change and local air pollution. Cold ironing (onshore power supply) reduces emissions while ships are berthed in port by providing power from shore-side electricity rather than onboard auxiliary generators. Previous research has focused on installing the technology in large ports but if policy goals (particularly in the EU) are to be achieved then smaller ports must also install the technology. Therefore, this study examines the feasibility of installing cold ironing in a medium sized port with several small berths, based on the case of Aberdeen. Vessel call data were analysed to calculate energy demand and a cold ironing system was designed, including separate OPS units for numerous small berths. The total capital cost was £6.6 m (€7.4 m) and the system could save annual emissions of 108 tonnes of NOx, 2.7 tonnes of PM and 4,767 tonnes of CO2 emissions worth £1.3 m (€1.4 m). Payback scenarios were examined via SCBA, based on the external costs of potential emission savings. In the best case scenario, the substantial external cost benefits would return the system capital and operating costs in only 7.0 years, or 3.5 years if subsidised 50% by the EU. Challenges result from several small berths needing individual OPS units, long cables and cable reel storage, as well as the need for several vessels to install the onboard technology, which must be overcome if ports besides the large cruise and container ports are to install cold ironing.

Measuring the car ownership impact of free-floating car-sharing: A case study in Basel, Switzerland

Abstract: Free-floating car-sharing schemes operate without fixed car-sharing stations, ahead reservations or return-trip requirements. Providing fast and convenient motorization, they attract both public transport users and (former) car-owners. Thus, their impact on individual travel behavior depends on the user type. Estimating the travel behavior impact of these systems therefore requires quantitative data. Using a two-wave survey approach (shortly after launch of the scheme plus one year later) including travel diaries, this research indicates that (due to their membership) 6% of the free-floating car-sharing customers reduce their private vehicle ownership. Moreover, the results suggest that free-floating car-sharing both complements and competes with station-based car-sharing.

Analysing the take up of Battery Electric Vehicles: An investigation of barriers amongst drivers in the UK

Abstract: The stream of announcements in 2017, effectively banning the production and sales of internal combustion engine vehicles within the next fifteen-twenty years, indicate how governments are seeking to regulate a mass market transition to electric vehicles. Yet despite significant policy initiatives to stimulate their uptake, EV market share remains far short of the level required to push them into the mainstream. This paper identifies a multitude of potential barriers to uptake and investigates these from the largely ignored perspective of mass market drivers of ICE vehicles in a European context. In addition it assesses the extent to which barriers are inter-related, and can be reduced down to larger explanatory ‘factors’. Findings, drawn from an original survey of 26,000 motorists suggest that resistance to EV adoption is characterised by twelve barriers that can be reduced and conceptualised as ‘economic uncertainty’ and ‘socio-technical’ factors. In turn, economic uncertainty was found to be significantly associated with age and geography, whilst socio-technical issues are related to gender. Problems of EV adoption are shown to be complex and multi-faceted, not easily solved by tackling individual issues, but requiring a more holistic ecosystem approach, the key policy components of which are posited in this paper. Such analysis is significant in enriching academic discourse and informing effective strategy and policy that will facilitate the transition to EVs.

Walk score® and its potential contribution to the study of active transport and walkability: A critical and systematic review

Abstract: The Walk Score® index has become increasingly applied in studies of walking and walkability. The index assesses the “walking potential” of a place through a combination of three elements: the shortest distance to a group of preselected destinations, the block length, and the intersection density around the origin. The Index links a gravity-based measure (distance accessibility), with topological accessibility (street connectivity) measured by two complementary indicators that act as penalties in the final score (linearly expanded in the range 0–100). A systematic review of Scopus® and Web of Science® was conducted with 42 journal articles eventually being evaluated. Research was primarily undertaken in North American urban geographies. Analysis of walkability using Walk Score® is inconsistent. Twenty-nine papers do not exclusively relying on Walk Score® as a single measurement of walkability and add further estimates to better capture the multiple dimensions of walkability. In 33 studies the Walk Score® was used as an independent variable, and only once as a mediating-moderating variable. In eight papers (18%) the Walk Score® was a part of a bivariate correlation model. On no occasion was it used as a dependent variable. Results tend to only partly support the validity of Walk Score®. The paper concludes that the Index is best understood as a surrogate measure of the density of the built environment of a specific neighborhood that indicates utilitarian walking potential. Implications for, and potential areas of, future research are discussed.

Promoting public bike-sharing: A lesson from the unsuccessful Pronto system

Abstract: In 2014, Seattle implemented its own bike-sharing system, Pronto. However, the system ultimately ceased operation three years later on March 17th, 2017. To learn from this failure, this paper seeks to understand factors that encourage, or discourage, bike-sharing trip generation and attraction at the station level. This paper investigates the effects of land use, roadway design, elevation, bus trips, weather, and temporal factors on three-hour long bike pickups and returns at each docking station. To address temporal autocorrelations and the nonlinear seasonality, the paper implements a generalized additive mixed model (GAMM) that incorporates the joint effects of a time metric and time-varying variables. The paper estimates models on total counts of pickups and returns, as well as pickups categorized by user types and by location. The results clarify that effects of hilly terrain and the rainy weather, two commonly perceived contributors to the failure. Additionally, results suggest that users in the University District, presumably mostly university students, tend to use shared bikes in neighborhoods with a higher household density and a higher percentage of residential land use, and make bike-sharing trips regardless workdays or non-workdays. The paper also contributes to the discussion on the relationship between public transportation service and bike-sharing. In general, users tend to use bike-sharing more at stations that have more scheduled bus trips nearby. However, some bike-sharing users may shift to bus services during peak hours and rainy weather. Several strategies are proposed accordingly to increase bike ridership in the future.

A global review of the hinterland dimension of green port strategies

Abstract: Despite a growing literature on strategies to reduce emissions and other externalities in shipping and ports, very little attention has been given to the port’s role in reducing negative externalities in its hinterland. This paper addresses this gap by reviewing ports across the globe to identify which ports have implemented measures to improve the environmental performance of hinterland transport. Results show that only 76 out of 365 ports examined are doing so. The measures applied are identified, related to different goals and their challenges discussed. The most common measures are found to be technology improvements, infrastructure development and monitoring programmes, and the most advanced ports in green hinterland strategies are Rotterdam, Los Angeles/Long Beach and Hamburg, although many ports that are world leaders in green port strategies have not implemented measures in the hinterland dimension. Different port groups are segmented according to their mix of goals and measures as a foundation for future research.

Selection of sustainable urban transportation alternatives using an integrated intuitionistic fuzzy Choquet integral approach

Abstract: Unrestrained urban development and rapid expansion of motorized vehicles inevitably lead to unsustainable transportation systems from economic, social and environmental points of view, not only endangering public health but also pressuring ecosystems. Trying to address these issues, transportation policy makers face major challenges in their attempts to identify sustainable transportation alternatives. To provide a systematic approach for such endeavors, this paper evaluates different public bus technologies as urban transportation alternatives. In order to incorporate expert opinion into the model environment, a set of sustainability related criteria is established and expert opinion regarding the sustainability of vehicle options are obtained based on each criterion. Since the fulfillment of a single criterion is not sufficient to deduct meaningful conclusions, the evaluation considered the dependencies among the decision criteria in search of compromising solutions. To address this, an aggregation method based on Intuitionistic Fuzzy Choquet Integral (IFCI) and Group Decision Making (GDM) techniques is proposed. A fuzzy pairwise-comparison measure identification method is used in IFCI in order to define its parameters. TOPSIS (Technique for Order Preference by Similarity to Ideal Solution), another multi-criteria method that ignores interactions, and 2-additive Choquet integral are also employed. The outcomes of IFCI, 2-additive Choquet integral and TOPSIS are compared with one another. The findings indicate that dependencies among decision criteria significantly affect the selection process of the most sustainable urban transportation system and can alter the rankings.

Life cycle environmental impacts and carbon emissions: A case study of electric and gasoline vehicles in China

Abstract: Under the pressure of the global demand for environmental protection, the Chinese government has placed significant importance to the development and application of electric vehicles (EVs). However, the energy-saving and emission-reduction features of EVs remain the subject of debate. The current study conducted a life cycle assessment (LCA) on the power system of a gasoline vehicle (GV) and two EVs powered by lithium–iron ferrous phosphate (LFP) battery and nickel cobalt manganese (NCM) lithium battery based on Chinese practical production data. Results show that EVs have larger abiotic depletion potential (ADP) and environmental impact comprehensive value than GVs during the life cycle. The comprehensive environmental load of the LFP power system is 376% higher than that of the GV power system, and the comprehensive environmental load of the NCM power system remains 119% higher than that of the GV power system. The amounts of CO2, PM2.5–10, PM2.5, SO2 and CO emissions from EVs are significantly lower than those from GVs with respect to Chinese energy-saving policies and actual emission-reduction techniques. In addition, sensitivity analysis results indicate that the optimisation of electric power structures can reduce GWP, CO and CO2 by 15%, 37% and 14%, respectively. Additionally, the increase in battery energy density by 100 Wh/kg can reduce the emissions of air pollutants by 14–20%. Lastly, this study puts forward the following suggestions: optimise domestic energy structures, increase the proportion of clean energy, prioritise the promotion of the EVs in South China and increase battery energy density.

Anxiety vs reality – Sufficiency of battery electric vehicle range in Switzerland and Finland

Abstract: Limitations of battery capacity in battery electric vehicles (BEVs) contribute to what is known as range anxiety, and therefore poses an obstacle to their mass-market adoption. While high-range BEVs have been recently introduced, it is not clear whether they will be able to cover all possible trips without long recharging detours, and what the infrastructure needs of those vehicles are. To understand the impact of range limitations in Switzerland and Finland, we constructed a simulation model that is based on representative national travel surveys. We use it to calculate the potential of BEVs to cover any trips and investigate options to increase this coverage. The options discussed in this paper are ways to facilitate easy recharging, such as infrastructure development policies. We complement our results with insights from three focus groups. The results suggest that 85–90% of all national trips could have already been covered with BEVs prevalent in 2016. If the charging station infrastructure is developed appropriately and high-range BEVs are adopted, it is possible to reach a potential coverage of 99% or more in both countries. Deploying charging stations at users’ homes and in residential areas does contribute significantly to this improvement and is desirable from a car user’s perspective. Providing fast-charging stations in other locations is necessary to maximise the potential. We recommend to focus policy efforts on the development of residential charging options and to increase the visibility of electro-mobility using fast-charging stations.

How open are Canadian households to electric vehicles? A national latent class choice analysis with willingness-to-pay and metropolitan characterization

Abstract: This paper reports on results developed from a 2015 national survey of Canadian consumers that sought to assess attitudes and preferences towards consumer electric vehicles. A latent class discrete choice model was developed based on stated preferences choices. Four classes emerged with each being oriented to one of the primary vehicle technologies considered. The dominant characteristics of the Internal Combustion Engine (ICE)-oriented class are purchase price sensitivity, EV scepticism and an apparent resistance to change; for the Hybrid Electric Vehicle (HEV)-oriented class it is reluctance to plug-in and an unusual combination of high environmental concern and an acceptance to burn gasoline; for the suburban-oriented Plug-in Hybrid Electric Vehicle (PHEV)-oriented class it is measured optimism about plugging-in combined with an orientation to a replacement vehicle for the next purchase; and for the younger and most urban Battery Electric Vehicle (BEV)-oriented class it is the highest optimism about electric vehicles and a focus on positive aspects such as rapid acceleration and minimized maintenance costs. By orientation of household mindset, approximately 40% are ICE, 30% are PHEV, 20% are HEV and 10% are BEV. These results suggest considerable openness to electric vehicles. Willingness-to-pay for vehicle and charging attributes and incentives were calculated and are highly useful in interpreting the latent classes. The results feature interesting geographical variation which is captured at the level of Canadian metropolitan areas.

Evolving urban spatial structure and commuting patterns: A case study of Beijing, China

Abstract: This research investigates how evolving urban spatial structure explains commuting patterns in Beijing, China. To describe the dynamic and multi-dimensional urban spatial evolution, we identify emerging-, persisting-, and non-center areas between 2000 and 2008 in Beijing’s three subregions—the inner city, inner-ring suburbs, and outer-ring suburbs. Based on individual-level commuting data from the 2010 Beijing Household Travel Survey, we estimate workers’ commute distance and time using multi-level regression models with interaction terms that capture the spatial evolution. Results reveal commuting differences among persisting-, emerging-, and non-center areas, and, more importantly, varying differences across the subregions: in the inner city, persisting and emerging center areas induce similarly longer commutes than non-center areas. In the inner-ring suburbs, commutes to emerging centers are shorter than those to persisting centers. In the outer-ring suburbs, emerging center areas incur the longest commutes, while persisting center areas the shortest. The results reflect varying economic and urban functions in different subregions of Beijing and caution us that promoting polycentric urban development may increase commutes and relevant negative externalities in Chinese cities.

Analysis of telecommuting behavior and impacts on travel demand and the environment

Abstract: The discussion of whether, and to what extent, telecommuting can curb congestion in urban areas has spanned more than three decades. This study develops an integrated framework to provide the empirical evidence of the potential impacts of home-based telecommuting on travel behavior, network congestion, and air quality. In the first step, we estimate a telecommuting adoption model using a zero-inflated hierarchical ordered probit model to determine the factors associated with workers’ propensity to adopt telecommuting. Second, we implement the estimated model in the POLARIS activity-based framework to simulate the potential changes in workers’ activity-travel patterns and network congestion. Third, the MOVES mobile source emission simulator and Autonomie vehicle energy simulator are used to estimate the potential changes in vehicular emissions and fuel use in the network as a result of this policy. Different policy adoption scenarios are then tested in the proposed integrated platform. We found that compared to the current baseline situation where almost 12% of workers in Chicago region have flexible working time schedule, in the case when 50% of workers have flexible working time, telecommuting can reduce total daily vehicle miles traveled (VMT) and vehicle hours traveled (VHT) up to 0.69% and 2.09%, respectively. Considering the same comparison settings, this policy has the potential to reduce greenhouse gas and particulate matter emissions by up to 0.71% and 1.14%, respectively. In summary, our results endorse the fact that telecommuting policy has the potential to reduce network congestion and vehicular emissions specifically during rush hours.

Consumer preferences for electric vehicles in lower tier cities of China: Evidences from south Jiangsu region

Abstract: China is the world biggest market of electric vehicles (EVs) in terms of production and sales. Existing studies on consumer preferences for EVs in China have generally focused on first-tier cities, while little attention has been paid to the lower tier cities. This exploratory study investigates consumer preferences for EVs in lower tier cities of China, by collecting stated preference (SP) data in two second-tier cities and three third-tier cities in the south Jiangsu region of China. The discrete choice modeling analysis shows that Chinese consumers in lower-tier cities are generally sensitive to monetary attributes, charging service and driving range of EVs. They also perceive Chinese vehicle brands to be disadvantaged compared with European brands. When comparing the differences in second-tier versus third-tier cities, we find that consumers in third-tier cities are more sensitive to purchase price, subsidy of purchase, and coverage of charging stations than their second-tier counterparts. This study also highlights the role of different psychological effects, such as symbols of car ownership, normative-face influence, and risk aversion, in shaping consumer preferences for EVs in lower-tier cities of China. Our results provide important implications for contextualizing government policies and marketing strategies in line with the different sizes and characteristics of the cities in China.

Built environment and public bike usage for metro access: A comparison of neighborhoods in Beijing, Taipei, and Tokyo

Abstract: This article presents a transnational comparison study to clarify the difference in the associations of built environment with public bike usage in three cities in eastern Asia. This study sampled passengers entering or leaving metro stations in seven neighborhoods in Beijing, Taipei, and Tokyo for home-based work trips. Their mode choices of connecting travels between trip origins/destinations and metro stations were analyzed using logit and latent class models . Empirical evidence reveals that the associations of built environments with public bike usage of the study cities rarely accord with one other. Results are unable to support that empirical knowledge on the association of built environment with public bike usage is transferable among transnational cities despite their geographical and cultural proximity. Collecting local empirical knowledge on travel behavior is critical for developing bike-friendly built environments for a city.

Policy effects on charging behaviour of electric vehicle owners and on purchase intentions of prospective owners: Natural and stated choice experiments

Abstract: Policy makers are looking for effective ways to promote the adoption of electric vehicles (EVs). Among the options is the roll-out and management of charging infrastructure to meet the EV drivers’ refuelling needs. However, policies in this area do not only have a long-term effect on the adoption of EVs among prospective owners, they also have short-term impacts on the usage of public charging infrastructure among current EV owners and vice versa. Presently, studies focusing on both effects simultaneously are lacking, missing out on possible cross-pollination between these areas. This study uniquely combines stated and revealed preference data to estimate the effect of particular policy measures aimed at EV adoption, on the one hand, and charging behaviour, on the other. Using a large dataset (1.7 million charging sessions) related to charging behaviour using public charging infrastructure in the Netherlands we quantify the effects of (i) daytime-parking (to manage parking pressure) and (ii) free parking (to promote purchase of EVs) policies on charging behaviour. To estimate the effects of these particular policies on EV purchase intentions, a stated choice experiment was conducted among potential EV-buyers. Results show that cross-pollinations between EV charging and adaptation policies exist and should be taken into account when designing policies for EV adoption.

A bibliometric analysis on trends and characters of carbon emissions from transport sector

Abstract: Transport sector’s substantial contribution to global greenhouse gas emissions has made it a growing area of study and concern. In order to identify trends and characteristics of carbon emissions research in the transportation sector we conducted a Bibexcel and complex network analysis for the period 1997–2016. In addition, we identify critical themes and contributions of research articles using h-index, PageRank and cluster analysis. We report contribution of countries, authors, institutions and journals, as well as performance of citations and keywords. Co-citing situations between different countries, authors, and institutions are also analyzed using network analysis. Between 1997 and 2016 we found a rise in publications on carbon emissions in the transportation sector and increased cooperation between countries, authors, and institutions. Authors from the USA, China and United Kingdom published the most articles and articles with the highest academic influence. Tsinghua University from China is the leading institution in carbon emissions research in the transportation sector. The most widely published author and cited author is Dr. He. We conclude our analysis by analyzing keywords and trends to suggest critical topic areas of future research. The systematic approach undertaken in this study can be extended and applied to other research topics and fields.

Accounting for traffic speed dynamics when calculating COPERT and PHEM pollutant emissions at the urban scale

Abstract: Coupling a traffic microsimulation with an emission model is a means of assessing fuel consumptions and pollutant emissions at the urban scale. Dealing with congested states requires the efficient capture of traffic dynamics and their conditioning for the emission model. Two emission models are investigated here: COPERT IV and PHEM v11. Emission calculations were performed at road segments over 6 min periods for an area of Paris covering 3 km 2 . The resulting network fuel consumption (FC) and nitrogen oxide (NOx) emissions are then compared. This article investigates: (i) the sensitivity of COPERT to the mean speed definition, and (ii) how COPERT emission functions can be adapted to cope with vehicle dynamics related to congestion. In addition, emissions are evaluated using detailed traffic output (vehicle trajectories) paired with the instantaneous emission model, PHEM. COPERT emissions are very sensitive to mean speed definition. Using a degraded speed definition leads to an underestimation ranging from −13% to −25% for fuel consumption during congested periods (from −17% to −36% respectively for NOx emissions). Including speed distribution with COPERT leads to higher emissions, especially under congested conditions (+13% for FC and +16% for NOx). Finally, both these implementations are compared to the instantaneous modeling chain results. Performance indicators are introduced to quantify the sensitivity of the coupling to traffic dynamics. Using speed distributions, performance indicators are more or less doubled compared to traditional implementation, but remain lower than when relying on trajectories paired with the PHEM emission model.

Vehicle route planning in e-waste mobile collection on demand supported by artificial intelligence algorithms

Abstract: Mobile collection of e-waste on demand is one of the methods that can contribute to an increase in the collection rate of waste. In this method, a person requests the waste pick up from a household at a preferred time. To support such a collection method an efficient algorithm and information system for convenient waste disposal for residents has to be applied. Our study investigates using artificial intelligence algorithms for solving the vehicle routing problem with time windows for a heterogeneous fleet of waste collection vehicles. We present an algorithm and a productive model of the online system enabling comprehensive communication for people that request waste equipment for collection, registering of data and solving the VRPTW. The system includes parametric models of four algorithms (simulated annealing, tabu search, greedy, bee colony optimization). The result of the optimization is the assignment of a minimal number of collection vehicles, a vehicle routing plan, timely collection of waste from a household and collection cost reduction. The study includes the simulation of e-waste collection requests in Tokyo, Philadelphia and Warsaw to compare algorithms for various urban arrangements of streets and buildings. The results show that the best of the four algorithms, to facilitate e-waste mobile collection on demand, is simulated annealing and the worst is tabu search. The proposed model and algorithm can bring significant improvement in planning the routes of the vehicles in the e-waste collection, including a positive social impact on the new method of waste collection, especially in urban areas.

Impact of public electric vehicle charging infrastructure

Abstract: This work uses market analysis and simulation to explore the potential of public charging infrastructure to spur US battery electric vehicle (BEV) sales, increase national electrified mileage, and lower greenhouse gas (GHG) emissions. By employing both scenario and parametric analysis for policy driven injection of public charging stations we find the following: (1) For large deployments of public chargers, DC fast chargers are more effective than level 2 chargers at increasing BEV sales, increasing electrified mileage, and lowering GHG emissions, even if only one DC fast charging station can be built for every ten level 2 charging stations. (2) A national initiative to build DC fast charging infrastructure will see diminishing returns on investment at approximately 30,000 stations. (3) Some infrastructure deployment costs can be defrayed by passing them back to electric vehicle consumers, but once those costs to the consumer reach the equivalent of approximately 12 ¢ /kWh for all miles driven, almost all gains to BEV sales and GHG emissions reductions from infrastructure construction are lost.

All plug-in electric vehicles are not the same: Predictors of preference for a plug-in hybrid versus a battery-electric vehicle

Abstract: This study analyzes data from a survey of drivers (n = 1080) administered in late 2013 to assess factors that influence potential car buyers to consider two different types of plug-in electric vehicles (PEVs) in the United States: plug-in hybrid electric vehicles (PHEVs) and battery electric vehicles (BEVs). The results indicate distinct profiles of respondents preferring PHEVs, which have a gasoline backup engine, versus battery BEVs, which rely solely on a battery for power. Respondents interested in selecting a PHEV consider it more for its economic benefits, such as reduced gasoline and maintenance expenditures. Respondents preferring a BEV are drawn to its environmental and technological appeal. The absence of range anxiety for PHEV is a major factor influencing potential PEV buyers.

Assessing the sustainability of mobile depots: The case of urban freight distribution in Rio de Janeiro

Abstract: To encourage the provision and use of more sustainable means of transportation, cities and companies are implementing a variety of measures, such as strengthening the use of public transportation infrastructure and services to alleviate traffic congestion and to democratize the urban space. In these cases, literature shows that the combined use of smaller vehicles and mobile depots is a practice to be explored more deeply. This paper focuses on the use of motorized cargo tricycles alongside conventional trucks in a mobile-depot-based procedure to accommodate the restrictions imposed on conventional freight vehicle access in densely populated areas. Therefore, a new method is proposed to identify the impact on service level, emissions footprint and delivery cost of this distribution strategy. Moreover, we assess the environmental benefits of this new distribution strategy by estimating the reduction in various pollutant emissions attributable to the adoption of smaller, more agile last-mile delivery vehicles. The analyses have shown that greenhouse gas emissions and local air quality pollutants can be significantly cut by the use of cargo tricycles and mobile depots in the last mile delivery. With respect to cost, we can show that the mobile-depot-based delivery setup yields slight cost advantages over the traditional setups for neighborhoods that are characterized by low average delivery drop sizes.

Promoting carsharing attractiveness and efficiency: An exploratory analysis

Abstract: Carsharing has grown significantly over recent years. Understanding factors related to the usage and turnover rate of shared cars will help promote the growth of carsharing programs. This study sets station-based shared car booking requests and turnover rates as learning objectives, by which generalized additive mixed models are employed to examine various effects. The results are: (1) stations with more parking spaces, longer business hours and fewer nearby stations are likely to receive more booking requests and have a higher turnover rate; (2) an area with a higher population density, a higher percentage of adults, a higher percentage of males, a greater road density, or more mixed land use is associated with more car usage and a higher turnover rate; (3) stations nearby transit hubs, colleges, and shopping centers attract more shared car users; (4) shared cars are often oversupplied at transit hubs; (5) both transit proximity and housing price present high degrees of nonlinearity in relation to shared car usage and turnover rates. Findings provide evidence for optimizing the usage and efficiency of carsharing programs: carsharing companies should identify underserved areas to initiate new businesses; carsharing seems more competitive in a distance to a bus stop between 1.2 km and 2.4 km, and carsharing is more effectively served in areas with constraints in accessing metro services; carsharing should be optimally discouraged at transit hubs to avoid the oversupply of shared cars; local authorities should develop a location-based and geographically differentiated quota in managing carsharing programs.

Eco-driving advisory strategies for a platoon of mixed gasoline and electric vehicles in a connected vehicle system

Abstract: As electric vehicles (EVs) have gained an increasing market penetration rate, the traffic on urban roads will tend to be a mix of traditional gasoline vehicles (GVs) and EVs. These two types of vehicles have different energy consumption characteristics, especially the high energy efficiency and energy recuperation system of EVs. When GVs and EVs form a platoon that is recognized as an energy-friendly traffic pattern, it is critical to holistically consider the energy consumption characteristics of all vehicles to maximize the energy efficiency benefit of platooning. To tackle this issue, this paper develops an optimal control model as a foundation to provide eco-driving suggestions to the mixed-traffic platoon. The proposed model leverages the promising connected vehicle technology assuming that the speed advisory system can obtain the information on the characteristics of all platoon vehicles. To enhance the model applicability, the study proposes two eco-driving advisory strategies based on the developed optimal control model. One strategy provides the lead vehicle an acceleration profile, while the other provides a set of targeted cruising speeds. The acceleration-based eco-driving advisory strategy is suitable for platoons with an automated leader, and the speed-based advisory strategy is more friendly for platoons with a human-operated leader. Results of numerical experiments demonstrate the significance when the eco-driving advisory system holistically considers energy consumption characteristics of platoon vehicles.