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Consumer acceptance of electric vehicles (EV) is considered one of the primary barriers to their widespread adoption, and paramount to this barrier is the negative perception of the higher initial purchase prices of EVs. This paper presents a comparative analysis on the costs of ownership of EVs and similar internal combustion engine vehicles (ICEVs) under an assortment of cost scenarios focusing on the myriad of options and variables available to EV users. The study incorporates a 10-year analysis period and as such differing electricity and gasoline price forecasts are utilised. Elements of real data returned from an EV trial are used to inform the analysis. Additional factors include the allowance of incentives to EV users since most incentives have limited availability, the potential effects of battery replacement, long-term vehicle ownership costs, and the costs of electric fleet vehicles. The results show that EVs are already cost-competitive with ICEVs when considering the 10-year analysis period, but the extent to which EVs are competitive with ICEVs depends on a number of factors, and payback period analyses quantify the results. It is recommended that governments continue to provide incentives to EV consumers beyond current capacity limits, and significant funding should be designated to EV battery technology development. [ABSTRACT FROM AUTHOR]

Bike-sharing is one of the fastest growing new modes of transport in the world, with more and more schemes opening every year. This paper examines the trends in a bike-sharing scheme that has been in operation in Cork since 2014. While many studies exist on how bike-sharing schemes are changing mobility in cities across the globe, few studies have looked at the dynamics of these schemes in smaller cities. One of the motivations in looking at a small city like Cork is to determine if smaller cites derive benefits from bike-sharing schemes and can bike-sharing schemes provide a prominent role in these cities. This research found that in a small, compact city like Cork, average trip times recorded are short with regular uses displaying habitual trip patterns. This includes using the same bike stations and following similar routes on a daily or weekly basis. The findings also suggest weather has an impact upon usage, with longer trips more likely during better weather conditions. The findings of the paper provide insights to the dynamics of usage of a smaller bike-sharing scheme and results on how bike-sharing is offering citizens a new transport alternative. [ABSTRACT FROM AUTHOR]

This paper uses a stochastic simulation methodology to generate a schedule of daily travel and charging profiles for a population of electric vehicles with GPS travel data collected during an electric vehicle demonstration trial. The dependence structure between six variables is modelled using a non-parametric copula function. Then an iterative method of conditional distributions with a Bayesian inference is used to generate travel patterns that comply with the uncertainty of the inputs. At each destination a probabilistic charging model is used to translate the travel patterns of the electric vehicles (EVs) into the respective power demand of the vehicles. These synthetic datasets capture the degree of uncertainty of the travel and charging behaviour of EVs (contrary to single realisations) and are scalable to different EV populations (allowing uncertainty reduction effects in large populations). Such charging profiles would be useful to electric vehicle grid integration studies such as aggregated power demand, power systems services and charging optimisation analyses. [ABSTRACT FROM AUTHOR]

Understanding real-world driving conditions in the form of driving cycles is instrumental in the design of efficient powertrains and energy storage systems for electric vehicles. In addition, driving cycles serve as a standardised measurement procedure for the certification of a vehicle’s fuel economy and driving range. They also facilitate the evaluation of the economic and lifecycle costs of emerging vehicular technologies. However, discrepancies between existing driving cycles and real-world driving conditions exist due to a number of factors such as insufficient data, inadequate driving cycle development methodologies and methods to assess the representativeness of developed driving cycles. The novel aspect of the work presented here is the use of real-world data from electric vehicles, over a six month period, to derive a driving cycle appropriate for their assessment. A stochastic and statistical methodology is used to develop and assess the representativeness of the driving cycle against a separate set of real world electric vehicle driving data and the developed cycle performs well in that comparison. Although direct comparisons with internal combustion engine driving cycles are not that informative or relevant due to the marked differences between how they and electric vehicles operate, some discussion around how the developed electric vehicle cycle relates to them is also included. [ABSTRACT FROM AUTHOR]

Abstract: There appears to be increasing policy emphasis globally on developing innovative technologies and promoting incentives to support the take-up of alternative fuels and vehicles (AFVs) among consumers. The primary reason for this is that they potentially offer a pathway to reduce greenhouse gas (GHG) emissions and air pollution in the transport sector, without the need for contentious transport demand management measures such as road pricing or restrictive land use planning. However, despite the fact that AFVs are often seen as a panacea by policy-makers, there are a number of barriers to their widespread market penetration and diffusion. The objective of this paper is to present a framework, which can be modified and used by policy-makers to identify and qualitatively evaluate these barriers as well as potential policies that might be implemented to address these barriers. The paper concludes by assessing the strengths and weaknesses of applying this framework. [Copyright &y& Elsevier]

Abstract: The Irish government has outlined plans for 10% of the national road fleet to be powered by electricity by 2020. The objective of this paper is to evaluate the potential reduction in road traffic related emissions due to commuting in the Greater Dublin Area under different electric vehicle market penetration scenarios. The results indicate that the introduction of electric vehicles offers the potential for reductions in all road traffic related emissions. However, the time required for electric vehicles to acquire a significant share of the fleet, suggests that they will have a limited impact on climate change and urban air quality for at least the next decade. [Copyright &y& Elsevier]

The article presents the result of the study which investigates the benefits embodied in using real-time public transit stop information through a nested logit model structure. It examines the preferences of individuals who decide to access real-time public transit information. It reveals that passengers obtain greatest benefits from accessing transit stop information than the real-time information displays. Further, bus users derive the highest benefit from real-time transit stop information.

The article presents a study that examines the stress levels caused by commuting into Dublin City centre in Ireland. It also assesses the comfort and reliability of public transport services perceived by respondents. The study conducted an online survey which collected data on respondents' typical commute, commute-related stress, and socio-economic background. It was found that commute satisfaction decreases for those who traveled on crowded services and those who have long wait-times.

The article cites a study on the feeder route structure that was developed using combined genetic algorithm and specialized repair heuristic. Feeder routes were first developed by genetic algorithm and then a specialized heuristic algorithm works as a repair algorithm to satisfy the demand of all the nodes. It found that developed route structure is better in terms of load factors in buses, satisfaction of demand, and waiting time for feeder buses as compared to earlier approaches adopted.

Abstract: Free work place parking has long been considered to have a strong influence on whether or not individuals use their car for their trips to work. A survey of local authority employees was conducted to examine their potential responses to the removal of free work place parking spaces, how they would respond to parking cash-out policies and to work place parking charges, and finally their responses to specific values of cash out payments. It was found that as age increases individuals are less likely to accept any form of cash out. When individuals have one or more cars available they are more likely to opt for a cash out scheme. Females are more likely to opt for the various cash out schemes than males. The results seem to suggest that if an individual has a higher income it does not necessarily mean they will opt to keep their space. [Copyright &y& Elsevier]

Abstract: Many attempts have been made to solve bus route network design problems by splitting it in two stages, one for routing and the other for scheduling. Some researchers have made attempts to solve network design problems using non-traditional optimization techniques also, but not much has been done on modelling coordinated operations involving transfers from one mode to another. In this research, feeder routes and frequencies leading to schedule coordination of feeder buses with main transit are developed simultaneously using genetic algorithms. The coordinated schedules of feeder buses are determined for the existing given schedules of main transit. Thus the developed feeder routes and schedules are complementary to each other. As a case study the Dun Laoghaire Dublin Area Rapid Transit (DART) (heavy rail suburban service) station of Dublin in Ireland is selected. Finally the outcome of the research is a generated feeder route network for feeder buses and coordinated schedules of feeder buses for the existing schedules of DART at the selected station. The results of the proposed model indicate improved load factors on developed routes and also the overall load factor is also improved considerably as compared to the authors’ earlier model. [Copyright &y& Elsevier]

The paper reports on research using a new type of pedestrian waiting countdown timer to influence pedestrian behaviour at signalised pedestrian crossings in Dublin. The aim was to evaluate the impact of the timers on pedestrian crossing behaviour and in particular to see if it had any impact on the number of illegal crossings (during red man––do not walk signal). The timers inform the pedestrian how many seconds they have to wait until the green man appears. Two surveys were used to evaluate the impact: an attitude survey to evaluate the perception of the users and a video survey to estimate quantitatively the impacts on pedestrian behaviour but also to evaluate the awareness levels of the pedestrians towards the countdown timers. Some of the results include observance of more compliant behaviour by females and that pedestrians tend to overestimate their waiting time. Before the timers were installed 65% of pedestrians started to cross during the green man and amber phases but this rose to 76% after the timers were installed. [Copyright &y& Elsevier]

• Developed wind sector land use regression model to estimate nitrogen dioxide (NO 2) • Inclusion of varying vehicle type emission rates an improvement on existing models. • Method transferrable to land use regression models that include distance travelled. • Application of model to NO 2 mitigation strategies also demonstrated. • Removal of diesel from public service fleet achieved NO 2 reduction of 0.3–1.9 μg/m3. The transport sector has been identified as one of the main contributors to nitrogen dioxide (NO 2) pollution in Ireland. This research develops an enhanced Wind Sector Land Use Regression (WS-LUR) model to estimate NO 2 concentrations across Ireland, in areas where air pollution monitoring is not available. The model incorporates details of the vehicle fleet breakdown to weight vehicle type flows based on the emission rates of the vehicle type, differentiating routes with varying proportions of heavier emitting vehicles. In 2008, car taxation underwent a significant change from an engine size based system to a carbon dioxide (CO 2) emission rate based system resulting in a significant transition towards diesel fuelled vehicles. A mitigation strategy to remove diesel fuelled vehicles from the public service vehicle fleet was tested achieving predicted NO 2 reductions in the range of 0.3 μg/m3 to 1.9 μg/m3. The impact of COVID-19 on NO 2 concentration levels was also investigated. [ABSTRACT FROM AUTHOR]

Fear of crime and a perceived sense of being unsafe have the potential to discourage individuals from using public transport. This paper presents analysis of the results of a survey on aspects of personal safety apps and how individuals perceive them in relation to their personal safety, privacy and their preference to purchase them. It explores their willingness to download for free or purchase such an app, their impression of features that an app might include such as revealing their location, how they would rate police force monitoring if included as a feature of the app and finally how they would rate a personal safety app against other technologies used to improve perceived transport user safety. The results show that the majority of respondents would consider downloading a personal safety app. Lower levels of engagement with technology, a higher level of education, being resident in the city of Dublin (as opposed to surrounding regions) and privacy concerns tended to make females less likely to consider downloading the app. These findings were not repeated for males. The results suggest that younger respondents were more likely to be negatively impacted by the inclusion of a facility to report location in an emergency on the app, while the older age groups were more likely to be unaffected. For the location tracking feature, cluster membership, gender and resident outside Dublin were significant. Less than half of the respondents would be negatively influenced in their decision to buy the app if a cost of €1.79 were introduced. When respondents were asked about the inclusion of police monitoring as a feature of the app, the results suggested that police monitoring had a more definite effect on perceived personal safety than on privacy. [ABSTRACT FROM AUTHOR]

New technologies are constantly being researched and developed to improve the sense of security of transport users. However, security technologies could also pose their own risks with regard to transport users’ privacy through the potential for data collection and storage. Transport, in particular, allows the data collector potential access to information on the users’ habits through the location information that could be collected during an individual’s interaction with technology during their travels. Some technologies, such as personal security apps (which essentially turn a smartphone into a type of panic alarm) also allow for the linking of the security technology and social networking apps. Given this link and the extent to which personal data, including location data, can be included in an individual’s social networking account, it was decided to investigate if the use of social networks could be related to individuals’ opinions on the use of their data through new technologies, such as personal security apps. This paper presents an exploration of the possibility of grouping respondents to a transport survey ( N = 469) based on their answers to questions on their social networking (SNS) use. It was hypothesised that if distinct groups exist within the SNS data, then they could be used as a supplementary personal variable for underlying privacy concerns and levels of engagement with technology in future transport studies. This would be in addition to the socio-demographic information collected in the survey. This paper presents the initial dimension reduction of the response variables to create composite variables. That is followed by the exploratory clustering of responses using two-step cluster analysis. Finally, the paper discusses the hypothesis testing of the resultant clusters against the socio-demographic responses to ascertain if additional information is provided by the clustering results. The transport survey responses were collected in Ireland, and a subset of responses, from the Greater Dublin Area, were used for the analysis in this paper. The results demonstrate that there is scope for this type of method to be used when researching new security technologies in transport. [ABSTRACT FROM AUTHOR]

Car-sharing services offer potential to reduce dependency on private cars, and their electrification may decarbonise the transportation sector even further. This study estimates the potential emission reduction if shared cars operated by GoCar- a car-sharing service in Ireland- are electrified and assesses which trips could be completed using shared electric vehicles (EVs). Based on historical and targeted growth scenarios, appropriate forecasting methods were explored to predict GoCar's fleet size and travel distance for 2030. The corresponding emissions were estimated using COPERT. Results showed that electrifying half of the GoCar fleet by 2030 can reduce total emissions by up to 45% compared with baseline, whereas emissions were elevated by 50% compared to 2021 fleet operations. Results also suggest that the majority (70% to 90%) of GoCar day bookings can be completed using the available EVs in the Irish market, indicating the feasibility of EVs in car-sharing services. [ABSTRACT FROM AUTHOR]

• Developing a novel framework for appraising shared electric micro-mobility hubs in Dublin. • Employing DEA and negative binomial regression and using six months of real-world data. • Proposing an e-bike sharing scalability measure using returns-to-scale analysis. • Assessing eco-efficiency based on trip and user characteristics and emission offset. • High scalability suggests system's expansion and improving infrastructure can boost performance. In car-dominated urban areas, shared electric micro-mobility offers a sustainable alternative to decarbonise and reshape mobility paradigms. This paper presents a comprehensive framework for evaluating Dublin's e-bike sharing system, comprising 12 stations (eHUBs). Using six months of real-world riding data, it employs data envelopment analysis to assess the eco-efficiency of each eHUB in utilising nearby infrastructure, population in the catchment area, and location to achieve desired economic, social, and environmental outputs. Results indicate an upward trajectory for the system's eco-efficiency. The returns-to-scale analysis provides insights into the system's scalability, suggesting that expanding the e-bike sharing system, along with infrastructural enhancements, would significantly increase ridership. Analysing decarbonisation, usage patterns, and spatial factors of eHUBs reveals the substantial potential of shared e-bikes if optimally used. The research highlights the need to reevaluate car-centric policies in favour of more inclusive and environmentally sustainable alternatives and proposes actionable policy recommendations to achieve this transformation. [ABSTRACT FROM AUTHOR]

This paper examines the charge and trip making behaviour of a fleet of electric vehicle (EV) users in Ireland. Through the analysis of real data from data loggers located within the EVs, valuable information is obtained on trip event characteristics, consumer preferences, timing and consumption patterns of charge events. The findings from this trial can be used to inform infrastructure providers in other small and medium size cities and in suburban or rural settings. An understanding of the likely usage patterns of EV users is critical for the rollout of charging infrastructure. Vehicles were separated into private use and business use vehicles, and the timings of EV usage events were divided into weekday and weekend events. Along with a descriptive analysis of the results, interquartile range (IQR) and analysis of variance (ANOVA) analyses were employed to quantify and characterise EV user behaviour. An early morning peak in charging behaviour was identified, and state of charge (SOC), charge consumption, and time and distance since last charge analyses indicate EV users charge more frequently than required. Trip event patterns identify the fact that EVs are generally available to be charged overnight, reducing demand on the electrical grid during peak hours. Trip distance analyses show that EVs are typically driven short distances, confirming their suitability to urban driving environments. The results can not only account for the effects of EV integration into the Irish vehicle fleet, but it can also provide information on the likely impacts of mass integration into European energy systems. [ABSTRACT FROM AUTHOR]