Transport Reviews最新文献

An accurate estimation of bus dwell time (BDT) is important as it directly influences the prediction of vehicles’ arrival times at bus stops and hence, the reliability of their services. Developing an efficient method to estimate BDT has received significant attention in the literature as numerous studies have been conducted on this topic. This paper provides an overview of research works conducted in the past on bus dwell time. It covers three aspects: first methods used in the literature to estimate BDT, second factors influencing BDT and third methods used in the literature to collect data. The methods used in the literature to estimate BDT are broadly classified and discussed under three categories namely, regression-based models, probabilistic and time series models and artificial intelligence-based models along with their strengths and weaknesses. The influence of different policy measures related to characteristics of bus, passengers, time-of-day, transit, and route are discussed. The research trends reveal an increasing tendency to employ more advanced methods for data collection (using GPS, APC and AVL) and modelling (e.g. using machine learning-based methods).

Electric scooters (e-scooters) have proliferated throughout North American cities in the past five years, with about 60 million shared e-scooter trips taken in 2021. That growth has resulted in safety and injury prevention challenges, and much of the regulatory approach has been to limit e-scooter use through technological or behavioural interventions. The past few years have yielded a patchwork of regulations based on a diversity of published safety and injury studies, including work on injury burden (e.g. hospitalisation studies), direct observation, rider surveys, or traffic crash (e.g. police-reported crash) analysis. This review draws from disparate studies to develop systematic policy conclusions related primarily to rider safety behaviour and associated injury outcomes, particularly severe injuries. This work focuses on perceived safety, demographics of scooter riders, injury trends of riders, temporal and spatial correlates of shared e-scooter rider injuries and contributing factors like roadway design, impairment, and helmets. While this review focuses on studies that occurred in the United States, some findings transfer elsewhere. The sum of the literature points to the importance of enhanced and maintained infrastructure to improve rider behaviour, predictability, and perceived safety, and increases in driver and e-scooter user education and enforcement to reduce violations and impairment.

We perform a systematic review of real-time control strategies for transfer synchronisations in public transport. In particular, we review inter-station and intra-station control measures that can be applied in near real-time, including vehicle holding, stop-skipping, speed control, short-turning, rescheduling, interlining, rerouting, and boarding limits. The topic of public transfer synchronisation at the operational phase is both a technically challenging and timely topic. It is technically challenging because finding optimal control measures is a computationally intensive problem and these measures should be computed in near real-time. It is also timely because of the emerging developments in shared mobility, Mobility-as-a-Service schemes, on-demand public transport, and vehicle automation that pose new opportunities as well as challenges in designing seamless passenger transfers. In our systematic review, we analyse the modelling approaches for real-time transfer synchronisation, including mathematical programmes, heuristics, rule-based approaches, and stochastic optimisation models. We then critically discuss the available literature and provide a future outlook, outlining six research directions.

This literature review is the first to explore the predictors of the ownership, mode choice, and use of private motorcycles for utilitarian travel. Existing literature reviews on motorcycles only focused on the adverse impacts of motorcycle transport. A total of 45 articles in English published up to 2022 from quantitative and qualitative studies were reviewed to identify socioeconomic and built environment predictors of motorcycle travel which can be affected by planning or policy interventions. Motorcycle ownership level of a country is explained by average income, population density, and urbanisation level; that of a province or city by average income; and that of a household by the numbers of adults and workers, car ownership level, income as well as the population density and road density at the residential location. The choice of individuals to use a motorcycle rather than other modes is predicted by income and age as well as the advantages of time and cost savings of motorcycles over other modes. The amount of motorcycle use of households or individuals is associated with the number of household members, car ownership level, the age of the principal user, and income. Supply of public transport should focus on areas prone to widespread motorcycle ownership to both slow down the growth in motorcycle ownership and pre-empt that in car ownership as both types of motorised vehicles bring environmental and public health harms. More research is needed for further understanding of the relationships between motorcycle travel, the built environment, and public transport supply.

Road users experience mobility impacts when a train occupies a highway-rail grade (level) crossing. Research has shown that the cost of reduced mobility exceeds safety costs, yet there is little consistency in the integration of mobility-related criteria into approaches for prioritising crossings for grade separation. A synthesis of findings from a review of literature and practice demonstrated the importance of mobility impacts at blocked crossings, identified and compared mobility-related decision criteria and actionable thresholds used within prioritisation approaches to rank crossings for grade separation, and revealed methods to quantify and monetise delay at blocked crossings. The review identified the need for the joint application of traffic microsimulation and intelligent transportation systems to quantify road user delay at blocked crossings. Such work should consider network-level effects, account for the severe consequences of delay for certain road users (e.g. emergency responders), and develop methods for monetising delay impacts associated with different road users. Moreover, a knowledge gap persists in establishing the interrelationship between road user delay at blocked crossings, risky behaviour, and safety impacts. Finally, further work is required to establish and calibrate thresholds for mobility-related criteria within prioritisation approaches used to rank crossings for all types of improvements, including grade separation.

The promotion of urban mobility by integrating people-and-goods transportation has attracted increasing attention in recent years. Within this framework, diversified forms such as co-modality, freight on transit, and crowdshipping have been proposed, piloted or implemented. The success of the implementation and market penetration depends on not only the novelties of the concept but also the planning and operational efficiency. Thus, a comprehensive review focusing on the operation of integrated people-and-goods transportation systems and associated critical decisions and subproblems is performed. Different practical forms in which people and goods are transported in an integrated manner are identified. The critical decisions associated with each form and subproblem are discussed, along with corresponding models and solution approaches. Notably, because integrated transportation systems are in the early exploration stage at present, new forms are expected to emerge. Therefore, this paper proposes a general framework to realise the planning and operation of new forms in the future. The decisions and subproblems identified from existing forms are fed to the proposed general framework to identify two key research opportunities: to improve or extend existing research and to conduct pioneering research to fill the gaps in the frameworks for operating potential forms of integrated people-and-goods transportation.

Identifying and assessing the likelihood and consequences of maritime accidents has been a key focus of research within the maritime industry. However, conventional methods utilised for maritime risk assessment have been dominated by a few methodologies each of which have recognised weaknesses. Given the growing attention that supervised machine learning and big data applications for safety assessments have been receiving in other disciplines, a comprehensive review of the academic literature on this topic in the maritime domain has been conducted. The review encapsulates the prediction of accident occurrence, accident severity, ship detentions and ship collision risk. In particular, the purpose, methods, datasets and features of such studies are compared to better understand how such an approach can be applied in practice and its relative merits. Several key challenges within these themes are also identified, such as the availability and representativeness of the datasets and methodological challenges associated with transparency, model development and results evaluation. Whilst focused within the maritime domain, many of these findings are equally relevant to other transportation topics. This work, therefore, highlights both novel applications for applying these techniques to maritime safety and key challenges that warrant further research in order to strengthen this methodological approach.

The increasing uptake of electric vehicles (EVs) has raised concerns about the impact a large fleet could have on electricity markets and distribution grids alike. Charging strategies have emerged as a means to provide flexibility, especially to electricity distribution grids, by controlling the EV charging process. This paper presents a typification of charging strategies and introduces a conceptual framework for appraising their flexibility in distribution grids. This is underpinned by data collected through an aggregative systematic literature review. The framework is derived from an exploratory qualitative content analysis of the sampled data and encompasses four flexibility dimensions: time, duration, quantity, and location of charging. Structural elements of a charging strategy are also explored, complementing the framework. Finally, the paper also presents a quantitative data analysis assessing the level of flexibility provided by each charging strategy. Results show that flexibility dimensions are not equally exploited, direct control strategies do not strictly outperform other control alternatives and innovative charging structures are yet to thrive for flexibility supply to increase. These findings contribute to better-informed, evidence-based policy interventions.

It is believed that shared transport services (STSs) can reduce transport poverty and social exclusion. This paper proposes a definition of “social acceptability” and “social acceptance” and examines whether vulnerable groups accept STSs. The notions “acceptability” and “acceptance” were distinguished and four necessary conditions, especially for vulnerable groups, or the 4As were identified: “availability”, “accessibility”, “affordability”, and “attractability”. In the context of STSs, “social acceptability” is defined as the degree to which an individual intends to use a STS before experiencing it in everyday travel based on the expected availability, accessibility, affordability, and attractability of the service, while “social acceptance” also incorporates the use of a STS after experiencing it in everyday travel based on a minimum level of perceived availability, accessibility, affordability, and attractability. This paper further reviews the scientific literature in transport research regarding the “acceptability” or “acceptance” of STSs by vulnerable groups. While several studies include socio-economic and demographic variables (e.g. age, gender) to explain the “acceptability” of STSs, only a few studies specifically focus on vulnerable groups. More research on the “social acceptance” of STSs, especially shared scooters, ride-sharing, and apps and Mobility as a Service (MaaS), by vulnerable groups is needed.