Covid-19 pandemic and the unprecedented mobilisation of scholarly efforts prompted by a health crisis: Scientometric comparisons across SARS, MERS and 2019-nCov literature

During the current century, each major coronavirus outbreak has triggered a quick surge of academic publications on this topic. The spike in research publications following the 2019 Novel Coronavirus (Covid-19), however, has been like no other. The global crisis caused by the Covid-19 pandemic has mobilised scientific efforts in an unprecedented way. In less than five months, more than 12,000 research items have been indexed while the number increasing every day. With the crisis affecting all aspects of life, research on Covid-19 seems to have become a focal point of interest across many academic disciplines. Here, scientometric aspects of the Covid-19 literature are analysed and contrasted with those of the two previous major Coronavirus diseases, i.e. SARS and MERS. The focus is on the co-occurrence of key-terms, bibliographic coupling and citation relations of journals and collaborations between countries. Certain recurring patterns across all three literatures were discovered. All three outbreaks have commonly generated three distinct and major cohort of studies: (i) studies linked to the public health response and epidemic control, (ii) studies associated with the chemical constitution of the virus and (iii) studies related to treatment, vaccine and clinical care. While studies affiliated with the category (i) seem to have been the first to emerge, they overall received least numbers of citations compared to those of the two other categories. Covid-19 studies seem to have been distributed across a broader variety of journals and subject areas. Clear links are observed between the geographical origins of each outbreak or the local geographical severity of each outbreak and the magnitude of research originated from regions. Covid-19 studies also display the involvement of authors from a broader variety of countries compared to SARS and MRS

What Type of Road Pricing Scheme might appeal to Politicians? Viewpoints on the Challenge in gaining the citizen and public servant vote by staging reform

The greatest hurdle facing road pricing reform is political commitment. With rare exception, efforts to introduce significant reform in road pricing, aimed at raising sufficient revenue to ensure that road investment and ongoing maintenance is secured, without an additional impost to users above current outlays, while at the same time reducing traffic congestion, has fallen largely on politically non-supportive ears. The big challenge is to convince politicians (and their advisers) that it is possible to reform road pricing so that users are made better off (at least the great majority) in terms of time spent travelling and monies outlaid, and that government secures growing levels of revenue, but with at least some funds being used to improve public transport and the existing road network. This paper identifies the major issues that make much of the academic research into road pricing somewhat limited in terms of achieving real change. Staging reform is an appealing way forward, but ensuring the order and timing of events to secure progress is the big challenge. We offer some suggestions, including some ideas on new language designed to increase the level of buy in, and recognise that progress through action will require compromises in respect of an ‘ideal’ economically efficient pricing reform agenda.Australian Research Council Discovery Program Gran

What type of road pricing scheme might appeal to politicians? Gaining the citizen vote by staging reform

The greatest hurdle facing road pricing reform is political commitment. With rare exception, efforts to introduce significant reform in road pricing aimed at raising sufficient revenue to ensure that road investment and ongoing maintenance is secured without an additional impost to users above current outlays, while at the same time reducing traffic congestion, has fallen largely on politically non-supportive ears. The big challenge is to convince politicians (and their advisers) that it is possible to reform road pricing so that users are made better off (at least the great majority) in terms of time spent travelling and monies outlaid, and government coffers secure growing levels of revenue, but with at least some funds being used in supporting vertical equity to improve public transport and the existing road network. This paper identifies the major issues that make much of the academic research into road pricing somewhat pointless in terms of achieving real change. Staging reform is an appealing way forward, but ensuring the order and timing of events to secure progress is the big challenge. We offer some suggestions, including some ideas on new language designed to increase the level of buy in, and recognise that progress through action will require compromises in respect of an ‘ideal’ economically efficient pricing reform agenda

Steady-state link travel time methods: formulation, derivation, and classification

Travel times are one of the most important outputs of transport planning models and this is unlikely to change in the future. It is therefore paramount that the methods that underpin the construction of travel times are well understood. However, while there exist many different travel time formulations to date, their relation to each other is not well researched, especially in the context of the three main types of macroscopic modelling paradigms: dynamic, semi-dynamic, and static traffic assignment. In this work, we provide consistent and general link travel time formulations across these three modelling paradigms, assuming steady state flow rates and by directly deriving them from a recent state-of-the-art continuous time macroscopic dynamic network loading model. We do so from two different perspectives; an experienced perspective, which actively tracks the tail of a physical queue, and a functional perspective, which does not. Based on the existing literature and our generalised link travel time formulations, a classification framework is proposed allowing one to compare existing (and future) methods in the literature in an objective fashion. We provide a number of explicit derivations of existing model formulations that can be considered special cases of our unified approach. In addition a number of representative existing methods in the literature has been classified based on the above mentioned framework for the reader’s convenience

Constructing Efficient Choice Experiments

Research on the construction of efficient designs for stated choice (SC) experiments has been limited to either unlabeled experiments with generic parameter estimates or labeled experiments with alternative specific parameter estimates. Designs combining both generic and alternative specific parameters have not yet been addressed. In this paper, by deriving the asymptotic (co)variance matrix for the most general MNL model, the authors are able to demonstrate how efficient experiments that allow for the estimation of both types of estimates may be generated. The authors go onto show how estimation of the asymptotic (co)variance matrix may also be used to determine sample size requirements for SC experiments

Continuous-time general link transmission model with simplified fanning, Part I: Theory and link model formulation

The kinematic wave theory is widely used to simulate traffic flows on road segments. Link transmission models are methods to find a solution to the kinematic wave model, however, their computational efficiency heavily relies on the shape of the fundamental diagram that is used as input. Despite the limitations and drawbacks of triangular and piecewise linear fundamental diagrams, they remain popular because they result in highly efficient algorithms. Using smooth nonlinear branches is often preferred in terms of realism and other desirable properties, but this comes at a significantly higher computational cost and requires time discretisation to find an approximate solution. In this paper we consider a nonlinear fundamental diagram as input and propose on-the-fly multi-step linearization techniques to simplify expansion fans. This leads to two simplified link transmission models that can be solved exactly in continuous time under the assumption of piecewise stationary travel demand. One of the models simplifies to shockwave theory in case of a single step. We show that embedding shockwave theory in the link transmission model allows for finding an exact solution in continuous time and we discuss the potential for the design of efficient event-based algorithms for general networks

Generalized Multivariate Extreme Value Models for Explicit Route Choice Sets

This paper analyses a class of route choice models with closed-form probability expressions, namely, Generalized Multivariate Extreme Value (GMEV) models. A large group of these models emerge from different utility formulas that combine systematic utility and random error terms. Twelve models are captured in a single discrete choice framework. The additive utility formula leads to the known logit family, being multinomial, path-size, paired combinatorial and link-nested. For the multiplicative formulation only the multinomial and path-size weibit models have been identified; this study also identifies the paired combinatorial and link-nested variations, and generalizes the path-size variant. Furthermore, a new traveller's decision rule based on the multiplicative utility formula with a reference route is presented. Here the traveller chooses exclusively based on the differences between routes. This leads to four new GMEV models. We assess the models qualitatively based on a generic structure of route utility with random foreseen travel times, for which we empirically identify that the variance of utility should be different from thus far assumed for multinomial probit and logit-kernel models. The expected travellers' behaviour and model-behaviour under simple network changes are analysed. Furthermore, all models are estimated and validated on an illustrative network example with long distance and short distance origin-destination pairs. The new multiplicative models based on differences outperform the additive models in both tests

Approximation of Bayesian Efficiency in Experimental Choice Designs

This paper compares different types of simulated draws over a range of number of draws in generating Bayesian efficient designs for stated choice studies. The paper examines how closely pseudo Monte Carlo, quasi Monte Carlo and polynomial cubature methods are able to replicate the true levels of Bayesian efficiency for SC designs of various dimensions. The authors conclude that the predominantly employed method of using pseudo Monte Carlo draws is unlikely to result in leading to truly Bayesian efficient SC designs. The quasi Monte Carlo methods analyzed here (Halton, Sobol, and Modified Latin Hypercube Sampling) all clearly outperform the pseudo Monte Carlo draws. However, the polynomial cubature method examined in this paper, incremental Gaussian quadrature, outperforms all, and is therefore the recommended approximation method for the calculation of Bayesian efficiency of stated choice designs

Cooperate or not? Exploring drivers’ interactions and response times to a lane-changing request in a connected environment

Lane-changing is one of the complex driving tasks that depends on the number of vehicles, objectives, and lanes. A driver often needs to respond to a lane-changing request of a lane-changer, which is a function of their personality traits and the current driving conditions. A connected environment is expected to assist during the lane-changing decision-making process by increasing situational awareness of surrounding traffic through vehicle-to-vehicle communication and vehicle-to-infrastructure communication. Although lane changing decision making process in a traditional environment (an environment without driving aids) has been frequently investigated, our understanding of drivers’ interactions during the lane-changing decision- making process in a connected environment remains elusive due to the novelty of the connected environment and the scarcity of relevant data. As such, this study examines drivers’ responses to lane-changing requests in a connected environment using the CARRS-Q Advanced Driving Simulator. Seventy-eight participants responded to the lane-changing request of a lane- changer under two randomised driving conditions: baseline (traditional environment without driving aids) and connected environment (with driving aids). A segmentation-based approach is employed to extract drivers’ responses to the lane- changing request and subsequently estimate their response time from trajectory data. Additionally, drivers’ response times are modelled using a random parameter accelerated failure time (AFT) hazard-based duration model. Results reveal that drivers tend to be more cooperative in response to a lane-changing request in the connected environment compared with the baseline condition whereby they tend to accelerate to avoid the lane-changing request. The AFT model suggests that on average drivers’ response times are shorter in the connected environment, implying that drivers respond to the lane-changing request faster in the presence of driving aids. However, at the individual level, connected environment’s impact on drivers’ response times is mixed as drivers’ response times may increase or decrease in the connected environment compared to the baseline condition, for instance, we find that female drivers have lower response times in the connected environment than that of male drivers. Overall, this study finds that drivers in connected environment, on average, take less time to respond and appear to be more cooperative, and thus, are less likely to be engaged in safety-critical events

Consumer Surplus based Method for Quantifying and Improving the Material Flow Supply Chain Network Robustness

Recent advances in network science has encouraged researchers to adopt a topological view when characterising the robustness of supply chain networks (SCNs). However, topology based characterisations, without considering the heterogeneity among the supply chains which form the SCN, can only provide a partial understanding of robustness. Hitherto, focus of robustness studies have been on cyclic SCNs, with unweighted and undirected links representing general inter-firm interactions. Here, we consider the specific case of a material flow SCN with multi-sourcing, which is characterised by a tiered structure with directed and weighted links. The proposed method uses the multinomial logit model to estimate the utility levels of supply chains within the SCN, as perceived by a focal firm which is indicative of the SCN consumers. The robustness of the SCN is characterised by considering the degree to which supply chains overlap with each other as a cost in the logit formulation. Finally, using a randomisation scheme to generate ensembles of SCN configurations which preserve the number of connections at each firm, the configuration which maximises the consumer surplus for the focal firm is identified. The proposed method is implemented on a real world SCN to identify the optimal configuration in terms of robustness