1,721,029 research outputs found
Substitution and complementarity patterns between traditional transport means and car sharing: a person and trip level analysis
Full text linkCar sharing is a new transport mode which combines characteristics of private and collective traditional transport means. Understanding the relationship of this mode with existing ones is very important for policy makers to create an efficient transport system and to properly address public resources. This paper aims to analyze the interaction of car sharing with the existing offer of competing modes, using data from a specific travel survey administered in the city of Turin, where both free-floating and one-way station based car sharing services are offered. All transport modes operating in the study area were considered. Bivariate models were estimated to study the propensity to have a car sharing subscription and the substitution patterns between different travel means for a representative random sample of trips taken by the Turin population. Results show that the current car sharing system is perceived as efficient and useful; car sharing members are young males, living in high-income and low-size household with, in particular, a high number of workers and low number of available cars; moreover, the presence of private parking near home has a strong negative impact. There is evidence that car sharing can substitute car driving trips, while the evidence that the same can happen with biking and walking trips is not supported by models but only marginally seen from descriptive statistics. There is also some complementarity between car sharing and public transport and a strong complementarity between car sharing and bike sharing, so that policy makers should jointly promote those modes
Last mile distribution using cargo bikes: a simulation study in Padova
Full text linkThe recent growth of e-Commerce has induced an increasing freight demand, which could lead to negative externalities, in particular in urban areas. To foster sustainable development of cities and increase their livability, many local authorities are implementing urban vehicle access regulations, such as low -emission zones, banning the circulation of polluting vehicles. These measures prompted the adoption of new sustainable freight transport solutions for last mile deliveries, such as cargo bikes. The aim of this paper is to describe the study for the implementation of such a system. The procedure was tested (1) to define the location of a transshipment facility where parcels are moved from vans to cargo bikes, (2) to estimate the environmental and economic sustainability of the system, and (3) to quantify the effects of uncertainty in the final results. The framework was applied to the city center of Padova (Italy), where two sets of delivery system were considered: the first with traditional vans starting from an existing urban consolidation center and the second with manual and electric cargo bikes starting from a micro-depot. In particular, demand of home deliveries was estimated for a typical weekday; routes of freight transport means were defined by an optimization procedure; these data were used as input to a Discrete Event Simulation model. A sensitivity analysis was carried out modelling the potential uncertainty associated with load/unload times and travel speed of means, due to traffic congestion. Several scenarios were tested considering three locations as potential transshipment points. Outcomes of the simulations were used to estimate key performance indicators, evaluating the environmental and economic effects of the two delivery schemes. Results highlighted the potentiality of cargo bikes as a sustainable delivery system, and the impacts of uncertainty on the ranking of alternative options (i.e. micro-hubs)
Permutation testing for goodness-of-fit and stochastic ordering with multivariate mixed variables
No full textPermutation tests are highly versatile non-parametric procedures that can be used to address a wide set of statistical problems, without strict assumptions on data distribution. The Non-Parametric Combination (NPC) procedure has been proposed in the multivariate context to combine the results of several univariate permutation tests. This work demonstrates the flexibility and power of the procedure with a focus on Goodness-of-Fit and the comparison of C>2 different distributions, and includes the particular case of stochastic ordering problems. For each problem, we propose a different extension of the NPC procedure and suitable solutions for contexts in which the data are not solely continuous or ordinal, but also mixed. Additionally, the paper shows how these procedures can work with small total sample size n, even when n is lower than the number of variables V, and how a higher value of V has a positive effect on the power of the tests
Evaluating car-sharing switching rates from traditional transport means through logit models and Random Forest classifiers
Full text linkPositive impacts of car-sharing, such as reductions in car ownership, congestion, vehicle-miles-traveled and greenhouse gas emissions, have been extensively analyzed. However, these benefits are not fully effective if car-sharing subtracts travel demand from existing sustainable modes. This paper evaluates substitution rates of car-sharing against private cars and public transport using a Random Forest classifier and Binomial Logit model. The models were calibrated and validated using a stated-preference travel survey and applied to a revealed-preference survey, both administered to a representative sample of the population living in Turin (Italy). Results of the two models show that the predictive power of both models is comparable, albeit the Logit model tends to estimate predictions with a higher reliability and the Random Forest model produces higher positive switches towards car-sharing. However, results from both models suggest that the substitution rate of private cars is, on average, almost five times that of public transport
Evaluating car-sharing switching rates from traditional transport means through logit models and Random Forest classifiers
No full textPositive impacts of car-sharing, such as reductions in car ownership, congestion, vehicle-miles-traveled and greenhouse gas emissions, have been extensively analyzed. However, these benefits are not fully effective if car-sharing subtracts travel demand from existing sustainable modes. This paper evaluates substitution rates of car-sharing against private cars and public transport using a Random Forest classifier and Binomial Logit model. The models were calibrated and validated using a stated-preference travel survey and applied to a revealed-preference survey, both administered to a representative sample of the population living in Turin (Italy). Results of the two models show that the predictive power of both models is comparable, albeit the Logit model tends to estimate predictions with a higher reliability and the Random Forest model produces higher positive switches towards car-sharing. However, results from both models suggest that the substitution rate of private cars is, on average, almost five times that of public transport
Travel demand prediction during covid‐19 pandemic: Educational and working trips at the university of padova
Full text linkThe diffusion of the COVID‐19 pandemic has induced fundamental changes in travel hab-its. Although many previous authors have analysed factors affecting observed variations in travel demand, only a few works have focused on predictions of future new normal conditions when people will be allowed to decide whether to travel or not, although risk mitigation measures will still be enforced on vehicles, and innovative mobility services will be implemented. In addition, few authors have considered future mandatory trips of students that constitute a great part of everyday travels and are fundamental for the development of society. In this paper, logistic regression models were calibrated by using data from a revealed and stated‐preferences mobility survey administered to students and employees at the University of Padova (Italy), to predict variables impacting on their decisions to perform educational and working trips in the new normal phase. Results high-lighted that these factors are different between students and employees; furthermore, available travel alternatives and specific risk mitigation measures on vehicles were found to be significant. Moreover, the promotion of the use of bikes, as well as bike sharing, car pooling and micro mobility among students can effectively foster sustainable mobility habits. On the other hand, countermeas-ures on studying/working places resulted in a slight effect on travel decisions
Low emission zone and mobility behavior: Ex-ante evaluation of vehicle pollutant emissions
Full text linkExposure of the population living in urban areas to an increasing level of air pollution has led local authorities to implement vehicle access restrictions to limit the circulation of pollutant vehicles and foster sustainable travel habits. With these aims, Low Emission Zones (LEZs) have been introduced in several European cities. Many previous works have evaluated the impacts of such regulation; however, they adopted pre-defined assumptions about new travels to access the regulated area and neglected potential behavioral changes induced by the measure. The aim of this paper is to quantify the effects of a LEZ on vehicle pollutant emissions, considering potential short-term variations of travel habits after its introduction (i.e., vehicle replacement, modal shift and destination change), and the associated uncertainty. The study area was the Municipality of Padova (Italy), where a LEZ is likely to be enforced. A holistic evaluation framework was applied combining a behavioral model and a traffic simulation model, calibrated using responses from a mobility survey administered to local stakeholders and traffic counts. The results highlighted the measure could contribute to induce fleet renewal and modal shift toward sustainable transportation means, that could be furtherly fostered by increasing the awareness of the benefits of the LEZ. Furthermore, the outcomes confirmed that the intervention could significantly reduce vehicle pollutant emissions within the area. Nevertheless, a spillover effect could occur outside the LEZ, due to the long detours that travelers deciding to avoid entering the zone have to perform
Effect of road traffic on air pollution. Experimental evidence from covid-19 lockdown
Full text linkThe increasing concentration of human activities in cities has been leading to a worsening in air quality, thus negatively affecting the lives and health of humans living in urban contexts. Transport is one of the main sources of pollution in such environments. Several local authorities have therefore implemented strict traffic-restriction measures. The aim of this paper is to evaluate the effectiveness and limitations of these interventions, by analyzing the relationship between traffic flows and air quality. The used dataset contains concentrations of NO, NO2, NOx and PM10, vehicle counts and meteorology, all collected during the COVID-19 lockdown in the city of Padova (Italy), in which severe limitations to contain the spread of the virus simulated long and large-scale traffic restrictions in normal conditions. In particular, statistical tests, correlation analyses and multivariate linear regression models were applied to non-rainy days in 2020, 2018 and 2017, in order to isolate the effect of traffic. Analysis indicated that vehicle flows significantly affect NO, NO2, and NOx concentrations, although no evidence of a relationship between traffic and PM10 was highlighted. According to this perspective, measures to limit traffic flows seem to be effective in improving air quality only in terms of reducing nitrogen oxide
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
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