Latin American Transport Studies最新文献

This paper presents a Scoping Review of methods used for the identification and prioritization of Traffic Crash Locations (TCL) in complex urban areas, considering different accident classes and outcomes with different degrees of severity. Were obtained relevant studies on identifying and prioritizing accident-prone locations from the consultation of two electronic databases (Scopus and Web of Science). The data obtained were evaluated by independent reviewers. Studies carried out in urban areas, which carry out the tasks of grouping accidents into units of analysis, identifying candidate areas, and prioritizing accident-prone locations, were selected. Forty-two studies were selected and evaluated. The applied units of analysis, identification methods, and criteria for prioritizing candidate areas for accident-prone locations were identified among the studies found. The mapping of the works that apply statistical significance criteria of the findings and longitudinal analyses of the candidate sites was carried out. Among the strategies used to identify TCL, the most frequently applied approach was Spatial Association (SA) (23.81%), followed by minimum threshold limit (MTL) (14.29%). Among the different ranking criteria identified, the upper control limit (UCL) criterion stood out, followed by the density and expected frequencies criteria. This work presents a narrative summary mapping the heterogeneity of applied approaches. The contribution of this study was the presentation of the roadmap for the different studies related to the analysis of TCL. Finally, this work points out the need to adopt longitudinal analyzes as a criterion for prioritizing TCL and the application of criteria of statistical significance during the prioritization stage of TCL.

Dockless micromobility services, including shared bicycles and scooters, are emerging as sustainable travel alternatives in many cities. The optimal operation of these services, however, often depends on rebalancing operations that redistribute micromobility vehicles to service area locations with less than desired vehicle levels. Existing rebalancing models typically prioritize operational efficiency or business objectives, such as relocating vehicles to maximize served demand or profits. This study contributes a rebalancing model that incorporates the goal of improving equity-in-access to dockless micromobility through rebalancing operations. Specifically, a two-step approach is proposed to optimize the rebalancing operations of dockless micromobility services according to efficiency and equity objectives. In the first step, an optimization model is used to find micromobility vehicle distributions that maximize system-level efficiency and equity performance indicators across a specified time horizon. In the second step, a multi-objective pick-up and delivery problem is used to develop vehicle relocation plans aimed at achieving the optimal distributions determined in the first step. Numerical examples are presented to illustrate the application of the proposed methods. As part of the numerical tests, machine learning-based models trained using real-world data were shown to accurately predict equity-based performance indicators for a dockless e-scooter service in Puerto Rico.

Foster road safety in school surroundings is an answer for high traffic injury rates and can help to build safe, healthy, and sustainable cities. This paper pursues two goals: identifying the built environment characteristics that influence the severity of traffic crashes in elementary school surroundings for a medium-sized city in Latin America, Porto Alegre (Brazil); and discussing safety measures to provide information for policy making. Ordered and unordered discrete choice models, with random parameters, were estimated in order to analyze the influence of built environment characteristics on the traffic crash severity. The modeling indicates that the severity of traffic injuries in school surroundings is influenced by school, crash, socioeconomic characteristics, and the built environment, highlighting the negative role of the number of four-way intersections and the positive impact of commercial land use for crash involving a car and at least one pedestrian or cyclist. Developing built environment strategies to encourage active mode trips should consider identifying measures to ensure safety.

Intelligent traffic systems require data and recent studies on Short-Term Traffic Forecasting (STTF) have incorporated the Spatiotemporal (ST) aspect to improve predictions. They consider road network characteristics by incorporating the impact of traffic at a given location and on its neighbouring locations. Spatial relationship weight matrices, or simply spatial matrices, facilitate direct incorporation by considering the correlation factors between various points. The Space-Time Autoregressive Integrated Moving Average Model (STARIMA) enables the application and comparison of various types of spatial matrices in ST-STTF. In this paper, we compare three types of neighbourhoods and eight types of weights to assess their impact in ST-STTF for different infrastructure and traffic characteristics. Several experiments in the road network of the city of São Paulo, Brazil, revealed that asymmetric matrices that consider the upstream and downstream traffic flow present higher accuracy than the commonly used symmetric matrices. The use of asymmetric matrices improved accuracy in 77.3% of scenarios, particularly when employing an asymmetric weight based on adjacent section speeds and travel time. Moreover, grouped matrices (GM) required less computational time to estimate the models when compared with contiguity (CN) and time lag (TL) matrices. Therefore, our results show the impacts of applying several spatial structures into short-term traffic prediction models and provide practical prediction methods for an urban network based on real traffic data, with a case study in one of the largest cities in Latin America.

Lockdowns to deal with the COVID-19 outbreak affected peoples' life in different dimensions. In particular, we are interested in evaluating the effects on traffic flows. For this purpose, it is necessary to accurately estimate the temporal variation of traffic flows during the pandemic period. New data collection techniques, including information from smartphones, can be used to collect this information at multiple locations of a road network. A key step in using this new data collection is the validation against more traditional measures to ensure consistency in traffic volume interpretation. This paper presents a case study whose main goals are to compare the smartphone-based traffic count predictions from the StreetLight data source against the values reported by traditional methods of traffic quantification and estimate reductions and recovery rates on traffic volumes in North Carolina during the COVID-19 pandemic. The results show that the largest reductions in traffic flows occurred mainly during the first three months of lockdown.

Cycling to access or egress from public transport (PT) systems potentially improves accessibility to opportunities for PT-dependent populations, which can reduce socio-spatial inequalities. While developing countries may benefit from the affordability and sustainability of bicycle-transit integration, current scientific research on the topic focuses mostly on metropolises in the industrialized world. Furthermore, Global South cities that invest in such systems see their population resistant to adopting the solutions well received in the North. This paper adapts a bicycle-transit conceptual model to the reality of Latin American metropolises to serve as a characterization tool to empirically investigate the barriers and challenges inhibiting large developing cities from benefiting from it. Fortaleza, a mid-sized Brazilian metropolis with recent significant investments in bicycle-transit integration, serves as a case study. All analyses are based on surveys with bike-sharing and bike-parking facilities users, associated with data from bus-system smartcard validation. The analyses aim at both supply and demand conditions to evaluate their policy implications. The challenges faced by North and Global South cities regarding bicycle-transit integration seem to be similar in terms of infrastructural necessities and outcomes (travel speeds, road safety, and comfort); however, they are significantly different in terms of hindering costs and public safety, which affect users’ behavior. Discussions revolve around how to attract new users while keeping costs at bay, as well as how public safety plays a key role in the Latin American context.

Ridesourcing services are rapidly expanding in cities around the world. Their implementation in the absence of prior planning of the operation, or without clear rules for management and inspection, can generate negative impacts on urban mobility, as well as opportunities that are not taken advantage of in the best way. However, there are few studies that have measured the impacts of these services on mobility in cities. The ones that exist have targeted large cities in developed countries. This work aims to measure the risks and opportunities created by the insertion of application-based transport in Latin-American small-sized cities. The use of a hybrid qualitative-quantitative analysis methodology is proposed, with uncertainty modeling supported by fuzzy logic, which was applied in a case study of Cachoeira do Sul, a city located in Southern Brazil. The results revealed a positive perception of the use of ridesourcing services, with opportunities being rated higher than risks, especially related to new options for mobility services. The risks associated with the planning, management, and operation of coordinated urban mobility stood out, in addition to those concerning the competition of ridesourcing services with public transport and taxis. The results obtained here should assist in the formulation of appropriate public policies for ridesourcing services in small Latin-American cities.

The paper's main objective is to quantify the potential market for Freight Demand Management (FDM) in metropolitan areas. To this effect, the authors define FDM and describe the various initiatives that could be undertaken to reduce the externalities produced by freight traffic. These changes involve altering the demand patterns enacted by the receivers of supplies. The literature on freight behavior research is reviewed to identify the industry segments most inclined to participate in FDM. Having identified the industry sectors of interest for FDM programs, the authors use freight trip generation models and publicly available data to quantify the freight trip generation for the industry sectors deemed to be the ideal target of FDM initiatives. These estimates are obtained for five large metropolitan statistical areas and a sample of representative medium to small metropolitan statistical areas of different sizes in the US. The paper concludes with a discussion of policy implications and chief results.

This article provides a comprehensive overview of the transport landscape of Belo Horizonte. Belo Horizonte, located in the southeast region, is the capital of Minas Gerais and the first planned city in Brazil in the late 1890 s. Nowadays, the city has 2.3 millions residents , and almost 99% of its residents live in urban areas. Rapid population growth that is out of step with urban and transportation planning has brought challenges to displacement of the population in our times. This article presents the background of Belo Horizonte, with the historical, geographical, demographic, and social context, the transport infrastructure, and the current transportation development agenda. The overview could support further work using Belo Horizonte as a study area.

E-commerce has been one of the main contributors to urban freight transport. However, equity studies related to e-commerce accessibility are still scarce in the literature. Equity is crucial in freight transportation to understand how access to places or goods is distributed between various social groups. Therefore, this paper aims to identify research opportunities related to equity in ecommerce accessibility through a systematic literature review. The results design a research agenda for future works. The main research gaps concern the use of utilitarianism, libertarianism, and capabilities approach to analyse e-commerce. The research opportunities are related to the use of different equity theories, proposing equity measures.