There are hundreds of millions of kilometers of paved roads and many people live in proximity. Pollution from road transportation is a well-documented problem potentially leading to chronic health ...impacts. However, research on the raw material production, construction, operation, maintenance, and end-of-life phases of paved roads, and corresponding supply chains, is generally limited to energy consumption and greenhouse gas emissions. No previous research efforts on the life-cycle stages of pavements and road operation connect pollutant emission inventories to intake of inhaled pollutants and resulting damages to exposed populations. We have developed a first-of-its-kind model quantifying human exposure to fine particulate matter (PM2.5) due to emissions from routine pavement resurfacing and vehicle operation. We utilize the Intervention Model Pollution Source-Receptor Matrix to calculate marginal changes in ground-level PM2.5 concentrations and resulting exposure intake from a spatially resolved primary and secondary PM2.5 emission precursors inventory. Under a scenario of annual road-resurfacing practices within the San Francisco Bay Area in California (population: 7.5 million), resurfacing activities, material production and delivery (i.e. cement, concrete, aggregate, asphalt, bitumen), and fuel (i.e. gasoline, diesel) supply chains contribute almost 65% to the annual PM2.5 intake from all the sources included in the study domain (the remaining 35% being due to on-road tailpipe emissions). Exposure damages range from $170 to $190 million (2019 USD). Complete electrification of on-road mobile sources would reduce annual intake by 64%, but a sizable portion would remain from material supply chains, construction activities, and brake and tire wear. Future mitigation policies should be enacted equitably. Results show that people of color experience higher-than-average PM2.5 exposure disparities from the emission sources included in the study, particularly from material production.
A user's perception of road surface conditions is usually measured by a subjective 1-to-5 scale defined as the Present Serviceability Rating (PSR). The subjectivity associated with the scale can ...result in different PSR values for the same pavement section. In this paper, we use multivariate data analysis to identify potential groups of users sharing similar perceptions on the condition of urban roads. We conducted a survey of 137 drivers of different modalities (bus, car, taxi, truck) after they had driven over some selected road sections in Barranquilla, Colombia. The survey included socioeconomic questions and a rating questionnaire containing a list of statements related to the ride quality and the acceptance of possible pavement defects. The study included 115 urban road sections with different pavement surfaces and geometric characteristics (e.g. slopes, lane width). We used factor analysis to identify two distinct user latent preferences while driving over urban roads. Then, we applied cluster analysis on the latent preferences. Results suggest a possible classification for surveyed participants into (a) those wanting more infrastructure investment to guarantee an excellent ride quality, and (b) those who are more tolerant toward pavement surfaces in poor condition. We found significant differences in the mean rate of acceptance of urban roads within groups, suggesting that more experienced drivers tend to be more sensitive when riding over pavements in poor condition. Ignoring these differences in the preference of raters could lead to biased results when evaluating the level of pavement serviceability in urban contexts.
With the ever-increasing emphasis on maintaining road assets to a high standard, the need for fast accurate inspection for road distresses is becoming extremely important. Surface distresses on roads ...are essentially three dimensional (3-D) in nature. Automated visual surveys are the best option available. However, the imaging conditions, in terms of lighting, etc., are very random. For example, the challenge of measuring the volume of the pothole requires a large field of view with a reasonable spatial resolution, whereas microtexture evaluation requires very accurate imaging. Within the two extremes, there is a range of situations that require 3-D imaging. Three-dimensional imaging consists of a number of techniques such as interferometry and depth from focus. Out of these, laser imagers are mainly used for road surface distress inspection. Many other techniques are relatively unknown among the transportation community, and industrial products are rare. The main impetus for this paper is derived from the rarity of 3-D industrial imagers that employ alternative techniques for use in transportation. In addition, the need for this work is also highlighted by a lack of literature that evaluates the relative merits/demerits of various imaging methods for different distress measurement situations in relation to pavements. This overview will create awareness of available 3-D imaging methods in order to help make a fast initial technology selection and deployment. The review is expected to be helpful for researchers, practicing engineers, and decision makers in transportation engineering.
•Debris distance is predicted for building damage states.•Haiti earthquake data is used for model calibration.•Fragility curves are developed to predict road section blockage.•Road blockage is ...modeled as a system reliability problem.•Conceptual illustrations are made using two examples.
Transportation infrastructure supports the social and economic activities of communities. One of the impacts of roads’ disruption is the obstruction of emergency services (e.g., ambulance, firefighting, evacuation). Furthermore, the recovery process of a community following an extreme event (e.g., a natural hazard) depends on the functionality of the transportation infrastructure. Therefore, conducting a risk and resilience analysis of transportation infrastructure is critical to help communities minimize the initial impact of hazards and promote a rapid recovery. Current approaches model the probability of road blockage due to building damage using high-resolution optical satellite images and aerial photographs collected after past events. However, the data used by these methods are limited, and few data have been collected before 2010. Besides, data may not be available for specific regions that have not experienced recent earthquakes. Thus, a probabilistic predictive method is needed for risk and resilience analysis of roads. This paper proposes a probabilistic model using the data from the 2010 Haiti Earthquake and calibrated by Bayesian approach to predict the debris distance from undamaged buildings (e.g., the distance debris can reach from the footprint of the undamaged building). The model is then used to construct fragility curves that give the conditional probability of road blockage at a given road section for a given seismic intensity. The proposed model considers the relevant factors affecting the road blockage probability, including building types, damage level, and road characteristics. The probability of road blockage at a given road section is estimated for the four general road section types, considering buildings on only one side of the road or both sides, and with or without a raised traffic median. The probability of road blockage for an entire road is then calculated by system and parallel reliability analysis. The proposed models apply to any general urban area without the dependence on historical data from past earthquakes.
During the last few decades, the European Union has promoted distance-based charges on heavy goods vehicles for the use of main roads as a means of funding the infrastructure and internalizing ...external costs. This approach has progressively been implemented by many European nations. From a macro perspective, this paper explores the impact of heavy vehicle tolling on road freight demand in the countries where it has been implemented. To that end, we develop a dynamic panel data methodology to analyze the evolution over time of road freight traffic and modal share for the European countries having implemented a nationwide per-km truck tolling policy. The results show that, with the exception of very specific cases, there is not strong evidence that heavy vehicle tolling had either influenced road freight volume or promoted the shift of freight to alternative modes. In addition, the limited effect of this charging policy has been partly or mostly counteracted by the evolution of other explanatory factors such as economic growth and the expansion of high capacity networks.
Automated driving can no longer be referred to as hype or science fiction but rather a technology that has been gradually introduced to the market. The recent activities of regulatory bodies and the ...market penetration of automated driving systems (ADS) demonstrate that society is exhibiting increasing interest in this field and gradually accepting new methods of transport. Automated driving, however, does not depend solely on the advances of onboard sensor technology or artificial intelligence (AI). One of the essential factors in achieving trust and safety in automated driving is road infrastructure, which requires careful consideration. Historically, the development of road infrastructure has been guided by human perception, but today we are at a turning point at which this perspective is not sufficient. In this study, we review the limitations and advances made in the state of the art of automated driving technology with respect to road infrastructure in order to identify gaps that are essential for bridging the transition from human control to self-driving. The main findings of this study are grouped into the following five clusters, characterised according to challenges that must be faced in order to cope with future mobility: international harmonisation of traffic signs and road markings, revision of the maintenance of the road infrastructure, review of common design patterns, digitalisation of road networks, and interdisciplinarity. The main contribution of this study is the provision of a clear and concise overview of the interaction between road infrastructure and ADS as well as the support of international activities to define the requirements of road infrastructure for the successful deployment of ADS.
► Network fundamental diagram is exploited to improve mobility in saturated traffic conditions. ► Based on a simple but efficient feedback control structure, gating is applied to control urban ...congestion. ► Application of the gating strategy leads to substantial improvements compared to the non-gating case.
Traffic signal control for urban road networks has been an area of intensive research efforts for several decades, and various algorithms and tools have been developed and implemented to increase the network traffic flow efficiency. Despite the continuous advances in the field of traffic control under saturated conditions, novel and promising developments of simple concepts in this area remains a significant objective, because some proposed approaches that are based on various meta-heuristic optimization algorithms can hardly be used in a real-time environment. To address this problem, the recently developed notion of network fundamental diagram for urban networks is exploited to improve mobility in saturated traffic conditions via application of gating measures, based on an appropriate simple feedback control structure. As a case study, the proposed methodology is applied to the urban network of Chania, Greece, using microscopic simulation. The results show that the total delay in the network decreases significantly and the mean speed increases accordingly.
As a significant role for traffic management, city planning, road monitoring, GPS navigation and map updating, the technology of road extraction from a remote sensing (RS) image has been a hot ...research topic in recent years. In this paper, after analyzing different road features and road models, the road extraction methods were classified into the classification-based methods, knowledge-based methods, mathematical morphology, active contour model, and dynamic programming. Firstly, the road features, road model, existing difficulties and interference factors for road extraction were analyzed. Secondly, the principle of road extraction, the advantages and disadvantages of various methods and research achievements were briefly highlighted. Then, the comparisons of the different road extraction algorithms were performed, including road features, test samples and shortcomings. Finally, the research results in recent years were summarized emphatically. It is obvious that only using one kind of road features is hard to get an excellent extraction effect. Hence, in order to get good results, the road extraction should combine multiple methods according to the real applications. In the future, how to realize the complete road extraction from a RS image is still an essential but challenging and important research topic.
Abstract In transportation, roads sometimes have cracks due to overloading and other reasons, which seriously affect driving safety, and it is crucial to identify and fill road cracks in time. Aiming ...at the defects of existing semantic segmentation models that have degraded the segmentation performance of road crack images and the standard convolution makes it challenging to capture the spatial and channel coupling relationship between pixels. It is difficult to differentiate crack pixels from background pixels in complex backgrounds; this paper proposes a semantic segmentation model for road cracks that combines channel-spatial convolution with the aggregation of frequency features. A new convolutional block is proposed to accurately identify cracked pixels by grouping spatial displacements and convolutional kernel weight dynamization while modeling pixel spatial relationships linked to channel features. To enhance the contrast of crack edges, a frequency domain feature aggregation module is proposed, which uses a simple windowing strategy to solve the problem of mismatch of frequency domain inputs and, at the same time, takes into account the effect of the frequency imaginary part on the features to model the deep frequency features effectively. Finally, a feature refinement module is designed to refine the semantic features to improve the segmentation accuracy. Many experiments have proved that the model proposed in this paper has better performance and more application potential than the current popular general model.
Patching holes, paying tolls Petterson, Danielle
Civil Engineering : Magazine of the South African Institution of Civil Engineering,
04/2022, Volume:
30, Issue:
3
Journal Article, Trade Publication Article
For vehicle owners in Johannesburg, dodging potholes has become a critical skill. Exacerbated by the recent heavy rains, declining municipal revenues and a loss of technical capacity over the last ...few years have left roads in a poor state. But the problem extends far beyond municipal level.
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