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Hazardous materials accidents during road transport have caused catastrophic losses to humans and the environment all over the world in recent years. Especially in an urban environment, heavy traffic congestion and road closures present serious and complex situations during hazmat transportation. The challenge of urban hazmat transportation is to determine the vehicle routes that minimize risk subject to cost considerations and road closures. This paper presents a bi-objective programming model and a heuristic algorithm to optimize the routing of hazardous materials transportation with road closure considerations. A model is formulated that minimizes hazmat risk and transportation cost subject to road closure constraints. A new heuristic algorithm is proposed to solve the bi-objective hazmat vehicle routing and it is applied to a realistic case study involving hazmat transportation in the highly populated metropolitan area of Shanghai, China. [ABSTRACT FROM AUTHOR]

We demonstrate the automated crack evaluation system for the rapid characterization of internal/external concrete structures. Practical generation and detection of reliable and consistent mechanical waves are made possible using an automatic impactor and air-coupled sensors, offering the potential to overcome limitations associated with the rapid damage assessment towards traffic disruption-free measurement. The objective is to demonstrate enhanced performance in laboratory and field tests when arrays of double-sided bounce impactors and microelectromechanical systems are used, suitable for automation without lane closures. The inspection includes detecting delamination, vertical cracks, and corroded reinforcement using flexural vibration mode of impact-echo testing, wave attenuation, and radar, respectively. The approach has novelty in three main techniques: the advanced auto-impacting system, multichannel acoustic scanning unit, and integrated scanning platform. The laboratory tests are performed to verify the system's performance under different conditions and parameters to these damages. The proposed system is applied in two highway bridge inspections. • An automated crack evaluation system is proposed using non-contact mechanical wave. • Double-sided bounce system is deployed for continuous mechanical wave generation. • Rapid damage assessment is performed with traffic disruption-free bridge inspection. • Non-stop scanning system is designed with an automated height-adjustable platform. • Integrated post-processing is performed to evaluate delamination and vertical crack. [ABSTRACT FROM AUTHOR]

Improving community resilience relies on our ability to evaluate and understand the direct and indirect role of the transportation network. This requires losing our fixation with network functionality in favour of an approach that evaluates whether the network is truly serving the community's needs. In this paper, we present such an approach. With the understanding that sufficient and equitable access to amenities is key to community resilience, we leverage open-source data and routing algorithms to simulate road and service closures under various hazard scenarios. Among our methodological contributions is the ability to efficiently modify entire transportation networks to reflect hazard damage and identify isolated communities. This makes integrating hazard simulation with access and equity evaluations practicable on a large scale. We illustrate this approach in three cities. Ultimately, a broader view of the transportation network's role will better support communities prepare for and respond equitably when a disaster occurs. [Display omitted] [ABSTRACT FROM AUTHOR]

• Develop a multi-class distribution network design problem with inventory and superimposed risks. • Introduce risk superposition coefficients for multi-class hazmat to capture the superimposed risks among different materials resulting from possible chemical reaction. • Formulate the long-term detour cost/risk and the cyclic time windows penalty costs under the time-dependent (periodic) road closure policy. • Propose a population-based risk definition that evaluates the risk for the population at any location and any time with respect to its multi-class hazmat logistics system Provide a metropolitan wide real-world application and new insights. Transportation and inventory are essential to hazardous materials logistics, while different classes of hazardous materials are often transported over a network simultaneously. Despite their in-transit and storage incompatibility, the superimposed risks among different materials, which results from possible chemical reaction once accidents (e.g., leakage, explosion) happen, further complicate the comprehensive plans. In this study, we introduce a new multi-class hazmat distribution network design problem with inventory and superimposed risks (MHND) in a multi-echelon supply chain, where the planning of locations, inventory, and routes are made together. The long-term detour cost/risk and the cyclic time windows penalty costs under the time-dependent (periodic) road closure policy are explicitly formulated. We further propose a new population-based risk definition that evaluates the risk for the population at any location and any time with respect to its multi-class hazmat logistics system. In particular, to capture the interactions between different types of materials, we introduce risk superposition coefficients to capture possible superimposed risks among different hazmat that accommodate a general system with more than two hazmat types. We develop a knowledge-based NSGA-II algorithm with cyclic dissimilarity-based elitist selection (NSGA-II-CD) to solve the problem. The devised cyclic dissimilarity-based elitist selection (CD) operator can tackle the issue of speeding proliferation, which greatly improves the solution quality. Our model is applied to a metropolitan-wide real-world case study in Guangzhou, China. The results suggest that, from the perspective of the traffic management sector, the periodic road closures policy in Guangzhou could be possibly upgraded to a full-time prohibition. Moreover, the results provide the following insights to authorities (1) there is a positive convex relation between risk minimization and risk equilibration. The authorities should not try to find a perfect distribution of risk, and they should make a trade-off between the risk equity and total exposed risk; (2) there is a positive correlation between the level of service and total risk. Thus, in practice, the agencies should make a trade-off between economic viability of the system, exposed risk, and maintaining good service for customers; and (3) the interactions between different types of hazmat considerably affect the distribution network design; specifically, the route overlapping ratio for different types of hazmat decreases when their interactions intensify. [ABSTRACT FROM AUTHOR]

In this paper, we exemplify the use of simple indicators of wind storm vulnerability of the road network that can be derived from existing geographic datasets. We point out the possible utilization of the datasets, applying GIS techniques, for highlighting road sections that, due to adjacency of high forest stands, are sensitive to closure by storm-felled trees. Indicators reflecting the reduced access to different areas or to the population in need of emergency aid can be derived based on the parameter tree height along roads and road network analysis. As a case in this study, the methodology is applied to elderly people (+80 years) with possible need of daily care at home following a severe storm. A comparison to the extreme 2005 storm felling in southern Sweden reveals that only limited estimates of road network disruption due to storm-felled trees are possible using the indicators, as other factors, for example, wind direction, which determine the exact impact of a particular storm are not taken into account. However, the indicators and network analysis also provide a possibility to draw attention to locations where disruptions of the road network would have significant effects on the accessibility to large surrounding areas. Potential critical road closures can be identified and preventive measures considered locally at these points. [ABSTRACT FROM AUTHOR]

During the height of the first lockdown in South Africa, commuter bus companies experienced as much as an 80% drop in the demand for services, and 18 months later patronage still has to fully recover to pre-COVID-19 levels. Worldwide supply chains depend on stable and reasonable forecastable demand and supply for goods and services to do what they do well - reduce inventory, deliver on a just in time basis, add value to products and services, and reduce costs. It is, however, important that the lessons learned from these crises be conveyed widely so that supply chain role players become closer aligned and attuned to potential risk and risk mitigation strategies to improve service and product availability. [Extracted from the article]

• Common proximity methods do not weigh crashes based on distance to a target segment. • Incorporating linear weighting into a crash outcome results in more robust analyses. • The equivalent property damage only (EPDO) method weighs fatal crashes too heavily. • Less precise EPDO weighting methods results in more robust safety analysis outcomes. • Horizontal curves with larger radii are less safe than curves with shorter radii. Despite the numerous breakthroughs in crash analytics, there remains a lack of consensus among safety practitioners as to the optimal method for locating high crash locations. Two critical components in the traffic safety analysis process not agreed upon are 1) how the crash distance to a target location is included in the analysis and 2) how crashes are weighted based on crash-related characteristics. For example, the commonly used buffering technique to determine which crashes are associated with a specific target road segment does not associate crashes that are closer to a target road segment with any additional weight, even though it is likely to be more greatly associated with the characteristics of the target location. Additionally, the commonly used equivalent property damage only (EPDO) crash weight method has been found to weigh fatal crashes significantly more than serious injury crashes, even if the difference between the two outcomes was a single factor. This study proposes more robust crash weighting techniques for use in high-risk location identification using an application of a novel horizontal curve dataset. Specifically, a heteroscedastic censored regression approach was used to investigate the impact of different crash proximity weighting techniques and crash severity weighting methods on model outcomes. The results demonstrate that the use of a linear distance weighting factor used in conjunction with the buffering technique as well as a less precise EPDO weighting factor method results in more robust safety analysis outcomes. The improved results have the potential to improve hot spot identification and resource allocation at both the federal and regional levels by employing models that more accurately link specific crash segments with contributing crash characteristics. [ABSTRACT FROM AUTHOR]

The point clouds acquired with a mobile LiDAR scanner (MLS) have high density and accuracy, which allows one to identify different elements of the road in them, as can be found in many scientific references, especially in the last decade. This study presents a methodology to characterize the urban space available for walking, by segmenting point clouds from data acquired with MLS and automatically generating impedance surfaces to be used in pedestrian accessibility studies. Common problems in the automatic segmentation of the LiDAR point cloud were corrected, achieving a very accurate segmentation of the points belonging to the ground. In addition, problems caused by occlusions caused mainly by parked vehicles and that prevent the availability of LiDAR points in spaces normally intended for pedestrian circulation, such as sidewalks, were solved in the proposed methodology. The innovation of this method lies, therefore, in the high definition of the generated 3D model of the pedestrian space to model pedestrian mobility, which allowed us to apply it in the search for shorter and safer pedestrian paths between the homes and schools of students in urban areas within the Big-Geomove project. Both the developed algorithms and the LiDAR data used are freely licensed for their use in further research. [ABSTRACT FROM AUTHOR]

• 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. [ABSTRACT FROM AUTHOR]

This article describes a data-driven approach to flood risk exposure evaluation and route delineation during heavy rainfall events. We cross-referenced diverse geospatial and drainage infrastructure datasets with the street network of Hoboken to uncover the factors that increase flood risk. Elevation, slope, precipitation level, imperviousness, and distance to the drainage system's outlets were the most significant predictors to link flooding. We used the link flood risk patterns found in the data to train a reinforcement learning model that generates routes that avoid flood-prone areas. We benchmarked the route assistance model with shortest path and most reliable path algorithms, demonstrating our model has balanced path length and path reliability. We provided the flood risk model outputs at the link-level, which city authorities can use to plan road closures ahead of heavy precipitation events. The route assistance model can be used by drivers to better navigate flood-prone environments by detouring around riskier areas or canceling trips altogether. • We devised a data-driven method for predicting flood susceptibility. • Elevation, slope and distance from outfalls severely influence street flood risk. • We devised a route assistance method for diverting traffic from flood-prone areas. • Our method balances path reliability and shortness, outperforming shortest paths. [ABSTRACT FROM AUTHOR]

• No study verified the factors affecting the dispersal of shoot beetles in Southwest China. • Landscape-level variables are the more important predictor, the roles of the stand-level variables are also important. • The prediction of damage severity distribution of Tomicus spp. highlights the need for forest management improvement. The outbreaks of shoot beetles (Tomicus yunnanensis Kirkendall and Faccoli and Tomicus minor Hartig) have caused widespread tree mortality in Southwest China. However, multi-scale variables explaining the shoot damage ratio (SDR) caused by shoot beetles have never been studied. The objective of this study was to determine the effects of stand-level and landscape-level variables on SDR during outbreaks of shoot beetles in Yunnan pine forests. Sixty-five plots were generated during 2015–2017 based on beetle infestation maps derived from multi-data Landsat images and field survey. Nine explanatory variables were quantified to explain the SDR severity. The forest cover was obtained from a Worldview-3 high‐resolution image. We used the forest resource planning and design survey data to develop landscape context variables. The beetle pressure variable was calculated using beetle infestation maps. The relative importance of the explanatory variables was analyzed using multi-model inference. We established that SDR was higher in the plots that were closer to roads and severely damaged forest areas in the previous year. SDR was negatively affected by edge density (ED) and forest cover, but positively affected by the mean shape index (SHAPE MN) and aspect. Landscape-level variables are probably the more important predictor, stand-level variables also had a significant effect on the shoot beetle outbreak. The prediction models including stand-level variables and landscape-level variables were built. Identifying variables that drive beetle-caused SDR contributed to the improvement of the existing strategies for outbreak control. [ABSTRACT FROM AUTHOR]

Recent studies have shown that a large portion of flood-associated fatalities are related to the use of vehicles. However, there is limited research on the role of infrastructure and geo-environmental conditions surrounding such incidents. This work exploits a dataset of 40 fatal vehicle-related events caused by flooding in Greece to explore the circumstances, the characteristics of infrastructure and of the surrounding environment and their possible influence in the studied incidents. The results showed that the majority of cases occurred in road segments and river crossings with a variety of design deficiencies related to safety and protection from flooding, including poor signage and lighting as well as the absence of road closures, road barriers and other crucial safety features. In high percentages incidents occurred in isolated/remote sites in rural areas, relatively narrow roads and low quality infrastructure (e.g., ford crossings) with a lack of easy alternate routes and absence of other individuals. In the vast majority of cases, the accidents occurred in small arid catchments drained by ephemeral torrents when experiencing extreme flows. The findings have practical implications as they provide a better understanding of dangerous circumstances and define the high-risk segments of the road, which is helpful in prioritizing and shaping appropriate interventions. [ABSTRACT FROM AUTHOR]

Unmanned aerial vehicles (UAV) are envisioned to become one of the new types of fifth/sixth generation (5G/6G) network users. To support advanced services for UAVs such as video monitoring, one of the prospective options is to utilize recently standardized New Radio (NR) technology operating in the millimeter-wave (mmWave) frequency band. However, blockage of propagation paths between NR base stations (BS) and UAV by buildings may lead to frequent outage situations. In our study, we use the tools of integral geometry to characterize connectivity properties of UAVs in terrestrial urban deployments of mmWave NR systems using UAV line-of-sight (LoS) blockage probability as the main metric of interest. As opposed to other studies, the use of the proposed approach allows us to get closed-form approximation for LoS blockage probability as a function of city and network deployment parameters. As one of the options to improve connectivity we also consider rooftop-mounted mmWave BSs. Our results illustrate that the proposed model provides an upper bound on UAV LoS blockage probability, and this bound becomes more accurate as the density of mmWave BS in the area increases. The closed-form structure allows for identifying of the street width, building block and BS heights, and UAV altitude as the parameters providing the most impact on the considered metric. We show that rooftop-mounted mmWave BSs allow for the drastic improvement of LoS blockage probability, i.e., depending on the system parameters the use of one rooftop-mounted mmWave BS is equivalent to 6–12 ground-mounted mmWave BSs. Out of all considered deployment parameters the street width is the one most heavily affecting the UAV LoS blockage probability. Specifically, the deployment with street width of 20 m is characterized by 50% lower UAV LoS blockage probability as compared to the one with 10 m street width. [ABSTRACT FROM AUTHOR]

Lane mark detection plays an important role in autonomous driving under structural environments. Many deep learning-based lane mark detection methods have been put forward in recent years. However, most of current methods limit their solutions within one single image and do not make use of the de facto successive image input during the driving scene, which may lead to inferior performance in some challenging scenarios such as occlusion, shadows, and lane mark degradation. To address the issue, we propose a novel lane mark detection network which takes pre-aligned multiple successive frames as inputs to produce more stable predictions. A Spatial-Temporal Attention Module (STAM) is designed in the network to adaptively aggregate the feature information of history frames to the current frame. Various structure of the STAM is also studied to ensure the best performance. Experiments on Tusimple and ApolloScape datasets show that our method can effectively improve lane mark detection and achieve state-of-the-art performance. [ABSTRACT FROM AUTHOR]

This study develops the first-of-its-kind seismic fragility models for estimation of approach backfill differential settlement for statewide bridges in California. Seismic compression analysis is carried out through a multi-step framework that estimates seismic-induced shear strain profiles for backfills, converts them to volumetric strains, and computes soil settlement through depth integration. As a crucial step, three independent methods are advanced on a uniform basis to estimate soil shear strains under earthquake loading: a simplified one-dimensional (1D) Static approach, a 1D Dynamic method from site response analysis, and a two-dimensional (2D) Dynamic method that accounts for the trapezoidal shape of the bridge embankment. Subsequently, seismic fragility models are derived using the multiple-stripe analysis (MSA) approach that convolves the seismic demands of backfill settlement with capacity models for several broad groupings of approach-slab designs having different abutment and abutment-foundation types, and abutment-connection details. A survey of California's bridge inventory provides stochastic data inputs that quantify various sources of uncertainties in backfill profile, embankment geometry, and both approach slab and abutment designs. Finally, a combined fragility model is developed by considering an equal methodological contribution from each mentioned approach. The final fragility models suggest that the lowest differential-settlement fragility is achieved by combining regular abutments on spread footings with long-length approach slabs connected to the bridge abutment, while the worst case occurs where bridge abutments on deep foundations are not connected with abutting pavements. The proposed seismic fragility models offer a sound basis for first-order estimation of approach-fill differential settlement which may lead to reduced ride quality, traffic speed reductions, and in extreme cases, temporary roadway closure. These represent one of many seismic fragility models for the full range of bridge components needed for prioritizing seismic retrofit measures, facilitating post-hazard inspections and repair actions, as well as assessing the network mobility for resilience quantification. • Develop seismic fragility models of backfill settlements for California bridges. • Integrate three methods to estimate soil shear strains under earthquake loading. • A survey provides stochastic data that quantify various sources of uncertainties. • The fragility models are sensitive to abutment foundation and approach slab design. [ABSTRACT FROM AUTHOR]

The containment and closure policies adopted in attempts to contain the spread of the 2019 coronavirus disease (COVID-19) have impacted nearly every aspect of our lives including the environment we live in. These influences may be observed when evaluating changes in pollutants such as nitrogen dioxide (NO 2), which is an important indicator for economic, industrial, and other anthropogenic activities. We utilized a data-driven approach to analyze the relationship between tropospheric NO 2 and COVID-19 mitigation measures by clustering regions based on pollution levels rather than constraining the study units by predetermined administrative boundaries as pollution knows no borders. Specifically, three clusters were discovered signifying mild, moderate, and poor pollution levels. The most severely polluted cluster saw significant reductions in tropospheric NO 2 , coinciding with lockdown periods. Based on the clustering results, qualitative and quantitative analyses were conducted at global and regional levels to investigate the spatiotemporal changes. In addition, panel regression analysis was utilized to quantify the impact of policy measures on the NO 2 reduction. This study found that a 23.58 score increase in the stringency index (ranging from 0 to 100) can significantly reduce the NO 2 TVCD by 3.2% (p < 0.05) in the poor cluster in 2020, which corresponds to a 13.1% maximum reduction with the most stringent containment and closure policies implemented. In addition, the policy measures of workplace closures and close public transport can significantly decrease the tropospheric NO 2 in the poor cluster by 6.7% (p < 0.1) and 4.5% (p < 0.1), respectively. An additional heterogeneity analysis found that areas with higher incomes, CO 2 emissions, and fossil fuel consumption have larger NO 2 TVCD reductions regarding workplace closures and public transport closures. [ABSTRACT FROM AUTHOR]

As our road infrastructure ages, more cities will be faced with the decision of what to do with freeways within their urban core. With local budgets tightening, more cities will begin considering the removal of these roads as a way to save on maintenance and rebuilding costs. In many cases, however, people fear that reducing road capacity will cause traffic gridlock or adversely affect the economy of a city. Limited empirical evidence exists to explain how removing a link affects travel behavior. Understanding how people adjust their transportation choices when faced with the removal of a high-capacity link is critical to planning efforts for future projects. In this study, we examine three case studies of urban freeway removal: two within San Francisco and one within Milwaukee. We performed a comprehensive assessment of travel patterns in the surrounding area, and in the city as a whole, to better assess how travel is impacted after a freeway is removed. The evidence presented in this analysis suggests that many of the fears involved with removing freeways are unwarranted. When this is coupled with the other positive impacts of freeway removal, the results show that freeway removal has very little downside for cities. [ABSTRACT FROM AUTHOR]

Mathematical models of transportation systems have played an important role in transportation planning in agglomerations. These models state the hypotheses of how people use transport systems and gives information how users respond to changes in the transportation systems. One of the issue connected with estimation of traffic infrastructure effectiveness is assessment of implementation period effect, when streets or public transport modes work under unusual conditions--street closure, detours, temporary lack of tram connection etc. As a result of such situation there is completely different scheme of traffic and PT connections which imply on modal split, assignment and of course on level of demand. In the paper are presented the results of questionnaire surveys conducted on the subject of roundabout in Krakow. Due to reconstruction of the existing roundabout to the three-level road junction, significant impediments to the traffic scheme have occurred. The main aim of the questionnaire was to define the impact of impediments on the travel behaviour of drivers on the demand level. Thus, it was possible to define changes in demand, trip distribution and trip assignment. The results of the survey state are the basis for calculation of demand elasticity rate. For the purpose of the analysis, the assignment was calculated with a simulation model of the city (calibrated in VISUM software). It was possible to quantify the impact of reduced traffic by changes of vehicle kilometres and vehicle hours on the street network, both in the area of direct impact of the traffic limitations and in the whole city. The same analysis was done for models of fixed demand and it was possible to compare impact of reduced traffic on traffic conditions in the city. The results of traffic research carried out during the reconstruction of the roundabout named Ofiar Katynia in Krakow will be presented in this paper. [ABSTRACT FROM AUTHOR]

This paper examines whether evacuees from two wildfires displayed different information seeking behavior than non-evacuees. Findings are the results of a mail survey sent to residents affected by wildfires outside Flagstaff, Arizona and Boulder, Colorado in 2010. We found evacuees sought information more actively than non-evacuees and placed a greater emphasis on use of interactive information sources, which they also tended to see as more useful and trustworthy. Evacuees also expressed lower satisfaction levels for receipt of information items that were more important to them including evacuation and road closure information. Finally, evacuees differed significantly in their assessments of pre-fire information suggesting that experiences during a fire may retroactively influence views of pre-fire information needs. Overall, findings support that of previous work and highlight the importance of disseminating information in as timely a manner as possible and through sources that allow as much interaction as possible with information providers. [ABSTRACT FROM AUTHOR]

Three alternative construction plans with full highway closures and limited capacity closures (partial closures) are evaluated for a large-scale freeway reconstruction project in the Sacramento metropolitan area. By using a dynamic network analysis tool, the potential impact resulting from different construction plans is estimated and analyzed measured by changes in total demand, travel delays, vehicle miles/hours traveled (VMT/VHT), fuel consumptions, and emissions. The results show that, for this Interstate 5 closure, if only user delay costs are considered, the actual full closure plan is the best. It produces considerably less total system travel delay than the two partial closure plans although it closed more lanes. This plan, however, may induce more VMT than the other two. In fact, the other two partial closure plans produce slightly fewer emissions and consume slightly less fuel. The outcome of which plan comes out on top crucially depends on two other factors, besides the chosen objective: the amount of demand reduction a plan induces and the availability of alternative routes to divert traffic away from the work zone area. Developing efficient demand management measures will be the key to improving the network performance and to reduce the emissions. Moreover, when data are available, construction costs and emissions produced by construction activities should also be included in the evaluations, in addition to the user costs considered in this study. [ABSTRACT FROM AUTHOR]

In this paper, we conduct a systematic study of human-initiated cascading failures in three critical inter-dependent societal infrastructures due to behavioral adaptations in response to a crisis. We focus on three closely coupled socio-technical networks here: (i) cellular and mesh networks, (ii) transportation networks and (iii) mobile call networks. In crises, changes in individual behaviors lead to altered travel, activity and calling patterns, which influence the transport network and the loads on wireless networks. The interaction between these systems and their co-evolution poses significant technical challenges for representing and reasoning about these systems. In contrast to system dynamics models for studying these interacting infrastructures, we develop interaction-based models in which individuals and infrastructure elements are represented in detail and are placed in a common geographic coordinate system. Using the detailed representation, we study the impact of a chemical plume that has been released in a densely populated urban region. Authorities order evacuation of the affected area, and this leads to individual behavioral adaptation wherein individuals drop their scheduled activities and drive to home or pre-specified evacuation shelters as appropriate. They also revise their calling behavior to communicate and coordinate among family members. These two behavioral adaptations cause flash-congestion in the urban transport network and the wireless network. The problem is exacerbated with a few, already occurring, road closures. We analyze how extended periods of unanticipated road congestion can result in failure of infrastructures, starting with the servicing base stations in the congested area. A sensitivity analysis on the compliance rate of evacuees shows non-intuitive effect on the spatial distribution of people and on the loading of the base stations. For example, an evacuation compliance rate of 70% results in higher number of overloaded base stations than the evacuation compliance rate of 90%. [ABSTRACT FROM AUTHOR]

Copyright of International Journal of Urban & Regional Research is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of International Journal of Urban & Regional Research is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Abstract: Forest roads reduce habitat quality for wildlife, in part by increasing susceptibility to hunting and poaching. Road removal is an increasingly common strategy for restoring habitat; however, little is known about responses of wildlife to road removal versus other methods of road closure. We assessed effects of different types of road closure (gated, barriered, and recontoured) on black bear (Ursus americanus) frequency and habitat on 18 open and closed road pairs in the western USA. Over 4years, 44 bears were photographed during 3545 camera-trap days. Bear frequency was significantly higher (2.4 versus 0.6/100days, respectively) and human frequency was significantly lower (2.4 versus 361.6/100days, respectively) on closed than on open roads. Additionally, abundance of fall foods was higher (23.9% and 12.8%, respectively) and line-of-sight (a measure of habitat security) shorter (54.9 versus 69.4m, respectively) on closed compared to open roads. Bears were detected on closed but not on open roads during daytime, suggesting avoidance of humans. Among-road-treatment differences included significantly higher frequency of bears on recontoured than on gated or barriered roads (4.6, 1.6, and 0.5/100days, respectively), and significantly higher cover of fall bear foods on recontoured than on gated or barriered roads (39.3%, 12.1% and 16.4%, respectively). Frequency of bears was negatively correlated with frequency of humans and line-of-sight distance and positively correlated with abundance of fall foods and hiding cover. Results suggest that while all types of road closure benefit sensitive wildlife, removal by recontour may be the most effective strategy for restoring habitat. [Copyright &y& Elsevier]

Managing roads and access on publicly owned forested lands should include assessments of the public's views of desirability for different approaches. To assess the public's views, we explored northeastern Ontario residents' desirability ratings towards approaches that remove, deactivate, or close forest access roads. From a social survey, respondents, on average, rated every restrictive approach as undesirable. From a principal components and cluster analysis, we identified four groups of respondents (open roads, road deactivation, road closure, and sign-based road closure supporters) that differed in their desirability ratings for the approaches. Comparisons of group members by the types and intensity of outdoor recreation use, attitudes towards roads and management, environmental value orientations, and sociodemographic characteristics revealed expected and important differences. On the one hand, almost one half of respondents had high levels of undesirability ratings towards any restrictive approach, suggesting that attempts to restrict road access might be met with stiff opposition. On the other hand, the presence of groups that support road deactivation, sign-based road closures, and general road closures suggests that many other residents might be willing to accept some access restrictions on roads. Consequently, managers must be aware of the heterogeneity in views about access when planning roads and access. [ABSTRACT FROM AUTHOR]

Objective: The road to a headland that had become a suicide jumping hotspot was temporarily closed because of construction work. This created an opportunity to assess whether loss of vehicular access would lead to a reduction in suicides and emergency police callouts for threatened suicide at the site. Method: Deaths at the headland were ascertained for a 10 year period before road closure and for 2 years following closure using records from the local police inquest officer, the coroner's pathologist and Marine Search and Rescue. Police provided a list of police callouts for threatened suicide at the site for a 4 year period before closure and for 2 years following closure. Simple rates were compared and incident rate ratios were calculated where possible. Results: There were 13 deaths at the headland involving suicide or open verdicts in the 10 years before access was restricted, and none in the 2 years following road closure. This difference was statistically significant (incident rate difference = 1.3 deaths per year, 95% confidence interval (CI) = 0.6-2.0). No jumping suicides occurred elsewhere in the police district following the road closure. Police callouts for threatened suicide also fell significantly, from 19.3 per year in the 4 years prior to road closure to 9.5 per year for the following 2 years (incident rate ratio = 2.0, 95%CI = 1.2-3.5). Conclusions: Preventing vehicular access to a suicide jumping hotspot was an effective means of suicide prevention at the site. There was no evidence of substitution to other jumping sites. [ABSTRACT FROM AUTHOR]

Resilient, smart and sustainable: these are the keywords for the next generation of road infrastructures. As a renewable and environment-friendly energy harvesting pavement, the concept of a solar pavement has become one of the most researched new highway transportation infrastructures with a goal to transform the road system from the energy consumer to the energy provider, and eliminate or alleviate pollution from the source of energy. At present, the commercial technology through photovoltaic is limited by space installation requirements, which restricts its popularization and application. On the other hand, applying photovoltaic power generation technology to the pavement can provide sustainable power support for smart transportation in the future. This paper introduces the working principle and basic features of solar cell and solar pavements, and summarizes the research status of solar pavements, highlighting the strengths and weaknesses of different solar pavement structures. The cost-effectiveness of four typical solar pavement structural systems is evaluated, and a case study is presented. Results show that the net present value (NPV) and Levelized cost of electricity (LCOE) of Hollow slab solar pavements are the lowest. Although the benefits deriving from the solar pavements are not enough to cover the cost during 20 years of lifetime, and it would be economically attractive if the LCOE will be lower than 0.2 $/kWh. With review and case study, the study provides a thorough and needed platform for more advances of the concept of solar pavements. • Working principle, research status, strengths and weaknesses of solar pavements. • The cost-effectiveness of four typical solar pavements is evaluated. • The power generation of solar pavements depends on location, climate, traffic and shadow occlusion. • Solar pavements could be economically attractive if the LCOE would be lower than 0.2 $/kWh. [ABSTRACT FROM AUTHOR]