Choosing to drive from alcohol serving establishments (ASEs).

OBJECTIVE: The prevalence of Driving Under the Influence (DUI) of alcohol or drugs has become a prominent factor in the occurrence of severe road crashes worldwide. Driving often occurs after visiting, and presumably drinking, at Alcohol-Serving Establishments (ASEs), and is thus of interest as a possible source of DUI events. METHODS: We apply statistical and machine learning models to the Victorian Integrated Survey of Travel and Activity (VISTA) to identify factors that contribute to driving in trips from ASEs in Australia's state of Victoria. RESULTS: Our results highlight that approximately 10% of individuals who traveled to ASEs as car passengers switched to driving after leaving there. It was also observed that travel distance shorter than 1 km and activity duration between 3 and 4 h positively impacts the mode switching from car driver to other modes in ASEs trips. Further findings illustrate a decline in driving after midnight, with an increase in the use of public transport and taxis. Individuals prefer driving for long-distance ASEs trips and walking for short distances. Going home also increased the likelihood of driving, whereas engaging in other social activities did not. Longer stays at ASEs and leaving vehicles overnight reduce the propensity to drive, likely due to increased alcohol consumption during these times. CONCLUSIONS: These findings suggest behavioral adjustments that can mitigate driving under the influence. Specifically, people may walk for short-distance trips and use public transport or taxis for longer ASEs trips.

The racial composition of road users, traffic citations, and police stops.

This paper exploits the potential of Global Positioning System datasets sourced from mobile phones to estimate the racial composition of road users, leveraging data from their respective Census block group. The racial composition data encompasses approximately 46 million trips in the Chicago metropolitan region. The research focuses on the relationship between camera tickets and racial composition of drivers vs. police stops for traffic citations and the racial composition in these locations. Black drivers exhibit a higher likelihood of being ticketed by automated speed cameras and of being stopped for moving violations on roads, irrespective of the proportion of White drivers present. The research observes that this correlation attenuates as the proportion of White drivers on the road increases. The citation rate measured by cameras better matches the racial composition of road users on the links with cameras than do stops by police officers. This study therefore presents an important contribution to understanding racial disparities in moving violation stops, with implications for policy interventions and social justice reforms.

Scheduling optimisation of alcohol test sites.

Drink driving is an infamous factor in road crashes and fatalities. Alcohol testing is a major countermeasure, and random breath tests (RBTs) deter tested drivers and passersby (observers who are not tested). We propose a genetic algorithm (GA)-based RBT scheduling optimisation method to achieve maximal deterrence of drink driving. The RBT schedule denotes the daily plan of where, when, and for how long tests should occur in the road network. The test results (positive and negative) and observing drivers are considered in the fitness function. The limited testing resource capacity is modeled by a number of constraints that consider the total duration of tests, the minimum and maximum duration of a single test site, and the total number of test sites during the day. Clustering of the alcohol-related crash data is used to estimate the matrix for drink driving on the scheduled day. The crash data and traffic flow data from Victoria, Australia are analysed and used to describe sober/drink driving. A detailed synthetic example is developed and a significant improvement with 150% more positive results and 59% more overall tests is observed using the proposed scheduling optimisation method.

The angiogenic growth of cities.

Describing the space-time evolution of urban population is a fundamental challenge in the science of cities, yet a complete theoretical treatment of the underlying dynamics is still missing. Here, we first reconstruct the evolution of London (UK) over 180 years and show that urban growth consists of an initial phase of diffusion-limited growth, followed by the development of the railway transport network and a consequential shift from central to suburban living. Such dynamics-which are analogous to angiogenesis in biological systems-can be described by a minimalist reaction-diffusion model coupled with economic constraints and an adaptive transport network. We then test the generality of our approach by reproducing the evolution of Sydney, Australia, from 1851 to 2011. We show that the rail system coevolves with urban population, displaying hierarchical characteristics that remain constant over time unless large-scale interventions are put in place to alter the modes of transport. These results demonstrate that transport schemes are first-order controls of long-term urbanization patterns and efforts aimed at creating more sustainable and healthier cities require careful consideration of population-transport feedbacks.

Creating a dataset of historic roads in Sydney from scanned maps.

This study creates a historic dataset of road opening dates in Sydney. A method was developed for map digitization to extract spatial data from historic maps and place them in a collective vector layer. The method includes extensive georeferencing of the maps, as well as editing and cleaning the maps through raster and vector analysis. Preferred methods for map digitization used in the project were identified. For a considerable area of Sydney, in which approximately 52000 road links were included, almost half of the links were identified with an open date by the start of the twentieth century. A further half of these links were confined to opening within a thirty-year period. The project has established a strong foundation for a historic road dataset for Sydney. It has also outlined methods and procedures that can be followed to progress the dataset further.

Improving access to extracorporeal membrane oxygenation for out of hospital cardiac arrest: pre-hospital ECPR and alternate delivery strategies.

BACKGROUND: The use of extracorporeal membrane oxygenation (ECPR) in refractory out-of-hospital cardiac arrest (OHCA) patients is usually implemented in-hospital. As survival in ECPR patients is critically time-dependent, alternative models in ECPR delivery could improve equity of access. OBJECTIVES: To identify the best strategy of ECPR delivery to provide optimal patient access, to examine the time-sensitivity of ECPR on predicted survival and to model potential survival benefits from different delivery strategies of ECPR. METHODS: We used transport accessibility frameworks supported by comprehensive travel time data, population density data and empirical cardiac arrest time points to quantify the patient catchment areas of the existing in-hospital ECPR service and two alternative ECPR strategies: rendezvous strategy and pre-hospital ECPR in Sydney, Australia. Published survival rates at different time points to ECMO flow were applied to predict the potential survival benefit. RESULTS: With an in-hospital ECPR strategy for refractory OHCA, five hospitals in Sydney (Australia) had an effective catchment of 811,091 potential patients. This increases to 2,175,096 under a rendezvous strategy and 3,851,727 under the optimal pre-hospital strategy. Assuming earlier provision of ECMO flow, expected survival for eligible arrests will increase by nearly 6% with the rendezvous strategy and approximately 26% with pre-hospital ECPR when compared to the existing in-hospital strategy. CONCLUSION: In-hospital ECPR provides the least equitable access to ECPR. Rendezvous and pre-hospital ECPR models substantially increased the catchment of eligible OHCA patients. Traffic and spatial modelling may provide a mechanism to design appropriate ECPR service delivery strategies and should be tested through clinical trials.

A bifurcation of the peak: new patterns of traffic peaking during the COVID-19 era.

This paper analyzes the emergence of two well-defined peaks during the morning peak period in the traffic flow diurnal curve. It selects six California cities as research targets, and uses California employment and household travel survey data to explain how and why this phenomenon has risen during the pandemic. The final result explains that the double-humped phenomenon results from the change in the composition of commuters during the morning peak period after the outbreak.

The relation of visual perception of speed limits and the implementation of cycle lanes - a cross-country comparison.

Speed plays a key role in road safety research. Recent studies have indicated an association between speed limits and driving behaviour. However, less attention has been paid to the role of context in the perception of speed limits, and the way cycle lanes influence this perception. This study examines how respondents in different countries of residence perceive speed limits, and how cycle lanes influence their perception of speed limits. An online survey provided quantitative data for a cross-country comparison from 1591 respondents in Australia, the Netherlands, and the United Kingdom. The findings show that country of residence influences the way speed limits are perceived, and cycle lanes are interpreted distinctly. In locations where cycle lanes are common, they act as indicators of either lower or higher speed limits, while in countries with less familiarity with cycle lanes respondents associate cycle lanes only with lower speed limits. Suggesting a safer and broader understanding of cycle lanes where they are familiar (the Netherlands) and a narrower understanding where cycle lanes are not common (Australia and the United Kingdom), this study provides evidence for policymakers explaining resistance to implementing cycle lanes and implies that implementing lower speed limits and cycle lanes are a road safety measure. Suggestions are identified for future research.

Feasibility of a virtual reality-based approach to improve behavioral weight management outcomes.

BACKGROUND: Behavioral weight loss interventions promote clinically significant weight loss over 12 months, but weight regain remains problematic and a substantial proportion of participants do not achieve long-term weight loss maintenance. Novel methods are needed that instill habit strength for sustaining weight control behaviors long term. Virtual reality (VR) has the potential to provide opportunities within behavioral treatment for patients to practice desired weight control behaviors in the frequency and magnitude necessary to build durable habits. A pilot randomized trial was done to test the feasibility integrating virtual reality (VR) into standard behavioral weight loss treatment. METHODS: Participants were 15 adults (43 years; 46.7% Hispanic), with overweight or obesity who were randomly assigned to a 4-week Standard Behavioral Weight Loss plus Non-Weight-Related VR app (i.e., Control Group) or Standard Behavioral Weight Loss plus Weight-Related VR app (i.e., Intervention Group). The Intervention's VR tool was designed to enable practice of behavioral skills taught in weekly group meetings, including managing social and home environmental cues for eating and activity. RESULTS: Participants were recruited over 3 months, and retention at the final assessment visit was high (86.6%). The VR footage and resulting app were rated as highly realistic (6.7 on a 10-point scale), and the VR program overall was rated as highly satisfactory (3.6 on a 4-point scale). Adverse effects of eye strain and motion sickness were minimal (~ 2 on a 7-point scale). As expected, the intervention and control groups both lost weight and unadjusted means (SD) averaged 3.4% (2.7) and 2.3% (3.6), respectively, over the 4 weeks. Overall, participants reported preferring a VR approach above traditional weight loss programs (rating of 5 on a 7-point scale). CONCLUSIONS: Future research is needed to develop and test the feasibility of using VR for other weight control skills with a larger sample size and longer evaluation period to determine if VR can improve standard behavioral weight loss outcomes by intensifying practice opportunities and building habit strength for weight loss maintenance. TRIAL REGISTRATION: NCT04534088 ; date of registration: 09/01/2020, retrospectively registered.

An energy loss-based vehicular injury severity model.

How crashes translate into physical injuries remains controversial. Previous studies recommended a predictor, Delta-V, to describe the crash consequences in terms of mass and impact speed of vehicles in crashes. This study adopts a new factor, energy loss-based vehicular injury severity (ELVIS), to explain the effects of the energy absorption of two vehicles in a collision. This calibrated variable, which is fitted with regression-based and machine learning models, is compared with the widely-used Delta-V predictor. A multivariate ordered logistic regression with multiple classes is then estimated. The results align with the observation that heavy vehicles are more likely to have inherent protection and rigid structures, especially in the side direction, and so suffer less impact.

Measures of speeding from a GPS-based travel behavior survey.

OBJECTIVE: Lacking information about actual driving speed on most roads in the Minneapolis-St. Paul region, we determine car speeds using observations from a Global Positioning System (GPS)-based travel survey. Speed of travel determines the likelihood and consequences of collisions. We identify the road segments where speeding occurs. This article then analyzes the relationship between link length, traveler characteristics, and speeding using GPS data collected from 152 individuals over a 7-day period as part of the Minneapolis-St. Paul Travel Behavior Inventory. METHODS: To investigate the relationship, we employed an algorithm and process to accurately match the GPS data with geographic information system (GIS) databases. Comparing actual travel speed from GPS data with posted speed limits, we measure where and when speeding occurs and by whom. We posit that link length and demographics shape the decision to speed. RESULTS: Speeding is widespread under both high speed limits (e.g., 60 mph [97 km/h]) and low speed limits (less than 25 mph [40 km/h]); in contrast, speeding is less common at 30-35 mph (48-56 km/h). The results suggest that driving patterns depend on the road type. We also find that when there are many intersections, the average link speed (and speeding) drops. Long links are conducive to speeding. Younger drivers and more educated drivers also speed more, and speeding occurs more often in the evening. CONCLUSIONS: Road design and link length (or its converse, frequency of intersections) affect the likelihood of speeding. Use of increasingly available GPS data allows more systematic empirical analysis of designs and topologies that are conducive to road safety.

Tracking job and housing dynamics with smartcard data.

Residential locations, the jobs-housing relationship, and commuting patterns are key elements to understand urban spatial structure and how city dwellers live. Their successive interaction is important for various fields including urban planning, transport, intraurban migration studies, and social science. However, understanding of the long-term trajectories of workplace and home location, and the resulting commuting patterns, is still limited due to lack of year-to-year data tracking individual behavior. With a 7-y transit smartcard dataset, this paper traces individual trajectories of residences and workplaces. Based on in-metro travel times before and after job and/or home moves, we find that 45 min is an inflection point where the behavioral preference changes. Commuters whose travel time exceeds the point prefer to shorten commutes via moves, while others with shorter commutes tend to increase travel time for better jobs and/or residences. Moreover, we capture four mobility groups: home mover, job hopper, job-and-residence switcher, and stayer. This paper studies how these groups trade off travel time and housing expenditure with their job and housing patterns. Stayers with high job and housing stability tend to be home (apartment unit) owners subject to middle- to high-income groups. Home movers work at places similar to stayers, while they may upgrade from tenancy to ownership. Switchers increase commute time as well as housing expenditure via job and home moves, as they pay for better residences and work farther from home. Job hoppers mainly reside in the suburbs, suffer from long commutes, change jobs frequently, and are likely to be low-income migrants.

Evaluating the Safety In Numbers effect for pedestrians at urban intersections.

Assessment of collision risk between pedestrians and automobiles offers a powerful and informative tool in urban planning applications, and can be leveraged to inform proper placement of improvements and treatment projects to improve pedestrian safety. Such assessment can be performed using existing datasets of crashes, pedestrian counts, and automobile traffic flows to identify intersections or corridors characterized by elevated collision risks to pedestrians. The Safety In Numbers phenomenon, which refers to the observable effect that pedestrian safety is positively correlated with increased pedestrian traffic in a given area (i.e. that the individual per-pedestrian risk of a collision decreases with additional pedestrians), is a readily observed phenomenon that has been studied previously, though its directional causality is not yet known. A sample of 488 intersections in Minneapolis were analyzed, and statistically-significant log-linear relationships between pedestrian traffic flows and the per-pedestrian crash risk were found, indicating the Safety In Numbers effect. Potential planning applications of this analysis framework towards improving pedestrian safety in urban environments are discussed.

Using temporal detrending to observe the spatial correlation of traffic.

This empirical study sheds light on the spatial correlation of traffic links under different traffic regimes. We mimic the behavior of real traffic by pinpointing the spatial correlation between 140 freeway traffic links in a major sub-network of the Minneapolis-St. Paul freeway system with a grid-like network topology. This topology enables us to juxtapose the positive and negative correlation between links, which has been overlooked in short-term traffic forecasting models. To accurately and reliably measure the correlation between traffic links, we develop an algorithm that eliminates temporal trends in three dimensions: (1) hourly dimension, (2) weekly dimension, and (3) system dimension for each link. The spatial correlation of traffic links exhibits a stronger negative correlation in rush hours, when congestion affects route choice. Although this correlation occurs mostly in parallel links, it is also observed upstream, where travelers receive information and are able to switch to substitute paths. Irrespective of the time-of-day and day-of-week, a strong positive correlation is witnessed between upstream and downstream links. This correlation is stronger in uncongested regimes, as traffic flow passes through consecutive links more quickly and there is no congestion effect to shift or stall traffic. The extracted spatial correlation structure can augment the accuracy of short-term traffic forecasting models.

Measuring the transportation needs of people with developmental disabilities: A means to social inclusion.

BACKGROUND: One of the major causes of social exclusion for people with developmental disability (PDD) is the inability to access different activities due to inadequate transportation services. OBJECTIVE: This research paper identifies transportation needs, and reasons for unmet, but desired untaken trips of adults with developmental disabilities in Hennepin County, Minnesota. We hypothesize that PDD cannot make trips they want to make due to personal and neighborhood characteristics. METHODS: A survey measuring existing travel behavior and unmet transportation needs of PDD (N = 114) was conducted. The survey included both demographic and attitudinal questions as well as a travel diary to record both actual and desired but untaken trips. Logistic regression analyses were conducted to determine reasons associated with their inability to make desired, but untaken trips. RESULTS: Most respondents did not live independently. More than half of the surveyed population worked every day and recreation trips occurred at least once a week for about two-thirds of the population. About 46% were unable to make trips they needed to make. Public transit posed physical and intellectual difficulties, however the presence of public transit in neighborhoods decreased odds of not making trips. Concerns about Paratransit services were also reported. CONCLUSION: Findings from this study can be of value to transportation engineers and planners interested in shedding light on the needs of a marginalized group that is rarely studied and have special transport needs that should be met to ensure their social inclusion in society.

Towards a Metropolitan Fundamental Diagram Using Travel Survey Data.

Using travel diary data from 2000-2001 and 2010-2012 this research examines fundamental traffic relationships at the metropolitan level. The results of this paper can help to explain the causes of some traffic phenomena. Network average speed by time of day can be explained by trip length and cumulative number of vehicles on the road. A clockwise hysteresis loop is found in the Metropolitan Fundamental Diagram in the morning period and a reverse process happens in the afternoon.

Do people use the shortest path? An empirical test of Wardrop's first principle.

Most recent route choice models, following either the random utility maximization or rule-based paradigm, require explicit enumeration of feasible routes. The quality of model estimation and prediction is sensitive to the appropriateness of the consideration set. However, few empirical studies of revealed route characteristics have been reported in the literature. This study evaluates the widely applied shortest path assumption by evaluating routes followed by residents of the Minneapolis-St. Paul metropolitan area. Accurate Global Positioning System (GPS) and Geographic Information System (GIS) data were employed to reveal routes people used over an eight to thirteen week period. Most people did not choose the shortest path. Using three weeks of that data, we find that current route choice set generation algorithms do not reveal the majority of paths that individuals took. Findings from this study may guide future efforts in building better route choice models.

Network structure and travel time perception.

The purpose of this research is to test the systematic variation in the perception of travel time among travelers and relate the variation to the underlying street network structure. Travel survey data from the Twin Cities metropolitan area (which includes the cities of Minneapolis and St. Paul) is used for the analysis. Travelers are classified into two groups based on the ratio of perceived and estimated commute travel time. The measures of network structure are estimated using the street network along the identified commute route. T-test comparisons are conducted to identify statistically significant differences in estimated network measures between the two traveler groups. The combined effect of these estimated network measures on travel time is then analyzed using regression models. The results from the t-test and regression analyses confirm the influence of the underlying network structure on the perception of travel time.

State of virtual reality based disaster preparedness and response training.

The advent of technologically-based approaches to disaster response training through Virtual Reality (VR) environments appears promising in its ability to bridge the gaps of other commonly established training formats. Specifically, the immersive and participatory nature of VR training offers a unique realistic quality that is not generally present in classroom-based or web-based training, yet retains considerable cost advantages over large-scale real-life exercises and other modalities and is gaining increasing acceptance. Currently, numerous government departments and agencies including the U.S. Department of Homeland Security (DHS), the Centers for Disease Control and Prevention (CDC) as well as academic institutions are exploring the unique advantages of VR-based training for disaster preparedness and response. Growing implementation of VR-based training for disaster preparedness and response, conducted either independently or combined with other training formats, is anticipated. This paper reviews several applications of VR-based training in the United States, and reveals advantages as well as potential drawbacks and challenges associated with the implementation of such training platform.

A typical bilateral Toxoplasma retinochoroiditis in a bone marrow transplant patient with negative serum titers.

BACKGROUND: Toxoplasma retinochoroiditis can have an atypical presentation and be difficult to diagnose in immunocompromised patients. Accurate diagnosis and appropriate treatment is important since the disease can be aggressive in these patients. This paper is a case report with literature review, emphasizing on the diagnosis and treatment of Toxoplasma retinochoroiditis. FINDINGS: A 27-year-old male with chronic myelogenous leukemia with history of bone marrow transplantation presented with floaters in his right eye. Fundus exam showed bilateral, multifocal retinochoroiditis with subsequent development of a mild vitritis. Serum cytomegalovirus and toxoplasmosis antibody titers and syphilis screen were negative. Aqueous polymerase chain reaction (PCR) analysis revealed the presence of Toxoplasma gondii DNA OU. Clindamycin (1.0 mg/0.1 mL) was injected bilateral intravitreal OU twice at 4 days apart with subsequent resolution of retinochoroiditis. CONCLUSIONS: When evaluating retinochoroiditis in an immunocompromised patient, one must keep a high index of suspicion for atypical presentations of well-known disease entities. Aqueous and vitreous samples for PCR can be useful in obtaining an accurate diagnosis and therefore provide appropriate management for the patient. Intravitreal clindamycin is an option for treatment in these patients.