Multi-object urban dataset: A resource for detecting pedestrians, traffic and motorbikes.

This article describes a dataset comprising 16,426 real-world urban photographs, capturing vehicles, cyclists, motorbikes, and pedestrians across Morning, Evening, and Night scenes. The dataset is valuable for machine learning tasks in traffic analysis, urban planning, and public safety. It enables the development and validation of algorithms for pedestrian detection, traffic flow analysis, and infrastructure optimization. Our main goal is to assist academics, urban planners, and decision-makers in creating sophisticated models for pedestrian safety, traffic control, and accident avoidance. This dataset is a useful resource for training and verifying algorithms targeted at boosting real-time traffic monitoring systems, optimizing urban infrastructure, and raising overall road safety because of its high variability and significant volume. This dataset represents a major advancement for smart city projects and the creation of intelligent transportation systems.

Cyclist safety around trams: A market survey.

Tram systems present safety risks to cyclists, however only limited research has explored this topic, of which most has focused on crash and hospital data, and severe crash events. This paper presents the first known cyclist market survey focused specifically on the experience of cyclists related to safety around trams, including unreported incidents and those that did not result in hospital attendance. Findings suggest that track-skid incidents are more common than track-wedge incidents, in contrast to previous research that emphasizes track-wedging as a larger issue than skidding. This is may be explained by the differing outcomes, with track-wedging more likely to result in injury. This research is thus significant in identifying track skidding as a major risk concern, causing a majority of crashes, while also confirming that track wedging is the major severity concern. In the last five years, 21% of respondents were involved in at least one tram-track-related crash. This was less than the share of respondents involved in falls (50%), crashes relating to road defects (36%) or collisions with motor vehicles (29%). However, half of survey respondents (52%) reported cycling on roads with tram tracks for 0-20% of their cycling, which might suggest that tram track-related crash rates are high given that most inner-city cycling occurs on roads without tracks. Track-skidding was found to be associated with wet conditions. Those involved in at least one track-skid in the last five years where more likely to have been cycling more than 3 years, but involvement in track-wedging was more likely amongst those cycling > 10 years and aged < 45 years. Implications for research and practice are suggested.

"Cyclist at 12 o'clock!": a systematic review of in-vehicle advanced driver assistance systems (ADAS) for preventing car-rider crashes.

Introduction: While Advanced Driver Assistance Systems (ADAS) have become a prominent topic in road safety research, there has been relatively little discussion about their effectiveness in preventing car collisions involving specific vulnerable road users, such as cyclists. Therefore, the primary objective of this systematic literature review is to analyze the available evidence regarding the effectiveness of in-vehicle ADAS in preventing vehicle collisions with cyclists. Methods: To achieve this goal, this systematic review analyzed a selection of original research papers that examined the effectiveness of ADAS systems in preventing car-cyclist collisions. The review followed the PRISMA protocol, which led to the extraction of 21 eligible studies from an initial pool of 289 sources indexed in the primary scientific literature databases. Additionally, word community-based content analyses were used to examine the research topics and their links within the current scientific literature on the matter. Results: Although the current number of studies available is still scarce (most sources focus on car-motorcyclist or car-pedestrian crashes), the overall quality of the available studies has been reasonably good, as determined by the selected evaluation methods. In terms of studies' outcomes, the literature supports the value of in-vehicle ADAS for preventing car-cyclist crashes. However, threatful side effects such as unrealistic expectations of these systems and users' overconfidence or desensitization are also highlighted, as well as the need to increase driver training and road user awareness. Conclusion: The results of this study suggest that Advanced Driver Assistance Systems have significant potential to contribute to the prevention of driving crashes involving cyclists. However, the literature emphasizes the importance of concurrently enhancing user-related skills in both ADAS use and road-user interaction through educational and training initiatives. Future research should also address emerging issues, such as ADAS-related behavioral ergonomics, and conduct long-term effectiveness assessments of ADAS in preventing car-cycling crashes and their subsequent injuries. Systematic review registration: PROSPERO, unique identifier CRD42024505492, https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=505492.

Enhancing Urban Mobility with Self-Tuning Fuzzy Logic Controllers for Power-Assisted Bicycles in Smart Cities.

In smart cities, bicycle-sharing systems have become an essential component of the transportation services available in major urban centers around the globe. Due to environmental sustainability, research on the power-assisted control of electric bikes has attracted much attention. Recently, fuzzy logic controllers (FLCs) have been successfully applied to such systems. However, most existing FLC approaches have a fixed fuzzy rule base and cannot adapt to environmental changes, such as different riders and roads. In this paper, a modified FLC, named self-tuning FLC (STFLC), is proposed for power-assisted bicycles. In addition to a typical FLC, the presented scheme adds a rule-tuning module to dynamically adjust the rule base during fuzzy inference processes. Simulation and experimental results indicate that the presented self-tuning module leads to comfortable and safe riding as compared with other approaches. The technique established in this paper is thought to have the potential for broader application in public bicycle-sharing systems utilized by a diverse range of riders.

Variation the in relationship between urban tree canopy and air temperature reduction under a range of daily weather conditions.

Mitigating heat is a vital ecosystem service of trees, particularly with climate change. Land surface temperature measures captured at a single time of day (in the morning) dominate the urban heat island literature. Less is known about how local tree canopy and impervious surface regulate air temperature throughout the day, and/or across many days with varied weather conditions, including cloud cover. We use bike-mounted air temperature sensors throughout the day in New Haven, Connecticut, USA, from 2019 to 2021 and generalized additive mixed models across 156 rides to estimate the daily variation in cooling benefits associated with tree canopy cover, and warming from impervious surface cover in 90 m buffers surrounding bike observations. Cooling is inferred by subtracting the bicycle-observed temperature from a reference station. The cooling benefits from tree canopy cover were strongest in the midday (11:00-14:00, -1.62 °C), afternoon (14:00-17:00, -1.19 °C), and morning (8:00-11:00, -1.15 °C) on clear days. The cooling effect was comparatively smaller on cloudy mornings -0.92 °C and afternoons -0.51 °C. Warming from impervious surfaces was most pronounced in the evening (17:00-20:00, 1.11 °C) irrespective of clouds, and during cloudy nights (20:00-23:00) and cloudy mornings 1.03 °C 95 % CI [1.03, 1.04]. Among the hottest observed days (top 25th percentile of reference station daily maxima), tree canopy was associated with lower temperatures on clear afternoons -1.78 °C [-1.78, -1.78], cloudy midday -1.17 °C [-1.19, -1.15], clear midday -1.12 °C [-1.12, -1.11]. We add a broader spectrum of weather conditions by explicitly including clouds, and greater temporal resolution by measuring throughout the day to bike-based urban heat research. Future mobile sampling campaigns may broaden the spatial extent with more environmental variation, representing an opportunity for public science and engagement.

A cooperative optimization method for the layout of shared bicycle parking areas and delivery quantity.

With the popularity of shared bicycles in urban areas, more and more residents choose this fast and convenient mode of transportation for short-distance travel. By optimizing the layout of shared bicycle parking areas and delivery quantity, the investment cost of shared bicycle enterprises can be effectively reduced, and the convenience of residents' travel can be improved at the same time. In this paper, we develop a collaborative optimization model for the layout of the shared bicycle parking area and delivery quantity, aiming at minimizing the walking distance of residents and the investment cost of enterprises, while considering the constraints of the parking area's attractive range and the number of bicycles placed. Aiming at the characteristics of this mixed integer nonlinear problem, an improved genetic algorithm incorporating symmetric individual precision control mechanism is designed. Finally, taking the planned area between the Second Ring Road and the Third Ring Road in the northern part of Jin-niu District, Chengdu as the background, the proposed collaborative optimization model for the layout of shared bicycle parking areas and delivery quantity is applied to a real scene. The results show that after optimization, the number of parking areas is reduced by 2, and the total investment cost is reduced by about 12.2%.

Remote 1,4-Carbon-to-Carbon Boryl Migration: From a Mechanistic Challenge to a Valuable Synthetic Application of Bicycles.

The present paper reports a remote carbon-to-carbon boryl migration via an intramolecular 1,4-B/Cu shift, which establishes an in situ stereospecific electrophilic trap on the alkene moiety. The synthetic application is developed to prepare functionalized cyclopentenes by means of a palladium-catalyzed regioselective intramolecular coupling that completes a strategic cyclopropanation and generates valuable structural bicyclic systems. The mechanism is characterized by DFT (density functional theory) calculations which showed that the 1,4-migration proceeds through an intramolecular, nucleophilic attack of the copper-alkyl moiety on the boron atom bonded to the C(sp2), leading to a 5-membered boracycle structure. The computation of the 1,3- and 1,4-B/Cu shifts is also compared as is the impact of the endo- or exocyclic alkene on the reaction kinetics.

Cell-Penetrating Peptide-Bismuth Bicycles.

Cell-penetrating peptides (CPPs) play a significant role in the delivery of cargos into human cells. We report the first CPPs based on peptide-bismuth bicycles, which can be readily obtained from commercially available peptide precursors, making them accessible for a wide range of applications. These CPPs enter human cells as demonstrated by live-cell confocal microscopy using fluorescently labelled peptides. We report efficient sequences that demonstrate increased cellular uptake compared to conventional CPPs like the TAT peptide (derived from the transactivating transcriptional activator of human immunodeficiency virus 1) or octaarginine (R8 ), despite requiring only three positive charges. Bicyclization triggered by the presence of bismuth(III) increases cellular uptake by more than one order of magnitude. Through the analysis of cell lysates using inductive coupled plasma mass spectrometry (ICP-MS), we have introduced an alternative approach to examine the cellular uptake of CPPs. This has allowed us to confirm the presence of bismuth in cells after exposure to our CPPs. Mechanistic studies indicated an energy-dependent endocytic cellular uptake sensitive to inhibition by rottlerin, most likely involving macropinocytosis.

Alternations of antibiotic resistance genes and microbial community dynamics on shared bicycles before and after pandemic lockdown.

The prevalence of shared bicycles has raised concerns over their potential to transmit pathogens and microbes harboring antibiotic resistance genes (ARGs), which pose significant human health risks. This study investigated the impact of anthropogenic activities on the composition of ARGs and microbial communities on shared bicycles during the COVID-19 pandemic and subsequent lockdown when shared bicycle usage was altered. A total of 600 swab samples from shared bicycle surfaces were collected in Shanghai before and during COVID-19 lockdown periods. Even during lockdown, 12 out of 14 initially detected ARG subtypes persisted, indicating their tenacity in the face of reduced anthropogenic activities. These ARGs displayed significantly higher absolute and relative abundance levels before the lockdown. In addition, the percentage of potential pathogens in the total microbial abundance remained at 0.029 % during the lockdown, which was lower than the pre-lockdown percentage of 0.035 % and suggested that these risks persist within shared bicycle systems. Interestingly, although microbial abundance decreased without the consecutive use of shared bicycles during lockdown, the microbial diversity increased under the impact of restricted anthropogenic activities (p < 0.001). This emphasizes the need for continuous monitoring and research to comprehend microbial community behaviors in various environments. This study uncovered the underlying impacts of the COVID-19 lockdown on the microbial and ARG communities of shared bicycles, providing comprehensive insights into the health management of shared transportation. Although lockdown can decrease the abundance of ARGs and potential pathogens, additional interventions are needed to prevent their continued spread.

Modeling collision avoidance maneuvers for micromobility vehicles.

INTRODUCTION: In recent years, as novel micromobility vehicles (MMVs) have hit the market and rapidly gained popularity, new challenges in road safety have also arisen. There is an urgent need for validated models that comprehensively describe the behavior of such novel MMVs. This study aims to compare the longitudinal and lateral control of bicycles and e-scooters in a collision-avoidance scenario from a top-down perspective, and to propose appropriate quantitative models for parameterizing and predicting the trajectories of the avoidance-braking and steering-maneuvers. METHOD: We compared a large e-scooter and a light e-scooter with a bicycle (in assisted and non-assisted modes) in field trials to determine whether these new vehicles have different maneuverability constraints when avoiding a rear-end collision by braking and/or steering. RESULTS: Braking performance in terms of deceleration and jerk varies among the different types of vehicles; specifically, e-scooters are not as effective at braking as bicycles, but the large e-scooter demonstrated better braking performance than the light one. No statistically significant difference was observed in the steering performance of the vehicles. Bicycles were perceived as more stable, maneuverable, and safe than e-scooters. The study also presents arctangent kinematic models for braking and steering, which demonstrate better accuracy and informativeness than linear models. CONCLUSIONS: This study demonstrates that the new micromobility solutions have some maneuverability characteristics that differ significantly from those of bicycles, and even within their own kind. Steering could be a more efficient collision-avoidance strategy for MMVs than braking under certain circumstances, such as in a rear-end collision. More complicated modeling for MMV kinematics can be beneficial but needs validation. PRACTICAL APPLICATIONS: The proposed arctangent models could be used in new advanced driving assistance systems to prevent crashes between cars and MMV users. Micromobility safety could be improved by educating MMV riders to adapt their behavior accordingly. Further, knowledge about the differences in maneuverability between e-scooters and bicycles could inform infrastructure design, and traffic regulations.

Electric bicycles (e-bikes) are an increasingly common pediatric public health problem.

Purpose: Electric bicycles (e-bikes) achieve higher speeds than pedal bicycles, but few studies have investigated the impact on injury rates specific to the pediatric population. Utilizing the National Electronic Injury Surveillance System (NEISS), we compared rates of pediatric injury for e-bikes, bicycles, and gas-engine bicycles (mopeds) from 2011 to 2020. Methods: Descriptive and bivariate inferential analyses were performed upon NEISS estimates of e-bike, bicycle, and moped injuries in children aged 2-18 years. Analyses were stratified by patient age and helmet usage. The Mann-Kendall test of trends was used. Results: We identified 3945 e-bike, 23,389 moped, and 2.05 million bicycle injuries. Over time, the incidence of injury increased for e-bikes (Kendall's τ=0.73, p = 0.004), decreased for pedal bicycles (Kendall's τ= - 0.91, p = 0.0003), and did not change for mopeds (Kendall's τ = 0.06, p = 0.85). Males accounted for 82.5 % of e-bike injuries. The age group most commonly affected by e-bike injury (44.3 %) was 10-13 years old. The proportion of injuries requiring hospitalization was significantly higher for e-bikes (11.5 %), compared to moped and bicycle (7.0 and 4.8 %, respectively, p < 0.0001). In cases where helmet use or absence was reported, 97.3 % of e-bike riders were without a helmet at the time of injury, compared to 82.1 % of pedal bicycle riders and 87.2 % of moped riders. Conclusions: The rate of pediatric e-bike injuries increased over the study period. Compared to riders on pedal bicycles or mopeds, children on e-bikes had infrequent helmet use and increased rate of hospitalization. These findings suggest that attention to e-bike safety and increasing helmet usage are important to public health among the pediatric population. Level of evidence: IV.

Impacts of the COVID-19 Pandemic on Pedestrian Push-Button Utilization and Pedestrian Volume Model Accuracy in Utah.

This work investigated the impacts of COVID-19 on pedestrian behavior, answering two research questions using pedestrian push-button data from Utah traffic signals: How did push-button utilization change during the early pandemic, owing to concerns over disease spread through high-touch surfaces? How did the accuracy of pedestrian volume estimation models (developed pre-COVID based on push-button traffic signal data) change during the early pandemic? To answer these questions, we first recorded videos, counted pedestrians, and collected push-button data from traffic signal controllers at 11 intersections in Utah in 2019 and 2020. We then compared changes in push-button presses per pedestrian (to measure utilization), as well as model prediction errors (to measure accuracy), between the two years. Our first hypothesis of decreased push-button utilization was partially supported. The changes in utilization at most (seven) signals were not statistically significant; yet, the aggregate results (using 10 of 11 signals) saw a decrease from 2.1 to 1.5 presses per person. Our second hypothesis of no degradation of model accuracy was supported. There was no statistically significant change in accuracy when aggregating across nine signals, and the models were actually more accurate in 2020 for the other two signals. Overall, we concluded that COVID-19 did not significantly deter people from using push-buttons at most signals in Utah, and that the pedestrian volume estimation methods developed in 2019 probably do not need to be recalibrated to work for COVID conditions. This information may be useful for public health actions, signal operations, and pedestrian planning.

Pedestrians and the Built Environment during the COVID-19 Pandemic: Changing Relationships by the Pandemic Phases in Salt Lake County, Utah, U.S.A.

The COVID-19 pandemic has dramatically altered people's travel behavior, in particular outdoor activities, including walking. Their behavior changes may have prolonged effects after the pandemic, and such changes vary by the context and are related to the characteristics of the built environment. But empirical studies about the relationships between pedestrians and the built environment during the pandemic are lacking. This study explores how COVID-19 and related travel restrictions have affected the relationship between pedestrian traffic volume and the built environment. We estimate daily pedestrian volumes for all signalized intersections in Salt Lake County, Utah, U.S.A., from pedestrian push-button log data between January 2019 and October 2020. Multilevel spatial filtering models show that the COVID-19 pandemic has altered the relationship between pedestrian traffic volume and the built environment. During the pandemic, the higher the number of COVID-19 cases, the less (or more negative) the effects of density, street connectivity, and destination accessibility on pedestrian volume being observed. The exception is access to urban parks, as it became more significant in increasing pedestrian activities during the pandemic. The models also highlight the negative impacts of the pandemic in economically disadvantaged areas. Our findings could help urban and transportation planners find effective interventions to promote active transportation and physical activity amid the global pandemic.

On the Effect of COVID-19 on Drivers' Behavior: A Survey Study.

COVID-19 had a disruptive effect on the global community. This study looks at the effects that the stringent lockdown measures enacted in March 2020 had on motorists' driving patterns. In particular, given the greater portability of remote working associated with the drastic decline in personal mobility, it is hypothesized that these may have served as accelerators for distracted and aggressive driving. To answer these questions, an online survey was conducted in which 103 respondents were asked to report on their own and other drivers' driving behavior. While respondents agreed they drove less frequently, they also indicated that they were not prone to more aggressive driving or engaging in potentially distracting activities whether for work or personal purposes. When asked to report on other motorists' behavior, however, respondents indicated they had witnessed more aggressive and distracting drivers on the road after March 2020 relative to the time before the pandemic. These findings are reconciled with the existing literature on self-monitoring and self-enhancement bias, and the existing literature on the effect of comparable large-scale, disruptive events on traffic patterns is used to discuss the hypothesis on how driving patterns may change after the pandemic.

Advancing Multicomponent Strategies to Macrobicyclic Peptides.

Macrocyclization of peptides is typically used to fix specific bioactive conformations and improve their pharmacological properties. Recently, macrobicyclic peptides have received special attention owing to their capacity to mimic protein structures or be key components of peptide-drug conjugates. Here, we describe the development of novel synthetic strategies for two distinctive types of peptide macrobicycles. A multicomponent macrocyclo-dimerization approach is introduced for the production of interconnected ß-turns, allowing two macrocyclic rings to be formed and dimerized in one pot. Also, an on-resin double stapling strategy is described for the assembly of lactam-bridged macrobicycles with stable tertiary folds.

Base-Promoted Intramolecular Addition of Vinyl Cyclopropanecarboxamides to Access Conformationally Restricted Aza[3.1.0]bicycles.

3-Azabicyclo[3.1.0]hexanes are common structural components in natural products and bioactive compounds. Traditionally, the metal-mediated cyclopropanation domino reaction of chain enzymes is the most commonly used strategy for the construction of this type of aza[3.1.0]bicycle derivative. In this study, a base-promoted intramolecular addition of alkenes used to deliver conformationally restricted highly substituted aza[3.1.0]bicycles is reported. This reaction was tailor-made for saturated aza[3.1.0] bicycle-containing fused bicyclic compounds that may be applied in the development of concise and divergent total syntheses of bioactive compounds.

Bikeability and the induced demand for cycling.

To what extent is the volume of urban bicycle traffic affected by the provision of bicycle infrastructure? In this study, we exploit a large dataset of GPS trajectories of bicycle trips in combination with a fine-grained representation of the Copenhagen bicycle-relevant network. We apply a model for bicyclists' choice of route from origin to destination that takes the complete network into account. This enables us to determine bicyclists' preferences for a range of infrastructure and land-use types. We use the estimated preferences to compute a generalized cost of bicycle travel, which we correlate with the number of bicycle trips across a large number of origin-destination pairs. Simulations suggest that the extensive Copenhagen bicycle lane network has caused the number of bicycle trips and the bicycle kilometers traveled to increase by 60% and 90%, respectively, compared with a counterfactual without the bicycle lane network. This translates into an annual benefit of €0.4M per km of bicycle lane owing to changes in generalized travel cost, health, and accidents. Our results thus strongly support the provision of bicycle infrastructure.

"I'm Hooked on e-cycling, I Can Finally Be Active Again": Perceptions of e-cycling as a Physical Activity Intervention during Breast Cancer Treatment.

Electrically-assisted bicycles (e-bikes) are a means through which to increase individual physical activity (PA) and overcome some commonly reported barriers to engaging in conventional cycling. Fatigue is a common side effect to breast cancer treatment, and the rate of PA engagement drops significantly following a breast cancer diagnosis. The aim of this qualitative study was to examine perceptions of e-cycling as a means of increasing PA in this population. Twenty-four participants (mean age = 57.88 (standard deviation 10.8), 100% female) who have had a breast cancer diagnosis, completed two semi-structured interviews via Zoom. One interview was conducted prior to an e-bike taster session and a second, after the session. Taster sessions were conducted by certified cycling instructors in the community. Interviews were conducted between December 2021 and May 2022. Data were transcribed verbatim and analyzed thematically using NVivo 12 software. An inductive and deductive approach to analysis was adopted. Five themes were generated: (1) Perceived role of e-bikes during treatment, (2) The relationship between e-bikes and fatigue, (3) Cancer-specific considerations, (4) Is e-cycling 'enough'?, and (5) Optimizing the intervention. Negative perceptions of e-bikes noted before the taster session were altered following riding an e-bike. The multiple levels of assistance made cycling manageable and less impacted by fatigue, thereby enabling individuals to re-establish previous cycling habits. E-cycling may be a suitable option to increase PA behavior amongst individuals being treated for breast cancer, with the potential to overcome many of the barriers of conventional cycling. Enabling this population to trial an e-bike elicits positive physical and psychological responses that may help to promote future engagement.

Examining the Effects of Gateway Width on Motorist Yielding to Pedestrians.

The gateway in-street sign configuration has been demonstrated to be a low-cost method for increasing motorist yielding the right of way to pedestrians at crosswalks. It has previously been hypothesized that the gateway is effective because it visually narrows a travel lane. In the present study, gateway widths (i.e., distance between signs) were compared to determine whether there was a differential effect on motorist yielding. Experiment 1 was a parametric analysis of distance between the signs, varying in 2-ft intervals from 12 to 18 ft. The results showed that the percentage of motorists yielding increased as the distance between the signs decreased. Experiment 2 examined curb-top and gutter-pan placements of the edge signs at three different sites. Both placements produced substantial increases in yielding compared with baseline, though the difference between gutter-pan and curb-top placement was not significant at two of the three sites. Based on the distance between signs in these two configurations, the results at two of the sites aligned with those in Experiment 1, and one site demonstrated much higher yielding than would have been predicted. This suggests that small increases in the distance between signs may result in a minor decrease in yielding but may improve the survivability of the signs and reduce maintenance costs over time. The potential to combine this sign effect with other engineering treatments (e.g., curb extensions and bicycle lanes) was additionally explored. The results are discussed in relation to a perceived narrowing hypothesis, sign survival, cost effectiveness, and equity.

Impacts of the COVID-19 Pandemic on Bikeshare Usage by Rider Membership Status Across Selected U.S. Cities.

Bikesharing is a popular transportation mode for people to commute, for leisurely travel, or for recreation purposes in their daily tasks. Throughout 2020, the COVID-19 pandemic had significant impacts on bikeshare usage in the United States. Previous studies show that the pandemic negatively affected bikeshare activity patterns. To examine the effects of the pandemic on bikeshare behavior across membership types, this study investigated trip volume- and trip duration patterns of both members and nonmembers of five bikeshare systems across the United States. The results showed that member ridership significantly decreased throughout the pandemic, but nonmember ridership tended to be stable. It was also found that trip durations increased across both groups throughout the pandemic. Additionally, inferences were made to determine the level of support for a reversion to prepandemic normality as the pandemic progressed and reopening occurred in phases. The findings from this study could benefit bikeshare agencies in developing postpandemic recovery strategies.