Risky Maneuvers Research Articles

When does Reckless Driving Occurs? Case Study in Nampula, Mozambique

This study investigates the influence of traffic conditions on reckless driving behavior in Nampula, Mozambique, where road accidents claim several lives daily. Previous research has largely focused on individual driving behaviors, neglecting the impact of traffic environments on such behaviors. This study addresses this gap by categorizing vehicles into four groups: passenger cars, minibuses, trucks, and motorcycles, and classifying traffic conditions using k-means clustering. Three distinct traffic patterns were identified: Motorcycle and Car Dominant Traffic (MCDT), High-Density Traffic Flow (HDTf), and Low-Density Traffic Flow (LDTf). Results show that reckless driving is significantly influenced by traffic conditions, with minibuses, motorcycles, and trucks being key contributors. Pattern 2 (HDTf) demonstrated the highest occurrence of reckless driving, driven by competition among minibus drivers, the obstructive presence of trucks, and risky motorcycle maneuvers. Pattern 1 also exhibited elevated risk, particularly performed among motorcycle riders, while Pattern 3 (LDTf) showed the lowest risk due to reduced traffic density. Poisson regression analysis revealed that increased traffic flow in any vehicle category is associated with higher rates of reckless driving. Minibuses and motorcycles, functioning as demand-oriented public transport, engage in competitive and unsafe behaviors, while trucks, though not engaging in reckless driving directly, act as barriers that exacerbate risky maneuvers by other vehicles. These findings highlight the need for dedicated lanes for minibuses and motorcycles and tailored traffic safety policies to mitigate reckless driving.

Os efeitos societários do “Caso Paola Carosella”

The argentine chef and former judge on the television show “Masterchef Brasil”, Paola Carosella, sparked controversy with the revelation of a supposed “business strategy” that would have resulted in her acquiring shares from her former partners in the restaurant “Arturito”, in São Paulo. Hoping for a hypothetical break with the other members, Paola would have adopted a risky maneuver in the management of the company: “banking” the devaluation of the restaurant, in order to buy the shares of the other partners. It is assumed, from her statements in an interview with journalist Ana Paula Padrão in 2022, that Paola achieved her goal, thus generating negative repercussions. After the controversy, the argentine had to clarify the situation publicly. The episode raises questions about the duties of partners and directors in limited companies, highlighting possible breaches of loyalty and contractual obligations. In view of this, the article proposes an analysis divided into two parts: the first, discusses potential breaches of directors’ duties and obligations, while, the second, addresses preventive measures that could have been adopted to mitigate such situations. This research aims not only to understand merely similar cases, but also to encourage business practices that promote legal certainty in corporate relations, highlighting, in this regard, the importance of specialized legal advice, both from a preventive and reactive point of view.

Controlling Traffic Congestion in a Residential Area via GLOSA Development

The phenomenon of traffic congestion started in the second half of the twentieth century. This arose because of our society’s constant increase in demand for mobility. The excessive traffic of vehicles attempting to use the same infrastructure at the same time is what causes congestion. The consequences are well-known: delays, air pollution, reduced speed, and dissatisfaction (which may lead to risky maneuvers, reducing pedestrian and other driver safety). Our objective is to simulate the change in traffic patterns brought about by app users in residential areas (using navigational tools like Google Maps and Apple Maps), where the majority of navigational tools provide shortcuts that go through residential areas. In addition to discouraging navigation apps from directing drivers through residential areas during peak hours to mitigate pollution levels, by developing an algorithm based on the technology of Green Light Optimized Speed Advisory (GLOSA) and implementing it in a simulated environment (VISSIM), we can see the effect of changing the duration of red lights while keeping green lights constant. Overall, this solution can be implemented to change the times of traffic lights without the need for supplies, additional equipment, or warning signs because most cities’ traffic lights are already remotely controlled. In addition, this procedure is temporary to provide some freedom and does not adhere to the speed specified for drivers who wish to pass through residential areas outside of rush hour.

Microsurgical Procedures of Microvascular Decompression for Trigeminal Neuralgia

Microvascular decompression for trigeminal neuralgia was successfully performed following the secure surgical steps. The most crucial step involves creating a safe operative field in the dural opening. The petrotentorial junction should be identified without cerebellar retraction before proceeding to the deeper areas. Dissecting the petrosal vein and opening the horizontal fissure contributed to the expansion of the operative field. Bleeding often occurs from the dorsal cerebellar bridging vein and junction of the petrosal vein into the superior petrosal sinus. Transposition of the most common offenders, the superior and anterior inferior cerebellar arteries, is effectively achieved by dissecting both the proximal and distal sides of the neurovascular compression site. Teflon should be placed at a sufficient distance to prevent contact with the nerve, which can lead to recurrence. Treating vertebrobasilar artery-related cases is challenging and involves the risk of cranial nerve injuries. Multiple offending vessels are commonly involved. In such cases, it is essential to be aware of the course of the trochlear and abducens nerves during decompression. Applying the most effective and least risky maneuver is necessary for treating cases involving the vertebrobasilar artery.

The deterministic condition for the ground reaction force acting point on the combined knee valgus and tibial internal rotation moments in early phase of cutting maneuvers in female athletes

BackgroundCombined knee valgus and tibial internal rotation (VL + IR) moments have been shown to stress the anterior cruciate ligament (ACL) in several in vitro cadaveric studies. To utilize this knowledge for non-contact ACL injury prevention in sports, it is necessary to elucidate how the ground reaction force (GRF) acting point (center of pressure (CoP)) in the stance foot produces combined knee VL + IR moments in risky maneuvers, such as cuttings. However, the effects of the GRF acting point on the development of the combined knee VL + IR moment in cutting are still unknown. MethodsWe first established the deterministic mechanical condition that the CoP position relative to the tibial rotational axis differentiates the GRF vector's directional probability for developing the combined knee VL + IR moment, and theoretically predicted that when the CoP is posterior to the tibial rotational axis, the GRF vector is more likely to produce the combined knee VL + IR moment than when the CoP is anterior to the tibial rotational axis. Then, we tested a stochastic aspect of our theory in a lab-controlled in vivo experiment. Fourteen females performed 60° cutting under forefoot/rearfoot strike conditions (10 trials each). The positions of lower limb markers and GRF data were measured, and the knee moment due to GRF vector was calculated. The trials were divided into anterior- and posterior-CoP groups depending on the CoP position relative to the tibial rotational axis at each 10 ms interval from 0 to 100 ms after foot strike, and the occurrence rate of the combined knee VL + IR moment was compared between trial groups. ResultsThe posterior-CoP group showed significantly higher occurrence rates of the combined knee VL + IR moment (maximum of 82.8%) at every time point than those of the anterior-CoP trials, as theoretically predicted by the deterministic mechanical condition. ConclusionThe rearfoot strikes inducing the posterior CoP should be avoided to reduce the risk of non-contact ACL injury associated with the combined knee VL + IR stress.

Interaction-Aware Prediction for Cut-In Trajectories With Limited Observable Neighboring Vehicles

Predicting the future trajectories of risky maneuvers such as cut-in is of great significance for intelligent vehicles to alarm potential crashes in advance. A more critical issue is the use of limited observable neighboring vehicles to achieve reliable trajectory prediction. Motivated by it, this paper studies the trajectory prediction for cut-in maneuvers from ego-vehicle's-view. An interaction-aware model is developed for long-term prediction based on the attention mechanism, where both the encoder and the social interactor are implemented through multi-head attentions and feed forward layers. First, an attention-based trajectory encoder module with temporal embedding is presented to extract hidden features from historical observations. Then another attention-based module is constructed to characterize social interactions between the target vehicle and its neighbors. In the interactor, a novel social mask layer is designed to improve prediction performance in different scenarios, especially for discretionary cut-in maneuvers. Experimental comparison with the state-of-the-art models on public dataset demonstrates the excellent performance of our proposed model on cut-in trajectory prediction. In addition, ablation studies are conducted to highlight the strengths of the main modules in our model.

Exploring the Factor Structure of a Modified Motorcyclist Behavior Questionnaire: Croatian Context

Road crashes, particularly those involving vulnerable road users, such as motorcyclists, are a major public concern worldwide, especially on rural roads. To understand the factors contributing to the heightened risk experienced by motorcyclists, a survey was conducted among motorcycle riders. The Motorcycle Rider Behavior Questionnaire (MRBQ), a widely used self-report instrument, was employed to gather insights into motorcyclists' perspectives, behaviors, and attitudes regarding road safety. This study focused on the factor structure of the MRBQ within the context of Croatia. Principal component analysis (PCA) with varimax rotation was performed to examine the underlying factors of motorcyclist behavior. Five distinct factors were identified: violations (e.g., speeding and reckless riding), errors (e.g., risky maneuvers and inattention), stunts (e.g., wheelie), safety equipment (e.g., use of protective gear), and substance use (e.g., riding under influence). These factors explained 40.44% of the variance among the analyzed items. These findings contribute to the understanding of motorcycle rider behavior patterns. Future research will explore the relationship between these factors and motorcyclists' involvement in risky situations and crashes.

A Context-Aware Framework for Risky Driving Behavior Evaluation Based on Trajectory Data

Risky driving behaviors are one of the key contributors to traffic accidents. The rapid and accurate identification of them is important to improve the safety of the driving environment. This study introduces a context-aware framework for the evaluation of risky driving behaviors based on trajectory data. It consists of three models to identify the context, determine risky maneuvers, and evaluate risky driving behaviors. We first propose a surrogate-based method to label risky maneuvers considering context factors. Then, the features of driving trajectories are extracted as the input features for the evaluation of risky behavior. Based on the labeling result and maneuver features, supervised machine learning algorithms are leveraged to model their relationships for evaluations. Three feature extraction methods and five classifiers are compared in this article to select the most suitable one. Last, a context-aware evaluation framework is proposed to recognize risky driving behaviors incorporating context. The trajectory data extracted from unmanned aerial vehicles are used to validate the proposed framework. The results show that the accuracy of risky driving behaviors evaluation could reach 97%. The proposed framework in this study can effectively evaluate risky driving behaviors based on trajectory data with the consideration of context factors.

Cascade Learning for Driver Facial Monitoring

As a non-invasive method, vision-based driver monitoring aims to identify risky maneuvers for intelligent vehicles and it has gained an increasing interest over recent years. However, most existing methods tend to design models for specific tasks, such as head pose or gaze estimation, which results in redundant models hampering real time applications. Besides, most driver facial monitoring methods ignore the correlation of different tasks. In this work, we propose a unified framework based on cascade learning for simultaneous facial landmark detection and head pose estimation, as well as simultaneous eye center detection and gaze estimation. In particular, built upon the key idea that facial landmark locations and 3D face model parameters are implicitly correlated, we introduce a cascade regression framework to achieve these two tasks simultaneously. After coarsely extracting the driver’s eye region from the detected facial landmarks, we perform cascade regression for simultaneous eye center detection and gaze estimation. Leveraging the power of cascade learning allows our method to alternatively optimize facial landmark detection, head pose estimation, eye center localization, and gaze prediction. The comparison experiments conducted on benchmark datasets of 300-W, GI4E, BU, MPIIGaze, and driving dataset of SHRP2 demonstrate that our proposed method can achieve state-of-the-art performance with robust effectiveness on the real driver monitoring applications.

Characteristics of early shared E-Scooter fatalities in the United States 2018–2020

This research examines the preliminary characteristics of early fatalities associated with shared e-scooters, a unique emerging mode of transportation. Using media and police reports, we identified 21 shared e-scooter fatalities which occurred in the United States from 2018 to 2020. We studied the cases and crash narratives in detail to document the characteristics present and identify potential risk factors.We found that most crashes (86%) involved motor vehicles and 28% of these were hit-and-runs. The majority of cases took place at night (81%), and adverse environmental conditions like precipitation and fog were present in 43% of cases. We suggest a framework of five possible crash configurations, and we find that two crash types represent a majority of fatalities. These two most common crash types occurred when a motor vehicle struck an e-scooter from behind, or when the e-scooter operator lost of control of the scooter.These results establish a useful point of reference for policymakers, e-scooter stakeholders, and future researchers by documenting the number and the characteristics of these fatalities. Our analysis suggests that many hazards, such as reduced visibility, poor surface conditions, and risky maneuvers, typically accumulate before a fatal e-scooter crash occurs. This may suggest multiple predictable points of conflict which could serve as places for intervention and areas of future study.

Assessing Willingness to Engage in Risky Driving Behaviour Using Naturalistic Driving Footage: The Role of Age and Gender.

Young novice drivers are more prone than older drivers to get involved in a risky driving situation. Some young drivers underestimate risk while overestimating their driving abilities, increasing the likelihood of engaging in risky behaviour. Age and inexperience both influence risk estimation, though it is not clear which of these variables is more important. Can drivers’ willingness to engage in risky behaviour be assessed in a similar way to hazard perception skill using video-based risky situations? The aim of the current study was to assess whether a video-based tool could measure the willingness to participate in risky driving situations and whether it can distinguish between different types of risky driving scenarios across gender and driver age groups. We also explored the moderating effect of age and gender on drivers’ experience in relation to the risky manoeuvres and participants’ willingness to engage in risky situations. Participants were presented with naturalistic videos from the perspective of the driver that contained active risky situations (result of driver’s own actions) and were asked to make a decision regarding a potential action (to overtake a bus/bicycle or pass through an amber light) and whether they would accelerate at this point. Participants reported that they were more willing to accelerate and overtake cyclists and buses and less willing to pass a light in amber. Young drivers were more willing to both engage in the risky behaviours and accelerate than older drivers, with young males reporting higher scores than the other groups. Gender differences were observed, with males being more prone to overtake and pass through a light in amber than females; however, this difference was not observed for the intention to accelerate. All the above effects remained when we tested the impact of experience on decision making while controlling for age and gender, although driving experience was no longer significant. These results demonstrate that drivers’ intention to assume risk can indeed be measured in a similar video-based methodology to that used by hazard perception tests. The findings raise the possibility of assessing and training drivers on a wider range of safety-related behaviours.

A data-driven feature learning approach based on Copula-Bayesian Network and its application in comparative investigation on risky lane-changing and car-following maneuvers

The era of ‘Big Data’ provides opportunities for researchers to have deep insights into traffic safety. By taking advantages of ‘Big Data’, this study proposes a data-driven method to develop a Copula-Bayesian Network (Copula-BN) using a large-scale naturalistic driving dataset with multiple features. The Copula-BN is able to explain the causality of a risky driving maneuver. As compared with conventional BNs, the Copula-BN developed in this study has the following advantages: the Copula-BN 1. Has a more rational and explainable structure; 2. Is less likely to be over-fitting and can attain more satisfactory prediction performance; and 3. Can handle not only discrete but also continuous features. In terms of technical innovations, Shapley Additive Explanation (SHAP) is used for feature selection, while Gaussian Copula function is employed to build the dependency structure of the Copula-BN. As for applications, the Copula-BNs are used to investigate the causality of risky lane-changing (LC) and car-following (CF) maneuvers, upon which the comparisons are made between the two essential but risky driving maneuvers. In this study, the Copula-BNs are developed based on the Second Highway Research Program (SHRP2) Naturalistic Driving Study (NDS) database. Upon network evaluation, the Copula-BNs for both risky LC and CF maneuvers demonstrate satisfactory structure performance and promising prediction performance. Feature inferences are conducted based on the Copula-BNs to respectively illustrate the causation of the two risky maneuvers. Several interesting findings related to features’ contribution are discussed in this paper. To a certain extent, the Copula-BN developed using the data-driven method makes a trade-off between prediction and causality within the ‘Big Data’. The comparison between risky LC and CF maneuvers also provides a valuable reference for crash risk evaluation, road safety policy-making, etc. In the future, the achievements of this study could be applied in Advanced Driver-Assistance System (ADAS) and accident diagnosis system to enhance road traffic safety.

Drivers’ workload measures to verify functionality of ferry boats boarding area

Functionality of a square used for ferry boats boarding has repercussions on safety and comfort of users, as well as on the efficiency of maritime transport. Inadequate use of the infrastructure causes driving errors followed by corrective manoeuvres, loss of time and potential accidents with consequences for community and the maritime transport compa-ny. The wide diversification of traffic components and payment methods are generally managed through a traditional horizontal and vertical signage system that does not refer to any current legislation. Therefore, the purpose of this research is to investigate driver's behaviour and the interaction that takes place between the latter and the environ-mental context. In particular, the authors focused on the study of the driver’s workload in a simulated environment, considering a users' sample and different driving scenarios inside the boarding area, concerning traffic conditions (isolated vehicle or presence of disturbing vehicles) and signs position. All this, in order to evaluate whether any change in a virtual context could bring real benefits to drivers, before being transferred to the real context. The results obtained, in terms of subjective workload and performance measures, have made it possible to judge the different solutions proposed in a simulated environment through synthetic indices referring to the entire boarding place or at certain parts of it. In this way, the manager can decide to change the circulation of the entire square or only some aspects of detail, such as some signals, in the event that they manifest an evident difficulty in the transfer of infor-mation. The use of the simulated environment allows greater speed in identifying the best solution, lower costs (avoid-ing the creation of a critical configuration for circulation) and greater user safety, since risky manoeuvres are identi-fied and corrected by the simulator. The proposed procedure can be used by managers for a correct arrangement of the signs, for the purpose of correctly directing the flows and maximizing the flow rate disposed of.

Comparing the usefulness of real-time driving aids in a connected environment during mandatory and discretionary lane-changing manoeuvres

Lane-changing manoeuvre is one of the risky manoeuvres performed by drivers either to reach the planned destination (i.e., mandatory lane-changing; MLC) or to achieve better driving conditions (i.e., discretionary lane-changing; DLC). Essentially both lane-changing types require the driver to acquire surrounding traffic information for efficient and safe lane-changing decisions. However, this does not discount the fact that both these lane-changings are fundamentally different from each other as the urgency of lane-changing is much higher during MLC compared to DLC. Real-time driving aids in a connected environment promise to assist during the lane-changing decision-making process, but the differential effectiveness (or usefulness) of real-time driving aids in a connected environment for these two lane-changing types remains unexplored due to the novelty of a connected environment and the consequent scarcity of data. To fill this research gap, this study collected lane-changing data from 78 participants who performed MLC and DLC in the CARRS-Q Advanced Driving Simulator. Participants were asked to drive in three randomised driving conditions: baseline condition (without driving aids), real-time driving aids in a connected environment with perfect communication, and delayed driving aids in a connected environment. While surrogate measures of safety are analysed and compared using descriptive statistics, a hybrid framework of data mining and classical statistical modelling is employed to examine the usefulness of the real-time driving aids in a connected environment for two lane-changing types. We find that the crash risk associated with MLC is significantly reduced in the driving conditions providing driving aids compared to that of DLC. Results also reveal that the probability of engaging in a hard-braking event decreases for both the lane-changing types in the presence of real-time driving aids in the connected environment driving conditions, but a higher decrease in magnitude is found for MLC. Age and gender-related differential impact have been observed where young and male drivers have a higher possibility of engaging in a hard-braking event when driving without driving aids, but the presence of real-time driving aids reduces such risk. This study concludes that the usefulness (or effectiveness) of the real-time driving aids in a connected environment is a function of the urgency of a task, which is evidently higher during MLC, thus providing the maximum advantage during MLC.

Wildfire Fighting by Unmanned Aerial System Exploiting Its Time-Varying Mass

This letter presents an approach for accurately dropping a relatively large amount of fire retardant, water or some other extinguishing agent onto a wildfire from an autonomous unmanned aerial vehicle (UAV), in close proximity to the epicenter of the fire. The proposed approach involves a risky maneuver outside of the safe flight envelope of the UAV. This maneuver exploits the expected weight reduction resulting from the release of the payload, enabling the UAV to recover without impacting the terrain. The UAV is tilted to high pitch angles, at which the thrust may be pointed almost horizontally. The vehicle can therefore achieve higher horizontal speeds than would be allowed by conventional motion planners. This high speed allows the UAV to significantly reduce the time spent close to the fire. As a result, the overall high heat exposure is reduced, and the payload can be dropped closer to the target, minimizing its dispersion. A constrained optimal control problem (OCP) is solved taking into account environmental parameters such as wind and terrain gradients, as well as various payload releasing mechanisms. The proposed approach was verified in simulations and in real experiments. Emphasis was put on the real time recalculation of the solution, which will enable future adaptation into a model predictive controller (MPC) scheme.

Constrained stability control with optimal power management strategy for in-wheel electric vehicles

This paper looks into the energy management and directional stability of four-in-wheel driven electric vehicles, simultaneously. In the proposed strategy, the optimal driving torques are initially distributed between the wheels by considering the condition for minimum losses of motors using the motor efficiency model. In risky maneuvers, a novel optimal torque vectoring system is developed to intentionally change the initial optimal torques for the generation of required stabilizing yaw moment. For designing the stability controller, a new constrained control method is analytically developed based on the prediction of continuous nonlinear vehicle models. The proposed control method restricts the side-slip angle to guarantee the stability. Also, the required control torque for each motor is restricted within the admissible range according to the motor map. As another result of the constrained strategy, a small change in the optimal energy consumption is occurred for improved stability because of using minimum external yaw moment. In simulation studies, a good performance of the developed control system to provide both directional stability and drivability of electric vehicle with high energy efficiency is presented at different driving conditions using 14-degrees-of-freedom vehicle model. A comparative study with the conventional model predictive control method indicates the speed of the proposed constrained control method and the ease of its solution and implementation.

Identifying and comparing the injury severity risk factors on rural freeways in different states in the United States

This study identifies and compares those risk factors affecting crash injuries and fatalities on rural freeways in Montana and West Virginia in the United States using the mixed logit model. Three-year crashes on rural freeway segments in both states are used. Higher annual average daily traffic (AADT) was associated with a reduction in injuries/fatalities in both states, with higher reduction in West Virginia (40%) than in Montana (25%). In both states, the impact of adverse road surface conditions (i.e., snowy/icy) was associated with a reduction in injuries/fatalities. The results show that separate injury severity models for individual states are suggested instead of lumping all crashes in one model. Enforcement of trucks' risky maneuvers (e.g., illegal traveling in the leftmost lane) and more education for older drivers are suggested in West Virginia. In Montana, it is recommended to monitor rural freeway segments with high sport utility vehicle (SUV) crash history.

Applied nonlinear control of vehicle stability with control and state constraints

For the vehicle dynamic control system, to guarantee directional stability in risky maneuvers, the side-slip angle should be restricted to the admissible range when the yaw rate tracks the proposed desired response for enhanced steerability. Meanwhile, the control input of the external yaw moment produced by asymmetric braking forces should be calculated in the practical range according to the capacity of tire forces. In the present study, a novel constrained controller with input and state constraints is developed. To this aim, a cost function consisting of predicted continuous response of yaw rate tracking error is expanded in terms of current control signal. Concurrently, the state constraint of side slip is transformed to the equivalent constraint of control signal by a novel nonlinear prediction approach. After that, the expanded performance index is analytically minimized in the presence of all input constraints to obtain the control law. The computed yaw moment is optimally distributed to asymmetric braking forces by designing a wheel slip control system. Simulation studies are conducted to evaluate the performance of proposed constrained controller compared with the unconstrained controller and a conventional nonlinear model predictive controller developed in the recent papers using a 14-degree-of-freedom vehicle model which includes suspension system dynamics. The results show that the proposed controller is much faster and easy to solve and implement.

Young e-cyclists in Israeli cities: a characterization of typical behaviours and risk factors based on field observations

Electric power-assisted bicycles (e-bicycles) provide a convenient form of mobility in urban areas, being an attractive alternative to private cars, usual cycling and walking. However, there is a growing concern of their associated injuries, resulting from the increasing exposure and apparently higher speeds. Unlike other countries, in Israel, a growing use of e-bicycles by youngsters (below 18) is observed, in many towns, accompanied by a substantial increase in the number of related injuries. In this study, an observational survey of young e-cyclists was undertaken in Israeli towns aiming to characterize their behaviours at typical urban settings and then to consider measures needed for their safe integration in the urban space. The observational survey was focused on teen e-cyclists' behaviours during their trips to and from school and during leisure hours. The data were collected by means of dynamic video-recording, at five types of urban settings: signalized and un-signalized intersections; roundabouts; street sections with and without bicycle-paths. The survey covered 225 locations in 15 cities, including 150 sites near high-schools and 75 in city centers. In total, over 2000 video-films were collected and their contents were coded for statistical analyses. The results showed that at all types of sites, most teenager e-cyclists were males, older than 16 and not wearing a helmet, despite the traffic law demands. High shares of them rode on sidewalks and crossed at crosswalks, violating the law that prohibits using pedestrian facilities for riding. At signalized intersections, substantial shares crossed on red, both on the roadway and on crosswalks, thus violating the traffic law and increasing accident risk. At various urban settings, young e-cyclists demonstrated a wide range of risky manoeuvres. They move faster than pedestrians and endanger them on sidewalks, but also disturb vehicle traffic and endanger themselves while riding on the road. A wider application of bicycle infrastructure, with better separation between the sidewalks, roadways and bicycle paths, would lead to a safer integration of e-bicycles in Israeli cities. Additionally, road safety education and training of teen e-cyclists supported by stronger enforcement of traffic regulations are required.

Investigating and Modeling the Illegal U-Turn Violations at Medians of Limited Access Facilities

Illegal U-turns on freeways and toll roads are risky maneuvers that sometimes result in the turning vehicles causing various types of collisions or disturbances to approaching traffic. These illegal U-turn maneuvers can occur at traversable grass medians and emergency crossovers. Limited literature was found regarding the impact of illegal U-turns on these facilities. Therefore, to understand the roadway and median characteristics that could influence drivers’ propensity to commit illegal U-turns, a sequential modeling methodology was adopted. This methodology combined a Poisson regression model with a Least Absolute Shrinkage and Selection Operator (LASSO) regression procedure to predict the cited violations at traversable median segments. Additionally, a logistic regression model was developed to predict the probability of a cited violation at official use only emergency crossovers. These models included illegal U-turn citations and crashes for the Orlando and Miami metropolitan areas in Florida from 2011 to 2016. The findings indicated that the average distance between access points, median width, speed limit, segment length, and distance to nearest segment were significant in predicting cited violations at traversable medians. Furthermore, the distance to the nearest interchange, distance to the nearest adjacent crossover, and median width were significant in predicting the probability of a cited violation occurring at an emergency crossover. This study helps agencies to predict the locations of illegal U-turn violations and to prioritize roadways for possible treatment to minimize the potential risk of head-on or other collisions due to illegal U-turn events.