Introduction: Intersections are the most dangerous locations in urban traffic. The present study aims to investigate drivers’ visual scanning behavior at signalized and unsignalized intersections. ...Method: Naturalistic driving data at 318 green phase signalized intersections and 300 unsignalized ones were collected. Drivers’ glance allocations were manually categorized into 10 areas of interest (AOIs), based on which three feature subsets were extracted including glance allocation frequencies, durations and AOI transition probabilities. The extracted features at signalized and unsignalized intersections were compared. Features with statistical significances were integrated to characterize drivers’ scanning patterns using the hierarchical clustering method. Andrews Curve was adopted to visually illustrate the clustering results of high-dimensional data. Results: Results showed that drivers going straight across signalized intersections had more often glances at the left view mirror and longer fixation on the near left area. When turning left, drivers near signalized intersections had more frequent glances at the left view mirror, fixated much longer on the forward and rearview mirror area, and had higher transition probabilities from near left to far left. Compared with drivers’ scanning patterns in left turning maneuver at signalized intersections, drivers with higher situation awareness levels would divide more attention to the forward and right areas than at unsignalized intersections. Conclusions: This study revealed that intersection types made differences on drivers’ scanning behavior. Practical applications: These findings suggest that future applications in advanced driver assistance systems and driver training programs should recommend different scanning strategies to drivers at different types of intersections.
Intersections are hazardous locations and many studies have been conducted to identify the factors contributing to the frequency and severity of intersection crashes. However, little attention has ...been devoted to investigating the differences between crashes at urban and rural intersections, which have different road, traffic and environmental characteristics. By applying a random parameters probit model to the data from the Canadian Province of Alberta between 2008 and 2012, we find that urban intersection crashes are more likely to be associated with hit and run behaviours, roads with higher traffic volume, wet surfaces, four lanes and skewed intersections, and crashes on weekdays and off-peak hours, whereas rural crashes are likely to be associated with increases in fatalities and injuries, roads with higher speed limits, special road features, exit and entrance terminals, gravel, curvature and two lanes, crashes during weekends, peak hours and night-time, run-off-road crashes, and police visit to crash scene. Hence, road safety professionals in urban and rural areas should consider these differences when designing and implementing counter-measures to improve intersection safety, especially their safety audits and reviews, enforcement activities and education campaigns, to target the more vulnerable times and locations in the different areas.
•The trajectory of the manual driving vehicle at intersections was modelled.•Steering and acceleration were incorporated as model inputs to model 2D motion.•The travelled distance was chosen as the ...main independent variable.•The descriptive power, plausibility, and accuracy were validated.•The model was extended with some realism considerations.
Modeling traffic flow at intersections is essential for the design, control, and management of intersections. A challenging feature of microscopic modeling vehicular movement at intersections is that drivers can choose among an infinite number of alternative traveling paths and speeds. This makes it fundamentally different from structured straight road sections with lanes. This study proposes a novel method to model the trajectories of vehicles in two-dimensional space and speed. Based on optimal control theory, it assumes drivers schedule their driving behavior, including the steering and acceleration, to minimize the predicted costs. The costs contain the running costs, which consist of the travel time and driving smoothness (longitudinally and laterally), and the terminal cost, which penalizes the deviations from the desired final state. Different than conventional methods, the vehicle motion dynamics are formulated in distance rather than in time. The model is solved by an iterative numerical solution algorithm based on the Minimum Principle of Pontryagin. The descriptive power, plausibility, and accuracy of the proposed model are investigated by comparing the calculated results under several cases, which can be solved from symmetry or analytically. The proposed model is further calibrated and validated using empirical trajectory data, and the quality of the predicted trajectory is confirmed. Qualitatively, the optimal trajectory changes in the range of the shortest path and smoothest path under different weights of the running cost. The proposed model can be used as a starting point and extended with more considerations of intersection operation in the real world for future applications.
In recent years, the growing development of Connected Autonomous Vehicles (CAV), Intelligent Transport Systems (ITS), and 5G communication networks have led to the advent of Autonomous Intersection ...Management (AIM) systems. AIMs present a new paradigm for CAV control in future cities, taking control of CAVs in scenarios where cooperation is necessary and allowing safe and efficient traffic flows, eliminating traffic signals. So far, the development of AIM algorithms has been based on basic control algorithms, without the ability to adapt or keep learning new situations. To solve this, in this paper we present a new advanced AIM approach based on end-to-end Multi-Agent Deep Reinforcement Learning (MADRL) and trained using Curriculum through Self-Play , called advanced Reinforced AIM ( adv. RAIM). adv. RAIM enables the control of CAVs at intersections in a collaborative way, autonomously learning complex real-life traffic dynamics. In addition, adv .RAIM provides a new way to build smarter AIMs capable of proactively controlling CAVs in other highly complex scenarios. Results show remarkable improvements when compared to traffic light control techniques (reducing travel time by 59% or reducing time lost due to congestion by 95%), as well as outperforming other recently proposed AIMs (reducing waiting time by 56%), highlighting the advantages of using MADRL.
Many practical problems involve sphere intersections. Examples include but are not limited to estimations using the Global Positioning System (GPS), data science applications and 3D protein structure ...determination. Motivated by practical situations, where radii of spheres are not known precisely, we consider what happens when a spherical shell must be included in the intersection. We present and compare two approaches for this problem: one uses linear algebra and the other is based on conformal geometric algebra (CGA). The theoretical development is illustrated with some numerical examples, where it is possible to note the main advantage of CGA compared to the linear algebra approach: even in dimensions higher than three, CGA naturally preserves the geometric intuition of the problem.
•We consider what happens when spheres and a spherical shell intersect.•We formulate our approach using conformal geometric algebra.•We compare approaches based on linear algebra and geometric algebra.
•Conduct theoretical analysis of intersection capacity and vehicle delay under reservation-based control.•Propose a mixed integer linear programming (MILP) model that can dynamically form batches ...with the optimal sizes and determine service sequence of vehicles under varying traffic condition.•Simulation results show that:○The proposed optimization-based control performs best compared with reservation-based control and vehicle-actuated control.○Reservation-based control outperforms actuated control under low demand or under-saturated demand.○FCFS-based control is incapable of handling high demand and multiple conflicting streams.
Reservation-based methods with simple policies such as first-come-first-service (FCFS) have been proposed in the literature to manage connected and automated vehicles (CAVs) at isolated intersections. However, a comprehensive analysis of intersection capacity and vehicle delay under FCFS-based control is missing, especially under high traffic demand. To address this problem, this study adopts queueing theory and analytically shows that such method is incapable of handling high demand with multiple conflicting traffic streams. Furthermore, an optimization model is proposed to optimally serve CAVs arriving at an intersection for delay minimization. This study then compares the performance of the proposed optimization-based control with reservation-based control as well as conventional vehicle-actuated control at different demand levels. Simulation results show that the proposed optimization-based control performs best and it has noticeable advantages over the other two control methods. The advantages of reservation-based control are insignificant compared with vehicle-actuated control under high demand.
Traffic delay is an effective index for estimating the performance of a signalized intersection. In this study, we provide a comprehensive review of the theoretical delay estimation model over the ...last ca. 90 years. For fixed-time signalized intersections, we classified the estimation development process into three stages. Stage 1 covered 1920s-1970s, when approaches based on steady-state theory were derived. These methods obtain accurate predictions with low degrees of saturation, but overestimate the delay with higher saturation and cannot provide reasonable results for oversaturated conditions. To accommodate high saturation, time-dependent models were proposed and improved in Stage 2, 1970s-2000s, using coordination transformation techniques. Progression factors to account for the filtering impact from upstream intersections were also introduced during this period. Due to inaccurate approximation of certain specific traffic conditions, some modified approaches and supplementary terms were derived from 2000 onwards (Stage 3), which facilitate the evolution of the delay estimation method and improved approximation results. Some new techniques, including artificial intelligence algorithms, were also introduced into delay estimation in this era. We also describe theoretical delay measurement methods for actuated control intersections with a similar time line. From our summary of the evolution of theoretical delay models, we highlight some deficiencies and future research directions.
On operations of soft sets Sezgin, Aslıhan; Atagün, Akın Osman
Computers & mathematics with applications,
03/2011, Letnik:
61, Številka:
5
Journal Article
Recenzirano
Odprti dostop
Soft set theory, proposed by Molodtsov, has been regarded as an effective mathematical tool to deal with uncertainties. In this paper, first we prove that certain De Morgan’s law hold in soft set ...theory with respect to different operations on soft sets. Then, we discuss the basic properties of operations on soft sets such as intersection, extended intersection, restricted union and restricted difference. Moreover, we illustrate their interconnections between each other. Also we define the notion of restricted symmetric difference of soft sets and investigate its properties. The main purpose of this paper is to extend the theoretical aspect of operations on soft sets.
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•We made a new approach to the classical ring theory via soft set theory, with the concept of soft intersection rings.•We defined ideals, (generalized) bi-ideals, interior ideals and ...quasi-ideals of soft rings.•By defining soft union–intersection product, we obtain the relationship between this new concept and soft intersection ring and its different ideals.•We also characterized regular, regular duo, intra-regular and strongly regular rings by soft intersection rings and ideals.
In this paper, we make a completely new approach to the classical ring theory via soft set theory, with the concept of soft intersection rings, ideals, (generalized) bi-ideals, interior ideals and quasi-ideals. Particularly, we define soft union–intersection product and obtain the relationship between this new concept and soft intersection ring and its different ideals. Moreover, we characterize regular, regular duo, intra-regular and strongly regular rings by soft intersection rings and ideals.
•Subjects initiated braking significant earlier in the field than in driving simulator.•Subjects in driving simulator showed significantly higher speed and braked distinctly more intensively than in ...the field.•In driving simulator, the subjects appeared to have reduced risk awareness.•Caution is required when using a driving simulator for designing intersection assistance systems.
Introduction: The majority of accidents involving personal injury occur in urban intersections. As human error is the primary cause of these accidents, it seems reasonable to support drivers by intersection assistants. Studies to evaluate such systems are usually performed in driving simulators. However, this implies driver behaviour validity, which cannot always be taken for granted due to the artificial nature of simulated environments. The paper pays special attention to the validity of braking behaviour in urban intersections. In particular, the effect of the test scenario and selected driving simulator design parameters is considered. Method: The Time to Intersection (TTI) time interval between field and simulator study was evaluated at five simple urban intersections. Results: Independently of the type of intersection and the parameter configuration of the simulator, subjects initiated braking in preparation for a turning manoeuvre significantly earlier in the field than in the driving simulator. In particular, the results of both tests differed more at intersections where the driver did not have right of way than at intersections with other layouts, confirming the impact of the test scenario. Some differences were also found when the driving simulator parameter set was varied. Conclusions: The braking behaviour near urban intersections differs between real and simulated experimental environments. From these results, we conclude that caution is required when designing intersection assistance systems based solely on the braking behaviour of subjects in simulated environments. The test scenario and the design parameters must be considered as factors which influence the results. Practical applications: Depending on the current traffic situation and interactions, multiple different kinds of accident can occur at the considered types of intersection, meaning that closely investigating the driver behaviour validity at these junctions is highly important for further intersection assistance systems. Validity of TTI is for example important when determining the best choice of warning interval for a turning assistance system.
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