Intersection Operations Research Articles

Differential confocal over-range determination method based on an information theory.

The existing differential confocal axial three-dimensional (3D) measurement method cannot determine whether the surface height of the sample in the field of view is within its effective measurement range. Therefore, in this paper, we propose a differential confocal over-range determination method (IT-ORDM) based on an information theory to determine whether the surface height information of the sample to be examined is within the effective measurement range of the differential confocal axial measurement. First, the IT-ORDM finds the boundary position of the axial effective measurement range by the differential confocal axial light intensity response curve. Then the effective intensity measurement ranges of the pre-focus axial response curve (ARC) and the post-focus ARC are determined by the correspondence between the boundary position and the ARC. Finally, the intersection operation of the pre-focus image of effective measurement and the post-focus image of effective measurement is used to realize the extraction of the effective measurement area of the differential confocal image. The experimental results show that the IT-ORDM can effectively determine and restore the 3D shape of the measured sample surface at the reference plane position in the multi-stage sample experiments.

Information dissemination dynamics through Vehicle-to-Vehicle communication built upon traffic flow dynamics over roadway networks

This research is dedicated to developing a discrete mathematical simulation framework to track information dissemination dynamics via Vehicle-to-Vehicle (V2V) communication factoring traffic flow dynamics, traffic intersection operation settings, and traffic intersection geometrical design over a road traffic network. Specifically, we develop information network flow models (INFMs), including IFNM-a and IFNM-r, respectively for tracking information wavefront spreading dynamics at arterial intersections and at highway-ramp intersections. Next, by integrating IFNMs with the information and traffic coupled cell transmission model (IT-CTM) model developed by Du et al. [16] for capturing the information front propagation dynamics on a road segment, we establish a discrete mathematical simulation framework (IFNM-CTM) to track the information front spreading dynamics over a road network at discrete time stamps. Furthermore, by combining the IFNM-CTM framework and the deep search algorithms, this study tracks the information coverage dynamics and investigates its correlation to traffic congestion evolution over a traffic network at discrete time stamps. Our experiments built upon Sioux Falls city network indicate that the IFNM-CTM is able to track the information front spreading, including location and coverage, accurately with the mean absolute error (MAE) less than 6% and 5%, respectively. More importantly, our studies found a strong correlation existing between information front spreading dynamics and traffic congestion evolution over the network. Specifically, a mild congestion condition (i.e., LOS C and D) provides the best traffic condition to sustain information spreading as compared to sparse (i.e., LOS A or B) and heavily congested (i.e., LOS E or F) traffic conditions since neither of them can sustain stable and constant wireless communication due to the limited transmission range of DSRC and interference issues.

Cross-Departmental Collaboration Approach for Earthquake Emergency Response Based on Synchronous Intersection between Traditional and Logical Petri Nets

In order to reduce the harm of earthquakes to human society, all governments actively promote the construction and development of earthquake emergency rescue work. The earthquake emergency response involves many departments, multiple personnel and large rescue forces, which presents a great challenge to the ability to carry out cross-departmental rescue work in a collaborative and joint manner. A novel collaboration approach based on traditional and logical Petri nets is proposed to improve the cross-departmental collaboration in earthquake emergency response. The approach extends the synchronization of transitions in traditional Petri nets to that of traditional and logical transitions in traditional and logical Petri nets, and defines the intersection of related logical functions. The approach builds a model for the earthquake emergency response plans of various departments with the help of traditional and logical Petri net models, and then performs synchronous intersection operations on the two kinds of Petri nets and merges the two kinds of Petri nets into new logical Petri nets. Meanwhile, through realizing the collaboration ability of cross-departmental work, the approach improves the rescue efficiency and reduces the damage of the earthquake emergency.

Intersection capacity adjustments considering different market penetration rates of connected and automated vehicles

ABSTRACT To better prepare and guide both intersection planning and operations under different market penetration rates (MPRs) of connected and autonomous vehicles (CAVs) and traffic demands, this research estimates both the lane-level and intersection-level capacity. On the lane-level, adjustment factors for saturation headway and saturation traffic flow rate for each lane under different MPRs of CAVs are investigated. On the intersection-level, the maximum throughput function for different MPRs of CAVs is calibrated. With 100% CAVs, the saturation headways for the exclusive through lane, exclusive left-turn lane, and shared-right-and-through lane decrease by 55.8%, 48.9%, and 42.4%, respectively. The maximum throughput of the intersection with 100% CAVs increases by 70% compared to the scenario with only human driving vehicles (HDVs). Moreover, the maximum throughput increases rapidly after 60% MPRs of CAVs. The research could provide a solid reference for traffic engineers and planners in calculating the intersection capacity under different MPRs of CAVs.

Potential of Ecological Benefits for the Continuous Flow Intersection

Energy conservation and emission reduction from the transportation sector are of great significance in coping with the global energy and environmental crisis. As the bottleneck of urban road traffic, intersection burdens the urban environment greatly. When the volume of left-turn traffic is large, the continuous flow intersection (CFI) can effectively improve intersection operation efficiency. This paper first put forward the definition and application conditions of CFI. Then its mechanism for energy saving and emission reduction was analysed. CFI transformation was designed taking a typical intersection in Xi’an as an example. Operating efficiency, energy consumption and emissions of the intersection before and after CFI transformation were evaluated using the VISSIM model. The results show that energy consumption and emissions in the intersection are greatly reduced after CFI transformation. Queue length is reduced by more than 41%. Energy consumption and pollutant emission are reduced by about 8%. Through the simulation analysis, the emission reduction benefits most when the volume of left-turn traffic is 80%–85% of the design capacity, and the ratio of leftturntraffic over through traffic is maintained between 50% and 100%. This study suggests that CFI is suitable for large-scale promotion with careful examination.

A High-Order Fuzzy Time Series Forecasting Method Based on an Intersection Operation for Forecasting USD Foreign Exchange Rate

A High-Order Fuzzy Time Series Forecasting Method Based on an Intersection Operation for Forecasting USD Foreign Exchange Rate

Traffic-Responsive Signal Control at Intersections Using Real-Time Data of Vehicles Connected via V2X Communication

The positive effect of traffic-responsive signal control can be assured when real-time traffic data is reliable, but data reliability may be an issue that depends on the number of probe vehicles equipped with navigation devices or smartphones. However, there is a high chance of improving reliability with the recent deployment of connected vehicles (CVs) that use the vehicle-to-everything (V2X) communication data. Therefore, this paper proposes a traffic signal control strategy that utilizes V2X communication data obtained from CV operations, which is called the capacity waste reduction (CWR) strategy. In this strategy, vehicle queues on each road lane as an intersection approaches are initially estimated using V2X data. Then, the signal control algorithm determines the duration of the green signal for the currently applied phase based on the estimated vehicle queues. Furthermore, the strategy includes an algorithm for active priority signal control for the vehicles of bus rapid transit systems. The efficiency of the provided control strategy is tested with the VISSIM microsimulation program at different levels of the market penetration rate (MPR) of CVs. Based on the results of the experiment, the proposed strategy shows positive effects in both decreasing travel delay and increasing traffic flow even at the low levels of MPR of CVs. The results of the proposed strategy can be used as the base data for the development of smart intersection operations.

Robust Successor and Precursor Sets of Hybrid Systems Using Hybrid Zonotopes

This letter presents identities for calculating robust successor and precursor sets of discrete-time linear hybrid systems. The proposed technique relies on generating a set containing all possible state transitions of a dynamic system over a region of interest, named the state-update set. Forward and backward reachability can then be performed using only projection, intersection, and Minkowski difference set operations with the state-update set. It is shown how state-update sets may be defined as hybrid zonotopes for mixed logical dynamical systems and linear systems in closed loop with model predictive control.

The Intersections Based on Joint Observables In Fuzzy Probability

“Fuzzy probability theory” appeared as a smooth extension of classical probability theory in 1995. It was expected that it will be of great importance in quantum mechanics, but the theory doesn’t keep its development as it was expected. This necessitates revising some of its fundamental basic concepts. We argue that if quantum probability theory should have less constrained than classical probability theory as can be seen in the case of joint random variables, we surely need to weaken the definition of the intersection operation. In this paper, discuss the definition validity in quantum probability theory and to discuss the consistency of the given definitions with the whole theory and the possibility to have a more suitable definition.

A NEW SOFT SET OPERATION: COMPLEMENTARY SOFT BINARY PIECEWISE UNION (∪) OPERATION

Molodtsov’s soft set theory has been used in various disciplines both theoretically and practically. It is an effective mathematical tool for dealing with uncertainty. Since its debut, numerous types of soft set operations have been presented and applied. In this study, we analyze the fundamental algebraic features of a novel soft set operation which we call complementary soft binary piecewise union operation. Additionally, by examining the distribution of complementary soft binary piecewise union operation over all other soft set operations’ type, it aims to contribute to the literature on soft sets by revealing relationships between this new soft set operation and other types of soft set operations. Moreover, we prove that the set of all the soft sets with a fixed parameter set together with the complementary soft binary piecewise union operation and the soft binary piecewise intersection operation is a zero-symmetric near-semiring.

Modeling the Operation of Signal-Controlled Intersections with Different Lane Occupancy

In many cities of the world, the problem of traffic congestion on the roads remains relevant and unresolved. It is especially noticeable at signal-controlled intersections, since traffic signalization is among the most important factors that reduce the maximum possible value of the traffic flow rate at the exit of a street intersection. Therefore, the development of a methodology aimed at reducing transport losses when pedestrians move through signal-controlled intersections is a joint task for the research and engineering community and municipalities. This paper is a continuation of a study wherein the results produced a mathematical model of the influence of lane occupancy and traffic signalization on the traffic flow rate. These results were then experimentally confirmed. The purpose of this work is to develop a method for the practical application of the mathematical model thus obtained. Together with the obtained results of the previous study, as well as a systems approach, traffic flow theory, impulses, probabilities and mathematical statistics form the methodological basis of this work. This paper established possible areas for the practical application of the previously obtained mathematical model. To collect the initial experimental data, open-street video surveillance cameras were used as vehicle detectors, the image streams of which were processed in real time using neural network technologies. Based on the results of this work, a new method was developed that allows for the adjustment of the traffic signal cycle, considering the influence of lane occupancy. In addition, the technological, economic and environmental effects were calculated, which was achieved through the application of the proposed method.

Vision-Based a Seedling Selective Planting Control System for Vegetable Transplanter

Seedling transplanting is an important part of vegetable mechanized production in modern agriculture. After the seedlings are cultivated on a large scale by the nursery tray, they are planted into the field by the transplanter. However, unlike manual transplanting, transplanter is unable to judge the status of seedlings in the hole during seedling planting, which leads to problems such as damaged seedlings and empty holes being picked in the same order and planted into the field, resulting in yield reduction and missed planting. Aiming at this problem, we designed a seedling selective planting control system for vegetable transplanter which includes vision unit, seedling picking mechanism, seedling feeding mechanism, planting mechanism, pneumatic push rod unit, limit sensor, industrial computer and logic controller. We used asymmetrical light to construct visual identification scenes for planting conditions, which suppresses environmental disturbances. Based on the intersection operation of mask and image, a fast framework of tray hole location and seedling identification (FHLSI) was proposed combined with FCM segmentation algorithm. The vision unit provides the transplanting system with information on the status of the holes to be transplanted. Based on the information, planting system chooses the healthy seedlings for transplanting, improving the survival rate and quality of transplanting. The results show that the proposed visual method has an average accuracy of 92.35% for identification with the selective planting control system of seedlings and improves the transplanting quality by 15.4%.

Configuration switch and path selection between Schönflies motion and non-Schönflies motion based on quotient manifold of novel reconfigurable parallel mechanisms

This paper investigates configuration switch and path selection of novel reconfigurable parallel mechanisms with two double-four-bar modular linkages in terms of subgroups SE(2), SO(3) and X(z). The motion representation of reconfigurable parallel mechanisms with three motion branches is proposed based on intersection operation of manifold generated, and the switching principle of motion generators is presented to realize the switching of the three motion branches of the reconfigurable parallel mechanism through the transformation of the submanifold generated by the suitable common motion generators. Two double-four-bar modular linkages are designed to constitute a subchain in terms of the switching principle, and the configuration transformation of the subchain is proposed with respects to the configuration switch of each modular linkage following different forms of the quotient submanifold generated. A reconfigurable parallel mechanism is synthesized by means of rearranging the configurations of two modular linkages of three identical subchains. Especially, the paths of three configurations of a reconfigurable parallel mechanism are selected to satisfy switching.

Ranking of Downstream Fish Passage Designs for a Hydroelectric Project under Spherical Fuzzy Bipolar Soft Framework

Nowadays, several real-world decision-making problems concerning falling economies, power crises, depleting resources, etc., require efficient decision-making. To solve such problems, researchers proposed several hybrid models by combining the spherical fuzzy sets with other theories, such as spherical fuzzy soft sets, which is an efficient tool to deal with the uncertainties concerning positive, neutral, and negative memberships in the soft environment. However, all the existing hybridizations of spherical fuzzy sets fail to deal with information symmetrically in a bipolar soft environment. Accordingly, this paper presents a novel hybrid model called spherical fuzzy bipolar soft sets (SFBSSs) by fusing spherical fuzzy sets and bipolar soft sets, considering the opposite sets of parameters in symmetry. An example considering the selection of a chief management officer (CMO) for a multi-national company illustrates the proposed model in detail. In addition, some symmetric properties and algebraic operations of the initiated model, including subset, complement, relative null SFBSSs, relative absolute SFBSSs, extended union, extended intersection, restricted union, restricted intersection, AND, and OR operations, are discussed and illustrated via numerical examples. Further, some fundamental results, namely, commutativity, associativity, distribution, and De Morgan’s laws are presented for SFBSSs. Moreover, by considering the massive impact of hydropower in combating the energy crisis and possible dangers to fish migration, a multi-attribute decision-making problem concerning the ranking of downstream fish passage designs for a hydroelectric project is modeled and solved under the developed algorithm based on SFBSSs. Finally, a comparative analysis discusses the supremacy of the initiated model over its building blocks.

Modeling the Impact of COVID-19 on Traffic Operation, Emission and Queue Length: a Case Study

The global COVID-19 outbreak has caused a drastic change in human travel behavior. Most of the measures that have been taken by governments and local authorities involve behavioral changes from citizens to reduce their social contact to a minimum in order to control the spread of the virus. Thus, these actions affect individual activity patterns and transport systems differently. This paper quantifies the impact of COVID-19 on intersection operation performance using data from the control management room at Greater Amman Municipality (GAM) in Jordan. In this paper, the operational performance of one of the heaviest signalized intersections in Amman has been modeled under COVID-19 prevention measures. The intersection's performance has been evaluated under three scenarios, namely, before CVOID-19 hits, using an odd/even license plate strategy with activities closure, and using a 70% capacity restriction. In the Analytical Hierarchy Process (AHP), multi-criteria have been used. Three criteria groups (efficiency, capacity, and environmental) have been developed, which have contained eight sub-criteria. The weights of the criteria groups have been varied based on practitioners' and academic perspectives. The application of the developed methodology has enabled the selection of the most suitable travel restriction decision that has helped improve the transportation system's operational status. The evaluation sub-criteria in the study are vehicle delay, queue length, stopped delay, stops, travel time, vehicle safety, CO emission, and fuel consumption. Results have indicated that, by comparing the intersection operation performance before and after COVID-19, there is a significant improvement in intersection performance due to the travel restrictions during the pandemic effect. Moreover, AHP has indicated that the odd/even system is the best strategy to improve intersection performance. The results have indicated that the odd/even system has the best operational performance compared to the other two travel restrictions.

Fuzzy Distribution Sets

We introduce a new type of fuzzy set called Fuzzy Distribution Set (FDS). Fuzzy distribution sets are fuzzy sets defined on a finite domain subject to a sum of membership values equal to 1. Such fuzzy sets can serve as models of subjective probability distributions and subjective weight distributions. Considering these distributions as fuzzy sets gives a possibility to extend on such distributions the operations of fuzzy sets and, more generally, the calculus of fuzzy restrictions developed during the last decades. Recently Yager introduced the concept of negation of probability distributions. In our works, we studied several classes of such negations. Here we consider an involutive negation of probability distributions as a complement of FDS. We introduce the operations of union and intersection of fuzzy distribution sets. These basic operations on FDS can serve as a basis for the application of fuzzy logic methods to subjective probability and weight distributions. These operations can be used for the development of reasoning models with subjective probability distributions and subjective weighting functions. Weight distributions can be used in multi-criteria, multi-person, and multi-attribute decision-making models.

Distracted Driving Effects on Headways at Signalized Intersections

Distracted driving poses one of the most difficult challenges to ensuring a safe and efficient transportation system. Modern communications have delivered greater convenience. However, this has come at the cost of attention spans. Safety has been thoroughly explored from the perspective of distracted driving. However, impacts on traffic operations have received minimal research attention. A few studies have provided a theoretical mechanism on how intersection operations can be affected, but fail to quantify the real-life impacts on traffic operations. This research aims to quantify how distracted driving affects vehicle discharge headways at signalized intersections for through lanes. Thousands of observations were collected from four intersections in Orange County, Florida, covering a variety of land uses, intersection configurations, and periods of high demand. The results demonstrated that approximately a quarter of all drivers were distracted. Drivers were less distracted in commercial zones and more attentive to signal changes compared to school and residential areas. Cell phone usage had the primary effect on headways among distraction types with a 20% increase, which resulted in reducing the intersection capacity by 16.5%. The statistical model demonstrated that the overall effect of distraction on the discharge headway is significant. The base headway increased by 0.93 s, which resulted in reducing the intersection capacity by 45.5%. The results also revealed that the 10th vehicle position in the queue had a detrimental effect on the headway and the overall intersection capacity. The green phase gaps out because of the amount of time needed to reach the stop bar.

Comprehensive Evaluation of Operational Efficiency of Intersections in Arterial Considering Pedestrians Yield Rule

Yield to pedestrians has become a new trend of civilized transportation in the metropolis. In order to evaluate the influence of yield behavior on the comprehensive operation efficiency of signalized intersections in arterial, the efficiency of the subject who gives way and the subject who is given up in the process of yielding to pedestrians was considered in this study, and the comprehensive operation evaluation of intersection in arterial was given. First, based on the rule of pedestrians yield, the concept of a safe headway gap of pedestrians was introduced in the process of conflict analysis of traffic flows at the intersection, and 3 situations were discussed, which are no yield, yield to 1 flow and 2 flows, to calculate the departure rate of traffic flow at the intersection. Furthermore, models of 3 evaluation indices were established, which are number of people passing per unit time, average delay per people, and average yield number per people at intersection. Moreover, the entropy weight method was taken to decide the weight of these 3 indices, and to calculate the comprehensive efficiency evaluation of intersection operation, with the standardized matrix. Finally, case study work was carried out to evaluate the comprehensive efficiency of 4 types of intersections in arterial considering pedestrians yield rule, which is the intersection between arterial and arterial (IAA), intersection between arterial and subarterial (IAS), intersection with one-time (IAA-1, IAS-1), and two-time (IAA-2, IAS-2) crossing of pedestrians. The relevant results show that the impact of an increase in the number of pedestrians on the combined efficiency of arterial intersections can vary dramatically in different scenarios. Therefore, in the implementation process of “yielding to pedestrians,” the flow fluctuation characteristics and channelization of each intersection should be taken into account, and the corresponding phase changes should be based on pedestrian and vehicle volumes to improve the efficiency of all parts, such as pedestrians and drivers.

Feature selection based on robust fuzzy rough sets using kernel-based similarity and relative classification uncertainty measures

The current research on fuzzy rough sets (FRSs) for feature selection has two major problems. On the one hand, most existing methods employ multiple intersection operations of fuzzy relations to define fuzzy dependency functions applied to feature selection. These operations can make the evaluation of the significance of feature subsets less identifiable in high-dimensional data space. On the other hand, the classical FRS implemented for feature selection is highly sensitive to noisy information. Thus, improving the robustness of the FRS model is critical. To address the above issues, first, we propose a radial basis function kernel-based similarity measure for computing fuzzy relations. The value difference metric and Euclidean metric are utilized to measure the distance values of the mixed symbolic and real-valued features. Hereafter, a novel robust FRS model is proposed by introducing the relative classification uncertainty (RCU) measure. k-nearest neighbours and Bayes rules are employed to yield an RCU level. Relative noisy information is detected in this way. Finally, extensive experiments are conducted to illustrate the effectiveness and robustness of the proposed model.

Establishing patterns of change in the efficiency of regulated intersection operation considering the permitted movement directions

The object of this study is a regulated intersection of city streets. The main task being solved is the reduction of queue lengths on approaches to such intersections by organizational measures. As a result of the research, patterns of change in queue lengths in front of the stop line were revealed, taking into consideration the specialization of traffic lanes and the distribution of traffic flows by directions. It was established that with an increase in the share of left-turning vehicles in the lane by 15 % and above, there is an increase in the length of the queue before the intersection from 45 to 80 m. The results indicate that when choosing a traffic pattern at the intersection, it is necessary to take into consideration not only the intensity of the flow itself but also the proportion of vehicles performing certain maneuvers (in this work, turning left is considered). A feature of the results is that they are obtained using simulation tools. This research method has made it possible to derive the value of the length of the queue in front of the intersection, changing the load on the approach from 200 to 1000 vehicle/h and the share of left-turning vehicles from 5 to 15 %. In addition, using a simulation model, it was checked how the intersection functions under various traffic management schemes on it when the input parameters of traffic flows change. The research results are recommended to be used in the development of traffic management schemes at regulated intersections. When determining the permitted directions of movement in the lanes, it is necessary to take into consideration the patterns of change in the length of queues before the intersection since under certain circumstances they may exceed critical values.