Probability Of Conflict Research Articles

Safety assessment of pedestrian-vehicle interaction at signalized intersections: An observational study

Road safety is a crucial aspect of global policies and management. Surrogate Safety Measures (SSMs) have gained attention in the study of pedestrian safety. This study aims to establish an effective SSM methodology to analyze driver-pedestrian interactions. The analysis relies on SSM indicators, without the need for an initial classification of driver-pedestrian interactions into specific interaction patterns. The proposed methodology offers several advantages, including the accurate identification of conflicts through an affordable approach making it easily accessible for public administrations and authorities to assess pedestrian safety at road intersections. A dataset comprising 270 driver-pedestrian interactions, observed at three road intersections in Rome, Italy, was examined. The severity level of each event was assessed through a preliminary classification of each interaction into three patterns: high, low, and none. Subsequently, the severity levels were evaluated using three methods, employing Time-to-Collision (TTC), Post-Encroachment Time (PET), and a combination of TTC and PET. A comparison between the severity levels identified by the two approaches was conducted. The findings reveal that Method 2, utilizing PET, consistently identifies conflicts. Additionally, a binomial logistic regression analysis was performed to identify the variables that influence the likelihood of an interaction escalating into a conflict. The results demonstrate that the probability of conflict increases with the duration of a red signal, particularly for younger pedestrians.

A coordinated scheduling approach for task assignment and multi-agent path planning

Path finding is an essential problem in multi-agent systems, widely employed in warehousing and logistics. However, most of the current studies focus on the problem of assigning one agent with one task in a period, which may hinder the efficiency of path planning of the systems when facing multi-tasks. To address this problem, we propose a multi-layer planner, under which a co-scheduling method for multi-agent with batch tasks and path planning in a continuous workspace is proposed. In the task allocation layer of the framework, a standard Genetic Algorithm (GA) is adopted, which optimizes the allocation of task sets, and minimizes the path lengths and the probability of conflicts. Secondly, an Improved Car-Like Conflict-Based Search (ICL-CBS) algorithm is presented as the conflict resolution layer to reduce the runtime. Finally, ICL-CBS and the Spatiotemporal Hybrid-State A* (SHA*) algorithm are jointly used to determine multi-agent paths in the path planning layer. We conduct experiments and compare our method with the baseline algorithm on random obstacles and practical scenarios. The results show that our method effectively improves the efficiency of multi-task completion, and alleviates the computational burden of underlying path planning. Specifically, our method has less runtime.

SONDERFALL SCHWEIZ: WILLENSNATION (NATION BY WILL) OR MULTICULTURAL POLITY

The article is devoted to the study of the origins of Swiss statehood, regarded through the prism of the political and cultural nation concepts. It traces the main stages of the Old Confederation, features of the formation of unique public institutions, such as direct democracy, communalism, eternal neutrality. Special attention is paid to the linguistic factor in the political life of the country and its conflict potential. The author concludes that the cumulative effect of consociational democracy and cross-cutting cleavages, together with institutionalized quadrilingualism, reduces the probability of ethno-political conflicts. Advocating the concept of «nation by will» (Willensnation) as the main source of Swiss statehood, the author appeals to such factors as the peculiarities of the historical development of the country and its geographical position in the environment of European absolutist regimes, direct democracy, «cantonization», religious landscape, high level of literacy of the population, contributed to social communication, economic modernization, system of «linguistic harmony» (Sprachfrieden). In conclusion, it is argued that in the late 19th century on the basis of civil identity, the cultural national consciousness was gradually formed under the influence of the state patriotic discourse, which united a complex of myths, symbols and narratives with the institutions of the Confederation.

Trade and Peace Revisited

The existing literature on trade and peace has not definitively established whether bilateral trade reduces the probability of militarized conflict. While estimated effects remain highly sensitive to empirical specifications, a commonly overlooked aspect within this literature is the insufficient consideration of potential heterogeneous relationships across country pairs and the temporal dependence of conflicts. In this paper, we present supportive evidence of the pacifying effect of trade when both heterogeneity and temporal dependence are simultaneously taken into account. By applying the Arellano-Bond model to datasets from Keshk, Pollins, and Reuveny (2004) and Hegre, Oneal, and Russett (2010), which respectively indicated no and negative effects of trade on conflict, we find that bilateral trade significantly reduces the likelihood of conflict in both datasets. This finding adds further support to liberal claims regarding the interconnected nature of economic interdependence and conflict.

Особливості врегулювання крос-культурних конфліктів в процесі здійснення зовнішньоекономічної діяльності

Any violations or problems in the establishment of cross-cultural communication in the organiza-tion can become the causes of potential conflicts. Therefore, for their prevention or faster solving, it is important to understand the possible causes of their occurrence. Problems related to the establishment of cross-cultural communication can be: the use of cultural filters when forming an opinion about foreign counterparties; insufficient level of tolerance towards part-ners or clients; incorrect use of verbal and non-verbal means of communication; the establishment of new connections may depend on the degree of implementation of the principles of social responsibility, as this indicates the reliability of the business entity. Conventionally, all problems of cross-cultural interaction can be divided into two groups: conducting negotiations with international business partners and commu-nication within the organization. Usually, cross-cultural conflict during business negotiations arises for two main reasons. First, when dealing with cultural differences, partners quite often rely on stereotypes. Stereotypes are often de-rogatory and can lead to distorted expectations about the opponent's behavior and potentially misinterpre-tations. The second most common cause of intercultural misunderstandings is the tendency to interpret the behavior, values, and beliefs of others through the lens of one's own culture. To overcome this tendency, it is important to learn as much as possible about the culture of the foreign partner's side. The classification of business cultures by Richard Lewis can help to better navigate the character-istics of different cultures, comparing one with another and identifying common and distinctive features. This method is useful for planning cooperation with new counterparties in order to minimize the risk of potential conflicts due to unfamiliarity with the foreign partner. Before starting each negotiation, especially if they take place with new counterparties, it is neces-sary to process an array of information about cross-cultural differences. It is thanks to this measure that the probability of cross-cultural conflict can be minimized. And when a dispute arises, the company's team still needs to review its training, because in most cases, knowing cultural characteristics and being able to use them correctly is the key to solving the problem. For the effective resolution of conflicts, it is worth using the recommended strategy for resolving cross-cultural conflicts in the company in the process of foreign economic activity.

Trade and peace: The WTO case

Investigating the impact of international trade on global peace assumes paramount significance given the current state of global political and economic instability, which is characterized by growing volatility and increased uncertainty. This paper empirically examines the impact of international trade on peace in the world and among different countries from the perspective of the World Trade Organization (WTO). Using data on interstate conflicts from 1950 to 2000, we find robust evidence that the international trade framework, represented by the WTO, reduces the probability and intensity of militarized interstate disputes, thereby making a significant contribution to the establishment and maintenance of global peace. The magnitude of this impact, however, varies depending on the geographical distance between nations, the extent of tariff concessions made by countries, and the changes in the institutional framework of the World Trade Organization. First, the WTO has the greatest impact on neighboring countries and those in close proximity, where the probability of conflicts is higher. Second, the peace-promoting effect of the WTO is significantly higher for developed countries that make greater tariff concessions compared to developing countries. Finally, changes in the WTO's institutional framework following the Uruguayan negotiations have diminished its effect in promoting peace. These results suggest that in order to mitigate the current concerns about global security, all countries must insist on expanding openness, deepening common interests, and avoiding engaging in direct military conflicts that would result in significant welfare losses.

Assessing human–carnivore conflict and the identification of hotspot areas to prioritize mitigation efforts

ABSTRACT Human‒carnivore conflict (HCC) is a worldwide conservation challenge. A multi-method approach was used to assess the perceived threats posed to human life or property by carnivores and determine the effects of socio-demographic and environmental factors on HCC in south-western Iran. Results showed that red foxes, gray wolves and honey badgers were the main species responsible for the conflict. People with higher education were less likely to kill carnivores or report negative attitudes toward them. Human alterations of natural habitats are responsible for the majority of HCC, with an anthropogenic factor (distance to cropland) as the top predictor. Villages with the highest probability of conflict were located in proximity to national parks. The presence of landfill sites in proximity of human settlements and improper waste disposal methods may increase HCC. Focusing mitigation measures on high-risk areas can potentially reduce conflicts and lead to a decrease in retaliatory killings of predators.

Cross-Layer Design for Energy-Efficient Reliable Multi-Path Transmission in Event-Driven Wireless Sensor Networks.

In event-driven wireless sensor networks (WSNs), a reliable, efficient, and scalable routing solution is required for the reliable delivery of sensory data to the base station (BS). However, existing routing algorithms rarely address the issue of energy efficiency under multi-path conflicts for multi-event-driven scenarios. In order to maximize energy efficiency while maintaining a manageable conflict probability, this paper investigates a cross-layer design of routing and power control for multi-event-driven WSNs. We first develop a mathematical characterization of the conflict probability in multi-path routing, and we then formulate the energy efficiency maximization problem as a non-convex combinatorial fractional optimization problem subject to a maximum conflict probability constraint. By utilizing non-linear fractional programming and dual decomposition, an iterative search algorithm was used to obtain near-optimal power allocation and routing solutions. Extensive results demonstrate that our proposed algorithm achieved a gain of 9.09% to 35.05% in energy efficiency compared to other routing algorithms, thus indicating that our proposed algorithm can avoid unnecessary control overhead from multi-path conflicts with a lower conflict probability and can ensure maximum energy efficiency through routing and power control design.

Assessing bicycle-vehicle conflicts at urban intersections utilizing a VR integrated simulation approach

Animosity between drivers and cyclists has existed on urban road networks for many years. Conflicts between these two groups of road users are exceptionally high in the shared right-of-way environments. Benchmarking methods of conflict assessments are mostly based on statistical analysis with limited data sources. The actual crash data would be valuable to understand the features of bike-car collisions, however the available data are spatially and temporally sparse. To this end, this paper proposes a simulation-based bicycle-vehicle conflict data generation and assessment approach. The proposed approach uses a three-dimensional visualization and virtual reality platform, integrating traffic microsimulation to reproduce a naturalistic driving/cycling-enabled experimental environment. The simulation platform is validated to reflect the human-resembled driving/cycling behaviors under different infrastructure designs. Comparative experiments are carried out on bicycle-vehicle interactions under different conditions, with data collected from a total of 960 scenarios. Based on the results of the surrogate safety assessment model (SSAM), the obtained key insights include: (1) scenarios of a high conflict probability do not lead to actual crashes, which suggests that the classic SSM-based measurements such as TTC or PET values may not sufficiently reflect real cyclist-driver interactions; (2) the major cause of conflicts is variation in vehicle acceleration, which suggests that drivers are considered to be the main party responsible for bicycle-vehicle conflict/crash occurrence; (3) the proposed approach is able to generate near-miss events and reproduce interaction patterns between cyclists and drivers, facilitating experiments and data collections which would be typically unavailable for this type of study.

Understanding the impact of vehicle dynamics, geometric and non-geometric roadway attributes on surrogate safety measure using connected vehicle data

Traditional safety research mostly relies on accident data to analyze the precedents to a crash. Alternatively, surrogate safety measures have the potential to proactively evaluate safety events. The era of connected vehicles and smart sensing has brought about tremendous innovations in safety research. GPS data from such vehicles form a useful case of big data analytics where surrogate safety measures have largely been unexplored. In this paper, we propose time to collision estimation from connected vehicle GPS data. The vehicle dynamics such as speed, acceleration, yaw rate, etc. are then coupled with geometric and non-geometric roadway attributes to understand the contributing factors for a traffic conflict. The dataset contains 2,568,421 GPS points from 14,753 unique journeys. 1:4 ratio of conflict to non-conflict events was used to select 15,258 samples with 28 independent vehicle dynamics, geometric, and non-geometric variables. Binary logit model was used to investigate the relationship of these variables with conflicts. Model results showed that out of 28 independent variables, 6 independent variables and 7 interaction variables were found significant. The results showed some interesting and unique relations of these variables with conflicts. Based on these significant variables, k-means clustering was performed to understand the threshold for the significant values for which the number of conflicts is significantly increased. Results from k-means clustering and two sample binomial proportion t-tests revealed that when absolute acceleration crossed 0.8 m/s2, conflict probability increased by 8 percentage points.​ Moreover, when the yaw rate crossed 8 degrees/s, the conflict probability doubled. Besides, vehicles traveling at more than 140% of the recommended speed limit increased conflict probability by 7 percentage points.

Learning of irrelevant stimulus-response associations modulates cognitive control

It has been shown that manipulating the proportion of congruent to incongruent trials in conflict tasks (e.g., Stroop, Simon, and flanker tasks) can vary the size of conflict effects, however, by two different mechanisms. One theory is the control learning account (the brain learns the probability of conflict and uses it to proactively adjust the control demand for future trials). The other is the irrelevant stimulus-response learning account (the brain learns the probability of irrelevant stimulus-response associations and uses it to prepare responses). Previous fMRI studies have detected the brain regions that contribute to the control-learning-modulated conflict effects, but it is less known what neural substrates underlie the conflict effects modulated by irrelevant S-R learning. We here investigated this question with a model-based fMRI study, in which the proportion of congruent to incongruent trials changed dynamically in the Simon task and the models learned the probability of irrelevant S-R associations quantitatively. Behavioral analyses showed that the unsigned prediction errors (PEs) of responses generated by the learning models correlated with reaction times irrespective of congruent and incongruent trials, indicating that large unsigned PEs associated with slow responses. The fMRI results showed that the regions of fronto-parietal and cingulo-opercular network involved in cognitive control were significantly modulated by the unsigned PEs, also irrespective of congruent and incongruent trials, indicating that large unsigned PEs associated with transiently increased activity in these regions. These results together suggest that learning of irrelevant S-R associations modulates reactive control, which demonstrates a new way to modulate cognitive control compared to the control learning account.

MRVs: Enforcing Numeric Invariants in Parallel Updates to Hotspots with Randomized Splitting

Performance of transactional systems is degraded by update hotspots as conflicts lead to waiting and wasted work. This is particularly challenging in emerging large-scale database systems, as latency increases the probability of conflicts, state-of-the-art lock-based mitigations are not available, and most alternatives provide only weak consistency and cannot enforce lower bound invariants. We address this challenge with Multi-Record Values (MRVs), a technique that can be layered on existing database systems and that uses randomization to split and access numeric values in multiple records such that the probability of conflict can be made arbitrarily small. The only coordination needed is the underlying transactional system, meaning it retains existing isolation guarantees. The proposal is tested on five different systems ranging from DBx1000 (scale-up) to MySQL GR and a cloud-native NewSQL system (scale-out). The experiments explore design and configuration trade-offs and, with the TPC-C and STAMP Vacation benchmarks, demonstrate improved throughput and reduced abort rates when compared to alternatives.

An accurate and efficient approach to probabilistic conflict prediction

Conflict prediction is a vital component of path planning for autonomous vehicles. Prediction methods must be accurate for reliable navigation, but also computationally efficient to enable online path planning. Efficient prediction methods are especially crucial when testing large sets of candidate trajectories. We present a prediction method that has the same accuracy as existing methods, but up to an order of magnitude faster. This is achieved by rewriting the conflict prediction problem in terms of the first-passage time distribution using a dimension-reduction transform. First-passage time distributions are analytically derived for a subset of Gaussian processes describing vehicle motion. The proposed method is applicable to 2-D stochastic processes where the mean can be approximated by line segments, and the conflict boundary can be approximated by piece-wise straight lines. The proposed method was tested in simulation and compared to two probability flow methods, as well as a recent instantaneous conflict probability method. The results demonstrate a significant decrease of computation time.

How are psychodynamic conflicts associated with personality functioning? A network analysis.

Personality functioning and psychodynamic conflicts are central constructs in psychoanalytic theories of psychopathology as well as in many psychodynamic treatment models. Although there has been a longstanding conceptual discussion on how they relate to each other, empirical evidence on this question is still scarce. In this study, we explore the associations between psychodynamic conflicts and levels of structural integration (which can be used synonymously with personality functioning) by means of a partial correlation network analysis in a sample of N = 220 outpatients interviewed and rated according to Operationalized Psychodynamic Diagnosis (OPD-2). We examined network centrality, bridge centrality, clustering, and network stability. The network analysis resulted in separate clusters for levels of structural integration and conflicts, supporting the assumption of distinct psychodynamic constructs. The greatest association between the two clusters was found between the individuation vs. dependency conflict (C1) and the structural capacity to attach to internal objects. In general, C1 showed significantly greater connections with structural dimensions compared to the other five OPD conflicts included. C1 was also more central in the network compared to most other conflicts, whereas the structural dimensions did not differ in centrality. All structural dimensions were found to be strongly interconnected. C1 showed exclusively negative edges to the other conflicts, suggesting that a profound C1 decreases the probability of other psychodynamic conflicts. We discuss clinical as well as conceptual implications of our findings for psychodynamic diagnosis and treatment.

Indonesia’s nickel export restriction policy: alternative on environmental approach for Article XI:1 GATT justification

PurposeThis paper aims to analyse the aspects of the demonstration process of Indonesia's regulation on nickel export restriction for its eligibility to be excluded from Article XI:1 GATT. It also analyses the possibility of the use of an environmental approach in the demonstration process and for an alternative measure in its implementation.Design/methodology/approachThe paper uses a normative research method in conducting its analysis. It analyses Indonesia's nickel export restriction policy based on the European Union's claim regarding quantitative restriction, with the international trade governance in the WTO framework, and certain international trade principles. The study also involves certain WTO jurisprudence to give a comprehensive analysis to the case.FindingsThis paper finds that Indonesia still needs to provide a complete and comprehensive demonstration to prove its eligibility for exclusion from Article XI:1. Demonstrating merely based on an economic approach is inadequate to convince the panel in Indonesia – measure relating to raw material for justification under Article XI:2. This study further finds that both parties generally focus on the economic aspect, which leaves room for conflict of interest. Other aspects with a lower probability of conflict of interest, such as the environmental approach, could be an alternative for the implementation.Originality/valueThis paper fulfils the need to provide a scientific analysis of the application of Indonesia's nickel export restriction policy, including its proceedings in WTO's dispute settlement body, which is essential for international trade governance enforcement.

A Novel Fault-Tolerant Air Traffic Management Methodology Using Autoencoder and P2P Blockchain Consensus Protocol

This paper presents a methodology for designing a highly reliable Air Traffic Management and Control (ATMC) methodology using Neural Networks and Peer-to-Peer (P2P) blockchain. A novel data-driven algorithm was designed for Aircraft Trajectory Prediction (ATP) based on an Autoencoder architecture. The Autoencoder was considered in this study due to its excellent fault-tolerant ability when the input data provided by the GPS is deficient. After conflict detection, P2P blockchain was used for securely decentralized decision-making. A meta-controller composed of this Autoencoder, and P2P blockchain performed the ATMC task very well. A comprehensive database of trajectories constructed using our UAS-S4 Ehécatl was used for algorithms validation. The accuracy of the ATP was evaluated for a variety of data failures, and the high-performance index confirmed the excellent efficiency of the autoencoder. Aircraft were considered in several local encounter scenarios, and their trajectories were securely managed and controlled using our in-house Smart Contract software developed on the Ethereum platform. The Sharding approach improved the P2P blockchain performance in terms of computational complexity and processing time in real-time operations. Therefore, the probability of conflicts among aircraft in a swarm environment was significantly reduced using our new methodology and algorithm.

The political trust impacts of land titling in China

This paper uses panel data from 2017 to 2019 in Yangshan County, Guangdong Province, to assess the impact of land titling on farmers’ political trust. The results of a generalized difference-in-differences model suggest that land titling increases farmers’ subjective trust in the local village council and reduces the probability of conflict with the local village council. We found that the mechanism by which land titling affects farmers’ political trust is the stability of land rights. Furthermore, regulated procedural implementation can strengthen the impact of land titling on political trust. Additionally, we unexpectedly found that land titling positively impacts the relationship between villagers and cadres, and collective action participation, in addition to influencing farmers’ political trust.

Effect of Construction Work Zone on Rear-End Conflicts by Vehicle Type under Heterogeneous Traffic Conditions

Road transportation is a critical mode of transportation because of its mobility characteristics. Road construction work zones (WZ) are widespread on roads because of increased travel demand. Thus, it is necessary to study traffic safety for WZs and regular sections. In this study, traffic safety is analyzed in terms of the conflict probability at selected roads with WZ and without work zone (WWZ) sections along the same road. Vehicular trajectory data for three traffic flow levels (free flow, near capacity, and congestion) were extracted using a newly developed machine learning–based semiautomated trajectory extractor tool. The derived trajectory data from both sections were used to identify the leader-follower vehicle pairs using MATLAB. Two surrogate safety measures were estimated to compute the rear-end conflicts: time-to-collision and deceleration rate to avoid a collision. Hence, the variation of the rear-end conflicts was further examined using the generalized extreme value theory. It is found that the conflict probability is more in the WWZ section than the WZ section, which may be attributed to the variation in speed and acceleration. It is also found that the conflict probability for the WWZ and WZ sections is reduced as the angle between the two vehicles increases. The study results should help highway authorities to implement suitable safety measures to reduce conflicts and crashes in the work zones.

Analysis of the traffic conflict situation for speed probability distributions

AbstractThe increasingly widespread application of drones and the emergence of urban air mobility leads to a challenging question in airspace modernisation: how to create a safe and scalable air traffic management system that can handle the expected density of operations. Increasing the number of vehicles in a given airspace volume and enabling routine operations are essential for these services to be economically viable. However, a higher density of operations increases risks, poses a great challenge for coordination and necessitates the development of a novel solution for traffic management. This paper contributes to the research towards such a strategy and the field of airspace management by calculating and analysing the conflict probability in an en-route, free-flight scenario for autonomous vehicles. Analytical methods are used to determine the directional dependence of conflict probabilities for exponential and normal prescribed speed probability distributions. The notions of geometric and speed conflict are introduced and distinguished throughout the calculations of the paper. The effect of truncating the set of available flight speeds is also investigated. The sensitivity of the calculated results to speed and heading perturbations is studied within the analytical framework and verified by numerical simulations. Results enable a fresh approach to conflict detection and resolution through distribution shaping and are intended to be used in an integrated, stochastic coordination framework.

Monte Carlo-Based Microsimulation Approach for Estimating the Collision Probability of Real Traffic Conflicts

During driving in real traffic, often conflict situations arise which do not lead to an accident; however, they offer a good indication of traffic (un)safety. There are many methods and indicators for classifying whether a current driving situation can be considered as a conflict or not (e.g., time to collision, post-encroachment time). However, not many approaches exist to predict how such conflicts will evolve once they have been identified and what the collision probability would be given the conditions of the conflict. Currently available methods make strong assumptions about driver behavior during the conflict, usually do not consider all participants involved in the conflict (only two vehicles), and have limited applicability to various types of real conflicts. In this paper, a Monte Carlo-based microsimulation approach is proposed to estimate the probability of collision for a conflict of any type. Unlike previous approaches, the proposed method can be used to simulate any type of conflict with an arbitrary initial conflict condition and an arbitrary number of vehicles in conflict. The method was developed based on real-world video data of a complex signalized intersection, from which conflicts were identified with the DOCTOR method. As proof of concept, the proposed method was applied to a real conflict involving four vehicles which was extracted from these video data and validated with a real traffic accident. The results show that our approach is capable of simulating real conflicts of various types with multiple participants and predicting their probability of collision.