Ansar Ul-Haque Yasar’s research while affiliated with Hasselt University and other places

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Publications (15)


Integrating Emotional Modeling and Feedback in UAV Systems for Enhanced Traffic Monitoring and Smart Transportation Management
  • Chapter

December 2024

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7 Reads

Mohamed Zaidan

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Ansar Yasar

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Michele Melchiori

As Unmanned Aerial Vehicles (UAVs) become integral to urban infrastructure, their ability to communicate effectively with human operators and adapt to dynamic environments is crucial. This paper presents an innovative approach to enhancing UAV performance in transportation and traffic monitoring by integrating emotional intelligence through the PAD (Pleasure, Arousal, Dominance) model. The proposed system architecture includes a comprehensive data collection layer that gathers diverse inputs from sensors and contextual information, a perception analysis layer that processes these inputs to generate emotional states using the PAD model, and a response layer that translates these emotional states into specific behaviors through behavioral mapping and adaptation modules. Detailed methodologies, including pseudocode and flowcharts for key modules such as data normalization, PAD calculation, mood updating, and mood octant determination, are provided for clarity and reusability. The system’s effectiveness is validated through practical scenarios such as routine surveillance, heavy traffic monitoring, and incident detection, demonstrating significant improvements in UAV adaptability and interaction. Key contributions include the development of a multi-dimensional emotional model for UAVs, a dynamic mood updater module, and the successful application of the PAD model in complex traffic monitoring scenarios. This approach significantly enhances UAV performance, ensuring more natural interactions with human operators and better adaptability to real-time traffic conditions. It paves the way for future exploration into emotionally intelligent autonomous UAV systems.


Proposed legal driving states
Mapping the legal driving states into the driving styles
Divide-and-Conquer approach for a simultaneous management of driving styles
The proposed agent-based IFAF architecture
Illustration of the number of hops between an initiator of an information and its receiver

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An intelligent divide-and-conquer approach for driving style management
  • Article
  • Publisher preview available

September 2023

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83 Reads

Personal and Ubiquitous Computing

Driving styles reflect the performance and the ability of drivers to drive in a safe and protective manner. As some of them would possibly result into harmful behaviors, the recognition of these styles continue to attract intensive investigations from the transportation community. In spite of the current promising results, the existing approaches did not yet address the management of simultaneous driving behaviors that are exhibited by a driver during the same commute. They did not also explicitly investigate the legal implication of these driving styles. To this end, we argue that intelligent collaborative solutions could adequately handle the constantly changing traffic environment, prevent aberrant driving behaviors, classify driving styles, and identify the right road traffic policies to apply at the right time to the right driver. Therefore, we are proposing a new intelligent divide-and-conquer approach that aims to process concurrent driver’s driving behaviors and identify the related driving styles, accordingly. Our solution relies on a four-layer Multi-Agent System (MAS) architecture, where intelligent agents execute injection, filtering, action, and feedback processing steps to ultimately generate personalized recommendations and feedback to drivers. For the sake of illustration, we collected driving data about braking and acceleration behaviors via our dedicated mobile app AWARIDE. We successfully classified the driving styles into aggressive, normal, and conservative. We also successfully identified the transitions between these styles.

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Parameters and variable meanings
A tripartite evolutionary game analysis of providing subsidies for pick-up/drop-off strategy in carpooling problem

September 2023

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56 Reads

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2 Citations

Autonomous Intelligent Systems

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Li Li

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[...]

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Ansar Yasar

Although the pick-up/drop-off (PUDO) strategy in carpooling offers the convenience of short-distance walking for passengers during boarding and disembarking, there is a noticeable hesitancy among commuters to adopt this travel method, despite its numerous benefits. Here, this paper establishes a tripartite evolutionary game theory (EGT) model to verify the evolutionary stability of choosing the PUDO strategy of drivers and passengers and offering subsidies strategy of carpooling platforms in carpooling system. The model presented in this paper serves as a valuable tool for assessing the dissemination and implementation of PUDO strategy and offering subsidies strategy in carpooling applications. Subsequently, an empirical analysis is conducted to examine and compare the sensitivity of the parameters across various scenarios. The findings suggest that: firstly, providing subsidies to passengers and drivers, along with deductions for drivers through carpooling platforms, is an effective way to promote wider adoption of the PUDO strategy. Then, the decision-making process is divided into three stages: initial stage, middle stage, and mature stage. PUDO strategy progresses from initial rejection to widespread acceptance among drivers in the middle stage and, in the mature stage, both passengers and drivers tend to adopt it under carpooling platform subsidies; the factors influencing the costs of waiting and walking times, as well as the subsidies granted to passengers, are essential determinants that require careful consideration by passengers, drivers, and carpooling platforms when choosing the PUDO strategy. Our work provides valuable insight into the PUDO strategy’s applicability and the declared results provide implications for traffic managers and carpooling platforms to offer a suitable incentive.


Components of automated enforcement systems
RADAR vs. LIDAR: working principles (source: Viion Systems (2020), [19])
Comparison review on LIDAR technologies vs. RADAR technologies in speed enforcement system

September 2023

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173 Reads

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2 Citations

Personal and Ubiquitous Computing

Traffic accidents are continuously rising in many countries all over the world. Violation of road safety regulations and traffic laws is one of major reason to this increasing trend. Existing intelligent transportation systems (ITS) to date are accurately enforcing safe municipal speed limits using enforcement technology solutions. The systems for automated traffic enforcement emerged in the last decade. Automated enforcement technologies provide opportunity to remotely capture images of drivers violating laws. RADAR/LIDAR-based tools are used to determine the speed of vehicles. Choosing the right speed detection technology is an area of significant concern for transportation agencies. This paper presents a comparison review of the use of LIDAR technologies vs. RADAR technologies in traffic enforcement systems. The current trend suggests an inclination toward LIDAR technology because of many advantages, particularly its precise identification of violators; especially, this functionality is being required in case of new travel modes (such e-bikes and e-scooty) emerged in urban areas. However, the objectives and available resources of enforcement programs are key factors that may result in growth in relation to demand for both types of technologies.


Figure 8. (a) Variation in the mean uncertainty over time in the temporal belief of the drone leader using only cumulative fusion operator; (b) Difference between the perceived and received opinions.
Figure 8. (a) Variation in the mean uncertainty over time in the temporal belief of the drone leader using only cumulative fusion operator; (b) Difference between the perceived and received opinions. Sensors 2022, 22, x FOR PEER REVIEW 16 of 21
Figure 9. Variation in the (a) Mean uncertainty over time in the temporal belief of the drone leader using only average fusion operator; (b) Difference between the perceived and received opinions.
Assignment of criteria values for different alternative strategies.
Hierarchical Analysis Process for Belief Management in Internet of Drones

August 2022

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62 Reads

Sensors

Group awareness is playing a major role in the efficiency of mission planning and decision-making processes, particularly those involving spatially distributed collaborative entities. The performance of this concept has remarkably increased with the advent of the Internet of Things (IoT). Indeed, a myriad of innovative devices are being extensively deployed to collaboratively recognize and track events, objects, and activities of interest. A wide range of IoT-based approaches have focused on representing and managing shared information through formal operators for group awareness. However, despite their proven results, these approaches are still refrained by the inaccuracy of information being shared between the collaborating distributed entities. In order to address this issue, we propose in this paper a new belief-management-based model for a collaborative Internet of Drones (IoD). The proposed model allows drones to decide the most appropriate operators to apply in order to manage the uncertainty of perceived or received information in different situations. This model uses Hierarchical Analysis Process (AHP) with Subjective Logic (SL) to represent and combine opinions of different sources. We focus on purely collaborative drone networks where the group awareness will also be provided as service to collaborating entities.


Fig. 1 PHASE A flowchart-methodological approach and methods used. H human/behavioral, T technological, O organizational, L legal/ regulatory, D domains/areas within each cluster. Attribute TD2
Fig. 2 PHASE B flowchart-methodological approach and methods used. H human/behavioral, T technological, O organizational, L legal/ regulatory, D domains/areas within each cluster. Attribute TD2 denotes an attribute that pertains to the Technological (T) cluster and
Fig. 3 Normalized and aggregated (by group) total scores for each feature. F/E first/early responder, Tech technology developer
A Proposed Methodological Approach for Considering Community Resilience in Technology Development and Disaster Management Pilot Testing

June 2022

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48 Reads

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5 Citations

International Journal of Disaster Risk Science

Nowadays, resilience has become an indispensable term in several aspects and areas of research and life. Reaching consensus on what actually constitutes ''resilience,'' ''community,'' and ''community resilience'' is still a task that guarantees a vivid exchange of opinions, sometimes escalating into debates, both in the scientific community and among practitioners. Figuring out how to practically apply resilience principles goes even a step further. This study attempts to circumvent the need for a universal agreement on the definition of ''community resilience,'' which may still be immature, if not impossible, at this time. We accomplish this by proposing a practical methodological approach with concrete methods on how to agree and implement commonly accepted community resilience principles in the context of technology development and pilot testing for disaster management. The proposed approach was developed, tested, and validated in the context of the Horizon 2020 EU-funded project Search and Rescue. Major aspects of the approach, along with considerations for further improvement and adaptation in different contexts, are addressed in the article.



Guest Editorial: Special Issue on Data Science Approaches and Applications

May 2022

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10 Reads

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1 Citation

Computing and Informatics

This special issue is based on best papers selected from the 1stInternational Con-ference on Applied Data Science and Intelligence (ADSI 2021), the 1stInternationalConference on Recent Theories and Applications in Transportation and Mobility The conferences, which were planned to take placeon 14–15 October 2021 in Prague, Czech Republic, were held online on the samedates due to COVID restrictions. They attracted a large number of scientific papers.Based on a thorough peer review process as well as on the evaluations of the GuestEditors, about 20 % of the papers were selected for their significant contributions tothe field of data science via innovative approaches and applications. We present inwhat follows a short abstract of each paper.


A Five-Step Drone Collaborative Planning Approach for the Management of Distributed Spatial Events and Vehicle Notification Using Multi-Agent Systems and Firefly Algorithms

July 2021

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55 Reads

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14 Citations

Computer Networks

In spite of the performance that existing approaches for drone collaborative planning have demonstrated, there is still a need for new solutions which are capable of effectively identifying the right tasks for the right drones at the right times while maximizing the total benefits obtained from the drones’ actions. These new solutions should be particularly tested within the context of intelligent transportation systems to assess their impact on mobility and traffic flow. In order to address these issues, we present in this paper a new a five-step solution for drone collaborative planning. Our solution uses a Multi-Agent System as well as a Firefly Algorithm solution to enable drones jointly neutralize ongoing events by considering trust factors and cost/benefit analysis. The solution, which is also capable of issuing appropriate warnings to vehicles to prevent them from incurring any undesirable/dangerous impact due to ongoing events, is using a reward-driven competition to encourage drones to join collaborating teams. Our simulations are showing promising results in terms of processing time, energy consumption, and total reward obtained compared to two other planning approaches relaying on random and priority-based selection of the next locations that drones will visit respectively.


A Survivable Communication Game based Approach for a network of cooperative UAVs

April 2021

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29 Reads

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2 Citations

Computer Communications

Unmanned Aerial Vehicle (UAV) based technologies are suitable for many civil and military application. In case of the occurrence of some natural disasters such as storms, the infrastructure of the communication system plays a vital role in offering rescue services. In such situations, energy and distance limitations can affect the operations of the UAVs and change the efficiency of the UAV network. To overcome intermittent connectivity and unstable links in this highly dynamic topology, a resilient UAV network is needed. In this paper, the communications infrastructure of a multi-UAV network is investigated in term of availability and survivability factors. We utilize the selected path in the multi-level multi-UAV network to avoid problems associated to interference, link failures, energy constrains, and routing. We present a distributed approach, namely: Survivable Communication Game based Approach (SCGA). SCGA works based on a cooperative communication between UAVs to guarantee a reliable data transmission using the best path. First, we build the utility of our approach based on the achievable rate, transmission delay, and energy consumption. Next, we formulate the interactions between UAVs based on a game framework approach. last, we conduct an extensive simulation using different communication scenarios to investigate the performance of the SCGA in terms of survivability, scalability, and reliability. In addition, the communication links and the connectivity between UAVs are tested using different performance metrics. Moreover, we compare SCGA against both of Nearest Neighbor (NN) and Nash Network Formation (NNF) schemes. The simulation results show that SCGA outperforms both of NN and NNF schemes in terms survivability, scalability, and reliability.


Citations (8)


... Darwin's seminal work, The Origin of Species, posits a natural selection paradigm that counters this cooperative ethos, highlighting innate selfinterest [2]. Given the central role of cooperation in fostering a sustainable future, its understanding emerges as a critical scientific mandate of the 21st century [3]- [5]. Meeting this This work has been supported in part by the National Natural Science mandate calls for interdisciplinary initiatives and innovative research, emphasizing cooperation's pivotal role in humanity's forthcoming challenges. ...

Reference:

Evolutionary game theory combined with reinforcement learning synthesis - A comprehensive survey
A tripartite evolutionary game analysis of providing subsidies for pick-up/drop-off strategy in carpooling problem

Autonomous Intelligent Systems

... Radar systems leverage radio waves to determine the velocity of vehicles through an analysis of the Doppler effect present in the reflected signals [15]. Lidar technology, on the other hand, measures the time it takes for light to return to the sensor after it has been pulsed with a laser beam to calculate distance and speed [16]. Video-based systems use cameras to record vehicle movements and calculate speed by monitoring the distance traveled over time [17]. ...

Comparison review on LIDAR technologies vs. RADAR technologies in speed enforcement system

Personal and Ubiquitous Computing

... In addition to attributes, some scholars further divided community resilience into two aspects: resources and capabilities. The Community-Based Resilience Assessment (CoBRA) toolkit developed by the United Nations Development Programme's Drylands Development Centre categorizes community resilience into community resources and community capabilities, assessing community resilience based on static community resources and dynamic community capabilities (15). Ma et al. (16) divided community resources and capabilities into four parts: community relationships, risk and vulnerability levels, emergency procedures, and community resource availability. ...

A Proposed Methodological Approach for Considering Community Resilience in Technology Development and Disaster Management Pilot Testing

International Journal of Disaster Risk Science

... Other strategies have concentrated on collaborative planning, a refinement process wherein collaborating organizations might alter current plans following intentions. Obstacle avoidance, route overlap avoidance, scheduling trajectories, and other challenges are studied in this context [89]. It is important to note that deploying several UAVs as opposed to one has a variety of benefits, which summarize below [ Usage scenarios for UAV swarms that may use in both urban and rural settings depict in Fig. 3 [88]. ...

A Five-Step Drone Collaborative Planning Approach for the Management of Distributed Spatial Events and Vehicle Notification Using Multi-Agent Systems and Firefly Algorithms
  • Citing Article
  • July 2021

Computer Networks

... It is not clear whether many of the proposed methods are building truly robust UAV detectors or if they will perform optimally against a specific dataset. Many different approaches compete against public UAV datasets [18][19][20], sometimes achieving accuracy up to 99% [21,22], which is very promising. However, one issue is that the public datasets are usually collected in a lab setting, with simulated noise added later, which does not accurately capture real channel conditions. ...

RF-Based UAV Detection and Identification Using Hierarchical Learning Approach

Sensors

... Energy improvement by path planning, a prediction mechanism for data transmissions and battery charging of devices, and dynamic path planning. 13 Gharrad et al. [51] Intelligent drone collaboration approach using the Multi-Agent System (MAS) paradigm, based on a new generic Belief-Desire-Intention (BDI) architecture, mimicking humans' reasoning and interactions to deal with Intelligent Transportation System (ITS) applications. ...

Enabling Drones Collaboration in ITS Applications Using a BDI Architecture Based on a 5-Dimensional
  • Citing Chapter
  • January 2021

Advances in Intelligent Systems and Computing

... Además, en el ámbito del transporte se destaca que los sistemas de gestión del tráfico basados en IoT contribuyen a reducir la congestión, las emisiones de gases de efecto invernadero y el consumo de combustible al optimizar las rutas y horarios del transporte público y privado [32]. La implementación de soluciones de movilidad inteligente, como el uso compartido de vehículos eléctricos y la planificación urbana centrada en peatones y ciclistas, fomenta un transporte más sostenible y reduce la dependencia de los vehículos tradicionales impulsados por combustibles fósiles [33,34]. ...

Toward the improvement of traffic incident management systems using Car2X technologies

Personal and Ubiquitous Computing

... Middelham pointed out that the temporary use of shoulders can significantly alleviate traffic congestion when control measures such as lower speed limits and prohibitions on overtaking are implemented [7]. Farrag et al. proposed a methodological framework based on simulation to assess the impacts of HSR on congested freeways during instances of non-recurring congestion [8]. ...

Evaluating Active Traffic Management (ATM) Strategies under Non-Recurring Congestion: Simulation-Based with Benefit Cost Analysis Case Study

Sustainability