Formal specification and preliminary design of an asynchronous traffic light controller

In this paper, a new method is proposed for digital hardware implementation of Petri net-based specifications. The purpose of this paper is to introduce a new discrete event control system paradigm, where the control system is modeled with extended Petri nets and implemented as an asynchronous controller using circuit elements. The applicability of the proposed method is demonstrated by an asynchronous implementation of a Petri net-based discrete event control system (DECS) for an experimental manufacturing system using a Xilinx field programmable gate array (FPGA). Unlike microprocessor, microcontroller or programmable logic controller (PLC)-based software implementations or hardware-based synchronous implementations, the implementation method used in this paper is asynchronous and based on hardware offering very high speed to control fast plants at low cost. This paper is expected to serve as a guideline to show how to obtain very high speed, concurrent and asynchronous Petri net-based controllers.

We advocate goal-oriented software security engineering to produce highly secure software in a constructive,provable and cost-effective manner. Our approach is to couple goal-oriented semi-formal requirements specifications with formal design and implementation. To this effect, we proposed FADES (formal analysis and design for engineering security)in as the first goal-oriented software security engineering approach that provides a systematic and automated bridge between the goal-directed semi-formal KAOS (knowledge acquisition for automated specifications) framework and the B formal method to derive formal design and implementation from security requirements. In this paper, we demonstrate the applicability of FADES and study its effectiveness through a generic Electronic Smart Card case study and a comparative analysis between FADES and strictly applying formal methods.We use the case study to demonstrate how the goal-oriented formulation of security requirements in FADES paves the way for formal design that provably preserves the security properties.Further, the results of the comparison between FADES and Z show that FADES achieves better requirements completeness,consistency and security quality.

In recent years, the problems of asynchronous control and filtering for Markov jump systems (MJSs) have received great research attention from scientific and engineering communities. The asynchronous situation between the original MJSs and the controller/filter is modelled by the hidden Markov model (HMM). This work gives a survey on the recent development of the HMM-based asynchronous controller and filter design for different MJSs, covering linear MJSs, fuzzy MJSs, semi-MJSs and 2D MJSs. Finally, a conclusion is drawn and the potential future research directions of MJSs are also discussed.

The Requirements to Design to Code (R2D2C) project of NASA's Software Engineering Laboratory is based on inferring a formal specification, currently using Communicating Sequential Processes (CSP), from system requirements supplied in the form of scenarios, a user-friendly medium often used to describe the behavior of computer systems under development. The scenarios are first converted into an intermediate form, CSP traces, from which are derived CSP specifications. This work, called Mise en Scene, defines a new medium (Scenario Notation Language, SNL) suitable for control-dominated systems, coupled with a two-stage process for automatic translation of scenarios to a new trace medium (Trace Notation Language, TNL) which encompasses CSP traces. A survey of the scenario concept and a small case study are also presented.

Efficient traffic control and management is a fundamental and urgent challenge in our ever-growing cities. Maximizing roadway capacity usage, balancing traffic flows, decreasing emission, improving traffic safety and providing motorists with the best end-to-end transportation experience are the most important goals of modern intelligent traffic control infrastructures. Evolving traffic light or traffic signal controller systems are playing an important role in these architectures by adaptively and dynamically coordinating individual traffic lights to achieve city-wide objectives of traffic operations. The integration of such systems with vehicle-to-vehicle (V2V) and vehicle-to- infrastructure (V2I) communication techniques (together referred as V2X) could easily be the next step of this evolution allowing for dynamic real-time information exchange between all the players of the traffic controlling ecosystem and fostering cooperative urban mobility. In this paper we propose a possible architecture for a V2X-integrated traffic light controller systems and present the testbed with our proof-of-concept implementation of the proposed scheme.

An optimization model and traffic light control scheme for heterogeneous traffic systems

Traffic crisis often happen because of traffic burden by the large number automobiles on the path. Increasing transportation move and decreasing the average waiting time of each vehicle are the aims of cooperative intelligent traffic control system. Each signal wishes to catch better travel move. During the course, signals form a strategy of cooperation in addition to restriction for neighboring signals to exploit their individual benefit. A superior traffic signal scheduling strategy is used to resolve the difficulty. The several parameters may influence the traffic control model. So it is hard to learn the best possible result. Traffic light controllers are not expert to study from previous results. Due to this, they are unable to include the uncertain transformation of traffic flow. Reinforcement learning algorithm based traffic control model used to get fine timing rules by properly defining real-time parameters of the real traffic scenario. The projected real-time traffic control optimization prototype is able to continue with the traffic signal scheduling rules successfully. The model expands traffic value of the vehicle, which consists of delay time, the number of vehicles stopped at a signal, and the newly arriving vehicles to learn and set up the optimal actions. The experimentation outcome illustrates a major enhancement in traffic control, demonstrating the projected model is competent of making possible real-time dynamic traffic control.

The paper concerns the problem of reliable dissipative asynchronous controller design for a type of stochastic Markov jump systems (MJSs) with general conditional probabilities in the presence of the dynamic event-triggered rule. Since the mode information of the stochastic MJS is impossible to obtain, a reliable asynchronous controller is established such that the phenomena of nonsynchronous modes between the original stochastic MJS and the developed controller is formulated as a hidden Markov model. A novel dynamic event-triggered strategy is constructed to further decrease the data transmission frequency over the communication network. By taking the internal dynamic variable into account, the criteria of stochastically stable with the reliable dissipativity performance for the resulting closed-loop stochastic MJS are provided based on a collection of linear matrix inequalities. Further, the designs of reliable dissipative asynchronous controller and the dynamic event-triggered strategy are developed simultaneously. Lastly, a numerical instance is supplied to elucidate the superiority of proposed method.

Traffic crisis frequently happen because of traffic burden by the large number automobiles are on the path. Increasing transportation move and decreasing the average waiting time of each vehicle are the objectives of cooperative intelligent traffic control system. Each signal wishes to catch better travel move. During the course, signals form a strategy of cooperation in addition to restriction for neighboring signals to exploit their individual benefit. A superior traffic signal scheduling strategy is useful to resolve the difficulty. The several parameters may influence the traffic control model. So it is hard to learn the best possible result. Traffic light controllers are not expert to study from previous results. Due to this they are unable to include uncertain transformation of traffic flow. Reinforcement learning algorithm based traffic control model can be used to obtain fine timing rules by properly defining real time parameters of the real traffic scenario. The projected real-time traffic control optimization prototype is able to continue with the traffic signal scheduling rules successfully. The model expands traffic value of the vehicle, which consists of delay time, the number of vehicles stopped at signal, and the newly arriving vehicles to learn and establish the optimal actions. The experimentation outcome illustrates a major enhancement in traffic control, demonstrating the projected model is competent of making possible real-time dynamic traffic control.

The congestion of the urban traffic is becoming one of critical issues with increasing population and automobiles in cities. Traffic jams not only cause extra delay and stress for the drivers, but also increase fuel consumption, add transportation cost, and increase carbon dioxide air pollution. The traffic controller is one of critical factors affecting the traffic flow. The conventional traffic patterns are nonlinear and complex. As a result, the fixed traffic light controller is not optimized to reduce the traffic jam. Moreover, it does not improve the response time for ambulances, fire trucks, police cars and other emergency vehicles. This paper is written with the endeavor to provide the readers an idea of the research that has been carried out in the intelligent traffic light field and the microcontroller based traffic light control system. The historical review of the technology and the recent development of the intelligent traffic light control system are stated in this paper. In addition, the future studies of the related work are also presented.

This paper presents a hardware approach to the design of fuzzy controllers which, by exploiting some peculiar characteristics of fuzzy logic computation, allows one to save power consumption and increase computing speed. We show that the computation involved in a fuzzy controller has some statistic features that can be exploited by asynchronous computation. This paper presents a quantitative study of the statistical properties of fuzzy computation. A design methodology is introduced, and two experimental applications are shown.

Introduction Drag on city traffic has escalated to be a pivotal problem in almost all cities in the world, and commuter travel time, fuel consumption and emission have also soared. Fixed-time signal control systems have been traditionally used in traffic signal control, but their optimality highly depends on the time of day they are applied and they are not capable of real-time traffic control. In order to overcome these drawbacks, intelligent and adaptive traffic control approaches are being explored by both scientists and traffic developers. Objective The purpose of this research is to create and assess a dynamic traffic light control system by utilizing Snake Optimization (SO), a novel meta-heuristic algorithm. In order to minimize vehicle queues, cut down on delays, and enhance overall traffic flow, the main goal is to examine how well SO optimizes traffic signal timings based on real-time traffic data. by contrasting conventional static control techniques and meta-heuristics with the SO-based dynamic approach. Proposed Method To find the best traffic light phase durations at intersections, the suggested approach uses the Snake Optimization (SO) algorithm, a bio-inspired meta-heuristic technique. Real traffic data from the Algerian city of Algiers, which depicts realistic traffic volumes and patterns, is used to test the method. The SUMO (Simulation of Urban Mobility) simulator, an open-source program popular for simulating microscopic traffic, is used to construct the experimental framework. Traffic scenario modeling, control algorithm implementation, and performance evaluation in a simulated urban setting are all made possible by SUMO. The following steps are part of the optimization process: gathering of data, using the SUMO simulator to model traffic flow and intersections, incorporating the SO algorithm to modify traffic light timings in real time in response to inputs, evaluation of performance using metrics like vehicle throughput, average waiting time, reduction of CO2 emission and total travel time, and evaluation of the benefits obtained by the SO-based approach through comparison with a baseline static control system and ACO-DSOS meta-heuristic. Conclusion According to the simulation results, the suggested approach, which is based on the Snake Optimization algorithm, performs better than other meta-heuristics and conventional static control systems. The algorithm's effectiveness in controlling traffic flows is validated by quantitative comparisons. According to the study's findings, SO is a practical and successful strategy for maximizing traffic light control in practical settings.

The development of an infrastructure for multiple autonomous agents, with an application to urban traffic signal control, is described. The agent-based infrastructure, Cybele, allows for distributed computing, interagent communication, agent migration, and computational resource allocation. The agents that are used to solve the traffic signal control problem are known collectively as DAARTS (Decentralized Adaptive Agents for contRol of Traffic Signals). DAARTS adopts a hierarchical multiagent-based architecture in which the lowest level (intersection agents) involves individual intersection-traffic dynamics and phase selection based on “local” information, while higher levels take into account the supervisory (network-level) dynamics. The controller design is based on a receding-horizon model predictive control approach. Coordination between intersections is achieved in a decentralized manner at the lowest level. The agents are integrated into a simulation test bed with the microsimulator CORSIM, using the DAARTS simulation tool kit. This kit enables communications between the CORSIM real-time extension, the communications management functions of Cybele, and the traffic control agents. The control process is truly distributed, and each of these components can reside on a different computer. Descriptions of all of the software components are given, and the control algorithm is discussed in detail. Some encouraging results from the simulation of a small network are included. Ongoing and future research activities are discussed.

Traffic problems often occur due to the traffic demands by the outnumbered vehicles on road. Maximizing traffic flow and minimizing the average waiting time are the goals of intelligent traffic control. Each junction wants to get larger traffic flow. During the course, junctions form a policy of coordination as well as constraints for adjacent junctions to maximize their own interests. A good traffic signal timing policy is helpful to solve the problem. However, as there are so many factors that can affect the traffic control model, it is difficult to find the optimal solution. The disability of traffic light controllers to learn from past experiences caused them to be unable to adaptively fit dynamic changes of traffic flow. Considering dynamic characteristics of the actual traffic environment, reinforcement learning algorithm based traffic control approach can be applied to get optimal scheduling policy. The proposed Sarsa(λ)-based real-time traffic control optimization model can maintain the traffic signal timing policy more effectively. The Sarsa(λ)-based model gains traffic cost of the vehicle, which considers delay time, the number of waiting vehicles, and the integrated saturation from its experiences to learn and determine the optimal actions. The experiment results show an inspiring improvement in traffic control, indicating the proposed model is capable of facilitating real-time dynamic traffic control.

Architectures based on Coordinated Atomic action (CA action) concepts have been used to build concurrent fault-tolerant systems. This conceptual model combines concurrent exception handling with action nesting to provide a general mechanism for both enclosing interactions among system components and coordinating forward error recovery measures. This paper proposes an architectural model to guide the formal specification of concurrent fault-tolerant systems. This architecture provides built-in CSP (Communicating Sequential Process) processes and predefined channels to coordinate exception handling of the user-defined components. As a result, a formal and general architecture supporting software fault-tolerance are ready to be used.