Identifying FMS repetitive patterns for efficient search-based scheduling algorithm: A colored Petri net approach

Proceedings of the Institution of Mechanical Engineers, Part G:

Baruwa

2015

The traffic alert and collision avoidance system (TCAS) currently mandated worldwide on all commercial transport aircraft is intended to provide last-minute collision avoidance (CA) guidance directly to the flight crew and has been shown to significantly reduce the risk of near-midair collisions. The TCAS logic uses a deterministic model to predict the future trajectories of the aircraft and does not explicitly represent variability in pilot response time which can have a great impact on the execution of the CA logic. Prior work has designed an encounter model to identify all the induced potential collision scenarios that are representative of possible hazardous situations that may occur with a fixed configuration of aircraft in the surrounding airspace. This paper extends the encounter model using an agent-based modeling approach developed via the colored Petri net (CPN) formalism to include the agent pilot response time that captures the variability delay in pilot behavior in order to analyze its influence on TCAS-induced collisions. Quantitative simulation results are conducted to validate the proposed causal model, dealing with challenging results about the extra airside capacity that could be obtained by offering a specific training on TCAS to the pilots or by use of automatisms, which is the case of remotely piloted aircraft systems.

Section: Resultsmentioning

confidence: 99%

A discrete-event modeling approach for the analysis of TCAS-induced collisions with different pilot response times

Tang

Proceedings of the Institution of Mechanical Engineers, Part G:

Baruwa

2015

“…Table 1 summarizes the parameter values [1,18] utilized in the case scenario that are used to test the feasibility of the proposed model. RADIUS is used as the state space analysis tool, and it has been shown to be effective for the performance analysis of very demanding and flexible industrial systems in [19,20].…”

Section: Resultsmentioning

confidence: 99%

Extended Traffic Alert Information to Improve TCAS Performance by means of Causal Models

Tang

Mathematical Problems in Engineering

Ling

et al. 2015

Near-midair collisions (NMACs) between aircraft have long been a primary safety concern and have incessantly motivated the development of ingenious onboard collision avoidance (CA) systems to reduce collision risk. The Traffic Alert and Collision Avoidance System (TCAS) acts as a proverbially accepted last-resort means to resolve encounters, while it also has been proved to potentially induce a collision in the hectic and congested traffic. This paper aims to improve the TCAS collision avoidance performance by enriching traffic alert information, which strictly fits with present TCAS technological requirements and extends the threat detection considering induced collisions and probabilistic pilot response. The proposed model is specified in coloured Petri net (CPN) formalism, to generate by simulation all the future possible downstream reachable states to enhance the follow-up decision making of pilots via synthesising relevant information related to collision states. With the complete state space, the potential collision scenarios can be identified together with those manoeuvres that may transform a conflict into a collision. The causal TCAS model is demonstrated to work effectively for complex multiaircraft scenarios and to identify the feasible manoeuvres that contribute to reduce the nonzero TCAS-induced collision risk.

“…ESS can be explored either in a classical manner, by evaluating both the untimed marking and time stamp together as one set for comparison in duplicate detection [8] or in a compact form, as a condensed state space (CSS) [9,16]. In the CSS, nodes are represented as state classes using the notion of untimed marking equivalence.…”

Section: Timed State Space Explorationmentioning

confidence: 99%

TIMSPAT – Reachability graph search-based optimization tool for colored Petri net-based scheduling

Baruwa

Computers & Industrial Engineering

Guasch

2016

Self Cite

The combination of Petri net (PN) modeling with AI-based heuristic search (HS) algorithms (PNHS) has been successfully applied as an integrated approach to deal with scheduling problems that can be transformed into a search problem in the reachability graph. While several efficient HS algorithms have been proposed albeit using timed PN, the practical application of these algorithms requires an appropriate tool to facilitate its development and analysis. However, there is a lack of tool support for the optimization of timed colored PN (TCPN) models based on the PNHS approach for schedule generation. Because of its complex data structure, TCPN-based scheduling has often been limited to simulation-based performance analysis only. Also, it is quite difficult to evaluate the strength and tractability of algorithms for different scheduling scenarios due to the different computing platforms, programming languages and data structures employed. In this light, this paper presents a new tool called TIMSPAT developed to overcome the shortcomings of existing tools. Some features that distinguish this tool are the collection of different HS algorithms, the event-driven exploration of the timed state space including its condensed variant, localized enabling of transitions, the introduction of a static place, and its easy-to-use syntax statements. The tool is easily extensible and can be integrated as a component into existing PN simulators and software environments. A comparative study is performed on a real-world eyeglass production system to demonstrate the usage of the tool for scheduling purposes.