LAUSR.org creates dashboard-style pages of related content for over 1.5 million academic articles. Sign Up to like articles & get recommendations!

Matlab algorithms for traffic light assignment using fuzzy graph, fuzzy chromatic number, and fuzzy inference system

Photo from wikipedia

We propose algorithms in Matlab that combine fuzzy graph, fuzzy chromatic number (FCN), and fuzzy inference system (FIS) to create traffic light assignment based on traffic flow, conflict, and queue… Click to show full abstract

We propose algorithms in Matlab that combine fuzzy graph, fuzzy chromatic number (FCN), and fuzzy inference system (FIS) to create traffic light assignment based on traffic flow, conflict, and queue length in an intersection. We evaluate the algorithms through two case studies each on a signalized intersection at Semarang City (Indonesia) and compare the result to the existing systems. The case studies show that the algorithm based on fuzzy graph-FCN-FIS could reduce traffic light cycle time on the intersections. We provide three results as follows:• A pseudocode to construct fuzzy graph of traffic data in an intersection.• Algorithm 1 is to Determine fuzzy graph model of a traffic light data and phase scheduling using FCN function which is presented using Matlab programming language.• Algorithm 2 is to Determine duration of green lights of each phase using Mamdani-FIS codes in Matlab.

Keywords: fuzzy graph; traffic; algorithms; traffic light; graph fuzzy

Journal Title: MethodsX
Year Published: 2020

Link to full text (if available)


Share on Social Media:                               Sign Up to like & get
recommendations!

Related content

More Information              News              Social Media              Video              Recommended



                Click one of the above tabs to view related content.