Maximizing traffic flows by determination of reversible lanes using deterministic demand

• Main Authors: Bilang, Juanito, Galian, Mary Joy, Tieng, Christine
• Format: text
• Language: English
• Published: Animo Repository 1998
• Subjects: Traffic flows; Philippines; Programming (Mathematics); Traffic regulations; Shipment of goods; Traffic engineering; Engineering
• Online Access: https://animorepository.dlsu.edu.ph/etd_bachelors/9343
• Institution: De La Salle University

Traffic is a controversial issue in the Philippines. Several projects have been undertaken to alleviate the heavy flow of traffic in the metropolis. There is the Unified Odd-Even scheme, the reinforcement of traffic agents (MMDA), manual signal setting, the construction of fly-overs at heavy demand points and the issue of reversible lanes. In the field of Operatoin Research, most traffic problems dealt with signal setting assignments, traffic demand and minimization of travel time. None of these were able to integrate the policy of lane reversal and signal setting given a deterministic demand at entrance link to optimize the flow of traffic. The objective function is to maximize the flow of traffic (in car units). The model uses the conservation of cars at nodes to distinguish cars waiting from the cars leaving the link. Other constraints include the capacity of the links, green time for each lane, and the movement patterns allowable for the network designed to avoid collision at intersections. The decisions that the model will yield are the green time for each period and the number of lanes to be allocated for a specified planning horizon. The model was validated using a network similar to President Quirino Avenue along with two intersections and six entrance nodes. The links intersecting the highway are one-way roads with traffic flowing in opposite directions for each road. Theoretical parameters were generated and used as inputs for the model. The program used for validation is the General Algebraic Modeling System (GAMS) which performs a linear programming technique in solving the problem. Several runs were executed for each model containing a combination of varied parameters to arrive with conclusions concerning a combination of varied parameters to arrive with conclusions concerning the behavior of variables and/or the objective function. A computer program based on the model was created and named C.A.R.S.S. or Computerized Allocation of Reversible Lanes and Signal Setting Software.