Deployment of an adaptive area traffic control system is expensive;
physical sensors require installation, calibration, and regular maintenance.
Because of the high level of technical and financial resources
required, area traffic control systems found in developing countries
often are minimally functioning. In Cebu City, Philippines, for example,
the Sydney Coordinated Adaptive Traffic System was installed
before 2000, and fewer than 35% of detectors were still functioning
as of January 2015. To address this challenge, a study was designed
to determine whether taxi company GPS data are sufficient to evaluate
and improve traffic signal timing plans in resource-constrained
environments. If this work is successful, the number of physical sensors
required to support those systems may be reduced and thereby
substantially lower the costs of installation and maintenance. Taxi
GPS data provided by a regional taxi-hailing app were used to design
and implement methodologies for evaluating the performance of traffic
signal timing plans and for deriving updated fixed-dynamic plans,
which are fixed plans (with periods based on observable congestion
patterns rather than only time of day) iterated regularly until optimization
is reached. To date, three rounds of iterations have been conducted
to ensure the stability of the proposed signal timings. Results of
exploratory analysis indicate that the algorithm is capable of generating
reasonable green time splits, but cycle length adjustment must be
considered in the future.