I am currently a postdoctoral researcher in Computational Social Science chair at ETH Zurich. Previously, I also worked as a data scientist at the Analytics, Computing, and Complex Systems lab (ACCeSs@AIM). In 2021, I received a Ph.D. in Physics from the University of the Philippines, where my research focused on using computational simulations to study driving behavior in traffic models, and machine learning applications for traffic-related research. My current research interests lie in the intersection of machine learning and artificial intelligence applied to multi-agent systems, including (but not limited to) traffic and transportation.
I am a part of the CX Team group of Prof. May T. Lim, under the Instrumentation Physics Laboratory. My research mostly revolves around studying traffic simulation models.
Crossover transitions in a bus–car mixed-traffic cellular automata model
Damian Dailisan, May Lim
Physica A: Statistical Mechanics and its Applications, 2020
We modify the Nagel–Schreckenberg (NaSch) cellular automata model to study mixed-traffic dynamics. We focus on the interplay between passenger availability and bus-stopping constraints. Buses stop next to occupied cells of a discretized sidewalk model. By parametrizing the spacing distance between designated stops, our simulation covers the range of load-anywhere behavior to that of well-spaced stops. The interplay of passenger arrival rates and bus densities drives crossover transitions from platooning to non-platooned (free-flow and congested) states. We show that platoons can be dissolved by either decreasing the passenger arrival rate or increasing the bus density. The critical passenger arrival rate at which platoons are dissolved is an exponential function of vehicle density. We also find that at low densities, spacing stops close together induces platooned states, which reduces system speeds and increases waiting times of passengers.
Vehicular traffic modeling with greedy lane-changing and inordinate waiting
Damian Dailisan, May Lim
Physica A: Statistical Mechanics and its Applications, 2019
Lane changing and vehicular slowdowns are known to impact traffic flow. Using a modified Nagel–Schreckenberg cellular automata model for two vehicle types: blocking (e.g. cars) and non-blocking (e.g. motorcycles), we determined the thresholds at which the interplay of lane changing, random and non-random slowdowns strongly impact vehicle speeds. Lane changing improves speed with diminishing returns as vehicles opt to change lanes. At the same time, lane changing is detrimental to the overall speed when lane straddling occurs. Increasing random slowdowns beyond a critical value (in the case of motorcycles, slowdown values of $p_{slow}\approx[0.2,0.3,0.4]$ for densities $\rho=[0.20, 0.15, 0.10]$ respectively) can force crossover from free flowing traffic into a state where interactions between vehicles reduce the average speed.
Modeling the residential distribution of enrolled students to assess boundary-induced disparities in public school access
Louie John Rubio, Damian Dailisan, Maria Jeriesa Osorio, Clarissa David, May Lim
PLoS ONE, 2019
Given school enrollments but in the absence of a student residence census, we present a gravity-like model to infer the residential distribution of enrolled students across various administrative units. Multi-scale analysis of the effects of aggregation across different administrative levels allows for the identification of administrative units with sub-optimally located schools and highlights the challenges in allocating resources. Using this method, we verify that the current scheme of free cross-enrollment across administrative boundaries is needed in achieving universal education in the Philippines.
Agent-based modeling of lane discipline in heterogeneous traffic
Damian Dailisan, May Lim
Physica A: Statistical Mechanics and its Applications, 2016
Designating lanes for different vehicle types is ideal road safety-wise. Practical considerations, however, require road sharing. Using a modified Nagel–Schreckenberg cellular automata model for two vehicle types (cars and motorcycles), we analyzed the interplay of lane discipline, lane changing, and vehicle density. In the absence of lane changing, the transition between free flow and congested states occurs at a higher vehicle (road occupation) density when the ratio of cars to motorcycles is increased. When lane changing is allowed, the smaller motorcycles tend to fill in unused spaces, until the point when the wider cars effectively block their way at high vehicle densities. When the condition of lane discipline is not imposed, i.e. staying wholly within lane boundaries is not required, further improvement in throughput becomes possible at the cost of required driver attentiveness.