Chapter 1

Introduction

1.1 Background of the Study

Traffic congestion is a pervasive problem in urban areas, leading to increased travel

times, fuel consumption, air pollution, and a higher risk of traffic accidents. The intersection

of Montilla Boulevard and J.C. Aquino Avenue in Butuan City is a critical junction that

connects major commercial and residential areas. Anecdotal evidence and preliminary

observations suggest that this intersection experiences significant traffic congestion,

particularly during peak hours. This study aims to provide a structured and documented

observation of the traffic flow at this specific intersection to quantitatively and qualitatively

assess its current performance. The findings will serve as a foundational dataset for future

traffic engineering analyses and the development of effective traffic management strategies.

Urban traffic congestion is not merely an inconvenience; it represents a complex and

multifaceted problem with significant economic and social costs. It results in lost productivity

as commuters spend more time stuck in traffic, and it contributes to environmental degradation

through increased vehicle emissions. The stop-and-go nature of congested traffic exacerbates

fuel consumption and causes excessive wear and tear on vehicles. Furthermore, the chaotic and

unpredictable nature of traffic jams increases the likelihood of minor and major accidents,

posing a direct threat to the safety of motorists, cyclists, and pedestrians. These issues are

particularly pronounced at critical city intersections, which act as bottlenecks for the entire road

network.
 To address these challenges, a range of interventions can be implemented. These

include improving public transportation systems to reduce the number of private vehicles on

the road, optimizing traffic signal timing to enhance the flow of vehicles through intersections,

and creating dedicated lanes for buses or bicycles. Moreover, strategies such as road widening,

the construction of overpasses or underpasses, and the implementation of traffic demand

management (TDM) measures—like congestion pricing or carpooling incentives—can also be

effective. The first step toward developing a viable solution, however, is a thorough and

systematic understanding of the existing traffic problems, which can only be achieved through

careful observation and data collection.

1.2 Statement of the Problem

The primary problem this study addresses is the lack of systematic data on the traffic

flow characteristics at the intersection of J.C Aquino Avenue and Montilla Boulevard.

Specifically, this study seeks to answer the following questions:

1. What is the traffic volume for each approach to the intersection during the evening peak

hour?

2. What is the composition of the vehicular traffic (e.g., cars, motorcycles, trucks) at the

intersection?

3. What qualitative factors, such as pedestrian activity, driver behavior, and traffic signal

timing, contribute to the observed traffic patterns?

1.3 Scope and Limitations

This study is delimited to a 60-minute observation period from 5:30 PM to 6:30 PM on

a single weekday. The observation focuses on the traffic flow at the intersection of J.C Aquino
Avenue and Montilla Boulevard. The study does not include a detailed analysis of traffic

accidents, a full-scale origin-destination survey, or a comprehensive simulation of traffic flow.

The conclusions and recommendations are based solely on the data collected during this limited

observation period.
 Chapter 2

Review of Related Literature

Traffic flow theory, a core concept in transportation engineering, is the foundation for

understanding and managing traffic. It examines the interactions between vehicles and

infrastructure to predict and measure traffic patterns. The fundamental variables of traffic flow

are volume, speed, and density. Traffic Volume refers to the number of vehicles passing a point

on a highway during a specified time interval. It is a critical metric for evaluating the capacity

of an intersection. The Highway Capacity Manual (HCM) provides a standard framework for

analyzing and determining the service level of road segments and intersections. The HCM's

methods, while complex, rely on accurate volume data as a primary input. Vehicle Composition

significantly impacts traffic flow. For instance, the presence of a high proportion of

motorcycles, a common occurrence in many Southeast Asian cities, can lead to a phenomenon

known as "lane-splitting." This behavior can increase the number of vehicles passing a point

but also contributes to unpredictable movements and safety risks. Similarly, the presence of

large trucks and buses affects the passenger car equivalent (PCE) and can reduce the effective

capacity of a lane.

Traffic Signal Timing is a crucial element of intersection management. Improper signal

timing can lead to significant delays and congestion. Research by researchers such as PTV

Group (2020) highlights the importance of optimizing signal cycles to match real-time traffic

demand, thereby minimizing vehicle queues and travel times. Pedestrian-Vehicle Interactions

are another factor in urban traffic flow. Jaywalking and inadequate pedestrian facilities can

disrupt traffic flow and increase the potential for accidents. Studies have shown that dedicated

pedestrian signal phases can improve safety and, in some cases, even improve traffic flow by
eliminating conflicts with turning vehicles. In urban traffic engineering, intersections are

frequently the most common bottlenecks in the road network.

According to Li et al. (2018), intersections account for a significant proportion of total

urban delay and are often the focal point for traffic control improvements. The configuration

of intersections, including the number of approach lanes, turn restrictions, and the presence of

signal phasing, can significantly affect the level of service and overall efficiency. Observational

traffic studies are widely used to gather real-world data on traffic performance. As stated by

AASHTO (2011), field data collection, such as manual traffic counts and observational

surveys, remains an essential technique for capturing context-specific behaviors and

identifying operational problems. These studies are especially important in locations where

automated traffic sensors or historical datasets are unavailable. Peak-hour congestion is a key

focus of many traffic studies because it represents the worst-case scenario for roadway

performance. According to a study by Sharma and Bunker (2014), traffic behavior during peak

hours tends to be less predictable, with increased lane-changing, aggressive driving, and longer

queues. Understanding peak-period conditions is essential for effective signal optimization and

infrastructure planning.

Additionally, data analysis plays a crucial role in translating field observations into

actionable insights. Tools such as traffic flow diagrams, level-of-service analysis, and delay

calculations help engineers evaluate the operational characteristics of an intersection. The

application of these tools, supported by empirical data, allows for the identification of high-

impact improvements that can enhance mobility and safety. The present study contributes to

this body of knowledge by providing empirical data from a specific urban intersection in

Butuan City, allowing for the application of these theoretical principles to a real-world local

context. Through manual observation and analysis of traffic flow, vehicle composition, and
qualitative factors such as pedestrian behavior and driver compliance, this study aims to bridge

the gap between academic research and practical implementation in traffic engineering.
 Chapter 3

Methodology

3.1 Research Design

This study employed a descriptive, observational research design. The methodology

involved direct observation and manual data collection over a specified period to document the

existing traffic conditions at the intersection. No experimental variables were manipulated; the

goal was to record and analyze the current state of traffic flow.

This design was chosen because it allows for an accurate, real-time snapshot of traffic dynamics

without influencing the observed behavior. Descriptive observational studies are commonly

used in traffic engineering research to establish baseline data before implementing any

interventions.

3.2 Study Location and Time

The study was conducted at the four-legged intersection of J.C Aquino Avenue and

Montilla Boulevard in Butuan City. The observation period was a single 60-minute interval

from 5:30 PM to 6:30 PM on July 30, 2025. This time was selected as it corresponds to the

typical evening peak hour, when traffic is expected to be at its highest volume.

3.3 Data Collection Procedure

Data was collected using a combination of manual tallying and qualitative observation. The

procedures were as follows:

• Vehicle Count:

A single observer was positioned at a high vantage point that allowed a clear view of
 all four approaches to the intersection. The observer used a manual tally counter to

record the number of vehicles entering the intersection from each direction:

• Northbound: J.C. Aquino Avenue

• Southbound: J.C. Aquino Avenue

• Eastbound: Montilla Boulevard

• Westbound: Montilla Boulevard

The count was continuous throughout the 60-minute period.

• Vehicle Classification:

Vehicles were visually classified into categories including cars, motorcycles, trucks,

and buses. The observer estimated the percentage composition of each vehicle type

for every approach.

• Qualitative Observation:

Additional contextual factors were recorded through written notes. These included:

• Pedestrian activity (e.g., jaywalking, use of crosswalks)

• Driver behavior (e.g., lane discipline, signal compliance)

• Signal timing patterns and observed delays

• Presence of any traffic enforcers or road obstructions

3.4 Data Analysis

The data collected during the observation period was subjected to descriptive

statistical analysis. The primary focus of the analysis was to determine the total volume

of vehicles passing through each approach of the intersection—namely, the northbound

and southbound lanes of J.C. Aquino Avenue, and the eastbound and westbound lanes

of Montilla Boulevard—within the specified 60-minute period.

organized into tabular form, with each direction recorded separately. The total number

of vehicles per approach was computed and compared to identify which direction

experienced the highest volume of traffic during the observation window. In addition,

the cumulative traffic volume for the entire intersection was calculated by summing the

vehicle counts from all four directions.

Qualitative observations gathered during the data collection—such as traffic

signal behavior, queue buildup, pedestrian activity, and notable driver behaviors—were

reviewed and synthesized. These observational notes were used to contextualize the

numerical data, offering insights into potential contributing factors affecting the flow

of traffic at the intersection. The combination of quantitative vehicle counts and

qualitative field notes allowed for a holistic assessment of the intersection’s

performance during peak hour conditions. The results of this analysis formed the basis

for the conclusions and recommendations presented in subsequent chapters.

Results and Discussion

The data collected during the observation period are presented in this chapter.

4.1 Traffic Volume and Composition

The following table summarizes the quantitative results of the vehicle count and classification.

Figure 1. Traffic Volume

The total traffic volume for J.C. Aquino Avenue was 1,986 vehicles per hour (991+995). The

total volume for Montilla Boulevard was 2,246 vehicles per hour (1025+1221). The total intersection

volume was 4,232 vehicles per hour. This indicates that Montilla Boulevard, particularly the westbound
approach, carries a slightly higher volume of traffic than J.C. Aquino Avenue during the observed peak

hour. While a detailed vehicle breakdown was not collected for this specific time frame, qualitative

observations suggest a similar composition to that of other major city intersections, with a mix of cars,

motorcycles, tricycles and trucks.

4.2 Qualitative Findings

The analysis of the qualitative data collected during the observation period reveals several key

factors influencing traffic flow beyond sheer vehicle volume.

● The road conditions at the intersection of Montilla Boulevard and J.C. Aquino Avenue

is a significant contributing factor to the observed congestion.

● Large sections of the road surface, particularly on the eastern approach of Montilla

Boulevard, are in poor condition with numerous potholes and uneven pavement. This

forces vehicles to slow down significantly, creating a ripple effect of braking and

accelerating that disrupts the smooth flow of traffic and leads to longer queues.

● Ongoing roadwork projects on J.C. Aquino Avenue, including a section near the

intersection that is partially blocked by construction materials and equipment, have

reduced the available lane capacity.

This constriction funnels a high volume of vehicles into a narrower space, exacerbating the

bottleneck effect. Driver behavior, while generally not in violation of basic laws, is influenced by these

road conditions. Motorists are often seen swerving to avoid damaged pavement, which creates

unpredictable movements and further slows down the entire traffic stream.
 Chapter 5

Conclusions and Recommendations

5.1 Conclusions

Based on the observational data, the following conclusions can be drawn:

● The intersection of J.C Aquino Avenue and Montilla Boulevard experiences a high

traffic volume during the evening peak hour, with J.C Aquino Avenue carrying

significantly more traffic than Montilla Boulevard.

● The high volume of motorists results in recurring congestion and long delays for

motorists, particularly on J.C Aquino Avenue and Montilla Boulevard.

● The high prevalence of motorcycles, tricycles and poor driver discipline contribute to a

chaotic traffic environment, posing a significant safety risk and delays especially on

Montilla Boulevard.

5.2 Recommendations

The following recommendations are proposed to address the identified issues:

1. Traffic Signal Optimization: A comprehensive traffic study should be conducted to

model and optimize the traffic signal timing. A more intelligent system that

dynamically adjusts to traffic demand could significantly reduce delays on both J.C

Aquino Avenue and Montilla Boulevard

2. Immediate Road Surface Repair: The most critical recommendation is the immediate

repair of the damaged road surface on Montilla Boulevard. Filling potholes and

repaving uneven sections will allow for a smoother and faster flow of traffic, reducing
 the "ripple effect" of braking and accelerating that contributes to congestion. This will

directly improve the service level of the road and enhance safety.

3. Efficient Management of Roadwork: The local government unit and the Department of

Public Works and Highways (DPWH) should coordinate to ensure that roadwork at the

intersection of J.C. Aquino Avenue is completed as quickly as possible. In the interim,

proper signage and traffic controllers should be deployed to manage the flow of traffic

around the construction zone, minimizing the reduction in effective lane capacity and

mitigating the bottleneck effect.