How Is Travel Demand Forecast?

What Are the Different Travel Demand Forecasting Models?

Travel demand refers to the expected number of travelers or vehicles that will travel on a given part of a transportation system, taking into account factors such as land use, socio-economics and the environment. Travel demand forecasts are extremely important for estimating future traffic, or traffic that changes within transportation systems. Methods for forecasting travel demand can range from simple estimates to complex computerized processes, depending on project constraints such as data availability and funding (Garber & Hoel, 1999).

Urban travel demand is influenced by three main factors: land use, the socio-economic characteristics of the population, and the quality and accessibility of transport services. Different types of land use, such as residential, commercial or office areas, can generate traffic. Beyond land use, socio-economic factors such as income and lifestyle affect how people use transport resources. The quality and accessibility of transport services — including factors such as cost, ease of use and safety — are also examples of factors that influence people's travel decisions (Garber & Hoel, 1999).

Figure 1 shows the structure of the traditional four-step model. Trip-based models such as the four-step model are among the earliest demand forecasting models and focus on independent trips.

Tour-based models emerged as a significant development in the late 1970s and 1980s. The tour-based models shown in Figure 2 represent the cycle of trips within a tour. This model takes temporal and spatial constraints into account but does not link multiple tours occurring within the same time period.

Figure 3 shows the structure of the activity-based model. The activity-based model is based on the notion that travel demand derives from the desire to participate in activities. Activity-based models aim to predict the activity and travel schedules of individuals within a given time period, taking temporal and spatial constraints into account (Omer, Kim, Sasaki & Nishii, 2010).

Different demand forecasting models are used to answer questions about why, how often, where and how people travel. In the literature there are different modeling types such as the Standard Four-Step Model, Tour-Based Modeling and Activity-Based Modeling.

THE FOUR-STEP MODEL

Before starting the technical aspects of travel forecasting, after the study area and problems have been identified, it is important to divide the study area into Transportation/Traffic Analysis Zones (TAZ) so as to cover the specified policy impacts. These zones can be of different sizes; moreover, these divided areas can also be grouped into larger regions for specific analyses (Garber & Hoel, 1999).

The four-step model is used as the basic tool for estimating the future demand and efficiency of a transportation system (McNally, 2007). Each step in the four-step demand model aims to address a different question:

• How much total travel demand is there?
• Where are the potential trip destinations located?
• Which travel modes are suitable for these trips?
• Which routes will be chosen to complete the trips?

In a simple network, demand functions can be estimated directly, but a realistic application in a complex network requires modeling. For this reason, the four-step model is formulated as a sequential four-step model (Figure 4) (McNally, 2007).

The four-step model can be summarized as in Figure 5 below:

1. Trip Generation is the first step of the four-step model. In the trip-generation step, the number of trips in a given time period and a given area is expressed. This step aims to obtain the travel tendency and trip frequency within the network. The trips that occur can be represented as trip ends, productions and attractions (McNally, 2007). Used as the main method for demand estimation, the four-step model is based on land use and travel characteristics (Garber & Hoel, 1999).
2. The second step, known as Trip Distribution, expresses how the trips occurring in the study area are distributed. In the trip-distribution step, factors such as distance, duration, transport mode, density, attraction areas and others are considered to estimate the distribution of trips. In short, in the trip-distribution step, the generated trips are matched with the distribution of trip attractions and distributed by considering travel impedance factors such as time and/or cost (McNally, 2007).
3. The third step is called Mode Choice. In this step, the aim is to determine which transport mode will be preferred, taking into account the trip tables created in the previous steps.
4. The final step of the four-step model is called Network Assignment. It aims to distribute the existing trip tables, with the transport modes added in the third step, to the relevant alternative routes (McNally, 2007). In short, route choice can be defined as the process of determining which route individuals will choose to travel from a given origin to another point.

THE TOUR-BASED MODEL

In the tour-based model, tours form the basis of the analysis. A tour can be defined as a closed chain of a series of activities that starts and ends at a specific location. For each tour there are two different destinations: a primary destination and a secondary destination. The primary destination is defined as the place where the most important activity takes place. The secondary destination is the destination of any vehicle trip during the tour. Trips refer to the journeys that occur during the tour between the origin and the primary destination or the secondary destination (Sener, Ferdous, Bhat & Reeder, 2009).

Figure 6 shows the tour of a parent who drops their child off at school and then goes to work. In this tour, the origin is home; the primary destination is work, while the secondary destination is the child's school. During this tour, the parent completes 3 trips: from home to school, from school to work, and from work to home. The tour ends at the origin, home.

There are some fundamental differences between the trip-based model and the tour-based model (Sener, Ferdous, Bhat and Reeder, 2009). These differences are explained in Table 1.

ACTIVITY-BASED MODELING

Activity-based models have gained more popularity than the traditional four-step model and offer improvements over it. Both types involve generating activities, determining destinations, determining transport modes and estimating network travel routes. However, activity-based models stand out for their ability to link the activities and trips of individuals and households while explicitly taking realistic time and space constraints into account (Figure 7). This allows for a more accurate representation of how travel conditions affect personal choices. Activity-based models include person and household characteristics in detail and, unlike most trip-based models that focus on the zone level, offer comprehensive performance metrics thanks to their detailed person-level approach (National Academies of Sciences, Engineering, and Medicine, 2014).

Activity-based travel models are based on the idea that travel demand arises from people's needs and desires to participate in activities. These models are based on behavioral theories that consider various constraints, accounting for how people make decisions about participating in activities, where they will do the activity, when they will do it, and how they will get to the destination.

Compared with trip-based models, activity-based models stand out in several respects. Table 2 presents the differences between the trip-based model and the activity-based model. This model comprehensively represents the activity and travel preferences of each individual throughout the day and takes activity types and their sequencing priorities into account. Activity-based models offer a more realistic representation for assessing the impact of investments, policies or other changes on people's travel choices.