Transportation systems consist of the intricate interactions between supply on the network side and demand on the traveler's side. It can be seen as a market that offers service instead of goods, and the price equals generalized travel cost, which consists of out-of-pocket money and travel time. This market (system) works on an equilibrium, which is a balance between the level of service that the network can provide overall for all modes and the travel demand derived from the needs of the individuals for participation in the activities. In fact, the load on the transport system is the consequence of trips, and trips result from people's needs at the personal and family levels, and needs are derived from many personal and familial demographic aspects, such as budget, resources, lifestyle, beliefs, and perceptions. Understanding this chain process is paramount, as it is a shift in transportation studies towards activity-based analysis from the conventional trip-based approach.
Travel behavior analysis is the study of the factors involved in individuals' decision-making processes regarding engagement in activities, and hence, derived trips. Two well-established methods in this field of science are the discrete choice analysis (DCA) and the stated preference (SP) methods. These methods help the researcher to explore the sensitivity of the decision-makers to the influential factors.
The Travel Behavior of Primary School Children
Understanding the dynamics of children's travel behavior is imperative, as it reflects the intricate interplay between household characteristics and individual choices. Household socioeconomic factors play a pivotal role in shaping various aspects of a child's life, notably impacting decisions related to school location and travel mode choices. In one of the studies I was involved in, we adopted a comprehensive approach, incorporating statistical analysis and discrete choice modeling, to unravel the complex web of parental decisions affecting primary school children's travel behaviors.
The study focuses on representative trip chains, mode choices, school locations, and escort statuses as fundamental elements shaping children's travel patterns. Through examining four different choice structures and contingency analysis, we explore correlations among explanatory variables, such as household socioeconomics, gender, and the influence of the cultural norms of the city living on travel behaviors. Statistical analyses bring to light the influential role of gender and family car ownership in parental decision-making.
Our findings underscore the profound impact of gender on children's daily travel behavior, a variable often overlooked in previous research. Furthermore, parental employment and educational levels emerge as key determinants of children's school trip behavior. Notably, cultural and religious beliefs in some Iranian households contribute to differences in travel behavior between boys and girls, a phenomenon not extensively explored in previous studies.
(Paper: TRB-2013).
Advancing Urban Travel Demand Modeling: A Comprehensive Study on Shopping Trips
The evolution of travel demand modeling has undergone a significant transformation with the emergence of more sophisticated behavioral models. Among the various trip purposes, shopping trips hold a pivotal role in the urban context, boasting the highest share after working and educational trips. Understanding the dynamics of shopping trips is crucial for urban planners and policymakers, given their significant contribution to overall travel demand. The traditional dichotomy between mode and destination choice models often overlooks the inherent interdependence of these choices. In a study, we addressed this gap by proposing a joint modeling approach, providing a more holistic understanding of the factors influencing shopping trip behaviors.
Utilizing the fast-evolving activity-based models, the research places a strong emphasis on the behavioral aspects of travel demand modeling. Statistical analyses are conducted on data from Mashhad, Iran, offering insights into the multifaceted dynamics of shopping trip decision-making.
The statistical analysis reveals that travelers exhibit a tendency to choose shopping destinations based on the location and connection to recreational facilities. In addition, travel time and fare emerge as influential factors for mode and destination choices, while factors such as CBD location, accessibility, and selected mode play pivotal roles in travelers' destination choices. Vehicle ownership and the number of workers also exhibit a substantial impact on the joint behavior of the models.
(Paper: ICTTE-2014)
Household Decision-Making Dynamics
The third episode in this series of my studies addresses the intricate intra-household relations and decisions regarding participating in activities and using household mobility resources by developing a joint model for simultaneously considering household activity and vehicle allocation.
Understanding the dynamics of household activity and vehicle allocation is crucial for policymakers seeking to implement effective transportation strategies. Traditional approaches often neglect the inherent relationship between these decisions, particularly in regions with single-vehicle dominant households. This study focuses on Iranian cities but holds implications for regions with similar characteristics, offering valuable insights for shaping transportation policies.
The research employs a Paired Combinatorial Logit (PCL) model to estimate the share of each household member in non-mandatory activities, coupled with a Multinomial Logit (MNL) model for vehicle allocation. A joint modeling framework is applied to estimate these models simultaneously.
We realized that gender, family-member roles, employment status, and activity duration strongly influence activity allocation patterns, particularly in households with young children. Moreover, it revealed that women's employment can reduce the ties between gender and vehicle allocation decisions.
(Paper: Trans. Res. Rec. 2015)
Analysis of Women's Activity and Travel Behavior
Studying women's travel behavior is pivotal for developing transportation models that accurately reflect gender-specific nuances. In patriarchal Muslim societies like Iran, where gender equity dilemmas persist, recognizing the factors influencing women's travel is essential. Beyond its relevance to Iran, this research enhances transportation policies worldwide, addresses safety concerns, and promotes gender equality in travel behavior.
Our study adopts a comprehensive approach, utilizing a joint mode and daily activity pattern (DAP) discrete choice model. This model captures women's intertwined decisions regarding their activity patterns and mode choices. Despite challenges, such as limited data on women's activity-travel and gender-based research funding disparities, this study overcomes obstacles to provide valuable insights into Iranian women's travel behavior.
Sociologically, parental educational levels emerge as influential in mitigating traditional norms, granting women greater freedom. The presence of children significantly impacts women's transportation behavior, emphasizing family dynamics. The correlation between mode and DAP choices highlights the interconnectedness of these decisions. Employment status emerges as a critical factor influencing the use of family cars and the evaluation of travel time.
Results indicate that women's age, employment status, work shift, and workplace location significantly shape their activity patterns. Marital status, occupation difficulty, and working hours influence after-work activities, underscoring the intricate web of factors impacting women's daily lives. Notably, this study sheds light on the variations in activity-travel behavior between single and married women.
(Paper: Trans. Plan. & Tech. 2018, TRB-2019).
Stated Preference Exploration of Willingness to Use Shared Automated Vehicles
In the realm of transportation, the fusion of vehicle automation and shared mobility has emerged as a transformative force, holding great promise for the future of our mobility system. This technological and conceptual amalgamation, known as Shared Automated Vehicles (SAVs), is seen as a solution to various challenges posed by urbanization, traffic congestion, and environmental concerns. However, deploying SAVs requires careful regulation to mitigate potential risks and steer the technology towards sustainability. Recognizing the need for informed policymaking, a very recent collaborative study of mine delves into understanding user-profiles and mode choice behavior related to SAVs through an online stated preference survey conducted in Flanders, Belgium. A comprehensive dataset of 652 completed questionnaires was collected, offering valuable insights into the ways SAVs might replace conventional modes such as private vehicles, public transportation, and bicycles. The study highlights the significance of the value of travel time associated with SAVs, ranking second only to private cars and varying across different trip purposes.
This research contributes significantly to the understanding of SAVs, particularly in the Belgian context, where research on this topic has been limited. The study's innovative approach evaluates SAVs as a novel transport alternative for various trip purposes within the mode choice context. With a robust dataset, including 4948 answered choice scenarios, the study estimates a mode choice model encompassing conventional modes alongside the emerging SAV service. This model integration facilitates consideration in an extended transportation model, providing insights into mode competition's impact on key performance indicators like Vehicle Kilometers Traveled (VKT). The study analyzes substitution patterns among alternatives by employing various models, including Nested Logit (NL) and Cross-Nested Logit (CNL).
(Paper: TRB-2024).