Op-Ed-Policy issues that motivate travel behavior

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Travel behavior is a study that explores different travel choices and outcomes. In the study of travel behaviors, we are trying to answer how many people travel? How they travel (what mode the choose)? Where do they go? When are they traveling? What route choices they make? Is there any pattern for their trips? There are so many constraints and factors that can influence travel behaviors such as the living location, the place of work, lifestyle, health, and economic condition. It’s important to know some individuals are more responsive to the travel behavior changes. In general, understanding people travel behaviors and their impact on public health is essential for the government and for those who are trying to make effective transportation system policies. Policymakers are interested to know what changes in travel behavior would be beneficial to society and how they can promote those behavior changes. 

Ram M. Pendyala et al. on “emerging issues in travel behavior analysis” provides an overview of some of the recent trends in activity and travel behavior research use in the US. There are different research and studies made the impact of income on mode choice and travel behavior. Studies show that the non-work trip characteristics changed a lot over time. Pendyala presumes that we should understand travelers needs and choices. These types of analysis are used to formulate the policies to meet the needs of particular groups. Another issue for data analyzing is the lack of availability of survey data in most of the urban areas. Policy makers are very interested in vehicle ownership and its relation to travel behavior. They are also interested to see the impact of safety, fuel consumption, change of gas prices, and knowledge about the environmental effects on the travel behavior. For example, if the gas price rise, are the travelers willing to switch to more fuel-efficient vehicles? Alternatively, does the environmental and climate impacts the travelers' mode choices? 

In economic models, as it mentioned by Thomas Domencich and Daniel McFadden in their book of “Urban Travel Demand-behavioral analysis,” travel demand models show when a condition changes in the travel system, the travel decisions of the users will change. Travel demand models that use economic tools are very policy sensitive. Some typical regional policy questions that planner would like to answer are what are the effect of population increase, income changes, car ownership on travel demand and future congestion? What is the impact of travel time and cost on demand and mode choices? What is the threshold for travel time that makes people divert their travel time from peak to off-peak hour?

Ian Heggie on “putting behavior into behavioral models of travel choice” claim that to develop better behavioral model the models should be more humanize and less mathematical. The author dissects the other literature on disaggregate behavioral models that claim to be policy relevant because there is no validation by comparing them with the empirical results. Heggie believes it’s important to understand that different families apply different constraints to the travel behavior models. Families with kids have different destinations in comparison with families without kids. The question is how the age of the member of the household, their marital status, and other factors can affect their travel behavior and mode choices? He also claims that households are adoptable. Their travel choice will change based on the alternative modes, destinations, and time of day. Income and spatial constraints could affect the travel behavior and mode choice. Some people may be trying to decrease the travel time while there are others who are interested in saving the cost. Cost saving will affect the activities and transportation choices. Researchers are still working on the impact of all these constraints mentioned by Heggie on to travel behavior and choices. 

Edward Beimborn et al. on “Making transportation models work for livable communities” show the fundamental questions we are asking to develop a model. These questions are including land use questions such as where people live and what activities will take place, travel forecast questions such as where people go and what mode they choose, and transportation impact questions such as what is the effect of people’s trip to their community?

Pendyala claims people are more aware of time and try to be as time efficient as possible with the help of technologies. One of the factors that impact travel behavior is the interaction between individuals and their surroundings. Land use pattern and residential location choice will affect the travel choices that people make. Over time the lifestyle of people changes. The recent study shows that people travel time expenditures increased over time. The use of phone, computers, and internet increased in the past decade. The impact of telecommunication on travel behavior and travel characteristics is much interested. E-commerce can affect the travel demand in different ways, and it is essential to understand these effects will have more accurate travel demand forecasting. To analyze the impact of technology on travel behavior, we need to understand how people choose to use their time or save their time by using technology? What is their expectation for travel time in the future? Travel time is one of the significant factors interact with travel demand and travel behavior.

REFERENCES:


·    Beimborn, E., & Kennedy, R. (1996). Inside the blackbox: Making transportation models work for livable communities. 

·      Domencich, T. A., & McFadden, D. (1975). “Chapter 1 Introduction” Urban travel demand: A behavioral analysis. New York, NY: American Elsevier Publishing Company, Inc. 

·      Heggie, I. (1978) “Putting Behaviour in Behaviour Models of Travel Choice”, Journal of the Operational Research Society, 29(6): 541–550. 


·     Pendyala, R.M., And C.R. Bhat (2004), “Emerging Issues in Travel Behavior Analysis,” Resource paper for workshop on Emerging Issues, National Household Travel Survey Conference, Washington, D.C., November.

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