An understanding of how individuals perceive congestion and the range of coping strategies they adopt is crucial for the development of relevant, effective policies. This study empirically tested two hypotheses: (1) that responses to unsatisfactory conditions, such as a congested commute, are a function of previously adopted adjustments; and (2) that responses to congestion are distributed differently across various socio-economic segments. Coping strategies were classified into tiers according to their similarity in implementation cost and effort: lower-effort strategies which increase the comfort in maintaining existing travel patterns; moderate-effort strategies which tend to reduce travel; and major lifestyle/location change strategies such as job or residence changes. Findings confirm that lower-effort strategies tend to be adopted first, with higher-effort strategies adopted if dissatisfaction persists. The adoption of most types of strategies, especially the more costly ones, appears to fall disproportionately to women. Additionally differences were identified by family status, income level, employment status, and household type. These results illustrate the need for further study into patterns of behavioral response to congestion, with the goals of improving forecasts of the effects of congestion mitigation policies and identifying distributional inequities in those effects.

This study continues the examination of a variety of strategies an individual may consider or adopt in response to congestion. It finds further evidence that individuals tend to progress from lower-cost, short-term strategies to higher-cost, longer-term ones as dissatisfaction persists or recurs. There is also a weaker tendency to cycle back to lower-cost strategies, although generally just one tier lower than a previously adopted strategy. Binary logit models of the consideration of each of 15 congestion-response strategies were estimated, as a function of work-, family-, leisure-, and travel-related attitudes, among other explanatory variables ρ2 goodness-of-fit measures for these models ranged from 16 to 75. Analysis of the contribution of commute-related variables to the consideration of each strategy found that contribution to be significant in fewer than half of the cases (seven out of 15 strategies). With only one exception, the strategies for which commute variables were significant fell into the higher-cost tiers. Commute variables never contributed more than 11% of a model’s explanatory power, and generally much less. While other explanatory variables may also be significant for transportation-related reasons, it is clear that individuals adopt and consider the strategies studied here for many reasons other than congestion relief. Further, the transportation-related reasons for considering these strategies may be intertwined in complex ways with non-transportation reason. One implication of these findings is that policies designed to change transportation behavior may be less powerful than expected, because reactions are filtered through a variety of other motivations and constraints. An improved understanding of the response to these policies must acknowledge and incorporate the complexity of the choice situation facing the typical individual in modern society.