Modeling individuals' consideration of strategies to cope with congestion (original) (raw)
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Behavioral response to congestion: identifying patterns and socio-economic differences in adoption
Transport Policy, 1997
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: (l) 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.
KSCE Journal of Civil Engineering, 2012
This study explores key factors affecting individuals' consideration of eight travel-related strategy bundles (auto improvement, mobile phone, work-schedule changes, hire someone to do house or yard work, mode change, home-based work, residential/ employment relocation, and alter employment status). The data for this study were collected from a fourteen-page survey returned by about 1,300 commuters living in three distinct San Francisco Bay Area neighborhoods. We developed discrete choice (binary logit) models for individuals' consideration of each bundle. The results suggest that besides adoption and time since adoption of individual strategies, qualitative and quantitative Mobility-related variables, Travel Attitudes, Personality, Lifestyle, Travel Liking, and Excess Travel significantly affect individuals' consideration of the travel-related strategy bundles.
Transportation, 2008
This study explores the relationships between adoption and consideration of three travel-related strategy bundles (travel maintaining/increasing, travel reducing, and major location/lifestyle change), linking them to a variety of explanatory variables. The data for this study are the responses to a fourteen-page survey returned by nearly 1,300 commuting workers living in three distinct San Francisco Bay area neighborhoods in May 1998. We first identified patterns of adoption and consideration among the bundles, using pairwise correlation tests. The test results indicate that those who have adopted coping strategies continue to seek for improvements across the spectrum of generalized cost, but perhaps most often repeating the consideration of a previously-adopted bundle. Furthermore, we developed a multivariate probit model for individuals’ simultaneous consideration of the three bundles. It is found that in addition to the previous adoption of the bundles, qualitative and quantitative Mobility-related variables, Travel Attitudes, Personality, Lifestyle, Travel Liking, and Sociodemographics significantly affect individual consideration of the strategy bundles. Overall, the results of this study give policy makers and planners insight into understanding the dynamic nature of individuals’ responses to travel-related strategies, as well as differences between the responses to congestion that are assumed by policy makers and those that are actually adopted by individuals.
Coping with congestion: Understanding the gap between policy assumptions and behavior
Transportation Research Part D-transport and Environment, 1997
With congestion being a major social and environmental cost of urban and metropolitan transportation, it has become a major target for policy-makers and planners. However, policies to curb congestion have had little effect. It is suggested that there is a wide gap between the assumptions which underlie policy measures and the manner in which individual users perceive and, consequently, respond to policy measures. This gap can partially be explained by the fact that the set of alternative responses to growing congestion is wider and somewhat different from that assumed by policy-makers. Moreover, the distributional impacts of various responses are such that their benefits and costs, as perceived by the user, create barriers to adoption. The dynamics of the behavioral response are also often overlooked by policy-makers, resulting in the promulgation of measures which have little or no effect on users' behavior. This paper reviews 16 possible behavioral responses from a coping strategy perspective, and emphasizes their distributional impacts. Finally, the paper analyzes some of the implications of the gap between policy-making and user response.
Commuters' Normal And Shift Decisions In Unexpected Congestion: En Route Responses To
Advanced Traveler Information Systems (ATIS) are being developed to provide travelers with real-time information about traffic conditions. To evaluate the benefits of ATIS products and services, questions concerning potential market, usage, and travel response must be addressed. This paper focuses on en-route travel response to ATIS. The main objective is to explore how travelers deal with unexpected congestion and how they might respond to qualitative, quantitative, prescriptive and predictive information. Data on travelers' route switching decisions are obtained through a survey of California Bay Area automobile commuters. The effects of various factors, such as sources of congestion information (radio traffic reports versus observation), trip characteristics, and route attributes on traveler response to unexpected congestion, are investigated. Future response to ATIS technologies is explored using stated preferences, i.e., hypothetical ATIS scenarios. A combined reported and stated preference model of traveler response is developed. The results show that expected delay on usual route, travel time on alternate routes, perceived congestion level on alternate routes, and information sources are important determinants of travel decision changes in response to unexpected delays. The modeling methodology identifies the effect of experience and behavioral inertia on choices, and captures inherent biases in the stated preference responses. Overall, travelers
Commuters normal and shift decisions in unexpected congestion: Pretrip response to ATIS
Advanced Traveler Information Systems (ATIS) are being developed to provide travelers with real-time information about traffic conditions. To evaluate the benefits of ATIS products and services, questions concerning potential market, usage, and travel response must be addressed. This paper focuses on en-route travel response to ATIS. The main objective is to explore how travelers deal with unexpected congestion and how they might respond to qualitative, quantitative, prescriptive and predictive information. Data on travelers' route switching decisions are obtained through a survey of California Bay Area automobile commuters. The effects of various factors, such as sources of congestion information (radio traffic reports versus observation), trip characteristics, and route attributes on traveler response to unexpected congestion, are investigated. Future response to ATIS technologies is explored using stated preferences, i.e., hypothetical ATIS scenarios. A combined reported and stated preference model of traveler response is developed. The results show that expected delay on usual route, travel time on alternate routes, perceived congestion level on alternate routes, and information sources are important determinants of travel decision changes in response to unexpected delays. The modeling methodology identifies the effect of experience and behavioral inertia on choices, and captures inherent biases in the stated preference responses. Overall, travelers
Advanced Traveler Information Systems (ATIS) are being developed to provide travelers with real-time information about traffic conditions. To evaluate the benefits of ATIS products and services, questions concerning potential market, usage, and travel response must be addressed. This paper focuses on en-route travel response to ATIS. The main objective is to explore how travelers deal with unexpected congestion and how they might respond to qualitative, quantitative, prescriptive and predictive information. Data on travelers' route switching decisions are obtained through a survey of California Bay Area automobile commuters. The effects of various factors, such as sources of congestion information (radio traffic reports versus observation), trip characteristics, and route attributes on traveler response to unexpected congestion, are investigated. Future response to ATIS technologies is explored using stated preferences, i.e., hypothetical ATIS scenarios. A combined reported and stated preference model of traveler response is developed. The results show that expected delay on usual route, travel time on alternate routes, perceived congestion level on alternate routes, and information sources are important determinants of travel decision changes in response to unexpected delays. The modeling methodology identifies the effect of experience and behavioral inertia on choices, and captures inherent biases in the stated preference responses. Overall, travelers
1994
The objective of this study is to evaluate the potential benefits of a multimodal Advanced Traveler Information System (ATIS). The propensity of auto commuters to switch to public transportation in response to unexpected traffic congestion is investigated using a detailed survey undertaken in the Golden Gate Bridge corridor in 1993. A stated preference analysis tied to the situation for which the commuting behavior was reported is used to estimate the propensity of travelers to divert to transit under a multimodal ATIS.