Modeling Effects of Transit System Transfers on Travel Behavior

2007 ◽  
Vol 2006 (1) ◽  
pp. 11-20 ◽  
Author(s):  
Zhan Guo ◽  
Nigel H. M. Wilson
Keyword(s):  
Travel Behavior ◽  
Transit System

Travel Behavior Reactions to Transit Service Disruptions

2017 ◽  
Vol 2649 (1) ◽  
pp. 79-88 ◽  
Author(s):  
Shanjiang Zhu ◽  
Hamza Masud ◽  
Chenfeng Xiong ◽  
Zhuo Yang ◽  
Yixuan Pan ◽  
...  
Keyword(s):  
Travel Behavior ◽  
Behavioral Reactions ◽  
Transit System ◽  
System Failures ◽  
Transit Service ◽  
Effective Strategies ◽  
Aging Infrastructure ◽  
Infrastructure System ◽  
Network Disruptions ◽  
System Impact

Major transit infrastructure disruptions have become more frequent because of increasing maintenance needs for aging infrastructure, system failures, and disasters. Understanding travel behavior reactions to service disruptions on the basis of empirical observations is a fundamental step toward planning and operating an efficient and reliable transportation system. Few studies in the literature have investigated the behavioral and system impact of transit service disruptions. To bridge this gap in the literature, this research investigated travel behavioral reactions to transit service disruptions during the Metro SafeTrack projects in Washington, D.C., with the use of a unique panel survey. This study offers new insights on multimodal, multidimensional travel behavioral responses to major transit network disruptions, a critically theoretical prerequisite for developing and implementing effective strategies (e.g., how to deploy the reserve bus fleet optimally) that minimize system impact and improve transit system reliability and resilience.

Reshaping the Region

2015 ◽  
Vol 2537 (1) ◽  
pp. 33-41
Author(s):  
Stephanie Pollack ◽  
Anna Gartsman ◽  
Timothy Reardon ◽  
Meghna Hari
Keyword(s):  
Land Use ◽  
Public Transportation ◽  
Travel Behavior ◽  
Massachusetts Bay ◽  
Data Set ◽  
Transit System ◽  
Transit Systems ◽  
Commuter Rail ◽  
In Transit ◽  
The Impact

The American Public Transportation Association's use of a “land use multiplier” as part of its methodology for calculating greenhouse gas reduction from transit has increased interest in methodologies that quantify the impact of transit systems on land use and vehicle miles traveled. Such transit leverage, however, is frequently evaluated for urbanized areas, although transit systems serve only a small proportion of those areas. If transit leverage is stronger in areas closer to transit stations, studies based on larger geographies may underestimate land use and travel behavior effects in transit-served areas. A geographic information system–based data set was developed to understand better the leverage effects associated with the mature and extensive Massachusetts Bay Transportation Authority transit system in areas proximate to its stations throughout Metropolitan Boston. The region was divided into the subregion that was transit-proximate (within a half mile of a rapid transit station or key bus route), the portion that was commuter rail–proximate, and the remaining 93.3% of the region that was not proximate to high-frequency transit. Households in the transit-proximate subregion were significantly more likely to commute by transit (and walking or biking), less likely to own a car, and drove fewer miles than households in the non-transit-served areas of the region. Commuter rail–proximate areas, although denser than the region as a whole, exhibited more driving and car ownership than regional averages. Given these spatial and modal variations, future efforts to understand transit leverage should separately evaluate land use and travel effects by mode and proximity to transit stations.

A Typological Approach to Individual Urban Travel Behavior Prediction

1975 ◽  
Vol 7 (2) ◽  
pp. 141-152 ◽  
Author(s):  
N Oppenheim
Keyword(s):  
San Francisco ◽  
Travel Behavior ◽  
San Francisco Bay ◽  
San Francisco Bay Area ◽  
Urban Resident ◽  
Transit System ◽  
Urban Travel ◽  
Behavior Type ◽  
Bay Area ◽  
Typological Approach

With the use of cluster analysis a sample of 1018 residents of the San Francisco Bay Area was classified into eleven types of urban residents on the basis of overall similarity of personal and environmental characteristics, and independently into nine types of travel behavior. The relations between the two typologies, and the comparative travel behavior of the types of urban resident were investigated in an attempt to gain insight into the determinants of urban travel. The probability of the correct assignment of a travel behaviour type to an urban resident type was of the order of 0·30. Monte Carlo simulation methods were used to test empirically whether the value of a given travel behavior characteristic for a given urban resident type can be assumed to be higher (or lower) than the value in the general population, thus testing the predictability of the travel behavior of the various urban resident types. Conversely, the prediction of the urban traveler's personal characteristics given his travel behavior type was also evaluated. This typological approach made the prediction of the usage of the San Francisco Bay Area rapid transit system (for going to work, for going to shop, for going out for leisure, or for some other purpose) possible, in about 15% of the cases, from the knowledge of the urban resident type and, in about 25% of the cases, from the knowledge of the travel behavior type.

scholarly journals Understanding Gender, Income and Travel Behavior in Casablanca City – Morocco

2021 ◽  
Vol 15 (1) ◽  
pp. 272-279
Author(s):  
Zineb Chamseddine ◽  
Asmaa Ait Boubkr
Keyword(s):  
Low Income ◽  
Travel Behavior ◽  
Cultural Context ◽  
Vulnerable Groups ◽  
Transit System ◽  
The Public ◽  
Work Related ◽  
Income Groups ◽  
Private Car ◽  
The City

Objective: The purpose of this paper is to extend the research on gendered differences in travel behavior in developing countries by analyzing travel behavior variability within as well as across gender and income groups in the case of Casablanca city. Methods: Data from the 2018 Casablanca Travel Survey show that overall, women are less mobile than men, make fewer work-related trips and more household maintenance trips, but these differences are heterogeneously distributed across income groups. With the increase in income, women tend to carry out more trips than men; the inverse is observed for the middle- and low-income categories. Results: While for the lowest income groups, walking is the most predominant mode for both men and women, we notice that the private car has the highest modal share within the highest income groups as with the increase in household income, both genders avoid non-motorized transport modes. The particular status of women in some households as breadwinners and reproducers as well as the socio-cultural context of the city shape their mobility and the choice of their activities. Conclusion: Hence, these findings suggest, from a policy perspective, that the public transit system along with spatial planning strategies need to be improved to help overcome women's mobility constraints, especially when they belong to low-income households so they can fully access the city amenities and opportunities. On the other hand, transport policies need to be not only gender-sensitive but also “vulnerable groups” sensitive as mobility impediments are similarly experienced by males and females in some contexts.

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