Joint Models for Consideration of Public Transit and Mode Choice for Work Commute

2020 ◽  
Vol 6 (1) ◽  
Author(s):  
Ganesh Ambi Ramakrishnan ◽  
Karthik K. Srinivasan ◽  
Surya Pavan Pynda
Keyword(s):  
Public Transit ◽  
Mode Choice ◽  
Joint Models ◽  
Work Commute

Discrete Choice Elasticities for Elderly and Disabled Travelers Between Fixed-Route Transit and Paratransit

1998 ◽  
Vol 1623 (1) ◽  
pp. 31-36 ◽  
Author(s):  
Joel P. Franklin ◽  
Debbie A. Niemeier
Keyword(s):  
Discrete Choice ◽  
Current Practice ◽  
Public Transit ◽  
Choice Model ◽  
Mode Choice ◽  
The Elderly ◽  
The Public ◽  
The Difference ◽  
Mode Choice Modeling ◽  
Significant Factors

In the current practice of mode-choice modeling, models typically focus on the more traditional choices, such as those between automobile, transit, and nonmotorized transportation. For most travelers these are, indeed, the most relevant modes. However, for some segments of the population, particularly the elderly, the choice is more limited. This study investigates the factors that affect the elderly and disabled travelers’ choice between public transit and paratransit. Data collected from the public transit service, Sacramento Regional Transit, and the paratransit service, Paratransit, Inc., in Sacramento, California, were used to develop a mode-choice model and to calculate elasticities of significant factors. Age was found to have an elastic effect, whereas the difference in fare had an inelastic effect.

scholarly journals The Implication of Road Toll Discount for Mode Choice: Intercity Travel during the Chinese Spring Festival Holiday

2018 ◽  
Vol 10 (8) ◽  
pp. 2700 ◽  
Author(s):  
Xiaomei Lin ◽  
Yusak Susilo ◽  
Chunfu Shao ◽  
Chengxi Liu
Keyword(s):  
Chinese Spring ◽  
High Speed ◽  
Public Transit ◽  
Mode Choice ◽  
Mixed Logit ◽  
Negative Effects ◽  
High Speed Rail ◽  
The Public ◽  
Spring Festival ◽  
Intercity Travel

Intercity travel congestion during the main national holidays takes place every year at different places around the world. Charge reduction measurements on existing toll roads have been implemented to promote an efficient use of the expressways and to reduce congestion on the public transit networks. However, some of these policies have had negative effects. A more comprehensive understanding of the determinants of holiday intercity travel patterns is critical for better policymaking. This paper aims to investigate the effectiveness of the road toll discount policy on mode choice behavior for intercity travel. A mixed logit model is developed to model the mode choices of intercity travelers, which is estimated based on survey data about intercity journeys from Beijing during the 2017 Chinese Spring Festival holiday. The policy impact is further discussed by elasticity and scenario simulations. The results indicate that the expressway toll discount does increase the car use and decrease the public transit usage. Given the decreased toll on expressways, the demand tends to shift from car to public transit, in an order of coach, high-speed rail, conventional rail, and airplane. When it comes to its effect on socio-demographic groups, men and lower-income travelers are identified to be more likely to change mode in response to variation of road toll. Finally, policy effectiveness is found to vary for travelers in different travel distance groups. Conclusions provide useful insights on road pricing management.

How Does Ride-Hailing Influence Individual Mode Choice? An Examination Using Longitudinal Trip Data from the Seattle Region

2021 ◽  
pp. 036119812110556
Author(s):  
Yiyuan Wang ◽  
Anne Vernez Moudon ◽  
Qing Shen
Keyword(s):  
Travel Behavior ◽  
Public Transit ◽  
Transportation Network ◽  
Mode Choice ◽  
Large Population ◽  
Past Research ◽  
Substitution Effects ◽  
Cross Sectional ◽  
Individual Mode ◽  
Walking And Biking

This study investigates the impacts of ride-hailing, which we define as mobility services consisting of both conventional taxis and app-based services offered by transportation network companies, on individual mode choice. We examine whether ride-hailing substitutes for or complements travel by driving, public transit, or walking and biking. The study overcomes some of the limitations of convenience samples or cross-sectional surveys used in past research by employing a longitudinal dataset of individual travel behavior and socio-demographic information. The data include three waves of travel log data collected between 2012 and 2018 in transit-rich areas of the Seattle region. We conducted individual-level panel data modeling, estimating independently pooled models and fixed-effect models of average daily trip count and duration for each mode, while controlling for various factors that affect travel behavior. The results provide evidence of substitution effects of ride-hailing on driving. We found that cross-sectionally, participants who used more ride-hailing tended to drive less, and that longitudinally, an increase in ride-hailing usage was associated with fewer driving trips. No significant associations were found between ride-hailing and public transit usage or walking and biking. Based on detailed travel data of a large population in a major U.S. metropolitan area, the study highlights the value of collecting and analyzing longitudinal data to understand the impacts of new mobility services.

scholarly journals Joint Analysis of the Commuting Departure Time and Travel Mode Choice: Role of the Built Environment

2018 ◽  
Vol 2018 ◽  
pp. 1-13 ◽  
Author(s):  
Xiaolei Ma ◽  
Jie Yang ◽  
Chuan Ding ◽  
Jianfeng Liu ◽  
Quan Zhu
Keyword(s):  
Built Environment ◽  
Socioeconomic Factors ◽  
Public Transit ◽  
Mode Choice ◽  
Joint Analysis ◽  
Mobile Source ◽  
Travel Mode ◽  
Study Region ◽  
Travel Mode Choice ◽  
Departure Time

This paper aims to conduct an empirical study to evaluate the influence of built environment features and socioeconomic factors on commuters’ simultaneous choice of departure time and travel mode. Using Kunming, China, as the study region, the 2015 Regional Household Travel Survey and 2016 Point of Interest data are used in the analysis. The results show that, in addition to socioeconomic factors, built environment, such as the density of residential building, employment, and service facility are correlated with joint choice behavior. Moreover, there exist differences regarding the influence of built environment and socioeconomic factors on departure time and travel mode choice. The dissimilarity parameters show that commuters prefer to shift travel mode than departure time generally when travel condition alters. In order to examine the policy measures’ potential performance, the paper conducts simulation tests based on the Monte Carlo method. The simulation results show that congestion pricing of car travel during peak hours can reduce the number of commuting trips, and reducing travel time of public transit would be a better strategy to attract more passengers during peak hours. Moreover, reasonable land use planning, such as building more bus stops around commuters’ home location, would be a long term and fundamental approach to reduce mobile-source emissions and attract more public transit passengers.

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