Geotourist Profile Identification Using Binary Logit Modeling: Application to the Villuercas-Ibores-Jara Geopark (Spain)

Geoheritage ◽  
2019 ◽  
Vol 11 (4) ◽  
pp. 1399-1412 ◽  
Author(s):  
Marcelino Sánchez Rivero ◽  
Ma. Cristina Rodríguez Rangel ◽  
José Manuel Sánchez Martín
Keyword(s):  
Binary Logit ◽  
Logit Modeling

CONDITIONAL AND MULTINOMIAL LOGITS AS BINARY LOGIT REGRESSIONS

2011 ◽  
Vol 03 (03) ◽  
pp. 309-324 ◽  
Author(s):  
STAN LIPOVETSKY
Keyword(s):  
Logistic Regression ◽  
Binary Logistic Regression ◽  
Link Function ◽  
Logit Models ◽  
Categorical Variable ◽  
Multinomial Models ◽  
Multinomial Logit Models ◽  
Dependent Variables ◽  
Binary Logit ◽  
Logit Modeling

For a categorical variable with several outcomes, its dependence on the predictors is usually considered in the conditional or multinomial logit models. This work considers elasticity features of the binary and categorical logits and introduces the coefficients individual by observations. The paper shows that by a special rearrangement of data the more complicated conditional and multinomial models can be reduced to binary logistic regression. It suggests the usage of any software widely available for logit modeling to facilitate constructing for complex conditional and multinomial regressions. In addition, for binary logit, it is possible to obtain meaningful coefficients of regression by transforming data to the linear link function, which opens a possibility to obtain meaningful parameters of the complicated models with categorical dependent variables.

Comparative study on e-bikes’ decision-making behaviors under flashing green and green countdown

2021 ◽  
pp. 1-8
Author(s):  
Haoyang Meng ◽  
Sheng Dong ◽  
Jibiao Zhou ◽  
Shuichao Zhang ◽  
Zhenjiang Li
Keyword(s):  
Decision Making ◽  
Critical Issue ◽  
Trajectory Data ◽  
Decision Points ◽  
Binary Logit ◽  
The One ◽  
Common Signal ◽  
And Function ◽  
Decision Behaviors ◽  
Stop Line

Green flash light (FG) and green countdown (GC) are the two most common signal formats applied in green-red transition that provides drivers additional alert before termination of green phase. Due to their importance and function in stop-pass decision-making process, proper use of them has become a critical issue to greatly improve the safety and efficiency of signalized intersections. Gradually e-bike riders have become more important commuters in China, however, the influence of FG or GC on them is not clear yet and need pay more attention to it. This study chooses two almost identical intersections to obtain highly accurate trajectory data of e-bike riders to study their decision-making behaviors under FG or GC. The e-bike riders’ behavior is classified into four categories and is to identify their stop-pass decision points using the acceleration trend. Two binary-logit models were built to predict the stop–pass decision behaviors for the different e-bike rider groups, explaining that the potential time to the stop-line is the dominant independent factor of the different behaviors of GC and FG. Furthermore empirical analysis of decision points indicated that GC provides the earlier stop-pass decision point and longer decision making duration on the one side while results in more complexity of decision making and greater risk of stop-line crossing than FG on the other side.

scholarly journals Commuter Train Mode Choice Modelling Using Binary Logit Model

2019 ◽  
Vol 6 (1) ◽  
pp. 1
Author(s):  
Ryan Septiady Nugraha
Keyword(s):  
Public Transportation ◽  
Choice Model ◽  
Mode Choice ◽  
Leisure Activity ◽  
Proper Solution ◽  
Choice Modelling ◽  
School Work ◽  
Trip Purpose ◽  
Public Transport System ◽  
Binary Logit

Car production in Malaysia increasing dramatically. This situation created serious impact such as pollution and congestion. The Malaysian government should find a proper solution to prevent the vehicles growth by controlling them and improve public transportation services. The only way to get people to switch to public transportation is by improving the public transport system becomes more efficient. To find out the solution, an understanding of traveler behavior by applying to mode choice model using binary logit approach is necessary. Stated preferences method was adopted in order to construct hypothetical choice in current and future situations. A total of 250 respondents were selected as the sample based on the research study. This research employed a discrete choice analysis to examine the relationship between the independent variables (travel time, fares, comfort and safety). With variation of trip purpose (school, work, leisure activity, and shopping), model has been developed and tested to check the validity. The result shows that the potential of new train services to compete with the current commuter (KTM) and private car user are quite competitive. This is no doubt due to the characteristics of the respondent to choose a good level of services especially a better comfortability and safety with an affordable price (fares). It can be concluded that scenario 2 has great potential to be implemented since forecasting demand reached above 90%.

Analysing pedestrian–vehicle conflicts behaviour at urban pedestrian crossings

2021 ◽  
pp. 1-25
Author(s):  
Babak Mirbaha
Keyword(s):  
Risk Taking ◽  
Logit Model ◽  
Video Recording ◽  
Elasticity Analysis ◽  
Gap Acceptance ◽  
Time To Collision ◽  
Binary Logit Model ◽  
Traffic Conditions ◽  
Rainy Weather ◽  
Binary Logit

Pedestrian safety has become a serious problem with the rapid growth of motorised vehicle in transportation system in developing counties. Pedestrians often respond differently to changes in surrounding and traffic conditions. A study was undertaken to investigate pedestrians’ gap acceptance and the parameters affecting their risk-taking behaviours based on time-to-collision and post-encroachment-time indexes. Three signalised intersections and two midblock crossings were selected in Qazvin, Iran. A total of 752 pedestrians were examined by video recording and field observation, and pedestrians’ gap acceptance behaviour was estimated by using binary logit model. Results showed that the average time to collision and post-encroachment time were 4.27 s and 1.44 s, respectively. In addition, the presence of children alongside the older pedestrians led to a less risk-taking crossing. Additionally, pedestrian risk-taking was reduced by increasing both time indexes. Rainy weather also reduced pedestrians’ risk-taking behaviour. Elasticity analysis indicated that parameters such as pedestrians’ conflict with vehicles at the first or second half of the crossings, walking with a child, speed of the approaching vehicle, the crossing type and running while crossing were the most important factors in pedestrian risk-taking.

Logit Modeling

2017 ◽  
pp. 122-133
Author(s):  
Joel Clarke Gibbons
Keyword(s):  
Logit Modeling

Modeling Incident-Related Routing Decisions by Using a Nested Logit Structure

1998 ◽  
Vol 1645 (1) ◽  
pp. 103-110 ◽  
Author(s):  
Mohamed A. Abdel-Aty
Keyword(s):  
Logit Model ◽  
Urban Areas ◽  
Potential Benefit ◽  
Traffic Information ◽  
Nested Logit ◽  
Traveler Information ◽  
Traveler Information Systems ◽  
Real Time Traffic ◽  
Alternative Routes ◽  
Logit Modeling

Unusual congestion that could be caused by an incident or other traffic problems is a major source of delay for drivers in urban areas. Real-time traffic information, the building block for advanced traveler information systems (ATIS), has a promising potential for alleviating such congestion by encouraging and assisting drivers to divert to less congested routes. Traffic information is envisioned to help more informed routing decisions in case of incident-related congestion. Drivers’ routing decisions made when they are faced with such unusual congestion are investigated. The factors that influence these decisions are explored, including the effect of traffic information. A nested logit modeling structure is introduced. This model proved that the nested logit approach is superior than the simple multinomial logit in modeling the choice in cases of incident-related congestion. The model also showed that the decisions not to divert from the usual route and to divert but only around the location of the problem share unobserved terms. Familiarity and usual use of alternative routes did not affect the decision in the case of an incident. Drivers who use more than one route to work do not necessarily switch routes if they encounter unusual congestion. The nested logit model also proved the significance of traffic information, indicating a promising potential benefit of ATIS in alleviating nonrecurring congestion.

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