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Commuter's sensitivity in mode choice: An empirical study of New Delhi
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... Most choice behavior models work on the principle of utility maximization derived from econometric theory [6]. Since the Multinomial Logit Model (MNL) was developed in 1970s, various statistical parametric models having different structures such as standard logit [7], nested logit, mixed logit [8] etc. have been widely used to analyze travel behavior. These models are not very effective recognizing any pattern in the dataset and capturing uncertainty in the choice making process [9]. ...
... Researchers across the world studied mode choice behavior of travelers since long. These studies reveal that sociodemographic characteristics such as age, income, gender [7], travel characteristics such as travel time, travel cost [8], attitudinal variables [14] and built environment factors [15] are decisive factors while selecting a travel mode. While, travel mode choice behavior is modeled for main trip, very less attention is given to feeder mode choice behavior for mass transit systems especially in developing economies [16]. ...
... Hensher and Rose [31] used MNL and Nested logit models to determine the preference of travel modes in existing conditions as well as for forecasting patronage levels for new transit. Minal and Chalumuri [8] analyzed commuters' sensitivity with respect to change in travel time and travel cost using MNL, Nested and Mixed logit model. ANNs have also been used by the scientists for classification problems. ...
First and last mile connectivity are the most crucial elements of transit system. However, inadequate attention is given to such issues in developing countries like India. The present study aims to analyze feeder mode choice behavior of people accessing Delhi metro. Multinomial logit model and Artificial Neural Network are deployed to analyze the travel behavior. Findings suggest that ANNs are highly efficient in learning and recognizing connections between parameters for best prediction of an outcome. Since, utility of ANNs has been critically limited due to its ‘Black Box’ nature, the study involves the use of Garson’s algorithm and Partial Dependence Plots for model interpretation. Findings of the study can be useful for policy makers and transport planners for improving service quality of existing feeder services and, establishing efficient feeder system that promote the use of transit.
... For Auto-rickshaw and bicycle modes the data retrieved from google maps was used. These factors play an important role in travel mode selection of commuters (Minal & RaviSekhar, 2016) thus, including these parameters in estimation of VoT along with LU parameters is vital. ...
... The travel time parameter 'θ TT ' in the study, follows a triangular distribution and so does VoT. Triangular distribution is selected in the study as it is bounded on both sides and evades the problem of large coefficients obtained due to large upper (or lower) bound for few decision makers as in the case with normal and lognormal distributions (Minal & RaviSekhar, 2016). It can also accommodate varying degrees of skewness in unobserved preference heterogeneity (Dekker, 2016). ...
The Value of Travel Time (VoT) refers to the cost of time spent on transport and forms the basis of performance evaluation of different policies and scenarios in transportation planning and engineering. It takes into account various factors like trip information, traveller information and household information. This study develops mode choice models to further estimate the value of travel time in context of Land Use (LU) pattern for different zones of National Capital Territory (NCT) of Delhi, the capital of India. The entire region of Delhi was sub-divided into 17 land-use based zones and LU data, demographic data and trip data were collected through a Revealed Preference (RP) survey. The LU intensity parameters used for study are population-density and employment density of the zones. To account for the LU diversity of each zone, mix area index was calculated to balance different complementary LUs as well as the functional relationship between trip origin zone and destination zone. Discrete mode-choice model based on mixed logistic regression were developed for zones to account for the effects of LU pattern on VoT. The VoT so estimated from the study depict fluctuating values for different travel modes in different zones with varying LU patterns. The study showed that larger tracts of land dedicated to residential LU leads to lowering value of estimated VoT. This effect is more pronounced in regions with higher population densities.
... Usage of personalised modes has an increased bearing on fuel consumption, air and noise pollution, road accidents and overall financial costs incurred (Minal and RaviSekhar, 2016). Multimodal transport is widely believed to be more sustainable and environmentally friendly, and to enable transport equity (Krygsman et al., 2004) for wider sections of society. ...
... It is only when the driving under congested conditions becomes taxing that they shift towards multimodal transport. Socio-economic factors play an important role in multimodal travel choices as they represent the 'biases' across individuals (Koppelman and Bhat, 2006;Minal and RaviSekhar, 2016). This difference in 'bias' among commuters contributes towards their overall decisions to select a particular travel mode. ...
This study investigates the trends and determinants that dictate the state of multimodal transport by incorporating the effect of travel time reliability at different level-of-service of traffic condition. To account for the taste variation of the commuters, a random parameter mixed logit model is used for the multimodal choice analysis. Multimodal transport is defined as use of multiple (more than one) transport modes for commuting in a specified time period. The data was collected through an interview-based household survey for a single day trip and land use data was collected from secondary sources. The parameters used in this study are interconnectivity ratio, penalty, multi-modal-level-of-service, travel cost, age, gender, income of traveller, trip purpose and land use intensity and diversity parameters like population density, employment density, entropy and transport network density. The results indicate that interconnectivity ratio and multi-modal-level-of-service plays the most influential role in selecting multimodal transport system. Commuters are most sensitive towards access and egress time. Also, the utility of multimodal transport system for a commuter is highest under road service condition of LOS-D as compared to LOS-A.
... Such improvements can considerably improve the likelihood of individuals choosing PT over PMVs for their travel needs. Furthermore, Idris et al. and Chandra & Chalumuri [36,37] underscore the significance of integrated and multimodal transport options that align with individual preferences and needs. This approach not only enhances the convenience and accessibility of transportation but also plays a crucial role in promoting sustainable mobility practices. ...
Efficient and sustainable urban mobility is critical for contemporary cities, and understanding the factors influencing modal choices is essential for addressing transportation challenges in metropolitan areas. This study focuses on the Porto Metropolitan Area (AMP) in Portugal and aims to gain insights into these factors. Using data from the last mobility survey (IMob) conducted in 2017, a multinomial logit (MNL) model is used to analyze individual modal choices amongst private motorized vehicles (PMVs), public transport (PT), and active modes (AMs). The findings unveiled that demographic, socioeconomic, and travel-related characteristics substantially influence individual modal choices within the studied area. Moreover, probability scenarios highlight the importance of financial considerations, environmental consciousness, and accessibility to public transport in promoting sustainable transportation options. These insights have significant implications for policymakers and stakeholders involved in urban planning and transportation management. This study contributes to the literature by providing valuable insights into individuals’ transportation preferences and behaviors, facilitating decision-making based on evidence for infrastructure improvements and targeted interventions. By promoting sustainable transportation alternatives and reducing reliance on PMVs, this study aims to enhance the livability and sustainability of the AMP, aligning with long-term sustainability goals.
... Delhi traffic is at saturation level (Minal and RaviSekhar 2016). One of the most effective way to reduce traffic on roads is by encouraging people to shift towards public transport and use a multimodal transport system (MMTS). ...
Metro is a rapid transit mode that helps in fast and efficient movement of the public. To make metro journey more convenient and attractive, from origin to destination, accessibility of metro must be good. In this study, tri-level analysis is carried out for the study area of Delhi. Traffic congestion and environmental condition of Delhi are degrading continuously, and to improve the situation, a sustainable Multi Modal Transport System (MMTS) with high accessibility must be explored. In this paper, policy to improve zone to zone metro accessibility for work purpose is discussed and the relation between multimodal transport system with accessibility is studied using GIS (ArcGIS), macrosimulation software (VISUM) and gravity model. It was observed that by the addition and extension of metro lines, transport accessibility is greatly improved. This study shows that percentage of zones in Delhi with higher accessibility level could increase from 5 to 13.88% with the implementation of phase IV of metro. In addition, the implementation of phase IV metro could reduce the average travel time between zones and metro stations. It will also reduce the travel time between metro stations substantially (for the zones covered in this study the average travel time is reduced by 23.63% and for the station covered in this study the average travel time is reduced by 17.73%). Further, it was found that ‘out vehicle travel time’ (OVTT) is having a major impact on the accessibility of metro. Lastly, it was concluded that with the higher level of metro accessibility, people will prefer the multimodal transport system with metro as the main mode. Travel time isochrones for public and private trips for the estimated MMTS model are also presented in this paper to depict the changes in accessibility for different scenarios. This will further help in improving private transport accessibility by reducing congestion on roads. Thus, planning for transport accessibility helps in developing the city in a sustainable manner in the future.
... The city has a good transport infrastructure in terms of road-and railways. DTC (Delhi Transport Corporation) provides the service of approximately 5000 buses [59]. Apart from buses, the city has another network of mass transit in the form of a metro system consisting of various metro ...
The first and last mile connectivity is the weakest element for any public transit system becoming successful. Huge investment in provision of mass transit is not justified when these services remain underused. The present study aims to determine accessibility to metro by feeder modes and its influence on feeder mode choice behavior. An accessibility index is estimated considering trip characteristics and built environment factors. Analytic Hierarchy Process is used to determine the weights of indicators. Mode choice analysis using nested logit model shows that accessibility has considerable impact on feeder mode choice behavior of people. Further, elasticity analysis is done to estimate the percentage change in the probability of selecting a mode with reference to the change in accessibility. Findings of the study can be useful for policy-makers and transport planners for improving service quality of existing feeder services and establishing efficient feeder system that promote the use of public transit.
Many cities in Iran, including the metropolis of Shiraz, are increasingly car-oriented, resulting in trafc congestion and related issues. Considering the current conditions of Iran, an automated transit network (ATN) can be one of the available solutions to this problem. ATN is an advanced type of public transit consisting of automated vehicles moving passengers on a network of dedicated guideways. As a combination of public, personal, and private transport, ATNs may decrease the use of cars and address related problems. In order to design efective policies aimed at achieving the benefts of ATN, it is necessary to have a better understanding of how people accept an ATN system, especially car users. Tis research aims at advancing future research on the efects of ATNs on travel behavior through identifying the characteristics of users who are likely to accept ATN services, by examining the heterogeneity in the preferences of these people. To achieve this goal, a stated choice survey was conducted and analyzed using multinomial logit (MNL) and mixed logit (ML) models. Te results showed that the parameters of trip purpose, owning a hybrid car, and the level of education afect the preferences toward the ATN system. Additionally, from the comparison of the results of the MNL and ML models, it was found that despite the greater ability of the ML model in estimating possible heterogeneities, likely the MNL model can also help to record some heterogeneities more realistically. In the end, the meth-odological limitations of the study were also acknowledged. Despite the potential hypothesis bias and the status quo bias, the results captured the directionality and relative importance of the attributes of interest.
As the population increases day by day, there has been a tremendous increment of ownership over two-wheeler and four-wheeler systems. Thereby usage of public transports system decreases than private vehicles system. In this scenario, this study focused on the significant factors in the mode choice behaviour of commuters from the extensive household survey conducted by Thiruvarur City to obtain detailed information on the modal split pattern analysis. The questionnaire of 4857 respondents was used in the Multinomial Logit Model using the Statistical Packages for Social Science (SPSS) tool to predict the mode choice behaviour of commuters. A total of seven explanatory variables were extracted from the responses; the Multinomial logit model was calibrated to fit the data, and the chi-square test was used to measure the goodness of fit. Apart from the MLM model, commuter behaviour prediction analysis is also made using soft computing technologies, which involves multi-linear regression and neuro-fuzzy model, keeping uncertainties involved in commuter behaviour to avoid collecting household data. It was found that two-wheeler commuters are more in numbers for their travel choice as cost minimizing than four-wheelers, public transport system commuters. Consequently, the developed model predicts the behaviour of commuters in a precise manner that closely matches the actual conduct.
The objective of this paper is to explore if and how the primary transport mode of women in Saudi Arabia changed since they are allowed to issue a driving license and drive, and what the factors affecting modal switch behavior are. A survey was launched as part of the national project She Drives KSA a year after the activation of the decree on allowing women drive. 20,504 women participated in the survey. Data analysis shows that modal shifts happened to several directions. A significant percentage of women (22.7%) has switched from “household car-as a passenger” to “household car-as a driver”. In total, 37.7% of the participants have switched to household car-as a driver. A nested logit model is developed and the model estimation results indicate that employed women, women in the age groups of 18 to 29 and 30 to 39, women with high educational level, and single women are more likely to change from “household private car-as a passenger”, “ridehailing” and “other” to “household private car-as a driver”. Women who are unemployed, with low educational level and from households with low monthly income, are more likely to not change their primary transport mode. To our knowledge, this is the first research investigating such a unique and sensitive topic that is expected to significantly affect women's travel behavior.
Mode choice is one of the most vital stages in transportation planning process and it has direct impact on the policy making decisions. Mode choice models deals very closely with the human choice making behaviour and thus continues to attract researchers for further exploration of commuter’s choice making process. The objective of this study is to carryout detailed review on various modeling methods of mode choice analysis and bottlenecks associated with the same. The factors that affect the psyche of the travelers have been discussed; further various types of data required and their method of collection has been briefed up. This paper particularly emphasizes on statistical mode choice models such as multinomial logit and probit models as well as recent advanced soft computing techniques such as Artificial Neural Network models (ANN) and Fuzzy approach model that are employed for modal split analysis. Comparative analysis were made among various modeling techniques for modeling the complex mode choice of behaviour of models carried out by various researchers in the literature and a discussion on the need of future hybrid soft computing models has been attempted.
Xi'an, as a typical inland city in China with a worse integrated transport system, has promoted the use of metro service to ease serious traffic congestion. This paper uses a logistic regression model to examine mode shifts behavior for auto, taxi, bus, electric bicycle, and bicycle users after the implementation of metro service based on stated preference data. The results indicate that auto travelers located in suburban regions are more willing to shift to metro for work trips. Female taxi and auto users are more likely to use metro than males. Longer trips for taxi and electric bicycle travelers prefer to choose the newly introduced metro. Additionally, a preference survey on newly opened metro concluded that metro passengers that shift from auto mode may decrease 8 to 19% because of incomplete transfer facilities. Finally, it was found that the impacts on easing traffic congestion by a single metro corridor are not significant, and some parallel policies need to be adopted. Furthermore, these findings are more useful for developing cities lacking modal joint and integration. (C) 2013 American Society of Civil Engineers.
Commuters can complete their “home-work-home” trips by three options: subway-only mode, auto-only mode, and park-and-ride mode on a bottleneck-constrained corridor. The purpose of this paper is to enhance the insights into pricing mechanism for subway and parking and corresponding mode choice behavior on the corridor with elastic demand. A nested logit-based stochastic user equilibrium model is proposed to characterize the commuters’ modal choice. Dispersion parameters in the nested logit model reflect the risk or uncertainty of mode choice. It is found by sensitivity analysis that the impacts of subway fare and parking fee on the commute pattern are not always monotonous. Optimal strategies of subway fare and parking fee are discussed, respectively, under four market schemes by assuming that the subway and the parking lot at workplace are operated by either the government or a private owner. A numerical example is presented to illustrate how the pricing policies affect demand implementation, mode choice behavior and benefits of private owners and the whole transportation system.
Commuters can complete their “home-work-home” trips by three options: subway-only mode, auto-only mode, and park-and-ride mode on a bottleneck-constrained corridor. The purpose of this paper is to enhance the insights into pricing mechanism for subway and parking and corresponding mode choice behavior on the corridor with elastic demand. A nested logit-based stochastic user equilibrium model is proposed to characterize the commuters’ modal choice. Dispersion parameters in the nested logit model reflect the risk or uncertainty of mode choice. It is found by sensitivity analysis that the impacts of subway fare and parking fee on the commute pattern are not always monotonous. Optimal strategies of subway fare and parking fee are discussed, respectively, under four market schemes by assuming that the subway and the parking lot at workplace are operated by either the government or a private owner. A numerical example is presented to illustrate how the pricing policies affect demand implementation, mode choice behavior and benefits of private owners and the whole transportation system.
Several previous attitudinal surveys indicated the importance of reliability of travel modes. This research identifies perceived reliability measures of urban transportation modes. These measures are included in a multinomial mode choice logit model for work trips in the Chicago area. The statistical significance of the reliability measures is evaluated as well as their importance relative to more traditional performance measures such as travel time and travel cost. -from ASCE Publications Abstracts
The worldwide increase in private car dependency poses a set of significant environmental, economic and social sustainability challenges that continue to undermine the urban quality of life. Rapid motorisation, particularly in South East Asia (SEA), has emerged as a global concern given the region’s cumulative population, rate of industrialisation, and large-scale urbanisation. Thus, there is a compelling need to enhance our understanding of the underlying dynamics of how people perceive and use transportation such that transport planning is better placed to address the current, unsustainable travel patterns in SEA. Despite this need, there has been relatively limited SEA-based research that has endeavoured to examine travel perceptions and transport mode choice from a non-instrumental perspective. This research redresses this deficit by investigating the relationship between transport users’ perceptions and travel behaviours within SEA, with a particular focus on psychosocial drivers of transport mode choice interfaced with more traditional instrumental measures.
This paper proposes an accessibility-based spatial mixed logit (SML) model with panel data structure to examine the impacts of High-Speed Rail (HSR) on land cover change in large urban areas. Using data between 1990 and 2006, impacts of the Spanish HSR on Madrid’s Atocha railway station influence area - a 20 km radius buffer centred on the station - were investigated. To model the HSR impacts, besides socioeconomic variables, the development of both local and regional transportation networks with corresponding accessibility improvement is also taken into account to segregate the impacts of land-cover change brought by different sources of accessibility measures. In this study, two SML models are used: one incorporates regional accessibility indicators as a base model, and the other does not, acting as a control model. The model estimation results reveal that the reduction of the local and regional weighted travel average time has positive impacts on the Atocha station catchment area’s urbanised land-cover rates. Although the base and control models both achieve high goodness-of-fit values, the base model that considers regional accessibility reveals a better goodness-of-fit statistic and is more robust than the control model. It is concluded that the improvement of regional accessibility due to the arrival of HSR at Atocha station plays an essential role in the urbanisation of land cover changes in the study area.