scholarly journals Choice Modelling of a Car Traveler towards Park-and-Ride Services in Putrajaya to Create Green Development

2021 ◽  
Vol 13 (14) ◽  
pp. 7869
Author(s):  
Irfan Ahmed Memon ◽  
Noman Sahito ◽  
Saima Kalwar ◽  
Jinsoo Hwang ◽  
Madzlan Napiah ◽  
...  
Keyword(s):  
Traffic Congestion ◽  
Choice Model ◽  
Low Cost ◽  
Mode Choice ◽  
City Centre ◽  
Choice Modelling ◽  
Park And Ride ◽  
Green Development ◽  
Mode Of Transport ◽  
The City

Putrajaya is facing an increasing number of private car ownership and its usage. Integrated transportation infrastructure connecting the city with suburban areas and comparatively low-cost housing schemes are at the fringes of Putrajaya City. It creates a discrepancy between housing and employment attentiveness. Due to the attractiveness of jobs in the city centre, commuters’ travelling pattern is morning/evening peak hours, and it leads to traffic congestion on a few major artilleries leading to and from the city. In contrast, Putrajaya was designed to achieve a 70:30 modal split ratio. This policy was introduced to target 70% of the commuters towards a sustainable mode of transport as their mode choice. Currently, congestion in Putrajaya is due to the use of single-occupant vehicles (SOV). The SOV users cannot be convinced to use the park-and-ride services (P&RS) without understanding their travel behaviors. Therefore, the mode choice models (MCM) were developed through binary logit regression (BLR) approaches to determine the factors that influence the SOV travelers’ decisions to adopt the P&RS. As a result, several factors, which included the socio-demographic factors, travel time, travel expenses, environmental protection, avoiding stress, parking problems, vehicles sharing, and traveling directly, were found to be significant and will promote green development. Furthermore, the quality of the developed mode choice model was validated through the training and testing approach of logistic regression. Ultimately, this study can help stakeholders to encourage SOV users towards P&RS by overcoming these factors.

scholarly journals A Critical Appraisal of Mode Choice Model of Work Trips

2019 ◽  
Vol 9 (1) ◽  
pp. 1766-1770
Keyword(s):  
Traffic Congestion ◽  
Choice Model ◽  
Mode Choice ◽  
Face To Face ◽  
Transportation Modes ◽  
Mode Choice Model ◽  
Private Car ◽  
Horizontal Spread ◽  
Work Education ◽  
The City

In the present scenario in world, many mode choice models have been developed to predict the travelers mode choice in the available modes of transportation system .The mode choice model is one of a very significantcomponent in the urban transportation planning and policies,specifically in countries that are toward development and urbanization, likeSouth Asian countries(India, Bangladesh, Nepal,etc.)the increasing horizontal spread of cities that led to increased travel demand.The aim of this review is to study the developing of mode choice model for various transportation modes .The developed models cover different modes of transportation currently employed in cities,which are Private car,Taxi,Publicbus,Autorickshaw,Motorcycles,Shared car,Bicycles,Walking.They have been tried to be estimated for work, education,shopping and other trips .There are some factors that considerablyinfluence the choice of transport modes are:Socio economics variables such as age,gender, car ownership,and family monthly income.Network variables are such as travel time,travel cost,comfort,reliability, employment, driving licenseweather,and dust &noise. The data was collected for eachof the alternative modes through questionnaire by face to face interview or by using Google form. There are different methods that can be applied for the developing a mode choice model,multinomial logitmodel is the easiest method with simple mathematical calculations; this method was also used by many authors for analysis and for checking the validation the likelihood ration test .the application of mode choice model is significant to mode user to have best choice, and also such models can assist in the alleviation of traffic congestion and air pollution in the city.

scholarly journals Mode Choice Modeling to Shift Car Travelers towards Park and Ride Service in the City Centre of Karachi

2021 ◽  
Vol 13 (10) ◽  
pp. 5638
Author(s):  
Irfan Ahmed Memon ◽  
Saima Kalwar ◽  
Noman Sahito ◽  
Mir Aftab Hussain Talpur ◽  
Imtiaz Ahmed Chandio ◽  
...  
Keyword(s):  
Public Transportation ◽  
Travel Behavior ◽  
Traffic Congestion ◽  
Travel Demand ◽  
Mode Choice ◽  
Central Business District ◽  
Choice Models ◽  
City Centre ◽  
Travel Demand Management ◽  
Park And Ride

Currently, congestion in Karachi’s central business district (CBD) is the result of people driving their cars to work. Consequently, a park and ride (P&R) service has proved successful in decreasing traffic congestion and the difficulty of finding parking spaces from urban centers. The travelers cannot be convinced to shift towards the P&R service without an understanding of their travel behavior. Therefore, a travel behavior survey needs to be conducted to reduce the imbalance between public and private transport. Hence, mode choice models were developed to determine the factors that influence single-occupant vehicle (SOV) travelers’ decision to adopt the P&R service. Data were collected by an adapted self-administered questionnaire. Mode choice models were developed through logistic regression modeling by using the Statistical Package for the Social Sciences version 22. The findings concluded that more than 70%, specifically motorbike users, to avoid mental stress, and to protect the environment are willing to adopt the P&R service. Moreover, to validate the mode choice models, logit model training and a testing approach were used. In conclusion, by overcoming these influencing factors and balancing push and pull measures of travel demand management (TDM), SOV users can be encouraged to shift towards P&R services. Thus, research outcomes can support policymakers in implementing sustainable modes of public transportation.

scholarly journals Understanding Spatial Variability of NO2 in Urban Areas Using Spatial Modelling and Data Fusion Approaches

Atmosphere ◽  
2021 ◽  
Vol 12 (2) ◽  
pp. 179
Author(s):  
Said Munir ◽  
Martin Mayfield ◽  
Daniel Coca
Keyword(s):  
Data Fusion ◽  
Spatial Variability ◽  
Urban Areas ◽  
Road Traffic ◽  
Dispersion Model ◽  
Low Cost ◽  
Spatial Modelling ◽  
City Centre ◽  
Small Scale ◽  
The City

Small-scale spatial variability in NO2 concentrations is analysed with the help of pollution maps. Maps of NO2 estimated by the Airviro dispersion model and land use regression (LUR) model are fused with measured NO2 concentrations from low-cost sensors (LCS), reference sensors and diffusion tubes. In this study, geostatistical universal kriging was employed for fusing (integrating) model estimations with measured NO2 concentrations. The results showed that the data fusion approach was capable of estimating realistic NO2 concentration maps that inherited spatial patterns of the pollutant from the model estimations and adjusted the modelled values using the measured concentrations. Maps produced by the fusion of NO2-LCS with NO2-LUR produced better results, with r-value 0.96 and RMSE 9.09. Data fusion adds value to both measured and estimated concentrations: the measured data are improved by predicting spatiotemporal gaps, whereas the modelled data are improved by constraining them with observed data. Hotspots of NO2 were shown in the city centre, eastern parts of the city towards the motorway (M1) and on some major roads. Air quality standards were exceeded at several locations in Sheffield, where annual mean NO2 levels were higher than 40 µg/m3. Road traffic was considered to be the dominant emission source of NO2 in Sheffield.

Bike your City: Planning and Designing Cycling Infrastructure in the Urban Environment

2021 ◽  
Author(s):  
◽  
Jack J. Jiang
Keyword(s):  
Urban Environment ◽  
Traffic Congestion ◽  
City Planning ◽  
Environment Design ◽  
Mode Of Transport ◽  
Design Case Study ◽  
Architecture And Design ◽  
Graphical Design ◽  
The City

<p>Cycling is a memory of the past for most of us, the lack of support from the authorities on the cycling infrastructure made it difficult to attract people to cycle in the city. Urban sprawl, traffic congestion, car dependency, environmental pollution and public health concerns have pressured cities around the world to consider reintegrating cycling into the urban environment.  Design as a research method was utilised to investigate the effectiveness of design methodology and workflow for cycling infrastructure from an architecture and design perspective. Using Wellington City as a design case study, this research aimed to improve the legibility, usability and the image of cycling as a mode of transport in the city. To achieve this, a customisable graphical design framework and branding strategies were developed to structure and organise the design components within cycling infrastructure. The findings from the iterative design processes were visualised through the appropriate architectural and presentation conventions.  This research provided an unique architectural perspectives on the issues of cycling infrastructure; the results would support the transportation advisers and urban planners to further the development and integration of cycling, as a viable mode of transport, within the city.</p>

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%.

scholarly journals Exploring the Influence of Attitudes to Walking and Cycling on Commute Mode Choice Using a Hybrid Choice Model

2017 ◽  
Vol 2017 ◽  
pp. 1-8 ◽  
Author(s):  
Chuan Ding ◽  
Yu Chen ◽  
Jinxiao Duan ◽  
Yingrong Lu ◽  
Jianxun Cui
Keyword(s):  
Travel Behavior ◽  
Traffic Congestion ◽  
Structural Equation ◽  
Choice Model ◽  
Mode Choice ◽  
Influential Factors ◽  
Travel Mode ◽  
Travel Mode Choice ◽  
The Impact ◽  
Hybrid Choice Model

Transport-related problems, such as automobile dependence, traffic congestion, and greenhouse emissions, lead to a great burden on the environment. In developing countries like China, in order to improve the air quality, promoting sustainable travel modes to reduce the automobile usage is gradually recognized as an emerging national concern. Though there are many studies related to the physically active modes (e.g., walking and cycling), the research on the influence of attitudes to active modes on travel behavior is limited, especially in China. To fill up this gap, this paper focuses on examining the impact of attitudes to walking and cycling on commute mode choice. Using the survey data collected in China cities, an integrated discrete choice model and the structural equation model are proposed. By applying the hybrid choice model, not only the role of the latent attitude played in travel mode choice, but also the indirect effects of social factors on travel mode choice are obtained. The comparison indicates that the hybrid choice model outperforms the traditional model. This study is expected to provide a better understanding for urban planners on the influential factors of green travel modes.

A Review on the Factors Influencing the Park-and-Ride Traffic Management Method

2014 ◽  
Vol 567 ◽  
pp. 663-668 ◽  
Author(s):  
Irfan Ahmed Memon ◽  
Napiah Madzlan ◽  
Mir Aftab Hussain Talpur ◽  
Muhammad Rehan Hakro ◽  
Imtiaz Ahmed Chandio
Keyword(s):  
Traffic Congestion ◽  
Urban Areas ◽  
Traffic Management ◽  
Demand Management ◽  
Service Research ◽  
Policy Makers ◽  
Park And Ride ◽  
Support Policy ◽  
Management Method ◽  
The City

Park-and-ride is a traffic management method of traffic congestion problem in urban areas. As an extent of total demand management, park-and-ride service (P&R service) has broadly implemented in many countries. P&R service has proven to be progressive in alleviating traffic congestion despite of complication in finding parking spaces in the city centers. The objective of this research is to discuss a model to shift car travelers’ to park-and-ride service (P&R service) and to investigate the factors which influence car travelers’ behavior. This study can support policy makers’ with useful information for future planning and development of park-and-ride service. Research outcomes will support policy-making and provide base for future study on modal choice behavior model for park-and-ride service.

scholarly journals FUZZY LOGIC APPROACH IN MODE CHOICE MODELLING FOR EDUCATION TRIPS: A CASE STUDY OF INDIAN METROPOLITAN CITY

Transport ◽  
2015 ◽  
Vol 30 (3) ◽  
pp. 286-293 ◽  
Author(s):  
Ashu Shivkumar Kedia ◽  
Krishna Bhuneshwar Saw ◽  
Bhimaji Krishnaji Katti
Keyword(s):  
Fuzzy Logic ◽  
Choice Model ◽  
Mode Choice ◽  
Vital Role ◽  
Sustainable Transportation ◽  
Indian Society ◽  
Choice Modelling ◽  
Choice Behaviour ◽  
Public Transport System ◽  
Fuzzy Logic Approach

Urban population in India has increased significantly from 62 million in 1951 to 378 million in 2011 in six decades. It is estimated to reach 540 million by the year 2021. This reflects on likely pressure on urban transportation system. The situation necessarily calls plans for balanced personal and public transport system. Mandatory trips bear more importance in this regard owing to their higher share in urban trips. Mode share and their choice behaviour in estimation of such trips play vital role in analysing and boosting sustainable transportation. Logit modelling approach is the conventional method generally adopted for analysing mode choice behaviour, which is based on the principle of random utility maximization derived from econometric theory. However, such models cannot address uncertainity prevailing in the choice decisions. On the contrary, fuzzy logic bypasses the binary crisp derivations of the inputs and accepts multivalued inputs in linguistic expressions, which make possible to resemble the human behaviour closely. Therefore, the attempt here is to develop fuzzy logic based mode choice model for education trips, which constitutes a good share in mandatory trips by covering various income groups of Indian society.

scholarly journals Incorporating MNL Model into Random Forest for Travel Mode Detection

2021 ◽  
Vol 40 (3) ◽  
pp. 496-501
Author(s):  
Muhammad Awais Shafique ◽  
Eiji Hato
Keyword(s):  
Decision Making ◽  
Random Forest ◽  
Learning Algorithm ◽  
Choice Model ◽  
Mode Choice ◽  
Decision Making Process ◽  
Accelerometer Data ◽  
Choice Modelling ◽  
Travel Mode ◽  
Mode Choice Model

Mode choice models have been used widely to forecast the relative probabilities of using available travel modes. These depend on mode-related and traveler-related characteristics. On the other hand, smartphones are increasingly being used to collect sensors’ data relating to trips made after selection of a suitable mode. Such sensors’ data may be correlated with decision-making process of travelers regarding travel mode selection. Discrete Choice Modelling is used to simulate this decision-making process by computing utilities of various travel alternatives, and then calculating their respective probabilities of being selected. In this paper, multinomial logit (MNL) mode choice model is utilized to enhance the prediction capacity of supervised learning algorithm i.e. Weighted Random Forest. To make the procedure less energy-intensive, GPS data was used only to locate the origin and destination of any trip, to be incorporated in mode choice model. Afterwards only accelerometer data was utilized in feature selection for the learning algorithm. One tenth of the classified data was used to train the algorithm whereas rest was used to test it. Results suggested that with incorporation of MNL, the overall prediction accuracy of learning algorithm was increased from 93.75% to 99.08%.

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