Mode Choice Modeling for Educational Trips in a Medium-Sized City: Case Study of Abbottabad City, Pakistan

Lodhi, Rida Hameed; Rana, Irfan Ahmad

doi:10.1061/(asce)up.1943-5444.0000755

Cited by 6 publications

(3 citation statements)

References 19 publications

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“…Family factors mainly include family income ( 22 – 25 ), family car ownership rate ( 26 – 29 ), family driver's license ownership rate, parents' convenience of transportation ( 12 , 30 , 31 ), parents' attitude toward students' travel ( 16 , 32 – 34 ), number of brothers and sisters ( 32 , 35 ), parents' education level ( 20 , 29 ) and other family factors. The impact of travel characteristic factors on students' choice of commuting mode is mainly reflected in travel distance ( 36 – 42 ) and travel duration ( 28 , 40 ). Compared with the first three types of factors, the built environment factors started late in the children's school travel and included a wide range of contents, so the impact on the choice of school age children's way of integration is also more complex.…”

Section: Literature Reviewmentioning

confidence: 99%

The built environment impacts on route choice from home to school for rural students: A stated preference experiment

Han

Wang

et al. 2022

Front. Public Health

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IntroductionRural roads and built environment in China have been developed enormously, but it is not clear whether these roads fulfill the needs of school children as they need to travel long to school every day.ObjectiveIt is crucial to understand the influencing factors of their travel mode choices to better design future country roads and built environment, aiming to promote physical activities of school children in a safe built environment.MethodThis study thus attempts to explore the impacts of rural built environment attributes on children's school travel mode preferences. Eight rural built environment attributes are considered: distance from home to school; the number of intersections passed on the way to school; whether there are sidewalks/bicycle lanes; the traffic speed of school access routes; whether there are separation facilities between motor vehicles and non-motor vehicles; whether there are traffic lights and zebra crossings; availability of greenery such as lawns, flower ponds and street trees and whether there are shops on the way to school and at the school gate. Six hundred and thirty eight valid questionnaires were obtained through face-to-face interviews with school-age children in villages. A multinomial logit model was estimated to unravel the preferences and choices of rural school-age children in different models of school travel using the stated choice data.ResultsAll the eight attributes have significant impacts on rural children's school travel choices on foot, bicycle, electric bicycle or motorbike. And four rural road design attributes have significant effects on rural children's school travel by private cars. A travel path with pavements or bike lanes, few intersections, low traffic speeds, greenery and shops can facilitate children's school travels on foot or by bike. The conclusions can provide reference for the further upgrading planning, designing and construction of rural roads, as well as enriching the theory and practice of child-friendly villages construction.

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Section: Literature Reviewmentioning

confidence: 99%

The built environment impacts on route choice from home to school for rural students: A stated preference experiment

Han

Wang

et al. 2022

Front. Public Health

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“…Mode choice is an important step in traditional four-step modeling. Discrete choice models (DCMs), such as the binary logit (BL) model [15], MNL model [16], nested logit…”

Section: Introductionmentioning

confidence: 99%

Understanding Travel Mode Choice Behavior: Influencing Factors Analysis and Prediction with Machine Learning Method

Zhang

Liu

et al. 2023

Sustainability

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Building a multimode transportation system could effectively reduce traffic congestion and improve travel quality. In many cities, use of public transport and green travel modes is encouraged in order to reduce the emission of greenhouse gas. With the development of the economy and society, travelers’ behaviors become complex. Analyzing the travel mode choices of urban residents is conducive to constructing an effective multimode transportation system. In this paper, we propose a statistical analysis framework to study travelers’ behavior with a large amount of survey data. Then, a stacking machine learning method considering travelers’ behavior is introduced. The results show that electric bikes play a dominant role in Jinan city and age is an important factor impacting travel mode choice. Travelers’ income could impact travel mode choice and rich people prefer to use private cars. Private cars and electric bikes are two main travel modes for commuting, accounting for 30% and 35%, respectively. Moreover, the proposed stacking method achieved 0.83 accuracy, outperforming the traditional multinomial logit (MNL) mode and nine other machine learning methods.

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“…In contrast, this subject matter has not yet been thoroughly examined in developing countries, particularly Asia. In most regional studies, e.g., in India [20,21], Sri Lanka [22], Thailand [23], Malaysia [24], Pakistan [25], Bangladesh [26], and Indonesia [27], researchers are still attempting to understand the underlying factors that influence school transportation choices in general [20]. As an emerging country in Asia, Iran has begun focusing on active school transportation [28][29][30][31].…”

Section: Introductionmentioning

confidence: 99%

An Active School Transport Instrument to Measure Parental Intentions: The Case of Indonesia

2022

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An active school transport (AST) instrument to measure parental intentions in a developing country context with 11 latent constructs and 108 measuring items has been created as part of an integrated framework, including psychological and social cognitive constructs, perceived environmental constructs, and habit constructs. The purpose of the current study is to develop and carry out the initial validation of these construct items for measuring parental intentions to promote AST in the context of a developing country. Three experts assigned a content validity index (CVI) to the measurement items and evaluated them based on the item-CVI (I-CVI) and the scale-level-CVI (S-CVI). A pilot study was conducted to test the validity and reliability of the construct items in Palembang, Indonesia, with 34 parents of school-aged children returning the instruments to be analyzed using SPSS Version 23. It was discovered that 93 items were legitimate, since their R values were greater than 0.3, and it was determined that 11 constructs were reliable because the measured items revealed a Cronbach’s alpha coefficient range of 0.8–0.9 (very good) to >0.9. (excellent). This instrument met the requirements for good validity and reliability and thus, can contribute as a novel instrument to measure parental intentions towards AST, especially in developing countries in Asia, particularly Indonesia.

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Mode Choice Modeling for Educational Trips in a Medium-Sized City: Case Study of Abbottabad City, Pakistan

Cited by 6 publications

References 19 publications

The built environment impacts on route choice from home to school for rural students: A stated preference experiment

The built environment impacts on route choice from home to school for rural students: A stated preference experiment

Understanding Travel Mode Choice Behavior: Influencing Factors Analysis and Prediction with Machine Learning Method

An Active School Transport Instrument to Measure Parental Intentions: The Case of Indonesia

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