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Roads play a pivotal role in the overall economic growth of any country. Developed countries allocated sufficient budget to make new roads and to maintain the existing roads. They also have a proper pavement management system (PMS) in practice to manage roads, whereas developing countries suffer from budgetary issues to make new roads and maintain the existing road network. Therefore, this paper explores the awareness of PMS via direct and indirect methods in Pakistan with a proposed framework of the low-cost model and pavement maintenance indicators for developing countries. This paper also performs a scientometric assessment of PMS. A detailed literature review has been carried out for this study, followed by a quantitative study from experienced professionals. The scientometric data is collected from the Scopus database from 1975 to 2020, whereas the data for PMS awareness assessment has been collected using questionnaires from different experts working directly and indirectly in the road management sector. The data has been analyzed using the arithmetic mean because of the nature of the questions and scope of the study. The direct method results show that experts are aware of PMS for a new road, but they have no PMS to rehabilitate roads. The indirect method results show that the authorities are applying various components of PMS, but there is no proper PMS in practice. This paper helps decision-makers to make better decisions and policies for improved road maintenance and rehabilitation. The proposed framework in the study can significantly assist the UN-SDG 9 (Facilitate Sustainable Infrastructure in Developing Countries) and 11 (Affordable and Sustainable Transport System).

The Bike-sharing systems are popular in most developed countries worldwide, including France, London, Germany, China, Belgium, Mexico, and Brazil. The system benefits the community because users do not have to purchase their bikes. There are many suppliers providing bicycle rental systems for community use in Malaysia, including Obike and Mobike. However, the implementation of this system was not successful because users prefer to use motorized transport. This study aims to identify the barriers that prevent users from using the bike-sharing system. Ten factors have been identified as the most dominant factors that prevent users from switching motor transport to bike-sharing systems. This study used random sampling research; 178 respondents have given feedback from 200 distributed forms. The data analysis method used is the Average Index. Based on the result, the highest average index recorded at the value of >4.00 is the weather condition (heat and rain) that has dampened the interest for cycling with an average score of 4.71. That is followed by distance from home to town, which is too far for cycling with an average of 4.57 points. Meanwhile, the third-highest value is that it takes too long to reach the destination with bicycles with an average score of 4.43. This result, then, can imply the number and location of bicycle rental should be increased. Besides that, more trees and shrubs should be planted to improve urban greenery so that the city is more shaded and cooler to attract commuters to cycle.

Driver behavior is a concerning issue in the area of intelligent transportation system (ITS). Driver behavior is a significant key player in a wide range of unpleasant events during the ride, such as accidents or crashes, traffic congestion, harsh braking, and acceleration/deceleration. Influencing factors of driver behavior have been explored in several studies. It is imperative to investigate these factors in order to provide a comprehensive analysis and to categorize them on the basis of a coherent taxonomy. With that, this study conducted a systematic review on prior studies that focused on bus driver behavior, particularly in the ITS. This study also established a taxonomy on the topic of driver behavior in multiple areas of ITS and their classifications. Different databases, namely ScienceDirect, Web of Science, and IEEE Explore, were utilized to obtain relevant articles from 2008 to 2021 (15 April). Several filtering and scanning stages were performed according to the exclusion/inclusion criteria on all 2,803 articles obtained; however, only 87 articles met the criteria. The final set of articles were categorized into a taxonomy. The first part of the taxonomy focuses on five main factors that influence driver behavior: environmental, demographic, habit, vehicle, and on-road routine factors. The second part of the taxonomy discusses the mapping of data collection methods on the basis of four categories: real-time data collection, survey, simulation, and benchmark. Discussion and analysis were provided to highlight the critical literature gaps on bus driver behavior in the ITS, involving the use of real-time data collection, which is imperative for acquiring highly accurate and sophisticated data. This multi-field systematic review has exposed new research opportunities, motivations, challenges, limitations, and recommendations and highlighted the need for the synergistic integration of interdisciplinary works. Overall, this study presented pathways solution in future direction on the basis of three sequenced phases, namely design, labeling and validation, and machine learning. This study can serve as a guide for future researchers, as it addressed the ambiguities in the ITS-driver behavior domain and provided valuable information on these ITS-driver behavior trends.

Private Cars (PC) are becoming the most common way to travel daily. This is one of the effects of poor access to Public Transport (PT). As a result, increase air pollution, traffic congestion, noise, accidents. This study aims to develop a modal shift model for car users to shift to PT and determine the factors that effects the performance of the mode of transportation. A survey of 384 of PT users was conducted in Kajang city, Malaysia. Data were processed by SPSS software. A binary logit model has been used for three different lines (car, train and bus). The explanatory factors that looked at two models include trip distances, a trip rate per day, trip time, gender, age, and occupation, which are important variables. Mode Choice Model (Car vs Bus) show the travel time and distance travelled are significant factors to increase the use of public buses and reduce dependence on the car. While in Model (Car vs Train), the travel time is an important variable that effects of the switching decision between car and train. Younger people are more likely to switch in both models. Improve some factors like reliability in public transport services and change some fundamental policy could be the most effective measures for shifting from PC to PT.

Pavement maintenance has been a key concern for any pavement management authority. Countries are facing a severe challenge of funds in maintenance schemes, especially in developing countries. The existing pavement maintenance methods are goal-specific and lack integration of various indicators that are significant for any low-cost PMS. Thus, this paper aims to investigate the possible defects which may occur in flexible pavements. It also investigates the relationship between the different defects. A detailed literature review has been done for this research to identify all possible defects in flexible pavements and key features considered in any PMS. A questionnaire was designed to seek the expert’s opinion on the defects and their possible relationships to be considered for a low-cost PMS. The data was collected from 283 experts currently working in pavement management authorities and pavement maintenance schemes. Aggregated Mean Score, Box plotting and Chi-Square test are used to analyze the data. It is concluded that Bumps/Sags (3.17) are one of the major defects reported by the experts in pavements in Pakistan, followed by the fatigue cracks (3.07). Rutting (2.98) and rut depth (2.98) stand at third key defects reported in this study. Depression (2.96), potholes (2.76), longitudinal crack (2.69), edge crack (2.55), roughness (2.51) and deflection (2.50) are also regularly arising defects in pavement maintenance activities in Pakistan. The results are in the acceptance range of the three mentioned validation methods. The correlation test results show that most of the defects in structural, functional, safety and serviceability indicators reject the null hypothesis thus, there is a close relationship between these defects observed in the flexible pavements. In last stage, a PMS model is suggested to assist the road management authorities of developing countries to make low cost decision for effective pavement rehabilitation.

This paper was using Getis–Ord (Gi*) spatial statistics to identify hot spots on the controlled-access expressway. The application of the method was demonstrated through a case study by using the reported road accident cases in North-South Expressway (NSE). The method successfully identified the clusters of accidents from more than 47,359 accident records from 2016 to 2019. 25 hotspot locations were identified at this study area represents 26.81% of reported cases with the lengthiest hotspot is 31.2 km and the shortest is 300m. The largest and the second largest means of z score of hotspots were identified near to well-known high populated and busy city Kuala Lumpur with scores of 6.17243 and 6.074437. The largest z score means the more intense clustering at the location will be and statistically significance to reject the null hypothesis. This study also found that the accident hotspots tend to occur at the location where the continuous traffic flow is disturbed. There are 16 hotspot locations were identified which is equivalent to 64% from the total hotspots that occur at the location where were the existing of interchange, exit ramp, slip road, rest area or lay by spotted at the area. The interference of traffic flows including diverge and merge activities will affect the speed consistency and which if often, leads to sideswipe and rear accidents. By using GIS, the location of hotspots can be analyzed meticulously at the location. It can help in determining effective countermeasures based on the analysis of the causal factors

e-Hailing system is one of the mediums that are functioning to minimize the person on using the private transportation. Due to modern technology era, internet is used to ease the user in communication. With the internet platform assist, the e-Hailing system has well in management with the users can request the destination, travel time and also the cost for this service. The objective of this study was to identify the contributing factors effect to use e-Hailing system and also to analyze modal shift between public transport and e-Hailing system. Therefore, a study towards user’s acceptance on using e-Hailing system as alternative transport based on the modal shift method with Binary Logistic regression analysis was necessary to identify factor and effect that influence modal shift occur from public transport to the alternative transport which is e-Hailing system. Johor Bahru area was the selected area as the location of the study due popular with the e-Hailing system. This study also shows the type of e-Hailing system that is used and will know the how this system really works with the safety, cost and also travel time. The binary logistic regression analysis shows that all the components were positively significant. This alternative transport is actually sending the user to the destinations that are selected by the user in the application. Therefore, the e-Hailing system is an alternative transport that must be used for people nowadays.

Governments face numerous challenges in sustaining road network conditions. This is attributed to road authorities’ shortages of financial and physical infrastructure. As a result, low-cost automated solutions are being pursued to solve these problems and provide people with appropriate road conditions. Several attempts have been made to improve these technologies and incorporate them into a Pavement Management System (PMS) but limited attempts are made for developing countries. This study aimed to design a low-cost pavement management system for flexible pavement maintenance. A detailed literature review has been carried out, followed by a qualitative assessment of the various indicators considered for PMS. The priority ranks of the PMS indicators were made using an Analytical Network Process (ANP) and each rank was validated by a sensitivity assessment test using the Super Decision-Making tool. This paper also provides the conceptual framework for the low-cost PMS, followed by a fishbone diagram of the indicators and sub-indicators. It is concluded that an emergency maintenance plan with an ANP weight of (0.41) is one of the most significant plans for a low-cost PMS, followed by a routine with an ANP weight of (0.39) and periodic maintenance plans with a (0.20) ANP weight. Moreover, the functional indicators with an ANP weight of (0.32) are the most significant indicators for a low-cost PMS, followed by structural (0.26), safety (0.24), and serviceability(0.18) indicators. This model will assist the road planners in making better decisions on pavement maintenance management plans. The model will suggest the pavement sections on a higher priority to be added in the maintenance plans, especially where the maintenance budget is limited.

The growth of Indonesia’s automotive sector has increased the number of end-of-life vehicles (ELVs), making ELV waste management a major issue. Most countries, such as Japan, China, and Europe, manage ELV waste well, but developing countries still do not. In developing countries, little is known about ELV social admissions. This study analyzes ELV management social acceptance in developing countries. Three hundred nine respondents from Jakarta, Bogor, Depok, Tangerang, and Bekasi (the district in Indonesia) were surveyed in a cross-sectional. A set of questions was designed to determine social acceptance (attitude, knowledge, social influence, institutional trust, health issues, and acceptance). After passing validity and reliability tests, the hypothesized research model was estimated using structural equitation. According to this study, social influence, attitude, knowledge, institutional trust, and health issues influenced public acceptance. The health issues variable was also a good moderator (Adj. R2 = 0.173, p < 0.001, average path coefficient = 0.299). The analysis of social acceptance models related to ELV management found that social influence, attitude, knowledge, and institutional trust play a role in one’s desire to accept a new rule, and health issues can strengthen a person in the admission process.

This paper presents the passengers’ perspective towards express bus safety issues based on the driver’s behavioural characteristics, providing an important aspect in reducing the accidents in Malaysia. A pilot study with a respondent of 40 people, aged between 16 to 41 years old were conducted in Universiti Kebangsaan Malaysia. The developed questionnaires based on the five-point Likert Scale were implemented to assess the safety perception on express buses, and it has a higher reliability of Cronbach’s Alpha score at 0.91. The findings show that more than 45 % of the respondents agreed that dangerous behaviour of express bus drivers were mainly due to the use of mobile during driving (63.33%), tailgating (57.58%) and driving above the given speed limit (48.59%). The reason of this behaviour is insufficient time to stick to running schedules and the shift pattern rotations. In terms of safety precautions, about 77% passengers preferred safety briefing using audio due to its ease in understanding the meaningful instruction. In addition, 97% passengers agreed on the needs of a second driver to ensure a safe journey to their destination. Hence, a proposed mitigated solution such as drivers monitoring is needed by the respective agencies to reduce this careless behaviour that may influence the dangerous driving behaviour.

The main cause of problematic soil failure under a certain load is due to low bearing capacity and excessive settlement. With a growing interest in employing shallow foundation to support heavy structures, it is important to study the soil improvement techniques. The technique of using geosynthetic reinforcement is commonly applied over the last few decades. This paper aims to determine the effect of using geogrid Tensar BX1500 on the bearing capacity and settlement of strip footing for different types of soils, namely Al-Hamedat, Ba’shiqah, and Al-Rashidia in Mosul, Iraq. The analysis of reinforced and unreinforced soil foundations was conducted numerically and analytically. A series of conditions were tested by varying the number (N) and the width (b) of the geogrid layers. The results showed that the geogrid could improve the footing’s bearing capacity and reduce settlement. The soil of the Al-Rashidia site was sandy and indicated better improvement than the other two sites’ soils (clayey soils). The optimum geogrid width (b) was five times the footing width (B), while no optimum geogrid number (N) was obtained. Finally, the numerical results of the ultimate bearing capacity were compared with the analytical results, and the comparison showed good agreement between both the analyses and the optimum range published in the literature. The significant findings reveal that the geogrid reinforcement may induce improvement to the soil foundation, however, not directly subject to the width and number of the geogrid alone. The varying soil properties and footing size also contribute to both BCR and SRR values supported by the improvement factor calculations. Hence, the output complemented the benefit of applying reinforced soil foundations effectively.

The study was carried out to produce an advisory system based on the blackspot accidents mapping at the North-South Expressway (NSE). Blackspots are location where the road traffic crashes have historically concentrated by type of accident in which the accident caused fatalities, severe injuries, minor injuries and damage. This research aims to identify accident blackspot and plotting accident data into a digital map of the study area to produce advisory systems for highway users. The software used in this study namely Google Earth Pro, ArcMap and ArcGIS online. Results showed that blackspot location are known in the form of mapping where it can be performed online. In addition, the path with high number of accident points weightage location were identified and prioritized. By applying Google Earth Pro and ArcGIS software, the advisory system was created, and these blackspot locations can also be easily accessed by highway users. Therefore, the advisory system helps in facilitate the users for trip planning base on the accident status locations as a precautionary measure and initiative to reduce the rate of road accident in expressway.

Carbon footprint is a global concern discussed throughout the globe. The daily activities on university campuses cause emission of greenhouse gases that contribute to the increasing amount of carbon dioxide (CO2) in the atmosphere. This research seeks to determine the CO2 emissions by members of the campus community of Universiti Kebangsaan Malaysia (UKM), Bangi Campus. This study will also analyse the factors influencing CO2 emission from the vehicles used on the campus. The findings of this study will serve as a basis to propose methods for reducing carbon footprint, especially from the transportation used on the campus. The study is carried out on the UKM campus to gather the data on the travel activity on the campus, where the members of the campus community serve as the study population. The DEFRA Model is used to calculate the CO2 emission and the multivariable linear regression model is used to identify the factors influencing CO2 emission. In the car category, petrol cars with 2.0L engine have the highest mean CO2 emission of 1181.0932 kg CO2/year/capita. In the motorcycle category, petrol motorcycles with engine capacity larger than 500cc recorded the highest emission of 999.1072 kg CO2/year/capita. The CO2 emissions by both categories are below the national mean carbon dioxide emission value of 7900 kg CO2/year/capita recorded by the 2019 National Transport Policy and the mean carbon dioxide emissions of 5400 kg CO2/year/capita in high-income countries. In this study, the critical factors influencing the daily and annual CO2 emissions are the mode of transportation, type of fuel, and travel distance

Significant risk factors that influence the occurrence of heavy vehicle accidents have been explored in numerous studies in order to lower injury severity in traffic accidents. It is imperative to explore road sections with a high risk of heavy vehicle accident occurrence by considering the significant consequences of such accidents for road users, despite the low number of heavy vehicles in traffic flow. To address this, this study proposes a method to predict clustering hotspots for heavy vehicle accidents on the basis of three different criteria, namely, heavy vehicle accident cases, the number of heavy vehicles involved, and accident severity index values. Moran’s I spatial autocorrelation was employed to identify the clustering for each criterion, and the Getis–Ord Gi* statistic was applied to estimate the likelihood of risk along the network. This study considers the features of hotspot points at significance levels from 0.10 to 0.01 with a 1355 m buffer radius to create segments for each criterion. The three criteria for hotspots were considered within the overlapped buffer zone. A total of 22 heavy vehicle risk segments (HVRSs) were identified and then ranked by crash rate. Overall, this study demonstrates the application of different criteria to identify accident hotspots involving a specific vehicle type, which could help in prioritizing segments with a high risk of heavy vehicle accidents, as well as providing information for HVRSs for the purpose of developing appropriate countermeasures for the identified accident hotspots.

Light rail transit (LRT) is a sustainable transportation mode that ensures sustainable environmental, economic, and social development. Generally, the rate of public transportation usage in many parts of the world remains low compared to private vehicles. There is a need to understand passengers&rsquo, perception of public transportation service quality to enhance passenger satisfaction and increase ridership. Thus, this study used the Kuala Lumpur LRT service as a case study to investigate the effect of a passenger&rsquo, s gender and age on their perception of the LRT service quality and their overall satisfaction. This survey involved 417 respondents. The outcome of factor analysis indicated that eight factors&mdash, i.e., signage, comfort, speediness, safety, ticketing service, facilities, staff service, and provision of information&mdash, influenced passenger satisfaction. The results of the Mann&ndash, Whitney U test and Kruskal&ndash, Wallis test indicated that the factors influencing passenger satisfaction significantly varied across a passenger&rsquo, s gender and age. A more in-depth and comprehensive analysis using the ordered logit model and segmentation approach proved that provision of information, comfort, staff service, and facilities were critical determiners of passenger satisfaction in most segments. Safety factors and ticketing services had no impact on overall passenger satisfaction. The findings of this research could help LRT service providers, researchers, and policymakers formulate effective strategies for enhancing passenger satisfaction and increase the ridership for LRT services.

This paper presents the bus agencies perspective towards the express bus safety based on the bus maintenance and safety factors to reduce the road accidents in Malaysia. Express buses were scored the highest percentage in bus accident cases primarily owning to the driver negligence. This survey was conducted among 34 respondents working with the bus agencies. The respondents composed of the employees in administration and management positions of the companies. The questionnaires were developed based on the five-point Likert Scale to assess the safety perception of express buses. The questionnaires have a high reliability of Alpha Cronbach’s score at 0.9362 in safety aspects. In the aspect of management commitment, the Alpha Cronbach’s score is 0.6479 and 0.6061 was recorded in the aspect of suggestion improvement. In term of improvement suggestion, 94.12% of respondents were satisfied with the decision of bus agencies to improve the safety and health aspects of the company drivers and employees. Furthermore, 91.18% agreed with the bus agencies to use the Information and Communication Technology (ICT) systems in order to monitor and manage the safety of buses during service period. Hence, effective safety protocols such as drivers monitoring system must be implemented by responsible agencies to mitigate the careless behaviours of drivers and improve the safety of buses.

This paper presents an analysis of express bus passengers’ perspective towards the safety and causes of express bus accidents. Express bus is an important mode of transport as it is cheap and has high connectivity between cities. However, the safety of express bus is a major concern in Malaysia. There have been many high-profile express bus accidents that have caused deaths to innocent victims. Therefore, it is important to study the safety of express bus and increase its safety. A survey with 880 respondents was conducted in Malaysia to study passengers’ perspective on the safety of express buses. The questionnaire is divided into seven sections: respondent background and demography, service, comfort, safety, information technology and safety education. The results are presented in a spider web diagram and shows the 12 most important factors that relate to express bus safety. In conclusion, this study helps to understand the perspective of express bus passengers on the safety of express bus and determine the important factors related to express bus safety and reduce the number of express bus accidents in Malaysia.

This paper presents a review of carbon dioxide (CO2) emissions from transportation in an attempt to establish a quick and suboptimal update of the methods used to calculate and analyze CO2 emissions from transportation. Transportation is the largest contributor to air pollution through the release of high amounts of CO2 gas into the atmosphere. The methods for calculating and analyzing the carbon footprint of transportation; which is of critical importance in the management of greenhouse gases that contribute to global warming; are still being developed. However; there are some differences in the definitions and methods used to calculate the carbon footprint of transportation in previous studies. This review focuses on the similarities of the methods used to measure CO2 emissions as well as the analyses used to evaluate the emissions. This paper will also highlight the advantages and limitations of each research work. By doing this; the present study contributes to the selection of appropriate methods for calculating CO2 emissions from transportation and draws attention to environmental issues. It is hoped that the implementation of the most appropriate framework will help to reduce CO2 emissions from transportation

Pedestrian is known as vulnerable road user, therefore proper crossing facility is needed to enhance the pedestrians’ safety. This study is to determine the effect of using 3D visual crossing facility inside the campus and its functionality. This 3D visual effect crossing facility is installed at selected location. The location selection is based on the absence of crossing facility, pedestrian volume and spot speed study. Pedestrian volume was collected by manually while spot speed study was collected using speed gun Apps. The 3D visual effect road crossing then is designed by using the perspective view from the driver height sight. After the installation of road crossing, the hypothesis is tested using chi-square analysis to determine the association between the effect on 85th percentile speed, pedestrians’ behaviour and the 3D visual effect crossing facility. The results of chi-square analysis shows there is a significant (p

Ground settlement is the main factor in slope stability. This paper reviews the application of artificial intelligence (AI) in predicting the slope ground settlement. The objective of this paper is to discuss the application of AI in three categories i.e. i) ANN, ii) ANFIS and iii) hybrid model which includes research reports over the last ten years. Additionally, future research proposals are presented. ANN is a predictive tool that is often used instead of ANFIS because of its non-linear behavior.

This study was conducted to develop two types of artificial neural network (ANN) model to predict the rheological properties of bitumen-filler mastic in terms of the complex modulus and phase angle. Two types of ANN models were developed namely; (i) a multilayer feed-forward neural network model and (ii) a radial basis function network model. This study was also conducted to evaluate the accuracy of both types of models in predicting the rheological properties of bitumen-filler mastics by means of statistical parameters such as the coefficient of determination (R2), mean absolute error (MAE), mean squared error (MSE) and root mean squared error (RMSE) for every developed model. A set of dynamic shear rheometer (DSR) test data was used on a range of the bitumen-filler mastics with three filler types (limestone, cement and grit stone) and two filler concentrations (35 and 65% by mass). Based on the analysis performed, it was found that both models were able to predict the complex modulus and phase angle of bitumen-filler mastics with the average R2 value exceeding 0.98. A comparison between the two types of models showed that the radial basis function network model has a higher accuracy than multilayer feed-forward neural network model with a higher value of R2 and lower value of MAE, MSE and RMSE. It can be concluded that the ANN model can be used as an alternative method to predict the rheological properties of bitumen-filler mastic.

Active transport is vital to ensure urban living in a clean, healthy and quality environment. Today, rapid motorisation in Malaysia has been associated with congestion and accidents. Besides, carbon gas emission is polluted the environment and grossly affect people’s quality of life. This study is aimed to predict the variable that effect shift to active transport for short trips. The study employed a survey method, where a set of questionnaire was distributed to 400 samples involved population of five sub-districts in Kota Bharu, which is within 12 km radius from the city centre. The data indicated that almost 100% of the respondents and their households use motorised for daily activities. In addition, 52% of respondents agreed to switch to active transport and 48% the rest did not agree. Willingness to shift to active transport based on state preference survey is significantly influence by level of education and occupation. A study using logistic regression has shown that the highest level of education and occupation of an increasingly less likely a user is to use active transportation. The findings of this study can help relevant agencies such as transportation planners and urban planners to introduce the use of active transport as a mode of transport in city centre.

Non-motorized is vital for sustainable living. The characteristics of sustainable transport are safe, comfortable and efficient in terms of economic and energy consumption and minimize environmental pollution. Today, transportation systems in most cities are no longer sustainable due to lack of natural materials such as oil reserves, increasing the number of deaths and injuries by motor vehicle accidents and traffic congestion. The carbon emissions into the atmosphere contribute to environmental pollution in terms of quality deficiencies that affects mobility of life in general. This study aimed is to design sustainable transport in terms of non-motor vehicle for a city that promises a better world for future generations. It provides strategies to change the choice of transport modes to road users of motor vehicles to non-motor vehicles through integration of land use and transportation planning. By improving pedestrian path and cycling zone to increase non-motorized travel and reduce motor vehicles travel. The use of non-motorized transportation such as cycling and walking is not only to reduce carbon but also healthy lifestyle and a physical activity.

Konsep pengangkutan tidak bermotor adalah penting bagi menjamin kehidupan dalam persekitaran yang bersih, sihat dan berkualiti tinggi. Hari ini, sistem pengangkutan bandar-bandar di Malaysia mempunyai imej buruk seperti kesesakan, kemalangan, ketiadaan pengangkutan awam sebagai alternatif serta konflik pembebasan gas karbon ke ruang atmosfera menyumbang kepada pencemaran alam dan kepincangan dari aspek kualiti mobiliti kehidupan secara umumnya. Tujuan kajian ini adalah untuk mengukur kesahan dan kebolehpercayaan Instrumen model kenderaan tidak bermotor. Instrumen 4 konstruk yang mengandungi 17 item skala 5 mata telah digunakan dalam kajian ini. Instrumen ini telah ditadbirkan kepada 400 orang responden di bandar Kota Bharu yang dipilih secara rawak berkelompok. Perisian Amos versi 7 digunakan untuk menganalisis data. Nilai Comparative Fit Index (CFI), Tucker Lewis Index (TLI) dan RMSEA digunakan untuk mengekal dan menggugurkan item. Dapatan akhir kajian menggunakan model pengukuran confirmatory factor analisis telah menggugurkan 7 item dan mengekalkan 10 item yang sah dan boleh dipercayai untuk mengukur 4 konstruk. Instrumen ini boleh digunakan untuk membentuk model penggunaan kenderaan tidak bermotor berdasarkan teori tingkah laku terancang (TPB) iaitu berbasikal dan berjalan kaki dalam menjadikannya sebagai mod pengangkutan pilihan di Malaysia.