Traffic accidents caused the most accidental deaths at work in Malaysia. The SOCSO (Social Security Organization) reported that the number of deaths due to commuting accidents was 760, nearly two times more than deaths caused by accidents that happened at the workplace (471 deaths). The aim of this study is to investigate the relationship of socio-demographic background and the risk exposure of the drivers during their work commuting trips. The study was based on compensation claims to SOCSO where data were extracted from "Form 21" provided by SOCSO. A total of 377 respondents were selected through systematic random sampling method from a list of SOCSO claimants. It was found that majority of the traffic accidents (83%) involved males and most of them (92.2%) were on motorcycles. Male drivers have an average driving experience of 10.7 years and 8.6 years for females. The estimation of the travelled distance for the sample from home to the workplace is 0.65~131 km. Mean accident occurrence time was 23 min whilst mean distance was 11.6 km. The multiple regression analysis showed that the accident distance was affected by the age of driver, actual travel distance, travel objective and speed.

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The purpose of this study is to critically review literature pertaining to the theoretical concept of perceived risk and its role in autonomous vehicle (AV) studies. A mapping on the placement of perceived risk to explain its position concerning AV acceptance either as a direct predictor or mediator as well as the number of dimensions used (i.e., single or multi-dimensions) in the context of AV, will be derived based on the critical review. Interestingly, a critical gap was discovered in which very little attention had been paid to the use of perceived risk as the multidimensional constructs that included financial risk, time risk, performance risk, psychological risk, social risk, and physical risk. The embedded meaning in the single perceived risk term might be one of the reasons leading to the inconclusive findings on the understanding of public acceptance of AVs. Furthermore, the review revealed that the role of perceived risk could be classified into four clusters using a knowledge map. This study enriches the literature by providing a summary framework map for various dimensions of perceived risk used in studying the public acceptance of AVs. Insights of the framework can help researchers to formulate better future research directions in evaluating the impacts of constructs in adopting AVs.

Change in activity patterns and travel behaviour were seen worldwide as a response to the COVID-19 pandemic. This is mainly due to the restrictive measures imposed by the government and perception of own safety or commitment in reducing the spread of the disease. However, with or without the restrictive measures, people still have various needs to travel. Thus, this study was initiated to understand the changes in travel behaviour due to the COVID-19 pandemic. An online questionnaire survey, including questions related to purpose of travel, transport mode choice, distance and frequency of trip was conducted. Findings from this study revealed that there is a significant change in activity pattern and travel behaviour, before and during the COVID-19 pandemic. Based on the 460 responses received, it is known that mode shifts, from public transportation to private vehicles, occurred mainly due to pandemic related concerns. This study reveals that people perceived public transportation as a potential risk for exposure of the COVID-19 virus, while private vehicles, bicycles and walking are viewed as the safest mode of transport during the pandemic. Gender, age group, vehicle ownership, marital status and purpose of travelling had significant impact on the mode choice during the pandemic. Based on these findings, it is hoped that rail and bus transport service providers will be able to plan measures and further encourage the usage of the rail and bus transport services post-pandemic.

In Malaysia, travel activities become more intense during the festive seasons, whereby traffic volume on the roads on average increases about 30%. Consequently, this inevitably increases road traffic fatalities. An integrated enforcement program called the OPS Bersepadu has been carried out since 2011 to ensure high road safety performance. This study was carried out to develop a statistical model for predicting the seasonality of traffic fatalities. A Seasonal Autoregressive Integrated Moving Average (SARIMA) model was used to fit road fatalities data between 1980 and 2000 and forecast traffic fatalities from 2001 to 2019. The results showed that the SARIMA (1, 1, 2) (1, 1, 2)12 model fitted the data fairly well and suggest that the SARIMA model is a possible tool that provides an overview of the seasonal patterns of traffic fatalities in Malaysia. The forecasted traffic fatalities based on the SARIMA model were then compared with the actual traffic fatalities during the festive months to explore the effectiveness of the OPS Bersepadu programme to help enforcement authorities allocate optimal resources that could increase the efficiency of enforcement activities to reduce road traffic fatalities.