| Author: | Chen, Tiantian |
| Title: | Safety of professional drivers in Hong Kong |
| Advisors: | Sze, Nang-ngai (CSE) Chen, Anthony (CSE) |
| Degree: | Ph.D. |
| Year: | 2021 |
| Subject: | Automobile drivers -- China -- Hong Kong Automobile drivers -- Health and hygiene Traffic safety Hong Kong Polytechnic University -- Dissertations |
| Department: | Department of Civil and Environmental Engineering |
| Pages: | xii, 183 pages : color illustrations |
| Language: | English |
| Abstract: | Safety of professional drivers is of great concern around the world, especially in the public transit-oriented cities like Hong Kong. The higher rates of traffic violation rates, fatigue driving, aggressive driving, as well as the increasing proportion of older drivers are the main contributory factors to the crashes involving commercial vehicles. In this study, safety of professional drivers in Hong Kong is assessed from the behavioural, psychological, and empirical perspectives. Therefore, effective traffic control and driver management measures can be implemented to improve the safety of professional drivers. First, effects of driving time, age, traffic condition and road environment on the driving performance of professional drivers are evaluated using the driving simulator approach, with which the difference in the driving performance between professional and non-professional drivers are considered. Results indicate that age-related impairments on driving performance could be reduced by the driving experience and task familiarity of professional drivers. Furthermore, two modified traffic conflict measures were used to investigate the compensatory strategy and strategic adaptation of professional drivers. It is found that, despite the longer brake reaction time of older drivers, the likelihood of more severe traffic conflict of older drivers was lower, especially for professional drivers. Second, attitudes of professional drivers towards the enforcement and penalties against speeding violations are evaluated using a perception survey. A stated preference survey approach is adopted to gauge the trade-off between enforcement strategies, penalty levels and speed choice of the professional drivers. A panel mixed logit regression model is adopted to account for the effects of unobserved heterogeneity. Results indicated that the professional drivers are more sensitive to the increase in driving-offence points as compared to monetary fines. Also, presence of a warning sign is effective in enhancing speed compliance. Several demographic and employment characteristics, driving history and perception variables also influence drivers' choices of speed compliance. Third, safety effects of the composition of commercial vehicles including taxis, public buses, light goods vehicles, and heavy goods vehicles are assessed based on the integrated traffic and crash data. A Bayesian random-parameter Tobit approach is adopted to measure the relationship between explanatory factors and the overall crash rates by injury severity. Results reveal significant increasing effects of the proportions of taxi, buses, light goods vehicles on the overall crash risk. Additionally, a Bayesian multivariate Tobit model is applied to identify possible risk factors to the crash rates across different vehicle types. Results indicate that crash rates of private car and light commercial vehicle would increase with the increase in average lane width and presence of on-street parking, while such finding is not valid for heavy commercial vehicle. Moreover, intersection density has significant increasing effect only for the crash rate of light commercial vehicle. Overall, findings of driving simulator study, stated preference survey and crash risk analysis of professional drivers should be indicative to the driver licensing, training and education, enforcement, and driver management strategies of the authorities and transport operators that can enhance the safety performance of professional drivers in the long run. |
| Rights: | All rights reserved |
| Access: | open access |
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