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Peng Z, Zuo J, Ji H, RengTeng Y, Wang Y. A comparative analysis of risk factors in taxi-related crashes using XGBoost and SHAP. Int J Inj Contr Saf Promot 2024:1-13. [PMID: 38708845 DOI: 10.1080/17457300.2024.2349555] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/17/2023] [Accepted: 04/26/2024] [Indexed: 05/07/2024]
Abstract
Taxis play a crucial role in urban public transportation, but the traffic safety situation of taxi drivers is far from optimistic, especially considering the introduction of ride-hailing services into the taxi industry. This study conducted a comparative analysis of risk factors in crashes between traditional taxi drivers and ride-hailing taxi drivers in China, including their demographic characteristics, working conditions, and risky driving behaviors. The data was collected from 2,039 traditional taxi drivers and 2,182 ride-hailing taxi drivers via self-reported questionnaires. Four XGBoost models were established, taking into account different types of taxi drivers and crash types. All models showed acceptable performance, and SHAP explainer was used to analyze the model results. The results showed that for both taxi drivers, risk factors related to risky driving behaviors are more important in predicting property damage (PD) crashes, while risk factors related to working conditions are more important in predicting person injury (PI) crashes. However, the relative importance of each risk factor varied depending on the type of crashes and the type of taxi drivers involved. Furthermore, the results also validated certain interactions among the risk factors, indicating that the combination of certain factors generated a greater impact on crashes compared to individual factors alone. These findings can provide valuable insights for formulating appropriate measures to enhance road safety for taxi driver.
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Affiliation(s)
- Zhipeng Peng
- School of Economics and Management, Xi'an Technological University, Xi'an, China
| | - Jingping Zuo
- School of Economics and Management, Xi'an Technological University, Xi'an, China
| | - Hao Ji
- School of Economics and Management, Xi'an Technological University, Xi'an, China
| | - Yuan RengTeng
- Jiangsu Key Laboratory of Urban ITS, School of Transportation, Southeast University, Nanjing, China
| | - Yonggang Wang
- College of Transportation Engineering, Chang'an University, Xi'an, China
- Key Laboratory of Transport Industry of Management, Control and Cycle Repair Technology for Traffic Network Facilities in Ecological Security Barrier Area, Xi'an, China
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2
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Gain-loss separability in human- but not computer-based changes of mind. COMPUTERS IN HUMAN BEHAVIOR 2023. [DOI: 10.1016/j.chb.2023.107712] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/16/2023]
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3
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Barati F, Pourshahbaz A, Nosratabadi M, Shiasy Y. Driving Behaviors in Iran: Comparison of Impulsivity, Attentional Bias, and Decision-Making Styles in Safe and High-Risk Drivers. IRANIAN JOURNAL OF PSYCHIATRY 2020; 15:312-321. [PMID: 33240381 PMCID: PMC7610067 DOI: 10.18502/ijps.v15i4.4297] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 11/24/2022]
Abstract
Objective: Road traffic injuries are leading cause of death and economic losses, particularly in developing countries such as Iran. Thus, increased understanding of the causes of traffic accidents can help solve this problem. The primary goal of this study was to examine attentional bias, decision-making styles, and impulsiveness in drivers with safe or risky driving behaviors. The secondary purpose was to determine the variance of each variable among 2 groups of drivers. Method: This was a cross sectional design study, in which 120 male drivers aged 20-30 years (60 males with risky driving behaviors and 60 with safe driving behaviors) were recruited from Tehran using sampling technique. Barratt Impulsiveness Scale (BIS), Decision-Making Style Scale (DMSQ), Manchester Driver Behavior Questionnaire (MDBQ), Self-Assessment Manikin Scale (SAM), and Dot Probe Task were used. The analyses were performed using IBM SPSS version 22. Results: The mean age of participants was 26 years. Significant differences were found between impulsiveness (attentional, motor, and non planning impulsiveness) and decision-making styles (spontaneous and avoidant) between the 2 groups. Also, based on the results of discriminant function analysis (DFS), the subscales of impulsiveness and 2 decision-making styles explained 25% of the variance in the 2 groups of risky and safe drivers. Conclusion: Findings of this study indicated that impulsiveness and 2 decision-making styles were predominant factors. Therefore, not only is there a need for research to reduce traffic accidents, but studies can also be helpful in issuing driving licenses to individuals.
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Affiliation(s)
- Fatemeh Barati
- Department of Clinical Psychology, University of Social Welfare and Rehabilitation Sciences, Tehran, Iran
| | - Abas Pourshahbaz
- Department of Clinical Psychology, University of Social Welfare and Rehabilitation Sciences, Tehran, Iran
| | - Masode Nosratabadi
- Research Unit, Paarand Specialized Center for Human Enhancement, Tehran, Iran
| | - Yasaman Shiasy
- Department of Clinical Psychology, University of Social Welfare and Rehabilitation Sciences, Tehran, Iran
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4
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Peng Z, Zhang H, Wang Y. Work-related factors, fatigue, risky behaviours and traffic accidents among taxi drivers: a comparative analysis among age groups. Int J Inj Contr Saf Promot 2020; 28:58-67. [PMID: 33108968 DOI: 10.1080/17457300.2020.1837885] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/23/2022]
Abstract
The main purpose of this study was to investigate the effect of work-related factors, fatigue, risky behaviours on accident involvement among different age groups of taxi drivers in China. A total of 2391 taxi drivers were selected to complete a self-reported questionnaire about their demographic data and information on working conditions, fatigue, risky behaviours, as well as involvement in traffic accidents between 2014 and 2016. The drivers were divided into three categories according to their age. Then, a set of comparative analyses and three structural equation models were used to analyze the samples of specific age groups. The results indicated that taxi drivers in the younger group rest the least with the most dissatisfaction with income while those in the mid-age group worked the longest time and were charged the most management fee, but the older taxi drivers more frequently engaged in risky behaviours and traffic accidents. Furthermore, two mediating chain processes were confirmed (i.e. 'work-related factors - fatigue - accidents' and 'work-related factors - risky behaviours - accidents') across the three age groups. However, the causes of fatigue, risky behaviours and accidents in different age groups are not exactly the same. These findings suggest that the regulation of the taxi industry should be carefully improved. Incentive policy and education aimed at taxi drivers may also hold promise.
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Affiliation(s)
- Zhipeng Peng
- College of Transportation Engineering, Chang'an University, Xi'an, Shaanxi, China
| | - Heng Zhang
- College of Transportation Engineering, Chang'an University, Xi'an, Shaanxi, China
| | - Yan Wang
- College of Transportation Engineering, Chang'an University, Xi'an, Shaanxi, China
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Zahid M, Chen Y, Khan S, Jamal A, Ijaz M, Ahmed T. Predicting Risky and Aggressive Driving Behavior among Taxi Drivers: Do Spatio-Temporal Attributes Matter? INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2020; 17:E3937. [PMID: 32498347 PMCID: PMC7312618 DOI: 10.3390/ijerph17113937] [Citation(s) in RCA: 31] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/07/2020] [Revised: 05/28/2020] [Accepted: 05/30/2020] [Indexed: 12/04/2022]
Abstract
Risky and aggressive driving maneuvers are considered a significant indicator for traffic accident occurrence as well as they aggravate their severity. Traffic violations caused by such uncivilized driving behavior is a global issue. Studies in existing literature have used statistical analysis methods to explore key contributing factors toward aggressive driving and traffic violations. However, such methods are unable to capture latent correlations among predictor variables, and they also suffer from low prediction accuracies. This study aimed to comprehensively investigate different traffic violations using spatial analysis and machine learning methods in the city of Luzhou, China. Violations committed by taxi drivers are the focus of the current study since they constitute a significant proportion of total violations reported in the city. Georeferenced violation data for the year 2016 was obtained from the traffic police department. Detailed descriptive analysis is presented to summarize key statistics about various violation types. Results revealed that over-speeding was the most prevalent violation type observed in the study area. Frequency-based nearest neighborhood cluster methods in Arc map Geographic Information System (GIS) were used to develop hotspot maps for different violation types that are vital for prioritizing and conducting treatment alternatives efficiently. Finally, different machine learning (ML) methods, including decision tree, AdaBoost with a base estimator decision tree, and stack model, were employed to predict and classify each violation type. The proposed methods were compared based on different evaluation metrics like accuracy, F-1 measure, specificity, and log loss. Prediction results demonstrated the adequacy and robustness of proposed machine learning (ML) methods. However, a detailed comparative analysis showed that the stack model outperformed other models in terms of proposed evaluation metrics.
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Affiliation(s)
- Muhammad Zahid
- College of Metropolitan Transportation, Beijing University of Technology, Beijing 100124, China;
| | - Yangzhou Chen
- College of Artificial Intelligence and Automation, Beijing University of Technology, Beijing 100124, China;
| | - Sikandar Khan
- Department of Mechanical Engineering, King Fahd University of Petroleum & Minerals, KFUPM Box 5069, Dhahran 31261, Saudi Arabia
| | - Arshad Jamal
- Department of Civil and Environmental Engineering, King Fahd University of Petroleum & Minerals, KFUPM Box 5055, Dhahran 31261, Saudi Arabia;
| | - Muhammad Ijaz
- School of Transportation and Logistics, Southwest Jiaotong University, Chengdu 610031, China;
| | - Tufail Ahmed
- UHasselt, Transportation Research Institute (IMOB), Agoralaan, 3590 Diepenbeek, Belgium;
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Peng Z, Wang Y, Luo X. How does financial burden influence the crash rate among taxi drivers? A self-reported questionnaire study in China. TRAFFIC INJURY PREVENTION 2020; 21:324-329. [PMID: 32363927 DOI: 10.1080/15389588.2020.1759046] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/17/2019] [Revised: 03/26/2020] [Accepted: 04/19/2020] [Indexed: 06/11/2023]
Abstract
Objective: Taxis play an important role in the transportation system of China, but they have a relatively high accident rate. The current study discusses the driver's financial burden in the Chinese context and explores its correlation with working conditions, risky driving behavior, and other characteristics of taxi drivers who are involved in accidents.Method: A total of 2,391 taxi drivers from 29 companies in four Chinese cities were interviewed and then asked to complete a questionnaire concerning their socio-demographic characteristics, working conditions, risky driving behavior, and accident frequency during the previous two years. Given the increase in the management fee (measured in CNY) charged by taxi companies, the drivers were divided into three groups: the "less than 150" group, the" 150 to 180" group and the "over 180" group, where were named Group 1, Group 2 and Group 3, respectively. Finally, the zero-inflated Poisson model was used to investigate the factors that contributed to the accident rate for each group.Result: The significant factors that lead to accidents differed significantly for drivers with different levels of financial burden. First, most of the factors were weakly correlated with the crash rate among Group 1 drivers. Second, many factors related to working conditions and risky driving behavior were significant for drivers in Groups 2 and 3, while working hours and off-duty days were significant only for drivers in Group 3. Third, working hours were negatively correlated with accident rates for drivers in Group 3, and the drivers who suffered from the heaviest financial burden were most affected by fatigue and sleep problems.Conclusion: Financial burden is the root cause behind the propensity of taxi drivers to be involved in accidents. Taxi companies should find ways to reduce drivers' expenses, and new technologies, such as taxi-calling or location and navigation based on mobile applications, should be introduced into the traditional taxi industry.
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Affiliation(s)
- Zhipeng Peng
- College of Transportation Engineering, Chang'an University, Xi'an, China
| | - Yonggang Wang
- College of Transportation Engineering, Chang'an University, Xi'an, China
| | - Xianyu Luo
- College of Transportation Engineering, Chang'an University, Xi'an, China
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7
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Chiu CWC, Law CKM, Cheng ASK. Driver assessment service for people with mental illness. Hong Kong J Occup Ther 2020; 32:77-83. [PMID: 32009859 PMCID: PMC6967224 DOI: 10.1177/1569186119886773] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/16/2019] [Accepted: 10/11/2019] [Indexed: 11/17/2022] Open
Abstract
Mental illness often leads to functional deficits that likely affect one’s
driving performance and may even pose threat to other road users. However,
having a mental illness does not automatically preclude one from driving which
is essential to mobility and productivity. Indeed, evaluating their
fitness-to-drive would be of necessary. Despite that, there is still a lack of a
local driving evaluation service that specifically addresses the impact of
mental illness on driving capacity. This paper discusses the needs to evaluate
the fitness-to-drive of people with mental illness. It advocates the development
of such specific driver assessment service with a local example as illustration.
Lastly, some of the challenges related to the drivers’ responsibility to declare
personal health status and large variety of assessment approaches are also
discussed.
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Affiliation(s)
- Calvin WC Chiu
- Occupational Therapy Department, Castle Peak Hospital, Hospital
Authority, Hong Kong
- Calvin WC Chiu, Occupational Therapy
Department, Castle Peak Hospital, 15 Tsing Chung Koon Road, Tuen Mun, N.T., Hong
Kong.
| | - Colin KM Law
- Occupational Therapy Department, Castle Peak Hospital, Hospital
Authority, Hong Kong
| | - Andy SK Cheng
- Department of Rehabilitation Sciences, The Hong Kong Polytechnic
University, Hong Kong
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Meng F, Wong SC, Yan W, Li YC, Yang L. Temporal patterns of driving fatigue and driving performance among male taxi drivers in Hong Kong: A driving simulator approach. ACCIDENT; ANALYSIS AND PREVENTION 2019; 125:7-13. [PMID: 30690275 DOI: 10.1016/j.aap.2019.01.020] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/18/2018] [Revised: 01/19/2019] [Accepted: 01/20/2019] [Indexed: 06/09/2023]
Abstract
This study uses a questionnaire survey and a driving simulator test to investigate the temporal patterns of variations in driving fatigue and driving performance in 50 male taxi drivers in Hong Kong. Each driver visited the laboratory three times: before, during, and after a working shift. The survey contained a demographic questionnaire and the Brief Fatigue Inventory. A following-braking simulator test session was conducted at two speeds (50 and 80 km/h) by each driver at each of his three visits, and the driver's performance in brake reaction, lane control, speed control, and steering control were recorded. A random-effects modeling approach was incorporated to address the unobserved heterogeneity caused by the repeated measures. In the results, a recovery effect and a lagging effect were defined for the driving fatigue and performance measures because their temporal patterns were concavely quadratic and had a 1-hour delay compared to the temporal patterns of occupied taxi trips and taxi crash risk in Hong Kong. Demographic variables, such as net income and driver age, also had significant effects on the measured driving fatigue and performance. Policies regarding taxi management and operation based on the modeling results are proposed to alleviate the taxi safety situation in Hong Kong and worldwide.
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Affiliation(s)
- Fanyu Meng
- Department of Civil Engineering, The University of Hong Kong, Hong Kong, China.
| | - S C Wong
- Department of Civil Engineering, The University of Hong Kong, Hong Kong, China
| | - Wei Yan
- Department of Social Work and Social Administration, The University of Hong Kong, Hong Kong, China
| | - Y C Li
- Department of Civil Engineering, The University of Hong Kong, Hong Kong, China
| | - Linchuan Yang
- Department of Civil Engineering, The University of Hong Kong, Hong Kong, China
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9
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Electrophysiological correlates of near outcome and outcome sequence processing in problem gamblers and controls. Int J Psychophysiol 2018; 132:379-392. [DOI: 10.1016/j.ijpsycho.2017.10.011] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2017] [Revised: 10/05/2017] [Accepted: 10/26/2017] [Indexed: 11/19/2022]
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10
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Zhao Q, Li H, Hu B, Wu H, Liu Q. Abstinent Heroin Addicts Tend to Take Risks: ERP and Source Localization. Front Neurosci 2017; 11:681. [PMID: 29270107 PMCID: PMC5723666 DOI: 10.3389/fnins.2017.00681] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2017] [Accepted: 11/21/2017] [Indexed: 11/13/2022] Open
Abstract
Abnormal decision making is a behavioral characteristic of drug addiction. Indeed, drug addicts prefer immediate rewards at the expense of future interests. Assessing the neurocognitive basis of decision-making related to drug dependence, combining event-related potential (ERP) analysis and source localization techniques, may provide new insights into understanding decision-making deficits in drug addicts and further guide withdrawal treatment. In this study, EEG was performed in 20 abstinent heroin addicts (AHAs) and 20 age-, education- and gender-matched healthy controls (HCs) while they participated in a simple two-choice gambling task (99 vs. 9). Our behavioral results showed that AHAs tend to select higher-risk choices compared with HCs (i.e., more "99" choices than "9"). ERP results showed that right hemisphere preponderance of stimulus-preceding negativity was disrupted in AHAs, but not in HCs. Feedback-related negativity of difference wave was higher in AHAs than HCs, with the P300 amplitude associated with risk magnitude and valence. Using source localization that allows identification of abnormal brain activity in consequential cognitive stages, including the reward expectation and outcome evaluation stages, we found abnormalities in both behavioral and neural responses on gambling in AHAs. Taken together, our findings suggest AHAs have risk-prone tendency and dysfunction in adaptive decision making, since they continue to choose risky options even after accruing considerable negative scores, and fail to shift to a safer strategy to avoid risk. Such abnormal decision-making bias to risk and immediate reward seeking may be accompanied by abnormal reward expectation and evaluation in AHAs, which explains their high risk-seeking and impulsivity.
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Affiliation(s)
- Qinglin Zhao
- Ubiquitous Awareness and Intelligent Solutions Lab, Lanzhou University, Lanzhou, China
| | - Hongqian Li
- Ubiquitous Awareness and Intelligent Solutions Lab, Lanzhou University, Lanzhou, China
| | - Bin Hu
- Ubiquitous Awareness and Intelligent Solutions Lab, Lanzhou University, Lanzhou, China
| | - Haiyan Wu
- Institute of Psychology, Chinese Academy of Sciences, Beijing, China.,Department of Psychology, University of Chinese Academy of Sciences, Beijing, China
| | - Quanying Liu
- Movement Control & Neuroplasticity Research Group, KU Leuven, Leuven, Belgium.,Neural Control of Movement Laboratory, ETH Zurich, Zurich, Switzerland
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Huang H, Wang X, Hu G. Traffic safety in China: Challenges and countermeasures. ACCIDENT; ANALYSIS AND PREVENTION 2016; 95:305-307. [PMID: 27506136 DOI: 10.1016/j.aap.2016.07.040] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/06/2023]
Affiliation(s)
- Helai Huang
- School of Traffic and Transportation Engineering, Central South University, Changsha, Hunan, China.
| | - Xuesong Wang
- School of Transportation Engineering, Tongji University, Shanghai, China
| | - Guoqing Hu
- Xiangya School of Public Health, Central South University, Changsha, Hunan, China
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