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Texas A&M University
Human computer interaction, Human Factors and Ergonomics, UX research, autonomous driving
Scopus Publications
Scholar Citations
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Maryam Zahabi, Xi Zheng, Azima Maredia, and Farzaneh Shahini
Informa UK Limited
Farzaneh Shahini, Junho Park, Kyle Welch, and Maryam Zahabi
Informa UK Limited
The objective of this study was to assess the effects of unreliable automation, non-driving related tasks (NDRTs), and takeover time budget (TOTB) on drivers' takeover performance and cognitive workload when faced with critical incidents. Automated vehicles are expected to improve traffic safety. However, there are still some concerns about the effects of automation failures on driver performance and workload. Twenty-eight drivers participated in a driving simulation study. The findings suggested that drivers require at least 8s of TOTB to safely take over the control of the vehicle. In addition, drivers exhibited safer takeover performance under the conditionally automated driving situation than negotiating the critical incident in the manual driving condition. The results of drivers' cognitive workload were inconclusive, which might be due to the individual and recall biases in subjective measures that could not capture subtle differences in workload during takeover requests.
Farzaneh Shahini and Maryam Zahabi
Elsevier BV
Maryam Zahabi, Vanessa Nasr, Ashiq Mohammed Abdul Razak, Logan McCanless, Azima Maredia, Ben Patranella, David Wozniak, and Farzaneh Shahini
Informa UK Limited
Motor vehicle crashes are a leading cause of police injuries and deaths in line of duty. These crashes have been mainly attributed to the use of in-vehicle technologies while driving. Police officers receive extensive training on driving skills; however, limited training is provided on the use of in-vehicle technologies. Variable priority training (VPT) is a computer-based training that has shown promising results in improving multi-tasking performance. Eighteen police officers participated in a driving simulation study to assess the effect of VPT on officers' performance and workload. Findings suggested that although VPT was effective in improving officers' performance in dual and multi-task simulations across the training sessions, this effect was not generally transferred to driving. However, the VPT might be effective for training of high-demand situations involving pursuit driving and multiple secondary tasks. The findings can be beneficial for police agencies to improve training protocols.
Maryam Zahabi, Farzaneh Shahini, Wei Yin, and Xudong Zhang
Informa UK Limited
Motor vehicle crashes are a leading cause of police officers' deaths in line of duty. These crashes have been mainly attributed to officers' driving distraction caused by the use of in-vehicle technologies while driving. This paper presents a 3-hour ride-along study of 20 police officers to assess the physical and cognitive demands associated with using in-vehicle technologies. The findings suggested that the mobile computer terminal (MCT) was the most frequently used in-vehicle system for the officers. In addition, officers perceived the MCT to significantly increase their visual, cognitive, and physical demands compared to other in-vehicle technologies. Evidence from electromyography and eye-tracking measures suggested that officers with more experience as a patrol officer and those who were working in more congested areas experienced higher cognitive workload. Furthermore, it was found that as the ride-along duration increased, there were indications of muscle fatigue in medial deltoid and triceps brachii muscles.Practitioner Summary: This study assessed the impact of police in-vehicle technology use in an on-road case study. The findings provide new data and knowledge for police agencies and vehicle manufacturers to develop administrative measures and in-vehicle technology innovations to improve police officers' health and safety.
David Wozniak, Farzaneh Shahini, Vanessa Nasr, and Maryam Zahabi
Elsevier BV
Farzaneh Shahini, Junho Park, and Maryam Zahabi
SAGE Publications
Young drivers are involved in a significantly higher number of crashes than any other age group. Highly automated vehicles are expected to improve traffic safety and reduce human errors; however, driver needs to take over in situations where the automation fails. A driving simulation study was conducted with twenty-eight young drivers to investigate the effects of unreliable automation, different takeover time budgets (TOTBs), and secondary tasks on mental workload during takeover situations. Mental workload was measured using a combination of physiological and secondary task performance measures. Results suggested that when faced with critical incidents, young drivers experienced lower mental workload under 10s of TOTB as compared to 5s or 8s of TOTB especially when they were engaged in a demanding secondary task. In addition, drivers experienced higher mental workload when regaining the control of the vehicle in the automated mode than the manual driving condition.
Vanessa Nasr, David Wozniak, Farzaneh Shahini, and Maryam Zahabi
SAGE Publications
Motor vehicle crashes are one of the leading causes of injuries and deaths for police officers. Advanced driver-assistance systems (ADAS) are driving control systems that have been found to improve civilian drivers’ safety; however, the impact of ADAS on police officers’ driving safety has yet to be investigated thoroughly. Disparities between driver states and tasks performed while driving between police and civilian drivers necessitate this distinction. This study identified the types of ADAS used in police vehicles, their impact on officers’ safety, and proposed potential future ADAS features to be implemented in police vehicles. A systematic literature review was conducted using Google Scholar, Compendex, Web of Science, Transport Research International Documentation (TRID), and Google Patents databases to identify the most prevalent police vehicles used in the U.S., available ADAS features in those vehicles, and the impact of ADAS on officers’ safety. A list of recommended ADAS features was developed based on the review of literature, authors’ knowledge and experience in the field, and the findings of an online survey with 73 police officers. Results indicated the addition of multiple ADAS features including the front vehicle detection system, intersection collision avoidance, evasive steering systems, left turn assist, traffic sign detection system, traffic jam assist, two lane and lane-ending detection, wrong-way alert, and autonomous highway driving features have the potential to improve officer safety and performance while driving. However, there was a void of studies focused on ADAS effects on police driving safety which needs to be addressed in future investigations.
Farzaneh Shahini, David Wozniak, and Maryam Zahabi
Informa UK Limited
ABSTRACT Motor vehicle crashes are a leading cause of police officers’ deaths in the line of duty. Previous studies have found that officer distraction caused by in-vehicle technologies such as the mobile computer terminal (MCT) is one of the main causes of these crashes. The objective of this study was to evaluate the usability issues of existing MCTs implemented in police vehicles across the U.S. and to provide recommendations to improve future technologies. Two focus group meetings were conducted with police officers from different departments. The discussion was analyzed based on Molich and Nielsen’s usability principles and using a directed content analysis approach. The most frequently mentioned usability issues were related to the inappropriate presentation of information on the MCT and the lack of interface consistency and adaptability. The provided recommendations can be beneficial in improving police in-vehicle technology design and safety of officers in police operations.