The practical part of train driver education: experience, expectations, and possibilities

Objectives The internship period of the Swedish train driver education was examined in terms of which types of situations can be sufficiently encountered in order to develop expertise to handle them safely and efficiently, and to quantify and specify the gap in expertise between expert and novice drivers in terms of risk of error and time efficiency. Focus was on special cases (i.e., situations that occur rarely but may cause severe accidents if not handled correctly and efficiently). Methodology Data on which situations and special cases a driver's student can be expected to experience during the internship period were collected via a web-based questionnaire. Also, ratings of expectations on novice and expert drivers were obtained from train driver educators, employers, and instructors with the purpose of comparing the expectations with the novices practical experience. Results and conclusions The main results suggest that many special cases are generally insufficiently practiced during the internship and therefore should be practiced in simulators; that both experienced and novice drivers prioritize safety over efficiency; and that expectations on novice drivers are realistic considering their limited professional expertise.

The Combination of Artificial Intelligence and Extended Reality: A Systematic Review

Artificial intelligence (AI) and extended reality (XR) differ in their origin and primary objectives. However, their combination is emerging as a powerful tool for addressing prominent AI and XR challenges and opportunities for cross-development. To investigate the AI-XR combination, we mapped and analyzed published articles through a multi-stage screening strategy. We identified the main applications of the AI-XR combination, including autonomous cars, robotics, military, medical training, cancer diagnosis, entertainment, and gaming applications, advanced visualization methods, smart homes, affective computing, and driver education and training. In addition, we found that the primary motivation for developing the AI-XR applications include 1) training AI, 2) conferring intelligence on XR, and 3) interpreting XR- generated data. Finally, our results highlight the advancements and future perspectives of the AI-XR combination.

Advanced vehicle technology: Mapping mental model accuracy and system exposure to driver behavior

Advanced driver assistance systems have potential to increase safety and comfort for drivers; however, drivers need to understand the capabilities and limitations of these systems to use them appropriately. This study sought to explore how the quality (accuracy) of drivers’ mental models of adaptive cruise control (ACC) impacted their behavior and interactions while using the system. Seventy-eight participants drove in a high-fidelity driving simulator while operating an ACC system, in normal conditions and while interacting with the system interface. Participants with stronger (more accurate) mental models glanced to the road ahead more often during normal conditions early on compared to drivers were less accurate mental models; however, these differences diminished with increased system exposure. Glance behavior while interacting with the system and time to complete the interactions were less effected by the strength of the participant’s mental model. Results are discussed in the context of driver education and training.

Assessment of Traffic Sign Comprehension Levels among Drivers in the Emirate of Abu Dhabi, UAE

Road traffic signs are part of the road infrastructure components meant to ensure the safe use of roads by motorists and pedestrians alike. A good knowledge and comprehension of road signs helps ensure smooth flow of traffic, improves safety for other motorists and provides drivers with good reaction time to comply with the message dictated by the signs. Abu Dhabi, being the capital of the UAE, brings together people from all over the world for work, business or tourism. Abu Dhabi has quality roads and traffic signage together with an efficient police force that enforces adherence to traffic rules. Despite all these and the reduced fatalities in absolute terms, traffic violations have been increasing exponentially, resulting in five million traffic fines in 2019 for a population of about 2.9 million inhabitants. This study sought to assess motorists’ comprehension of the various traffic signs used across the UAE. The results of the survey (N = 200) revealed that the drivers were able to correctly identify 77% of the road signs in the survey. It was also found that the respondents failed to correctly identify traffic signs within the specific category referred to as “advance warning signs”. Respondents’ education, nationality, gender, and marital status did not have any statistically significant effects on the results compared to earlier studies. It is recommended that more attention be focused on driver education and training.

Driver Compliance in Daytime Headlights Zones in the U.S

Aims: Observe driver compliance with daytime headlights requirements along two-lane highways in California and Arizona. Determine overall compliance rates, while identifying any statistical differences between highways. Study Design: Travel along highways having daytime headlight use requirements during daylight hours, recording ambient conditions and compliance. Distinguish between cars, large commercial trucks, and motorcycles, and between manual (low-beam) and automated (very low-beam) headlights. Add supportive information from synergistic research. Place and Duration of Study: California State Routes 4, 18, 74, 247, and U.S. Highway 95 in Arizona, during September 2010, and June and July 2015, over seven data collection days during the summer, and one on the first day of autumn. Methodology: Calculate average driver headlight compliance rates and deviations to a 95% level of confidence. Assume that compliance follows a normal probability distribution pattern. Results: A total of 758 motor vehicles were observed. Removing the 104 vehicles observed on a “cloudy” highway, 266 of the 654 drivers were using their headlights (40.7% ± 3.6% compliance). There was no difference between the proportions of compliant drivers on the six highways (95% level of confidence). A total of 66 of 104 drivers used their headlights under cloudy conditions (63.5% ± 9.6% compliance). A Facebook survey of 24 respondents found that 20% of drivers were unaware of daytime headlights zones (DHZs), and an additional 13% were deliberately noncompliant. Interviews of two California Highway Patrol officers revealed that citations for noncompliance were “not popular” (among the officers), and that there was some skepticism as to the effectiveness of the requirement. Conclusions: Further observation is needed under cloudy skies to develop a more precise proportion of compliance. The low compliance suggests that the effectiveness of DHZs cannot be truly assessed. Compliance might be improved with enhanced driver education, as to their existence and purpose, less reluctant enforcement, a revised headlight sign design, and more frequent signing.

Analysis of Vehicle Moving Parameters in Various Road Conditions

The safety of road users is one of the priority issues raised by those involved in vehicle design, latest passive and active safety systems, traffic organization or driver education. Nowadays, an important road safety problem is the behaviour of drivers in emergency situations. In order to measurably estimate the driving quality, parameters such as velocity, acceleration, the way and frequency of using the control pedals are quite often used. This article describes how to assess driver's behaviour based on measurements taken on the road. The frequency of different acceleration ranges during the vehicle drive was determined based on the results obtained. For the arbitrarily adopted acceleration range of - 0.5 - 0.5 m/s2, the driver's working time was over 77 percent on average, with the difference varying significantly between different route sections. Similarly, the study compares the driving times for other ranges of acceleration.

Challenges of enforcing cellphone use while driving laws among police in the USA: a cross-sectional analysis

ObjectivesResearch suggests that cellphone use while driving laws may be difficult for police to enforce in the USA, but this is unknown. A national survey of police officers was conducted to determine whether barriers to enforcing these laws exist, what aspects of laws make them easier to enforce and ways to discourage the behaviour among drivers.DesignCross-sectional survey.SettingUSA.ParticipantsIndividuals >18 years of age employed as a law enforcement officer from all 50 states were recruited via convenience sampling through multiple modalities from November 2019 to April 2020. Officers (N=353) from 31 states participated.Primary and secondary outcome measuresDescriptive statistics and multi-level logistic regression analyses were run to assess the responses.ResultsThe most common barriers to enforcing texting bans (ie, the most prevalent law) were drivers concealing their phone use (78%) and the officer not being able to determine what the driver was doing on their phone (65%). If a universal hand-held cellphone ban was in effect in their state, officers were 77% less likely (adjusted OR=0.23; 95% CI 0.08 to 0.70) to report that a texting ban was difficult to adjudicate. The majority of officers (86%) agreed that having one general law that prohibits any type of hand-held cellphone use would aid with enforcement, and that laws must be a primary offence (87%), and be applicable to all licensed drivers (91%). Most officers felt that driver education is needed.ConclusionsWhile numerous barriers to enforcement were identified, opportunities exist to improve current legislation to aid enforcement efforts and to prevent the behaviour among drivers.