Estimated potential death and disability averted with vehicle safety interventions, Association of Southeast Asian Nations.

Objective: To evaluate road safety in member countries of the Association of Southeast Asian Nations and estimate the benefits that vehicle safety interventions would have in this group of countries. Methods: We used a counterfactual analysis to assess the reduction in traffic deaths and disability-adjusted life years (DALYs) lost if eight proven vehicle safety technologies and motorcycle helmets were entirely in use in countries of the Association of Southeast Asian Nations. We modelled each technology using country-level incidence estimations of traffic injuries, and the prevalence and effectiveness of the technology to calculate the reduction in deaths and DALYs if the technology was fitted in the entire vehicle fleet. Findings: The availability of electronic stability control, including the antilock braking systems, would provide the most benefits for all road users with estimates of 23.2% (sensitivity analysis range: 9.7-27.8) fewer deaths and 21.1% (9.5-28.1) fewer DALYs. Increased use of seatbelts was estimated to prevent 11.3% (8.11-4.9) of deaths and 10.3% (8.2-14.4) of DALYs. Appropriate and correct use of motorcycle helmets could result in 8.0% (3.3-12.9) fewer deaths and 8.9% (4.2-12.5) fewer DALYs. Conclusion: Our findings show the potential of improved vehicle safety design and personal protective devices (seatbelts and helmets) to reduce traffic deaths and disabilities in the Association of Southeast Asian Nations. These improvements can be achieved by vehicle design regulations and creating consumer demand for safer vehicles and motorcycle helmets through mechanisms such as new car assessment programmes and other initiatives.

Design and evaluation of cooperative human-machine interface for changing lanes in conditional driving automation.

This study analyzes the impact of cooperative human-machine interface designs on drivers' trust in and interaction with automated driving systems (ADSs) during lane changes on highways. While drivers' inappropriate trust in ADSs can affect their behavior toward the system, capability to detect inadequate system performance, and perception of surrounding traffic disturbances, their engagement in the automated process can improve their comprehension of the system and traffic conditions, which is necessary for the safe practice of automated driving. Forty drivers practiced conditional driving automation in a driving simulator and encountered traffic congestion on the main lane of a two-lane highway. Four ADS designs were proposed to bypass the congestion. ADS-1 detects the congestion and synchronizes the speed accordingly. ADS-2 requests the driver to resume manual control and overtake the congestion. ADS-3 requests the driver to push a button to let the system overtakes the congestion automatically. ADS-4 overtakes the congestion automatically after informing the driver, while the driver can cancel it by pushing a button within 6 s. In all these conditions, driver intervention was optional. Although the drivers preferred and trusted ADS-1 and ADS-2 more than ADS-3 and ADS-4, the results indicate significant improvements in the driving performance and system usage under ADS-3 and ADS-4. Driving with ADS-3 improved drivers' engagement and reduced the requirement for control transfer compared with other systems. However, the time headway between the subject and adjacent vehicles indicated that lane changes were more critical under ADS-3 and ADS-4 than ADS-1 and ADS-2. Such deficiency of alignment between driver perception and safe behaviors has implications for the design of future studies and systems that need to balance satisfaction and safety. These observations are likely to improve driver interaction with automated vehicles.

Effects of gender, age, experience, and practice on driver reaction and acceptance of traffic jam chauffeur systems.

This study conducted a driving simulation experiment to compare four automated driving systems (ADS) designs during lane change demanding traffic situations on highways while accounting for the drivers' gender, age, experience, and practice. A lane-change maneuver was required when the automated vehicle approaches traffic congestion on the left-hand lane. ADS-1 can only reduce the speed to synchronize with the congestion. ADS-2 reduces the speed and issues an optional request to intervene, advising the driver to change lanes manually. ADS-3 offers to overtake the congestion autonomously if the driver approves it. ADS-4 overtakes the congestion autonomously without the driver's approval. Results of drivers' reaction, acceptance, and trust indicated that differences between ADS designs increase when considering the combined effect of drivers' demographic factors more than the individual effect of each factor. However, the more ADS seems to have driver-like capacities, the more impact of demographic factors is expected. While preliminary, these findings may help us understand how ADS users' behavior can differ based on the interaction between human demographic factors and system design.

Long-Term Evaluation of Drivers' Behavioral Adaptation to an Adaptive Collision Avoidance System.

OBJECTIVE: Taking human factors approach in which the human is involved as a part of the system design and evaluation process, this paper aims to improve driving performance and safety impact of driver support systems in the long view of human-automation interaction. BACKGROUND: Adaptive automation in which the system implements the level of automation based on the situation, user capacity, and risk has proven effective in dynamic environments with wide variations of human workload over time. However, research has indicated that drivers may not efficiently deal with dynamically changing system configurations. Little effort has been made to support drivers' understanding of and behavioral adaptation to adaptive automation. METHOD: Using a within-subjects design, 42 participants completed a four-stage driving simulation experiment during which they had to gradually interact with an adaptive collision avoidance system while exposed to hazardous lane-change scenarios over 1 month. RESULTS: Compared to unsupported driving (stage i), although collisions have been significantly reduced when first experienced driving with the system (stage ii), improvements in drivers' trust in and understanding of the system and driving behavior have been achieved with more driver-system interaction and driver training during stages iii and iv. CONCLUSION: While designing systems that take into account human skills and abilities can go some way to improving their effectiveness, this alone is not sufficient. To maximize safety and system usability, it is also essential to ensure appropriate users' understanding and acceptance of the system. APPLICATION: These findings have important implications for the development of active safety systems and automated driving.