Discrimination of Effects between Directional and Nondirectional Information of Auditory Warning on Driving Behavior

This study examines the impacts of directional and nondirectional auditory warning information in a collision warning system (CWS) on driving behavior. The data on driving behavior is collected through experiment, with scenarios containing unexpected hazard events that include different warning content. As drivers approached the collision event, either a CWS auditory warning was given or no warning was given for a reference group. Discriminant analysis was used to investigate the relationship between directional auditory warning information and driving behavior. In the experiment, the CWS warnings significantly reduced brake reaction time and prompted drivers to press the brake pedal more heavily, demonstrating the effectiveness of CWS warnings in alerting drivers to avoid red-light running (RLR) vehicles when approaching a signalized intersection. Providing a clear warning with directional information about an urgent hazard event could give drivers adequate time to prepare for the potential collision. In terms of deceleration, a directional information warning was shown to greatly help drivers react to critical events at signalized intersections with more moderate braking. From these results, requirements can be derived for the design of effective warning strategies for critical intersections

A Co-Simulation Study to Assess the Impacts of Connected and Autonomous Vehicles on Traffic Flow Stability during Hurricane Evacuation

Hurricane evacuation has become a major problem for the coastal residents of the United States. Devastating hurricanes have threatened the lives and infrastructure of coastal communities and caused billions of dollars in damage. There is a need for better traffic management strategies to improve the safety and mobility of evacuation traffic. In this study hurricane evacuation traffic was simulated using SUMO a microscopic traffic simulation model. The effects of Connected and Autonomous Vehicles (CAVs) and Autonomous Vehicles (AVs) were evaluated using two approaches. (i) Using the state-of-the-art car-following models available in SUMO and (ii) a co-simulation study by integrating the microscopic traffic simulation model with a separate communication simulator to find the realistic effect of CAVs on evacuation traffic. A road network of I-75 in Florida was created to represent real-world evacuation traffic observed in Hurricane Irma s evacuation periods. Simulation experiments were performed by creating mixed traffic scenarios with 25, 50, 75 and 100 percentages of different vehicle technologies including CAVs or AVs and human-driven vehicles. HDV Simulation results suggest that the CACC car-following model, implemented in SUMO and commonly used in the literature to represent CAVs, produces highly unstable results On the other hand the ACC car following model, used to represent AVs, produces better and more stable results. However, in a co-simulation study, to evaluate the effect of CAVs in the same evacuation traffic scenario, results indicate that with 25 percentage of CAVs the number of potential collisions decrease up to 42.5 percentage

Design MythBusters

When highway project designs depart from design values found in the Kentucky Transportation Cabinet (KYTC) Highway Design Manual and AASHTO’s A Policy on Geometric Design of Highways and Streets, project managers at the agency must obtain either a design exception or design variance. While designers are more comfortable with exceptions and variances than they were 10 or 20 years ago, some hesitancy remains, especially among the Cabinet’s consultants. Misperceptions about what exceptions or variances entail or about their performance may underlie this reluctance. Exceptions and variances are best conceptualized as formal justifications for design decisions. Project managers merely need to describe why a design does not adhere to published guidance and illustrate that safety and mobility performance are not significantly compromised — in every instance new designs offer improvement over existing conditions. The limited number of research studies on design exceptions have found no evidence to suggest facilities where exceptions have been used have worse safety performance than those which abide by typical design values. To encourage project managers and designers to embrace cost-effective, context-adapted designs — and the role of variances and exceptions play in delivering those solutions — this report presents design axioms and case studies that document projects on which exceptions and variances have been used with success. Most of the exceptions and variances used on these projects are minor (e.g., narrowing shoulders, reducing design speeds), were critical for addressing the stated purposes and needs, and resulted in a solution that blended improved roadway with the surrounding contexts. Addition examples of mostly Highway Safety Improvement Program (HSIP) projects are catalogued that illustrate how creative fixes can be used to mitigate safety concerns

A link between attentional function, effective eye movements, and driving ability

The misallocation of driver visual attention has been suggested as a major contributing factor to vehicle accidents. One possible reason is that the relatively high cognitive demands of driving limits the ability to efficiently allocate gaze. We present an experiment that explores the relationship between attentional function and visual performance when driving. Drivers performed two variations of a multiple object tracking task targeting aspects of cognition including sustained attention, dual-tasking, covert attention and visuomotor skill. They also drove a number of courses in a driving simulator. Eye movements were recorded throughout. We found that individuals who performed better in the cognitive tasks exhibited more effective eye movement strategies when driving, such as scanning more of the road, and they also exhibited better driving performance. We discuss the potential link between an individual's attentional function, effective eye movements and driving ability. We also discuss the use of a visuomotor task in assessing driving behaviour

Autonomous, Context-Sensitive, Task Management Systems and Decision Support Tools I: Human-Autonomy Teaming Fundamentals and State of the Art

Recent advances in artificial intelligence, machine learning, data mining and extraction, and especially in sensor technology have resulted in the availability of a vast amount of digital data and information and the development of advanced automated reasoners. This creates the opportunity for the development of a robust dynamic task manager and decision support tool that is context sensitive and integrates information from a wide array of on-board and off aircraft sourcesa tool that monitors systems and the overall flight situation, anticipates information needs, prioritizes tasks appropriately, keeps pilots well informed, and is nimble and able to adapt to changing circumstances. This is the first of two companion reports exploring issues associated with autonomous, context-sensitive, task management and decision support tools. In the first report, we explore fundamental issues associated with the development of an integrated, dynamic, flight information and automation management system. We discuss human factors issues pertaining to information automation and review the current state of the art of pilot information management and decision support tools. We also explore how effective human-human team behavior and expectations could be extended to teams involving humans and automation or autonomous systems