Проверка эффективности вспомогательной системы для маневрирования в местах слияния автомобильных потоков в режиме реального вождения автомобиля

In the latest study conducted by the National Highway Traffic Safety Administration in 2018, it was published that human error is still considered the major factor in traffic accidents, 94 %, compared with other causes such as vehicles, environment and unknown critical reasons. Some driving scenarios are especially complex, such as highways merging lanes, where the driver obtains information from the environment while making decisions on how to proceed to perform the maneuver smoothly and safely. Ignorance of the intentions of the drivers around him leads to risky situations between them caused by misunderstandings or erroneous assumptions or perceptions. For this reason, Advanced Driver Assistance Systems could provide information to obtain safer maneuvers in these critical environments. In previous works, the behavior of the driver by means of a visual tracking system while merging in a highway was studied, observing a cognitive load in those instants due to the high attentional load that the maneuver requires. For this reason, a driver assistance system for merging situations is proposed. This system uses V2V communications technology and suggests to the driver how to modify his speed in order to perform the merging manoeuver in a safe way considering the available gap and the relative speeds between vehicles. The paper presents the results of the validation of this system for assisting in the merging maneuver. For this purpose, the interface previously designed and validated in terms of usability, has been integrated into an application for a mobile device, located inside the vehicle and tests has been carried out in real driving conditions.In the latest study conducted by the National Highway Traffic Safety Administration in 2018, it was published that human error is still considered the major factor in traffic accidents, 94 %, compared with other causes such as vehicles, environment and unknown critical reasons. Some driving scenarios are especially complex, such as highways merging lanes, where the driver obtains information from the environment while making decisions on how to proceed to perform the maneuver smoothly and safely. Ignorance of the intentions of the drivers around him leads to risky situations between them caused by misunderstandings or erroneous assumptions or perceptions. For this reason, Advanced Driver Assistance Systems could provide information to obtain safer maneuvers in these critical environments. In previous works, the behavior of the driver by means of a visual tracking system while merging in a highway was studied, observing a cognitive load in those instants due to the high attentional load that the maneuver requires. For this reason, a driver assistance system for merging situations is proposed. This system uses V2V communications technology and suggests to the driver how to modify his speed in order to perform the merging manoeuver in a safe way considering the available gap and the relative speeds between vehicles. The paper presents the results of the validation of this system for assisting in the merging maneuver. For this purpose, the interface previously designed and validated in terms of usability, has been integrated into an application for a mobile device, located inside the vehicle and tests has been carried out in real driving conditions

Assessment of traffic impact on future cooperative driving systems: challenges and considerations

Connect & Drive is a start-up project to develop a cooperative driving system and improve the traffic performance on Dutch highways. It consists of two interactive subsystems: cooperative adaptive cruise control (CACC) and connected cruise control (CCC). To assess the traffic performance, a traffic simulation model will be established for large-scale evaluation and providing feedbacks to system designs. This paper studies the factors determining the traffic performance and discusses challenges and difficulties to establish such a traffic simulation model

Evaluating the Performance of Cooperative Merging Assistance System for Aging Drivers

Freeway merging maneuvers demand considerable attention by drivers and are among the more complex operations drivers must perform on freeways. Aging drivers, a growing population in the United States, face added challenges when merging. This study utilized Vissim models created in a previous study that modeled the behavior of aging drivers during freeway merging. An algorithm for Cooperative Merging Assistance System (CMAS) that utilizes Connected Vehicle (CV) technology was developed in this study. The Vissim models were created for two interchanges on I-75 in Fort Myers, Florida, each with different geometric characteristics. Acceleration lane lengths of 1000ft and 1500ft were analyzed in this study, and the CV environment was created in Vissim through the Component Object Model (COM) Interface. A sensitivity analysis was conducted by varying CV penetration rates, composition of aging on-ramp drivers, and mainline and on-ramp traffic flows to analyze the effects of CV technology under different levels of service (LOSs). Merging location, merging speed and vehicle interaction states (braking for lane change, emergency stop and cooperative braking) together with deceleration rate were the measures of effectiveness (MOEs) considered. Findings showed the number of aging drivers merging late onto the freeway can be decreased by up to 60.0% when CMAS was employed, while there was no significant change in merging speed at 95% confidence level when CMAS was employed. Furthermore, the results showed that CMAS reduced the percentages of aging drivers braking for lane change or emergency stop and also hard braking by up to 100% for low traffic conditions (LOS A and B). A maximum reduction of 82.2% was observed for cooperative braking of mainline vehicles when CMAS was employed. The reductions in interaction states were significant at 95% confidence level according to Mann-Kendall trend test

PLANNING AND COORDINATION IN DRIVING SIMULATION

We present an overview of coordination and planning tasks that we face with during the development of the AgentDrive simulation platform. We particularly describe an integration of the AgentDrive with a driving simulator OpenDS. We demonstrate how the planning and coordination mechanisms can be applied in a driving simulator for automated driving applications or realistic traffic generation. We emphasize particular planning and/or coordination methods that were already developed using AgentDrive platform

Assessing the effects of work zone configurations on drivers\u27 visual attention

This study assessed the effects of two different work zone configurations on driver’s visual attention by eye movement monitoring. A driving simulator study was conducted with thirty participants. Variations in traffic density and warning sign placement distance were added to the merge configurations to simulate the real time situation. A 2 x 2 x 3 within-subjects factorial design was used for this research. The independent variables used in this study were (1) merge configuration [(i) Conventional Lane Merge (CLM) and (ii) Joint Lane Merge (JLM)], (2) traffic density [(i) high and (ii) low] and (3) distance between traffic signs [(i) standard distance, (ii) 25% reduction from standard and (iii) 25% increase from standard]. The dependent variable used for this study was the total number of eye movements (gaze) of the participants towards the three mirrors (rear view, left side view and right side view), and towards ‘other areas’ such as dash board, warning signs, environment, and other vehicles etc., were analyzed. Results from the research show that, the total number of gazes at mirrors and ‘other areas’ in CLM and JLM are nearly the same and they are not significantly different (p value: \u3e0.05). Changes in traffic density and sign placement distances have a significant effect on number of gazes at mirrors and ‘other areas’ (p value: \u3c0.05). Gender and driving experience have a significant effect on number of gazes at mirrors, but not at ‘other areas’. Reducing the sign placement distances by 25% from the standard distances does not show any significant effect on the number of gazes at mirrors, however it shows an increase in the number of gazes at ‘other areas’ by nearly 11.6%. An increase in sign placement distances by 25% from the standard distances, show an increase in number of gazes at mirrors by nearly 16.9%, while it does not show any significant effect on the number of gazes at the ‘other areas’

Driver Assistance for Safe and Comfortable On-Ramp Merging Using Environment Models Extended through V2X Communication and Role-Based Behavior Predictions

Modern driver assistance systems as well as autonomous vehicles take their decisions based on local maps of the environment. These maps include, for example, surrounding moving objects perceived by sensors as well as routes and navigation information. Current research in the field of environment mapping is concerned with two major challenges. The first one is the integration of information from different sources e.g. on-board sensors like radar, camera, ultrasound and lidar, offline map data or backend information. The second challenge comprises in finding an abstract representation of this aggregated information with suitable interfaces for different driving functions and traffic situations. To overcome these challenges, an extended environment model is a reasonable choice. In this paper, we show that role-based motion predictions in combination with v2x-extended environment models are able to contribute to increased traffic safety and driving comfort. Thus, we combine the mentioned research areas and show possible improvements, using the example of a threading process at a motorway access road. Furthermore, it is shown that already an average v2x equipment penetration of 80% can lead to a significant improvement of 0.33m/s^2 of the total acceleration and 12m more safety distance compared to non v2x-equipped vehicles during the threading process.Comment: the article has been accepted for publication during the 16th IEEE International Conference on Intelligent Computer Communication and Processing (ICCP 2020), 8 pages, 8 figures, 1 tabl