scholarly journals Sectional Information-Based Collision Warning System Using Roadside Unit Aggregated Connected-Vehicle Information for a Cooperative Intelligent Transport System

2020 ◽  
Vol 2020 ◽  
pp. 1-12
Author(s):  
Sehyun Tak ◽  
Jinsu Yoon ◽  
Soomin Woo ◽  
Hwasoo Yeo

Vehicular collision and hazard warning is an active field of research that seeks to improve road safety by providing an earlier warning to drivers to help them avoid potential collision danger. In this study, we propose a new type of a collision warning system based on aggregated sectional information, describing vehicle movement processed by a roadside unit (RSU). The proposed sectional information-based collision warning system (SCWS) overcomes the limitations of existing collision warning systems such as the high installation costs, the need for high market penetration rates, and the lack of consideration of traffic dynamics. The proposed SCWS gathers vehicle operation data through on-board units (OBUs) and shares this aggregated information through an RSU. All the data for each road section are locally processed by the RSU using edge computing, allowing the SCWS to effectively estimate the information describing the vehicles surrounding the subject vehicle in each road section. The performance of the SCWS was evaluated through comparison with other collision warning systems such as the vehicle-to-vehicle communication-based collision warning system (VCWS), which solely uses in-vehicle sensors; the hybrid collision warning system (HCWS), which uses information from both infrastructure and in-vehicle sensors; and the infrastructure-based collision warning system (ICWS), which only uses data from infrastructure. In this study, the VCWS with a 100% market penetration rate was considered to provide the most theoretically similar result to the actual collision risk. The comparison results show that in both aggregation and disaggregation level analyses, the proposed SCWS exhibits a similar collision risk trend to the VCWS. Furthermore, the SCWS shows a high potential for practical application because it provides acceptable performance even with a low market penetration rate (30%) at the relatively low cost of OBU installation, compared to the VCWS requirement of a high market penetration rate at a high installation cost.

Author(s):  
West M. O’Brien ◽  
Xingwei Wu ◽  
Linda Ng Boyle

Collision warning systems alert drivers of potential safety hazards. Forward collision warning (FCW) systems have been widely implemented and studied. However, intersection collision warning systems (ICWS), such as intersection movement assist (IMA), are more complex. Additional studies are needed to identify the best alert for directing the driver toward the hazard. A driving simulator study with 48 participants was conducted to examine three speech-based auditory alerts (general, directional, and command) in a simulated red light running (RLR) collision scenario. The command alert that informed the drivers to brake was the most effective in reducing the number of collisions. The post-drive questionnaire showed that drivers also rated the brake alert to be best in terms of interpretation (based on the Kruskal Wallis test). This study provides insight into the performance of different types of speech-based alerts for an intersection collision warning system and can provide guidance for future studies.


2021 ◽  
Author(s):  
Matej Barbo ◽  
◽  
Blaž Rodič ◽  

In this paper we present research findings on collision warning systems and their influence on traffic safety, and present MEBWS – Motorcycle Emergency Braking Warning System, a patented innovation developed at the Faculty of Information Studies in Novo mesto. MEBWS analyses motorcycle movement in real-time using an accelerometer and GPS speed measurement and monitors the following vehicles using a LIDAR. In case a dangerous situation is detected, the MEBWS alerts vehicles behind the motorcycle with an autonomous flashing LED. Furthermore, we are developing a simulation model that will allow us to gauge the influence of MEBWS on traffic safety in large traffic systems and its contribution to the European Union’s goal “Vision Zero” – to reduce road deaths to almost zero by 2050.


2014 ◽  
Vol 2014 ◽  
pp. 1-9 ◽  
Author(s):  
Ki-Yeong Park ◽  
Sun-Young Hwang

We propose a range estimation method for vision-based forward collision warning systems with a monocular camera. To solve the problem of variation of camera pitch angle due to vehicle motion and road inclination, the proposed method estimates virtual horizon from size and position of vehicles in captured image at run-time. The proposed method provides robust results even when road inclination varies continuously on hilly roads or lane markings are not seen on crowded roads. For experiments, a vision-based forward collision warning system has been implemented and the proposed method is evaluated with video clips recorded in highway and urban traffic environments. Virtual horizons estimated by the proposed method are compared with horizons manually identified, and estimated ranges are compared with measured ranges. Experimental results confirm that the proposed method provides robust results both in highway and in urban traffic environments.


2017 ◽  
Vol 10 (2) ◽  
pp. 44-47
Author(s):  
Manuel Fischer ◽  
Muhammet Albayrak

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