Predicting Driver Behavior during the Yellow Interval Using Video Surveillance
نویسندگان
چکیده
منابع مشابه
Predicting Driver Behavior during the Yellow Interval Using Video Surveillance
At a signalized intersection, drivers must make a stop/go decision at the onset of the yellow signal. Incorrect decisions would lead to red light running (RLR) violations or crashes. This study aims to predict drivers' stop/go decisions and RLR violations during yellow intervals. Traffic data such as vehicle approaching speed, acceleration, distance to the intersection, and occurrence of RLR vi...
متن کاملDriver Behavior During Yellow Change Interval
When drivers are approaching a signalized intersection at the onset of a yellow change interval, they must decide whether to stop or cross the intersection. This can be a difficult decision when the vehicle is located within the dilemma zone and the result is sometimes a rear-end crash due to a sudden stop. This paper presented a new pavement-marking countermeasure which purpose is to reduce th...
متن کاملoverview of ways to enhance the security of video surveillance networks using blockchain
In recent decades, video surveillance systems have an increasing development that are used to prevent crime and manage facilities with rapid diffusion of (CCTV)cameras to prevent crime and manage facilities. The video stored in the video surveillance system should be managed comfortably, but sometimes the movies are leaking out to unauthorized people or by unauthorized people, thus violating i...
متن کاملDriver perception response time during the signal change interval.
The importance of perception response time (PRT) values for traffic signal change interval design, and the need to monitor the design PRT value, are challenges facing transportation professionals. However, current methods used to validate the design PRT value from on-site observational studies have failed to yield convincing proof that the 1 second design value is adequate. A modification to on...
متن کاملCrowd Behavior Recognition for Video Surveillance
Crowd behavior recognition is becoming an important research topic in video surveillance for public places. In this paper, we first discuss the crowd feature selection and extraction and propose a multiple-frame feature point detection and tracking based on the KLT tracker. We state that behavior modelling of crowd is usually coarse compared to that for individuals. Instead of developing genera...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: International Journal of Environmental Research and Public Health
سال: 2016
ISSN: 1660-4601
DOI: 10.3390/ijerph13121213