Open AccessDevelop right‐turn real‐time crash warning system at arterial access considering driver behaviour
Author(s) -
Li Yi,
Wang Junhua,
Chan Chingyao,
Fu Ting
Publication year - 2017
Publication title -
iet intelligent transport systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.579
H-Index - 45
eISSN - 1751-9578
pISSN - 1751-956X
DOI - 10.1049/iet-its.2016.0016
Subject(s) - crash , duration (music) , warning system , turn (biochemistry) , engineering , outlier , real time computing , computer science , automotive engineering , simulation , transport engineering , telecommunications , artificial intelligence , art , biochemistry , chemistry , literature , programming language
To help drivers safely enter the arterial road from the access road, the authors develop a crash warning system for vehicles in right‐turn scenario based on DSRC (dedicated short range communications). Drivers’ right‐turn behaviours from an access road to an arterial highway are considered in the system. Warning algorithms were tested with field data and DSRC on‐board and roadside equipment. Corresponding outliers filter shows a reliable performance. In this system, right‐turn process is divided into three phases: turn‐in, keep‐steady, and turn‐out. Based on the field data, they establish regression models for each phase. Model results show that: (i) the overall duration of the three phases of the right‐turn manoeuvre increases with the amount of cars coming from left on main artery; (ii) the amount of cars that are influenced by the arterial traffic increases the duration of first two phases, but decreases the last phase duration; (iii) the longer the first two phases last, the shorter the last phase would be; and (iv) drivers tend to decelerate before turning right when there are more than two cars coming from left.