Analysis of Driver Decisions at the Onset of Yellow at Signalized Intersections
Drivers’ decisions to either slow and stop or go at the onset of yellow signal impact on intersection safety. This novel study contributes to the new classification scheme for drivers. Two driving style indexes (i.e., the driving reliability index and dangerous driving index) are adopted, along with...
Main Authors: | , , , , |
---|---|
Format: | Article |
Language: | English |
Published: |
Hindawi-Wiley
2020-01-01
|
Series: | Journal of Advanced Transportation |
Online Access: | http://dx.doi.org/10.1155/2020/2023093 |
id |
doaj-dfd1df100d1e4eed97e7fec0547ddad3 |
---|---|
record_format |
Article |
spelling |
doaj-dfd1df100d1e4eed97e7fec0547ddad32020-11-25T03:36:10ZengHindawi-WileyJournal of Advanced Transportation0197-67292042-31952020-01-01202010.1155/2020/20230932023093Analysis of Driver Decisions at the Onset of Yellow at Signalized IntersectionsJuan Li0Boyu Jiang1Chunjiao Dong2Jue Wang3Xuan Zhang4School of Traffic and Transportation, Beijing Jiaotong University, Beijing, ChinaSchool of Traffic and Transportation, Beijing Jiaotong University, Beijing, ChinaSchool of Traffic and Transportation, Beijing Jiaotong University, Beijing, ChinaCenter for Forecasting Science, Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing, ChinaSam’s Club Technology, Austin, TX, USADrivers’ decisions to either slow and stop or go at the onset of yellow signal impact on intersection safety. This novel study contributes to the new classification scheme for drivers. Two driving style indexes (i.e., the driving reliability index and dangerous driving index) are adopted, along with other known factors to analyze stop/go decision-making. Initially, the driving reliability index is extracted using a Hidden Markov Model (HMM). The dangerous driving index is calculated based on statistics extracted from dangerous driving records. A latent class logit model is then proposed to explore the factors which influence drivers’ decisions. Drivers are classified for analytical purposes into “low-risk” and “high-risk” categories according to driving styles and age. Results indicate that those considering “low-risk” tend to stop, while drivers considering “high-risk” are inclined to pass intersections. Furthermore, distractions from cell phones have different influences on each group of drivers. These findings help to determine driver preferences and may be used to formulate strategies to reduce unsafe driving occurring at signalized intersections.http://dx.doi.org/10.1155/2020/2023093 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Juan Li Boyu Jiang Chunjiao Dong Jue Wang Xuan Zhang |
spellingShingle |
Juan Li Boyu Jiang Chunjiao Dong Jue Wang Xuan Zhang Analysis of Driver Decisions at the Onset of Yellow at Signalized Intersections Journal of Advanced Transportation |
author_facet |
Juan Li Boyu Jiang Chunjiao Dong Jue Wang Xuan Zhang |
author_sort |
Juan Li |
title |
Analysis of Driver Decisions at the Onset of Yellow at Signalized Intersections |
title_short |
Analysis of Driver Decisions at the Onset of Yellow at Signalized Intersections |
title_full |
Analysis of Driver Decisions at the Onset of Yellow at Signalized Intersections |
title_fullStr |
Analysis of Driver Decisions at the Onset of Yellow at Signalized Intersections |
title_full_unstemmed |
Analysis of Driver Decisions at the Onset of Yellow at Signalized Intersections |
title_sort |
analysis of driver decisions at the onset of yellow at signalized intersections |
publisher |
Hindawi-Wiley |
series |
Journal of Advanced Transportation |
issn |
0197-6729 2042-3195 |
publishDate |
2020-01-01 |
description |
Drivers’ decisions to either slow and stop or go at the onset of yellow signal impact on intersection safety. This novel study contributes to the new classification scheme for drivers. Two driving style indexes (i.e., the driving reliability index and dangerous driving index) are adopted, along with other known factors to analyze stop/go decision-making. Initially, the driving reliability index is extracted using a Hidden Markov Model (HMM). The dangerous driving index is calculated based on statistics extracted from dangerous driving records. A latent class logit model is then proposed to explore the factors which influence drivers’ decisions. Drivers are classified for analytical purposes into “low-risk” and “high-risk” categories according to driving styles and age. Results indicate that those considering “low-risk” tend to stop, while drivers considering “high-risk” are inclined to pass intersections. Furthermore, distractions from cell phones have different influences on each group of drivers. These findings help to determine driver preferences and may be used to formulate strategies to reduce unsafe driving occurring at signalized intersections. |
url |
http://dx.doi.org/10.1155/2020/2023093 |
work_keys_str_mv |
AT juanli analysisofdriverdecisionsattheonsetofyellowatsignalizedintersections AT boyujiang analysisofdriverdecisionsattheonsetofyellowatsignalizedintersections AT chunjiaodong analysisofdriverdecisionsattheonsetofyellowatsignalizedintersections AT juewang analysisofdriverdecisionsattheonsetofyellowatsignalizedintersections AT xuanzhang analysisofdriverdecisionsattheonsetofyellowatsignalizedintersections |
_version_ |
1715167689023946752 |