121 related articles for article (PubMed ID: 38325183)
1. Lane-change intention recognition considering oncoming traffic: Novel insights revealed by advances in deep learning.
Liu H; Wang T; Li W; Ye X; Yuan Q
Accid Anal Prev; 2024 Apr; 198():107476. PubMed ID: 38325183
[TBL] [Abstract][Full Text] [Related]
2. A proactive lane-changing risk prediction framework considering driving intention recognition and different lane-changing patterns.
Shangguan Q; Fu T; Wang J; Fang S; Fu L
Accid Anal Prev; 2022 Jan; 164():106500. PubMed ID: 34823098
[TBL] [Abstract][Full Text] [Related]
3. Driver Behavior During Overtaking Maneuvers from the 100-Car Naturalistic Driving Study.
Chen R; Kusano KD; Gabler HC
Traffic Inj Prev; 2015; 16 Suppl 2():S176-81. PubMed ID: 26436229
[TBL] [Abstract][Full Text] [Related]
4. Research on Vehicle Lane Change Warning Method Based on Deep Learning Image Processing.
Zhang Q; Sun Z; Shu H
Sensors (Basel); 2022 Apr; 22(9):. PubMed ID: 35591016
[TBL] [Abstract][Full Text] [Related]
5. A Lane-Changing Decision-Making Model of Bus Entering considering Bus Priority Based on GRU Neural Network.
Lv W; Lv Y; Guo J; Ma J
Comput Intell Neurosci; 2022; 2022():4558946. PubMed ID: 36248950
[TBL] [Abstract][Full Text] [Related]
6. A hybrid deep learning approach for driver anomalous lane changing identification.
Fan P; Guo J; Wang Y; Wijnands JS
Accid Anal Prev; 2022 Jun; 171():106661. PubMed ID: 35462211
[TBL] [Abstract][Full Text] [Related]
7. How do oncoming traffic and cyclist lane position influence cyclist overtaking by drivers?
Rasch A; Boda CN; Thalya P; Aderum T; Knauss A; Dozza M
Accid Anal Prev; 2020 Jul; 142():105569. PubMed ID: 32445969
[TBL] [Abstract][Full Text] [Related]
8. A proactive crash risk prediction framework for lane-changing behavior incorporating individual driving styles.
Zhang Y; Chen Y; Gu X; Sze NN; Huang J
Accid Anal Prev; 2023 Aug; 188():107072. PubMed ID: 37137214
[TBL] [Abstract][Full Text] [Related]
9. A spatio-temporal deep learning approach to simulating conflict risk propagation on freeways with trajectory data.
Wang T; Ge YE; Wang Y; Chen W
Accid Anal Prev; 2024 Feb; 195():107377. PubMed ID: 37984114
[TBL] [Abstract][Full Text] [Related]
10. An interpretable prediction model of illegal running into the opposite lane on curve sections of two-lane rural roads from drivers' visual perceptions.
He L; Yu B; Chen Y; Bao S; Gao K; Kong Y
Accid Anal Prev; 2023 Jun; 186():107066. PubMed ID: 37058902
[TBL] [Abstract][Full Text] [Related]
11. A new method of temporal and spatial risk estimation for lane change considering conventional recognition defects.
Wu J; Wen H; Qi W
Accid Anal Prev; 2020 Dec; 148():105796. PubMed ID: 33099126
[TBL] [Abstract][Full Text] [Related]
12. Multi-Modal Vehicle Trajectory Prediction by Collaborative Learning of Lane Orientation, Vehicle Interaction, and Intention.
Tian W; Wang S; Wang Z; Wu M; Zhou S; Bi X
Sensors (Basel); 2022 Jun; 22(11):. PubMed ID: 35684916
[TBL] [Abstract][Full Text] [Related]
13. Key feature selection and risk prediction for lane-changing behaviors based on vehicles' trajectory data.
Chen T; Shi X; Wong YD
Accid Anal Prev; 2019 Aug; 129():156-169. PubMed ID: 31150922
[TBL] [Abstract][Full Text] [Related]
14. Interaction driver-bicyclist on rural roads: Effects of cross-sections and road geometric elements.
Bella F; Silvestri M
Accid Anal Prev; 2017 May; 102():191-201. PubMed ID: 28319757
[TBL] [Abstract][Full Text] [Related]
15. Time-Series-Based Personalized Lane-Changing Decision-Making Model.
Ye M; Pu L; Li P; Lu X; Liu Y
Sensors (Basel); 2022 Sep; 22(17):. PubMed ID: 36081119
[TBL] [Abstract][Full Text] [Related]
16. The safety potential of enhanced lateral vehicle positioning.
Sternlund S
Traffic Inj Prev; 2021; 22(2):139-146. PubMed ID: 33556264
[TBL] [Abstract][Full Text] [Related]
17. Modelling duration of car-bicycles overtaking manoeuvres on two-lane rural roads using naturalistic data.
Moll S; López G; Rasch A; Dozza M; García A
Accid Anal Prev; 2021 Sep; 160():106317. PubMed ID: 34333159
[TBL] [Abstract][Full Text] [Related]
18. Detecting lane change maneuvers using SHRP2 naturalistic driving data: A comparative study machine learning techniques.
Das A; Khan MN; Ahmed MM
Accid Anal Prev; 2020 Jul; 142():105578. PubMed ID: 32408143
[TBL] [Abstract][Full Text] [Related]
19. PSO algorithm particle filters for improving the performance of lane detection and tracking systems in difficult roads.
Cheng WC
Sensors (Basel); 2012 Dec; 12(12):17168-85. PubMed ID: 23235453
[TBL] [Abstract][Full Text] [Related]
20. The effect of motor control requirements on drivers' eye-gaze pattern during automated driving.
Goncalves RC; Louw TL; Quaresma M; Madigan R; Merat N
Accid Anal Prev; 2020 Dec; 148():105788. PubMed ID: 33039820
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]