Two-thirds of vehicle accidents in Malaysia occurred at the straight type of roads, followed by intersection-type roads. Despite the deployment of traffic lights on the road, accidents still occur which are caused by illegal maneuvers, speeding or misjudgment of other’s actions. Hence, motivated by the lack of previous research regarding causes of accidents on intersectional roads, this study aims to observe the pattern of the vehicles’ speed and turning angle during the right turn after the traffic stop at the intersection road. To obtain these parameters, video samples of vehicles at two types of intersections were obtained and analyzed via YOLOV7 and DeepSORT. The two road intersections researched are four-legged intersection and three-legged intersection. 153 and 35 vehicle samples were collected from these types of road intersections, respectively. It was observed that 78 and 75 vehicles exit towards the nearest and furthest lanes at four-leg controlled crossings on divided roads. While, at a single-lane to a dual carriageway road intersection, 26 and 9 vehicles exit towards the nearest and furthest lanes, respectively. From the research, 16.52 - 17.53 km/h and 67.57°-73.33° are the most optimal turning speeds and angles respectively for vehicles at four-leg controlled crossings. Whereas 14.48 - 15.51 km/h and 144.77° - 154.403° are the most optimal turning speeds and angles respectively for vehicles at a single-lane to a dual carriageway road intersection.


    Zugriff

    Download


    Exportieren, teilen und zitieren



    Titel :

    Investigation of the Vehicle Driving Trajectory During Turning at Intersectional Roads Using Deep Learning Model




    Erscheinungsdatum :

    2024




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Unbekannt






    Finite-state machine-based automatic driving vehicle trajectory planning method for ice and snow roads

    ZHENG HAOTIAN / WANG JIANQIANG / XU QING et al. | Europäisches Patentamt | 2023

    Freier Zugriff


    Deep learning vehicle trajectory prediction method fused with kinematic model

    LI LINHUI / FU YIFAN / WANG XUECHENG et al. | Europäisches Patentamt | 2023

    Freier Zugriff