3 research outputs found
Constructing Model of Bicycle Behavior on Non-signalized lntersection Using Nonlinear Autoregressive Exogenous Model
This study focuses on bicycle travel flow to prevent traffic accidents at non-signalized intersections. A bicycle's behavior can be characterized by various parameters, such as travel speed position, trajectory, acceleralion, and deceleration. The prevention of vehicle collisions with bicycles traveling at 10-15 km/h was regulated in the Advanced Emergency Braking System (AEBS) for passenger cars in regulation No. 152 of the World Forum for Harmonization of Vehicle Regulations in the United Nations. Therefore, it is essential to analyze the characteristics of bicycles in a reall trafflc environment to prevent traffic accidents involving cyclists. Meijer et. al. (2017) investigated bicycle behavior and charactericics using measurement devices installed on biccycles [1 ]. Ma et al. (2016) conducted a model of acceleration behavior on eleven cyclists using GPS data [2]. And it was pointed out that there was a need for modeling research for more cyclists.Hirose et al. (2021) examined bicycles' both travel speed and trajectory as bicycle travel flows based on data obtained from fixed-point observations at a non-signalized intersection in Tokyo, Japan [3]. This used fixed-point observalions to obtain raw data of bicycle travel flows in real traffic environment and reported various traffel speed, trajectory, and acceleration/deceleration patterns for bicycles entering intersections. The purpose of this study was to construct a model of bicycle travel flows based on fixed-point observations. It could simulate actual bicycle behaviors based on data that was obtained from measuring bicycle travel flows for 2828 cases from fixed-point observations. Furthermore, the data was divided into five patterns of bicycles entering intersections, and the accuracy of the model was evaluated for each pattern
Constructing Model of Bicycle Behavior on Non-signalized lntersection Using Nonlinear Autoregressive Exogenous Model
This study focuses on bicycle travel flow to prevent traffic accidents at non-signalized intersections. A bicycle's behavior can be characterized by various parameters, such as travel speed position, trajectory, acceleralion, and deceleration. The prevention of vehicle collisions with bicycles traveling at 10-15 km/h was regulated in the Advanced Emergency Braking System (AEBS) for passenger cars in regulation No. 152 of the World Forum for Harmonization of Vehicle Regulations in the United Nations. Therefore, it is essential to analyze the characteristics of bicycles in a reall trafflc environment to prevent traffic accidents involving cyclists. Meijer et. al. (2017) investigated bicycle behavior and charactericics using measurement devices installed on biccycles [1 ]. Ma et al. (2016) conducted a model of acceleration behavior on eleven cyclists using GPS data [2]. And it was pointed out that there was a need for modeling research for more cyclists.Hirose et al. (2021) examined bicycles' both travel speed and trajectory as bicycle travel flows based on data obtained from fixed-point observations at a non-signalized intersection in Tokyo, Japan [3]. This used fixed-point observalions to obtain raw data of bicycle travel flows in real traffic environment and reported various traffel speed, trajectory, and acceleration/deceleration patterns for bicycles entering intersections. The purpose of this study was to construct a model of bicycle travel flows based on fixed-point observations. It could simulate actual bicycle behaviors based on data that was obtained from measuring bicycle travel flows for 2828 cases from fixed-point observations. Furthermore, the data was divided into five patterns of bicycles entering intersections, and the accuracy of the model was evaluated for each pattern
Constructing Model of Bicycle Behavior on Non-signalized lntersection Using Nonlinear Autoregressive Exogenous Model
This study focuses on bicycle travel flow to prevent traffic accidents at non-signalized intersections. A bicycle's behavior can be characterized by various parameters, such as travel speed position, trajectory, acceleralion, and deceleration. The prevention of vehicle collisions with bicycles traveling at 10-15 km/h was regulated in the Advanced Emergency Braking System (AEBS) for passenger cars in regulation No. 152 of the World Forum for Harmonization of Vehicle Regulations in the United Nations. Therefore, it is essential to analyze the characteristics of bicycles in a reall trafflc environment to prevent traffic accidents involving cyclists. Meijer et. al. (2017) investigated bicycle behavior and charactericics using measurement devices installed on biccycles [1 ]. Ma et al. (2016) conducted a model of acceleration behavior on eleven cyclists using GPS data [2]. And it was pointed out that there was a need for modeling research for more cyclists.Hirose et al. (2021) examined bicycles' both travel speed and trajectory as bicycle travel flows based on data obtained from fixed-point observations at a non-signalized intersection in Tokyo, Japan [3]. This used fixed-point observalions to obtain raw data of bicycle travel flows in real traffic environment and reported various traffel speed, trajectory, and acceleration/deceleration patterns for bicycles entering intersections. The purpose of this study was to construct a model of bicycle travel flows based on fixed-point observations. It could simulate actual bicycle behaviors based on data that was obtained from measuring bicycle travel flows for 2828 cases from fixed-point observations. Furthermore, the data was divided into five patterns of bicycles entering intersections, and the accuracy of the model was evaluated for each pattern