To tackle the problems of power saturation and high energy consumption heavy-load servo system in a process, we propose motion planning algorithm based on stimuli-induced equilibrium point (SIEP), named SIEP-MP algorithm. First, explore correlation between various modes bionic eye through head-eye control theory derive core formula from psychological field theory. Then, design speed loop by combining controller disturbance observer. Furthermore, create position feed-forward controller. We...

In complex real-world traffic environments, the task of automatic lane changing becomes extremely challenging for vehicle control systems. Traditional methods often lack flexibility and intelligence to accurately capture respond dynamic changes in flow. Therefore, developing intelligent strategies that can predict behavior surrounding vehicles make corresponding adjustments is crucial. This paper presents an driving scheme autonomous (AVs) based on a responsibility-sensitive safety (RSS)...

A vehicle platoon is a group of vehicles driving together with harmonized speed and short inter-vehicle gap by using automation vehicle-to-vehicle communication. Platoons have to share road human-driven (HDVs) can only be applied in heterogeneous traffic flow for long period. Driver cut-in behavior (DCB) towards frequently expected such context. In this paper, understand simulate behavior, we propose platoon-oriented (POCB) model fusing lateral longitudinal control into the queuing network...

Accurate vehicle type classification serves a significant role in the intelligent transportation system. It is critical for ruler to understand road conditions and usually contributive traffic light control system response correspondingly alleviate congestion. New technologies comprehensive data sources, such as aerial photos remote sensing data, provide richer high-dimensional information. Also, due rapid development of deep neural network technology, image based methods can better extract...

This article proposes a dynamic platoon management and cooperative driving framework for mixed traffic flow consisting of multiple connected automated vehicles(CAVs) possible human-driven vehicles(HDVs) that can be regarded as the surrounding vehicles(SVs). Specifically, proposed consists three stages. At first stage, cruising information all SVs will collected by leader CAV through Cellular-Vehicle-to-X(C-V2X) infrastructure, while an automatic decision-making assistance system(ADMDSS) is...

Recent research on the prediction of driver's lane-changing behaviour requires vehicle surrounding information, as it is believed that decision lane changing made consciously based those information. However, current has shown usage such information leads to high false alarm rate predict system [1]. Therefore this paper contributes developing a method which uses state only. From perspective observer's daily experience, selects vehicle's lateral trajectory and spectrum its input drivers'...

Although the existing autonomous driving systems (ADS) can implement lane-change behaviors without human operation, they still rely on decisions made by drivers in a complex traffic environment. The reason is that reasonably estimate intentions of surrounding vehicles advance, and decide their own trajectory according to experiences. Therefore, future ADS needs learn ability beings predict vehicles. Alternatively, it make safer than sacrificing possibility as much possible. This paper...

With the map navigation system achieving positioning accuracy at lane level, level began to be applied in digital software. The new generation of allows human drivers accurately identify road conditions without experience. However, actual use, still need complete lane-changing behavior independently. does not provide relevant real-time traffic flow information and safety prediction. Therefore, this paper innovatively combines free space detection change prediction algorithm driving, puts...

For a long period, autonomous vehicles (AVs) and human-driven (HDVs) need to share roads in mixed traffic flow, where the cut-ins of HDVs towards AVs can frequently occur. To better understand address cut-in behavior, it is crucial comprehend driving style this behavior. Thus, paper investigates how classify analyze process. The features driver behavior context are selected from speed-change lane-change phases principal component analysis (PCA) t-distributed stochastic neighbor embedding...

In recent years, researchers are very interested in the development of autonomous vehicle platoons that can be commercialized on a large scale. The research progress this field raises new demand for real-time traffic flow information and safety prediction. Therefore, an On-road Safety Prompt Framework (OSPF) combines free space detection lane change prediction has beed developed by paper. This OSPF predict lane-change decision trajectory around short period time future according to current...

In this article, a new long short-term memory (LSTM) network with horizontal heading change modeling is proposed to predict and position of large civil aircraft. data segmentation preprocessing, smoothing filter method forward sliding processing used, the ensures continuity trajectory. Our encodes aircraft information in relation nearest waypoints. The encoded vectors are used as input part prediction network, which improves accuracy prediction. higher prediction, better results...

The trend of intelligent transportation has been leading the world for years, and human acceptance applying Advanced Driver Assistance Systems (ADAS) in driving is increasing. Among all types driving, large vehicle one that requires assistance ADAS most. It imperative to use automatic technology assist further integrate those successful cases into increase safety experience. According [1] [2], improper lane changes are top 10 driver-related factors involved truck crashes. Due their size...

Current common choices of data-driven lane change predicting targets are left change, right and car-following. However, to achieve accurate long-term prediction, the motivation behind drivers' changes must also be considered. Motivated by this necessary consideration, we propose a Lane Change Attention Model (LCAM). Unlike past prediction models, LCAM applied mandatory (MLC), discretionary (DLC) lane-keeping (LK) as predicted driving states instead This approach expands horizon LCAM,...

The unknown sharp changes of vehicle acceleration rates, also called the jerk dynamics, may significantly affect driving performance leader in a platoon, resulting more drastic car-following movements platooning tracking control, which could cause safety and traffic capacity concerns. To address these issues, this paper, we investigate cooperative control intermittent optimization problems for connected automated vehicles (CAVs) with nonlinear model. We assume that external inputs CAV...

Public transport forms the backbone of city's operation. Proper planning and investment public can create additional jobs to revitalize recover cities from covid-19. In this paper, we propose a combined dispatching-operation bus model predictive control strategy, where rolling horizon mechanism is adopted system in real-time manner. Either platoon or single allowed be dispatched each trip, re-dispatching captured realistically reflect real-world. Also, initial constraints allow applied at...

There is no doubt that in the near future, machines will share roads with human drivers [1] [2]. Therefore, prediction of drivers' lane changing behavior imperative. Lane-change one most important ones. Both and autonomous vehicles should make sure other vehicle switches lanes or moves into same region target as ego vehicle. The existing short-term algorithms can only provide a horizon 3 ~ 5s, leaving limited reaction time for path planning modules. Additionally, majority previous research...