Results 1 to 10 of about 274,567 (117)

A CNN-LSTM Car-Following Model Considering Generalization Ability [PDF]

Sensors, 2023
To explore the potential relationship between the leading vehicle and the following vehicle during car-following, we proposed a novel car-following model combining a convolutional neural network (CNN) with a long short-term memory (LSTM) network. Firstly,
Pinpin Qin, Hao Li, Ziming Li, Weilai Guan, Yuxin He   +4 more
doaj   +2 more sources

An Investigation into the Appropriateness of Car-Following Models in Assessing Autonomous Vehicles [PDF]

Sensors, 2021
The dramatic progress of Intelligent Transportation Systems (ITS) has made autodriving technology extensively emphasised. Various models have been developed for the aim of modelling the behaviour of autonomous vehicles and their impacts on traffic ...
Akito Higatani, Wafaa Saleh
doaj   +2 more sources

FollowNet: A Comprehensive Benchmark for Car-Following Behavior Modeling [PDF]

Scientific Data, 2023
Car-following is a control process in which a following vehicle adjusts its acceleration to keep a safe distance from the lead vehicle. Recently, there has been a booming of data-driven models that enable more accurate modeling of car-following through ...
Xianda Chen, Meixin Zhu, Kehua Chen, Pengqin Wang, Hongliang Lu, Hui Zhong, Xu Han, Xuesong Wang, Yinhai Wang   +8 more
doaj   +2 more sources

A Hierarchical Framework for Multi-Lane Autonomous Driving Based on Reinforcement Learning

IEEE Open Journal of Intelligent Transportation Systems, 2023
This paper proposes a hierarchical framework integrating deep reinforcement learning (DRL) and rule-based methods for multi-lane autonomous driving.
Xiaohui Zhang, Jie Sun, Yunpeng Wang, Jian Sun   +3 more
doaj   +1 more source

Evaluation of Mental Load of Drivers in Long Highway Tunnel Based on Electroencephalograph

Frontiers in Psychology, 2021
In recent years, the mileage of the tunnels has substantially increased with the rapid highway construction that led to increasing highway tunnels.
Yanqun Yang, Yanqun Yang, Yang Feng, Yang Feng, Said M. Easa, Said M. Easa, Xinyi Zheng   +6 more
doaj   +1 more source

Research into Autonomous Vehicles Following and Obstacle Avoidance Based on Deep Reinforcement Learning Method under Map Constraints

Sensors, 2023
Compared with traditional rule-based algorithms, deep reinforcement learning methods in autonomous driving are able to reduce the response time of vehicles to the driving environment and fully exploit the advantages of autopilot.
Zheng Li, Shihua Yuan, Xufeng Yin, Xueyuan Li, Shouxing Tang   +4 more
doaj   +1 more source

Comparing Measured Driver Behavior Distributions to Results from Car-Following Models using SUMO and Real-World Vehicle Trajectories from Radar

SUMO Conference Proceedings, 2023
In this study, the physical principles governing car-following (CF) behavior and their impact on traffic flow at signalized intersections are investigated. High temporal-resolution radar data is used to provide valuable insights into actual CF behavior,
Max Schrader, Mahdi Al Abdraboh, Joshua Bittle   +2 more
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Action-points in human driving and in SUMO

SUMO Conference Proceedings, 2022
When following a vehicle, drivers change their acceleration at so called action-points (AP), and keep it constant in between them. By investigating a large data-set of car-following data, the state- and time-distributions of the APs is analyzed.
Peter Wagner, Jakob Erdmann, Ronald Nippold   +2 more
doaj   +1 more source

Intelligent Total Transportation Management System for Future Smart Cities

Applied Sciences, 2020
Smart mobility and transportation, in general, are significant elements of smart cities, which account for more than 25% of the total energy consumption related to smart cities. Smart transportation has seven essential sections: leisure, private, public,
Dinh Dung Nguyen, József Rohács, Dániel Rohács, Anita Boros   +3 more
doaj   +1 more source

Modelling and Analysis of Mutually Adaptive Vehicle Maneuvers During the Inserting Process of Lane Changing Vehicle in Urban Driving Context

IEEE Access, 2020
This study developed a pair of lane changing (LC) model and car following (CF) model. They are used to investigate mutually adaptive maneuver of LC vehicle (LCV) and its immediate CF vehicle during the LCV's inserting process.
Guiping Wang, Zhendong Ping, Dong Zhang, Xu Lei, Xiaoyun Cheng, Li Li   +5 more
doaj   +1 more source