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  • Open Access


    Forecasting Future Trajectories with an Improved Transformer Network

    Wei Wu1, Weigong Zhang1,*, Dong Wang1, Lydia Zhu2, Xiang Song3

    CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 3811-3828, 2023, DOI:10.32604/cmc.2023.029787

    Abstract An increase in car ownership brings convenience to people’s life. However, it also leads to frequent traffic accidents. Precisely forecasting surrounding agents’ future trajectories could effectively decrease vehicle-vehicle and vehicle-pedestrian collisions. Long-short-term memory (LSTM) network is often used for vehicle trajectory prediction, but it has some shortages such as gradient explosion and low efficiency. A trajectory prediction method based on an improved Transformer network is proposed to forecast agents’ future trajectories in a complex traffic environment. It realizes the transformation from sequential step processing of LSTM to parallel processing of Transformer based on attention mechanism. To perform trajectory prediction more… More >

  • Open Access


    Tracking Pedestrians Under Occlusion in Parking Space

    Zhengshu Zhou1,*, Shunya Yamada2, Yousuke Watanabe2, Hiroaki Takada1,2

    Computer Systems Science and Engineering, Vol.44, No.3, pp. 2109-2127, 2023, DOI:10.32604/csse.2023.029005

    Abstract Many traffic accidents occur in parking lots. One of the serious safety risks is vehicle-pedestrian conflict. Moreover, with the increasing development of automatic driving and parking technology, parking safety has received significant attention from vehicle safety analysts. However, pedestrian protection in parking lots still faces many challenges. For example, the physical structure of a parking lot may be complex, and dead corners would occur when the vehicle density is high. These lead to pedestrians’ sudden appearance in the vehicle’s path from an unexpected position, resulting in collision accidents in the parking lot. We advocate that besides vehicular sensing data, high-precision… More >

  • Open Access


    Estimating Fuel-Efficient Air Plane Trajectories Using Machine Learning

    Jaiteg Singh1, Gaurav Goyal1, Farman Ali2, Babar Shah3, Sangheon Pack4,*

    CMC-Computers, Materials & Continua, Vol.70, No.3, pp. 6189-6204, 2022, DOI:10.32604/cmc.2022.021657

    Abstract Airline industry has witnessed a tremendous growth in the recent past. Percentage of people choosing air travel as first choice to commute is continuously increasing. Highly demanding and congested air routes are resulting in inadvertent delays, additional fuel consumption and high emission of greenhouse gases. Trajectory planning involves creation identification of cost-effective flight plans for optimal utilization of fuel and time. This situation warrants the need of an intelligent system for dynamic planning of optimized flight trajectories with least human intervention required. In this paper, an algorithm for dynamic planning of optimized flight trajectories has been proposed. The proposed algorithm… More >

  • Open Access


    Intent Inference Based Trajectory Prediction and Smooth for UAS in Low-Altitude Airspace with Geofence

    Qixi Fu1, Xiaolong Liang1, 2, Jiaqiang Zhang1, *, Xiangyu Fan1, 2

    CMC-Computers, Materials & Continua, Vol.63, No.1, pp. 417-444, 2020, DOI:10.32604/cmc.2020.07044

    Abstract In order to meet the higher accuracy requirement of trajectory prediction for Unmanned Aircraft System (UAS) in Unmanned Aircraft System Traffic Management (UTM), an Intent Based Trajectory Prediction and Smooth Based on Constrained State-dependent-transition Hybrid Estimation (CSDTHE-IBTPS) algorithm is proposed. Firstly, an intent inference method of UAS is constructed based on the information of ADS-B and geofence system. Moreover, a geofence layering algorithm is proposed. Secondly, the Flight Mode Change Points (FMCP) are used to define the relevant mode transition parameters and design the guard conditions, so as to generate the mode transition probability matrix and establish the continuous state-dependent-transition… More >

  • Open Access


    Ship Trajectory Prediction Based on BP Neural Network

    Hai Zhou1,2,*, Yaojie Chen1,2, Sumin Zhang3

    Journal on Artificial Intelligence, Vol.1, No.1, pp. 29-36, 2019, DOI:10.32604/jai.2019.05939

    Abstract In recent years, with the prosperity of world trade, the water transport industry has developed rapidly, the number of ships has surged, and ship safety accidents in busy waters and complex waterways have become more frequent. Predicting the movement of the ship and analyzing the trajectory of the ship are of great significance for improving the safety level of the ship. Aiming at the multi-dimensional characteristics of ship navigation behavior and the accuracy and real-time requirements of ship traffic service system for ship trajectory prediction, a ship navigation trajectory prediction method combining ship automatic identification system information and Back Propagation… More >

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