TY - JOUR AU - Hu, Hongyu AU - Cheng, Ming AU - Li, Zhengyi AU - Wang, Zixuan AU - Jin, Sheng AU - Gao, Zhenhai AU - Shen, Chuanliang TI - A cooperative interaction strategy for vehicle platoons to obtain merging gaps in connected environments JF - PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART D-JOURNAL OF AUTOMOBILE ENGINEERING J2 - P I MECH ENG D-J AUT VL - 2024 PY - 2024 SN - 0954-4070 DO - 10.1177/09544070231220701 UR - https://m2.mtmt.hu/api/publication/34580605 ID - 34580605 AB - Vehicle platoons can significantly improve traffic throughput and reduce fuel consumption and emissions. In the formation of platoons, it is crucial to generate safe merging gaps. This process requires appropriate cooperative management and control strategies. This study proposes a cooperative interaction strategy for vehicle platoons, including a communication management system and vehicle control strategies. These strategies can reduce velocity fluctuation in the process of gap generation and improve traffic performance. First, a communication management system within a platoon was developed, according to the standard communication protocol (SAE J2735), ensuring that external vehicles can join the platoon efficiently and orderly. Next, a cooperative adaptive cruise control (CACC) system was designed, which adopts feedforward and feedback control. Furthermore, the influence of increasing gaps on the stability of the platoon was considered. A cooperative control strategy for a virtual guiding vehicle (VGV) was introduced to switch the following target and linearly change the distance input of the controller. In this way, the downstream vehicles were guided to smoothly generate a safe merging gap, which can reduce speed fluctuation, and ensure the stability and safety of the platoon. Finally, the entire process of interaction in a vehicle platoon was tested in a simulation environment. The results showed that, compared with the parameter adaptive control strategy, the maximum velocity overshoot of the platoon vehicles was reduced by 56%, recovery stabilization time was reduced by 47%, and vehicle jitter was reduced by 43%. The driving security and platoon stability were both within the control boundaries set for evaluation. LA - English DB - MTMT ER - TY - JOUR AU - Li, Yun AU - Zhang, Shengrui AU - Pan, Yingjiu AU - Zhou, Bei AU - Peng, Yanan TI - Exploring the Stability and Capacity Characteristics of Mixed Traffic Flow with Autonomous and Human-Driven Vehicles considering Aggressive Driving JF - JOURNAL OF ADVANCED TRANSPORTATION J2 - J ADV TRANSPORT VL - 2023 PY - 2023 SP - 1 EP - 21 PG - 21 SN - 0197-6729 DO - 10.1155/2023/2578690 UR - https://m2.mtmt.hu/api/publication/33684057 ID - 33684057 AB - With the popularization of autonomous vehicle (AV) technology, mixed traffic flows that consist of AVs and human-driven vehicles (HDVs) will appear in the real world. Although many studies of the features of mixed traffic flow have been carefully evaluated, few studies have focused on the effect of aggressive driving performance on mixed traffic flow. This study aims to develop an approach to evaluate the effects of aggressive driving on the stability and capacity performance under the conditions of AV and HDV mixed traffic flow. First, since a car-following model can describe the relationship between vehicles, we calibrate a car-following model for aggressive driving and nonaggressive driving behaviors based on real traffic data and previous research results. Then, in a mixed traffic flow environment, a basic linear stability formula and capacity calculation expression are developed that consider the effects of vehicle order on the capacity. Finally, because the proportion of aggressive driving and aggressive driving parameters may change, nine combinations of three aggressive driving proportions and three driving parameter cases are used for the sensitivity analysis. The results indicate that the effect of aggressive driving on mixed traffic flow is complex. When the proportion of aggressive driving is less than 35%, the increase in the proportion of aggressive driving increases the traffic capacity and reduces the unstable part. However, when the proportion of aggressive driving is greater than 35%, the increase in the proportion of aggressive driving increases the unstable part. When the penetration rate of AVs exceeds 0.490, mixed traffic flow remains stable at all aggressive driving proportions. In addition, the capacity of a mixed traffic flow may be improved as the penetration rate of AVs increases. To a certain extent, these conclusions provide a theoretical basis for formulating different management modes of AVs and HDVs. LA - English DB - MTMT ER - TY - JOUR AU - Mohammed, Dilshad AU - Horváth, Balázs TI - Vehicle Automation Impact on Traffic Flow and Stability: A Review of Literature JF - ACTA POLYTECHNICA HUNGARICA J2 - ACTA POLYTECH HUNG VL - 20 PY - 2023 IS - 5 SP - 129 EP - 148 PG - 20 SN - 1785-8860 DO - 10.12700/APH.20.5.2023.5.9 UR - https://m2.mtmt.hu/api/publication/33831491 ID - 33831491 LA - English DB - MTMT ER - TY - JOUR AU - Péter, Tamás AU - Háry, A AU - Szauter, Ferenc AU - Szabó, Krisztián AU - Vadvári, Tibor AU - Lakatos, István TI - Mathematical Description of the Universal IDM - some Comments and Application JF - ACTA POLYTECHNICA HUNGARICA J2 - ACTA POLYTECH HUNG VL - 20 PY - 2023 IS - 7 SP - 99 EP - 115 PG - 17 SN - 1785-8860 DO - 10.12700/APH.20.7.2023.7.6 UR - https://m2.mtmt.hu/api/publication/33930648 ID - 33930648 N1 - Funding Agency and Grant Number: Ministry of Technology and Industry National Research [TKP2021-NKTA-48] Funding text: The research presented in this paper was carried out as part of the TKP2021-NKTA-48 a Ministry of Technology and Industry National Research, With support from the Development and Innovation Fund, a Funded by the TKP2021-NKTA tender program" was realized. LA - English DB - MTMT ER - TY - JOUR AU - Xu, Yang AU - Zhang, Changjian AU - He, Jie AU - Liu, Ziyang AU - Chen, Yikai AU - Zhang, Hao TI - Comparisons on methods for identifying accident black spots using vehicle kinetic parameters collected from road experiments JF - Journal of Traffic and Transportation Engineering (English Edition) J2 - Journal of Traffic and Transportation Engineering (English Edition) VL - 10 PY - 2023 IS - 4 SP - 659 EP - 674 PG - 16 SN - 2095-7564 DO - 10.1016/j.jtte.2021.08.007 UR - https://m2.mtmt.hu/api/publication/34100386 ID - 34100386 N1 - School of Transportation, Southeast University, Nanjing, 211189, China School of Automotive and Transportation Engineering, Hefei University of Technology, Hefei, 230009, China Export Date: 26 September 2023 Correspondence Address: He, J.; School of Transportation, China; email: hejie@seu.edu.cn LA - English DB - MTMT ER - TY - JOUR AU - Kiss, Gábor TI - How to impede the external manipulation of autonomous cars? JF - JOURNAL OF INTELLIGENT & FUZZY SYSTEMS J2 - J INTELL FUZZY SYST VL - 43 PY - 2022 IS - 2 SP - 1761 EP - 1769 PG - 9 SN - 1064-1246 DO - 10.3233/JIFS-219277 UR - https://m2.mtmt.hu/api/publication/32808162 ID - 32808162 LA - English DB - MTMT ER - TY - JOUR AU - Horváth, Zsolt Csaba AU - Buics, László AU - Földesi, Péter AU - Eisingerné Balassa, Boglárka TI - The Role of Hungarian Traffic Rules Education and Examination System – a Quality Function Deployment Approach JF - ACTA POLYTECHNICA HUNGARICA J2 - ACTA POLYTECH HUNG VL - 19 PY - 2022 IS - 7 SP - 7 EP - 26 PG - 20 SN - 1785-8860 UR - https://m2.mtmt.hu/api/publication/33023630 ID - 33023630 LA - English DB - MTMT ER - TY - JOUR AU - Szakács, Tamás TI - A dynamic model of a pneumobile vehicle JF - JOURNAL OF PHYSICS-CONFERENCE SERIES J2 - J PHYS CONF SER VL - 1935 PY - 2021 IS - 1 SN - 1742-6588 DO - 10.1088/1742-6596/1935/1/012016 UR - https://m2.mtmt.hu/api/publication/32050254 ID - 32050254 LA - English DB - MTMT ER - TY - CHAP AU - Zsombor, Géczi AU - Laufer, Edit ED - Szakál, Anikó TI - Fuzzy-based Braking System Model in Driver Assisted Technology T2 - 15th IEEE International Symposium on Applied Computational Intelligence and Informatics SACI 2021 PB - IEEE CY - Budapest CY - Piscataway (NJ) SN - 9781728195438 PY - 2021 SP - 311 EP - 316 PG - 6 DO - 10.1109/SACI51354.2021.9465597 UR - https://m2.mtmt.hu/api/publication/32087174 ID - 32087174 N1 - Funding Agency and Grant Number: Obuda University; Hungarian Fuzzy Association, Department of the John von Neumann Computer Society, Hungary Funding text: The research was supported by the Obuda University and the Hungarian Fuzzy Association, which is a Department of the John von Neumann Computer Society, Hungary. AB - The development of self-driving cars has emerged as a key research areas. Autonomous, or semi-autonomous vehicles can be classified into six different levels based on the driver assistance technology advancements, defined by the Society of Automotive Engineers (SAE). In this paper, a braking system model is presented in a Driver Assistance level implementation. In the proposed model one of the most commonly used computational intelligence methods, fuzzy inference, is applied to handle the arising uncertainties and imprecision. In real-time applications computational requirements should be reduced. For this reason a hierarchical Sugeno model is implemented to evaluate the necessary deceleration in an ideal environment, taking into account certain traffic signals. LA - English DB - MTMT ER - TY - CHAP AU - Péter, Tamás AU - Lakatos, István AU - Háry, András AU - Szauter, Ferenc ED - Péter, Tamás TI - Az Univerzális IDM modell matematikai felírása és alkalmazási területe T2 - XIV. IFFK 2020: Innováció és fenntartható felszíni közlekedés konferencia PB - Magyar Mérnökakadémia (MMA) CY - Budapest SN - 9789638887566 PY - 2020 SP - 1 EP - 7 PG - 7 UR - https://m2.mtmt.hu/api/publication/31681874 ID - 31681874 LA - Hungarian DB - MTMT ER -