Demand Estimation for Aerial Vehicles in Urban Settings

被引:36
作者
Balac, Milos [1 ]
Schmid, Basil [1 ]
Vetrella, Amedeo R. [2 ]
Rothfeld, Raoul [3 ]
机构
[1] Swiss Fed Inst Technol, Inst Transport Planning, Zurich, Switzerland
[2] Univ Naples Federico II, Naples, Italy
[3] Bauhaus Luftfahrt, Taufkirchen, Germany
关键词
SIMULATION; OPERATIONS;
D O I
10.1109/MITS.2019.2919500
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
The idea of flying has always fascinated mankind. A century ago it became reality when in 1914 the first commercial flight was offered. In recent times, many entities are planning, developing and testing aerial vehicles and systems that will move goods and people in urban scenarios. Consequently, the need to develop appropriate planning tools and to investigate the potentials for this kind of transportation is needed. In this paper we present a methodology for simulation and demand estimation for personal aerial vehicles (PAVs) in urban settings. The methodology is then utilized to analyze the impacts of PAVs with different vehicle and system parameters on the demand. The findings show that with higher automation and falling prices, PAVs have a potential to be an important transportation mode, by serving not only middistance trips, but also shorter trips in urban settings. The analysis also show that unlike for car and public transport service, vehicle parameters of PAVs have a substantial impact on the demand and turnover. Furthermore, an optimization procedure that minimizes fixed costs of the PAVs by minimizing the fleet size and variable costs by minimizing the empty kilometers of PAVs for the estimated demand in the region of Zurich, Switzerland, is proposed. Optimized service ensures that much wider range of possible vehicle concepts can be utilized to serve the demand.
引用
收藏
页码:105 / 116
页数:12
相关论文
共 22 条
[11]   Agent-based simulation of autonomous taxi services with dynamic demand responses [J].
Horl, Sebastian .
8TH INTERNATIONAL CONFERENCE ON AMBIENT SYSTEMS, NETWORKS AND TECHNOLOGIES (ANT-2017) AND THE 7TH INTERNATIONAL CONFERENCE ON SUSTAINABLE ENERGY INFORMATION TECHNOLOGY (SEIT 2017), 2017, 109 :899-904
[12]  
Horni A., 2016, MULTIAGENT TRANSPORT, DOI [10.5334/baw, DOI 10.5334/BAW]
[13]  
Kelemen J, 2003, COMPUT INFORM, V22, P513
[14]  
Neubauer K., 2015, Unmanned aircraft systems (UAS) at airports: A primer (No. Project 03-30)
[15]   Agent-Based Modelling and Simulation to Assess the Impact of Parking Reservation System [J].
Ni, Xun-You ;
Sun, Daniel .
JOURNAL OF ADVANCED TRANSPORTATION, 2017,
[16]  
Rodier C., 2004, P 83 ANN M TRANSP RE P 83 ANN M TRANSP RE
[17]  
Schmitt D., 2016, AIR TRANSPORT SYSTEM, P19, DOI [10.1007/978-3-7091-1880-1_2, DOI 10.1007/978-3-7091-1880-1_2]
[18]  
Shamiyeh M., 2017, AEROSPACE 6 CEAS C, V913, P1, DOI DOI 10.1109/ICACCS.2017.8014695
[19]  
Steck F., 2018, P 97 ANN M TRANSP RE
[20]  
TomTom, 2017, CONG MEX CIT