Transportation Research Interdisciplinary Perspectives最新文献

Drone traffic, consisting of anything from small quadcopters for video and photography to large eVTOL transporting people, is expected to grow rapidly as soon as the challenges currently barring urban flights can be solved. One of the main challenges is how to automate authorization while both keeping full control over where and how drones fly over specific areas, and at the same time allowing the operators the freedom they require to successfully provide their services. While restrictions are necessary, being overly restrictive on plans has a negative impact on capacity, safety and efficiency. In this article we propose the combination of no-fly zones and flight grids into design elements for airspace design, to be used only where and when necessary. City planners can use these design elements to make both strategic decisions and real-time updates, and thereby set the rules for an automated system for planning and authorization. We describe the design elements, how to automatically find the optimal end-to-end route between or through these elements, a set of modifications or extension to improve flexibility even more, and demonstrate the efficacy of the approach through example airspace design patterns and by showing the resulting traffic in a drone traffic simulator.

Long-term exposure to aircraft noise has been linked to various negative health impacts, with annoyance playing a key role in mediating stress-related health effects. Fairness can be seen as a fundamental aspect potentially reducing annoyance reactions. This study delves into the concept of fairness within airport management, drawing on research from fields such as social and organizational psychology. It specifically examines the viewpoint of noise-affected residents, offering insights into their perception of fairness in regard to airport management. The research involved focus group discussions and in-depth interviews at three different European airports in Germany and France. These sessions were transcribed and analyzed using qualitative content analysis. Participants were surveyed based on their exposure to lower (≤55 dB L_den) and higher (>55 dB L_den) levels of aircraft noise. The findings indicate that distributive, procedural, informational, and interpersonal fairness are viewed as important elements for fostering a fair and neighborly relationship with the airport. Residents emphasized the importance of receiving adequate compensation for the disadvantages they incur due to their proximity to the airport, such as aircraft noise-related sleep disturbance. Additionally, residents expressed the need for earnest inclusion in the decision-making processes, as well as access transparent information. Additional focus group discussions were conducted to validate the results and to gather input from affected residents, aiming to establish a fair and neighborly relationship. Based on these insights, recommendations are formulated for airport managers from the perspective of the affected residents, emphasizing the aim of fostering a fair and neighborly relationship.

Naturalistic driving studies (NDS) are an emerging method of collecting driving data from drivers in instrumented vehicles undertaking everyday trips without experimental control. A computational literature review was performed to assess the NDS research domain that aimed to quantitatively describe the extent and structure of existing applications of NDS data. A corpus of 1120 documents was analysed using the methods of scientometrics and text mining to identify prominent contributors and topics. NDS research saw particular prominence in the US and China, however, international collaboration was limited compared to other disciplines. Network mapping of documents and words showed a high degree of overlap in the data sources, types, and analysis methodologies across NDS research. In the context of a safe system approach to road safety, driver-centred behaviours and characteristics such as distraction, risk, and older age were most relevant in terms of number and occurrence, in contrast to relatively underrepresented aspects of road infrastructure and vehicles.

Electric car charging stations are in high demand as a result of the development of the e-mobility sector and the adoption of electric vehicles in transportation. This study aims to construct and analyze a stand-alone solar PV-powered electric car charging station to fulfil electric vehicle load demand and make recommendations for optimizing its operation. The goal is to achieve 3D’s i.e., Decarbonization, Digitalization and Decentralization in both the transport and power supply (electricity supply). Advancing towards attaining 3D’s goal, an off-grid solar PV-powered EV charging station was built at the University of Sharjah to meet the load demand. The EV charging station includes PV panels, inverters, energy storage devices and EV charging outlets. A solar PV system of 7.4 kWp with an energy storage capacity of 34.56 kWh is installed. A battery inverter of 4.6 kW is incorporated to meet the load demand of three electrical vehicles simultaneously. The performance of the system is monitored over a year. The EV charging station is in off-grid mode; thus, it is following the load demand for PV energy production. The findings reveal that the total energy production by the PV system is 2971.59 kWh from which the direct consumption is 383.77 kWh (12.91 %), and 2587.83 kWh (87.09 %) is stored in the energy storage devices. The total energy consumption by electric vehicles is 2379.01 kWh of which 1995.24 kWh (83.87 %) is taken from the battery bank. The PV system is working at 24.58 % of its full capacity. By elevating the daily load demand to 33 kWh, the full utilization of the solar resource can be achieved. To evaluate the adverse effect of dust, natural dust is allowed to settle down on the surface of PV panels continuously for 322 days. A linear degradation was recorded in the performance ratio from 77.92 % to 27.30 % in 218 days. Thereafter a plateau was attained and insignificant variation (min. 26.36 % and max. 33.78 %) was observed in the next 104 days. It is concluded that once a thick layer of dust forms on the surface of the PV panels, further dust accumulation becomes minimal.

The Central Business Districts (CBDs) of Dhaka are characterized by heavy traffic congestion, air pollution and peak office hour commuting density. Pedestrian-friendly environment is crucial for accessing the CBDs as it reduces auto-mobile dependency and encourages transit use. As of now, no research has assessed the walkability of Dhaka’s CBDs considering meso-scale factors such as land use diversity, density, street connectivity and micro-scale factors such as footpath continuity and quality, accessibility, safety, security, amenity and comfort of the streets. This paper evaluates the built environment attributes of total 15 wards across core CBDs of Dhaka North City Corporation (DNCC) and Dhaka South City Corporation (DSCC): Motijheel, Karwan Bazar, Mohakhali, Gulshan-Banani, and Mirpur to objectively assess walkability at both meso and micro scales. At meso-scale, a walkability index is generated that categorizes the wards into the most and least walkable using GIS, with Mirpur DNCC Ward-03 identified as the most walkable and Motijheel DSCC Ward-08 as the least walkable. At micro-scale, the walking environments in Mirpur Ward-03 and Motijheel Ward-08 are assessed based on Multi-Criteria Decision-Making (MCDM) approach. Results reveal several challenges such as narrow and discontinuous footpaths, presence of multiple barriers including utility poles, pillars, trees and, limited accessibility in Mirpur Ward-03 and garbage dumping, illegal car parking, haphazard hawker encroachments in Motijheel Ward-08. Our findings identify targeted areas needing improvement to enhance overall pedestrian-friendliness of the CBDs. The methodology followed in this study could be applied to evaluate the walkability of CBDs worldwide.

California possesses multiple major freight gateway and logistics facilities that serve both the state and the entire U.S. But the economic, environmental, and local community impacts of trucks, especially heavy-duty trucks that are currently essential to our supply chains and freight transportation system remain poorly measured due to the lack of comprehensive and detailed truck activity data. This paper describes the pilot implementation of the real-time, scalable, and cost-efficient Freight Mobility Living Laboratory (FML2). This system provides truck characterizations across multiple attributes, such as truck body types, axle-based and Gross Vehicle Weight Rating (GVWR)-based classification and is currently deployed at 30 detection locations in Southern California along major freight corridors to support freight modeling and analysis needs. This paper details the design of the FML2 from edge data processing, predictive model development, communication architecture, and backend data storage to the real-time data dashboard to visualize the classification results. Three case studies have been presented at the end of the paper to demonstrate the potential of FML2 for use by both researchers and practitioners to gain further insights on truck activities.