| 1. |
- Cui, Shaohua, 1995, et al.
(författare)
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Integration of UAVs with public transit for delivery: Quantifying system benefits and policy implications
- 2024
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Ingår i: Transportation Research Part A: General. - 0965-8564. ; 183
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Tidskriftsartikel (refereegranskat)abstract
- The maturation and scalability of unmanned aerial vehicle (UAV) technology offer transformative opportunities to revolutionize prompt delivery. This study explores integrating UAVs with public transportation vehicles (PTVs) to establish a novel delivery paradigm that enhances revenue for public transit operators and improves transport system efficiency without compromising passenger convenience or operational efficiency. Employing hexagonal planning technology, this study identifies and quantifies the available spatio-temporal resources of PTVs for UAV integration. This involves aligning the spatio-temporal dynamics of prompt delivery orders with PTV ridership, based on field data from Beijing's Haidian District. Utilizing these outputs, we quantitatively analyze the benefits of integrating UAVs with PTVs on increasing public transit revenue, and potentials of reducing carbon emissions and mitigating congestion. Furthermore, we quantify the long-term benefits of UAV-PTV integration by predicting future increases in delivery demand. Based on obtained quantitative results, this study discusses practical and policy implications to support the sustainable integration of UAVs with PTVs.
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| 2. |
- Yao, Baozhen, et al.
(författare)
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Dynamic Pricing for Mobile Charging Service Considering Electric Vehicles Spatiotemporal Distribution
- 2023
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Ingår i: Smart Innovation, Systems and Technologies. - 2190-3026 .- 2190-3018. ; 356, s. 23-33
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Konferensbidrag (refereegranskat)abstract
- As mobile charging service has the advantages of flexible charging and simple operation, it is selected by more and more users of electric vehicles. However, due to the differences in road network density and traffic flow distribution, the uneven distribution of charging demand occurs in different regions. It reduces the service efficiency of mobile charging vehicles during the peak charging demand period, thus affecting the final revenue of operators. In order to solve this problem, this paper proposes a dynamic pricing strategy considering the spatiotemporal distribution of charging demand to induce users to transfer between different regions, which can alleviate the phenomenon that users wait too long during peak demand. In order to realize the city-level operation of mobile charging service, we divide the region into hexagons and make statistics on the charging demand in each region. The established demand updating model can reflect the impact of charging price on users’ charging behavior. Finally, we simulate the generation of charging demand in Haidian District, Beijing. According to the demand of each area, a thermodynamic diagram of charging demand is generated.
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| 3. |
- Yao, Baozhen, et al.
(författare)
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LSTM-Based Vehicle Trajectory Prediction Using UAV Aerial Data
- 2023
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Ingår i: Smart Innovation, Systems and Technologies. - 2190-3026 .- 2190-3018. ; 356, s. 13-21
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Konferensbidrag (refereegranskat)abstract
- Accurately predicting the trajectory of a vehicle is a critical capability for autonomous vehicles (AVs). While human drivers can infer the future trajectory of other vehicles in the next few seconds based on information such as experience and traffic rules, most of the widely used Advance Driving Assistance Systems (ADAS) need to provide better trajectory prediction. They are usually only of limited use in emergencies such as sudden braking. In this paper, we propose a trajectory prediction network structure based on LSTM neural networks, which can accurately predict the future trajectory of a vehicle based on its historical trajectory. Unlike previous studies focusing only on trajectory prediction for highways without intersections, our network uses vehicle trajectory data from aerial photographs of intersections taken by Unmanned Aerial Vehicle (UAV). The speed of vehicles at this location fluctuates more frequently, so predicting the trajectory of vehicles at intersections is of great importance for autonomous driving.
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| 4. |
- Cui, Shaohua, 1995, et al.
(författare)
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Delay-throughput tradeoffs for signalized networks with finite queue capacity
- 2024
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Ingår i: Transportation Research Part B: Methodological. - 0191-2615. ; 180
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Tidskriftsartikel (refereegranskat)abstract
- Network-level adaptive signal control is an effective way to reduce delay and increase network throughput. However, in the face of asymmetric exogenous demand, the increase of network performance via adaptive signal control alone is at the expense of service fairness (i.e., phase actuation fairness and network resource utilization fairness). In addition, for oversaturated networks, arbitrary adaptive signal control seems to have little effect on improving network performance. Therefore, under the assumption that the mean routing proportions/turn ratios of vehicles at intersections are fixed, this study investigates the problem of optimally allocating input rates to entry links and simultaneously finding a stabilizing signal control policy with phase fairness. We model the stochastic optimization problem of maximizing network throughput subject to network stability (i.e., all queue lengths have finite means) and average phase actuation constraints to bridge the gap between stochastic network stability control and convex optimization. Moreover, we further propose a micro-level joint admission and bounded signal control algorithm to achieve network stability and throughput optimization simultaneously. Joint control is implemented in a fully decomposed and distributed manner. For any arrival rate, joint control provably achieves network throughput within O(1/V) of optimality while trading off average delay with O(V), where V is an adjusted control parameter. Through a comparative simulation of a real network with 256 O-D pairs, the proposed joint control keeps network throughput at maximum, guarantees service fairness, and fully utilizes network capacity (i.e., increases network throughput by 17.54%).
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| 5. |
- Cui, Shaohua, 1995, et al.
(författare)
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Joint optimal vehicle and recharging scheduling for mixed bus fleets under limited chargers
- 2023
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Ingår i: Transportation Research Part E. - : Elsevier BV. - 1366-5545 .- 1878-5794. ; 180
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Tidskriftsartikel (refereegranskat)abstract
- Owing to the high acquisition costs, maintenance expenses, and inadequate charging infrastructure associated with electric buses, achieving a complete replacement of diesel buses with electric counterparts in the short term proves challenging. A substantial number of bus operators currently find themselves in a situation where they must integrate electric buses with their existing diesel fleets. Confronted with the constraints of limited electric bus range and charging infrastructure, the primary concern for bus operators is how to effectively utilize their mixed bus fleets to adhere to pre-established bus timetables while maximizing the deployment of electric buses, known for their zero pollution and cost-effective travel. Consequently, this paper introduces the concept of the joint optimization problem for vehicle and recharging scheduling within mixed bus fleets operating under constrained charging conditions. To tackle this issue, a mixed integer linear model is formulated to optimize the coordination of bus schedules and recharging activities within the context of limited charging infrastructure. By establishing a set of feasible charging activities, the problem of electric buses queuing for charging at constrained charging stations is transformed into a linear optimization model constraint. Numerical simulations are conducted within the real transit network of the Dalian Economic Development Zone in China. The results indicate that the judicious joint optimization of vehicle and charging scheduling significantly enhances the service frequency of electric buses while reducing operational costs for bus lines. Notably, the proportion of total trips performed by electric buses rises to 80.4%.
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| 6. |
- Zhang, Zhe, et al.
(författare)
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Environmental impacts of ridesplitting considering modal substitution and associations with built environment
- 2024
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Ingår i: Transportation Research Part D: Transport and Environment. - 1361-9209. ; 130
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Tidskriftsartikel (refereegranskat)abstract
- Ridesplitting promises to reduce emissions. Previous studies mainly compared ridesplitting with single rides like taxis, leaving its impact on other modes unclear. This study quantifies the reduction or increase in CO2 emissions due to ridesplitting from a modal substitution perspective and explore the nonlinear impacts of built environment factors on emission reductions. Considering different urban contexts, we choose Chengdu and Xi'an as representative examples for analysis. The results indicate that most ridesplitting trips lead to an increase in CO2 emissions when compared to other modes. In Chengdu, a mere 8.92% of ridesplitting trips result in emission reduction, whereas in Xi'an, this figure stands at 4.68%. Emission reduction is predominantly linked to taxi substitution. Moreover, many built environment factors exhibit positive relationship with the increase in emission resulting from ridesplitting, and present nonlinear and threshold effects. The findings offer a framework to assess ridesplitting's environmental benefits, aiding urban planners and policymakers.
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