Abstract
With the development of technology, shared autonomous vehicles may become one of the main traffic modes in the future. Especially, shared autonomous vehicle reservation system, commuting, and other trips with fixed departure time mostly submit their travel requests in advance. Therefore, it is important to reasonably match shared autonomous vehicles and reservation demands. In this paper, reservation requests are divided into short-term and long-term requests by inputting requests in a more realistic way. An integer linear programming model considering operator scheduling cost and system service level is established. A detailed scheme considering rolling horizon continuity and ridesharing is used to improve the dispatching result. Based on traffic data in Delft, the Netherlands, 164 scenarios are tested in which the parking cost, fuel cost, ridesharing effect, service level, and network size are analyzed. The results show that a better relocation and ridesharing matching scheme can be obtained when the rolling horizon is small, while the overall effect is better when the rolling horizon is large. Moreover, the buffer time, distance, and travel time limit for vehicle relocation should be selected according to the request quantity and the calculation time requirement. The result can provide a suggestion for the dispatching of shared autonomous vehicle reservation system with ridesharing.
Highlights
With the rapid development of science and technology, autonomous vehicles, which can improve safety, alleviate traffic congestion, and reduce pollutant emissions and energy consumption, have become a hot issue in the automotive field in recent years. e introduction of autonomous vehicles will have a great impact on the future travel mode, especially mass transit [1]
Shared autonomous vehicles (SAVs) apply automatic driving technology to car sharing and taxi services, which is convenient for travelers: travelers do not need to get to the car sharing location before they can use it
When passengers are willing to share a vehicle with other passengers on similar routes, the fleet size and vehicle miles travelled (VMT) of the SAV system can be further reduced [4,5,6,7]. erefore, the wide use of SAVs can effectively reduce the number of vehicles to improve the utilization rate of vehicles
Summary
With the rapid development of science and technology, autonomous vehicles, which can improve safety, alleviate traffic congestion, and reduce pollutant emissions and energy consumption, have become a hot issue in the automotive field in recent years. e introduction of autonomous vehicles will have a great impact on the future travel mode, especially mass transit [1]. Using traffic data from Delft in the Netherlands, the influence of different optimization times and scopes on the matching and scheduling of SAV reservation requests, such as parking costs, fuel costs, and penalties, is tested. In order to improve the performance of the SAV reservation system, the reservation request is divided into the short-term and long-term request It is more realistic when requests enter the system, and it can better reflect the relative state between requests and optimization time. A detailed rolling horizon continuity scheme is proposed, and the best system parameter setting under different goals is described by analyzing system scheduling cost, and service-level and operation efficiency. In the literature review part, the demand matching and scheduling methods of traditional shared vehicle reservation services and shared autonomous vehicle reservation services are summarized, respectively, and the research motivation is clarified. The research conclusion and future research direction are put forward
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