Modeling a Distance-Based Preferential Fare Scheme for Park-and-Ride Services in a Multimodal Transport Network

Chen, Xinyuan; Yin, Ruyang; An, Qinhe; Zhang, Yuan

doi:10.3390/su13052644

Cited by 7 publications

(3 citation statements)

References 33 publications

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“…It encourages people to use urban public transportation systems more and to integrate private car transportation into urban public transportation systems, which substantially simplifies travel for city residents living in the suburbs and corresponds to the low-carbon travel philosophy. The application and development space for P&R traffic modes is extensive [39][40][41]. For example, by the end of 2022, the number of P&R parking lots in Shanghai has grown to 20.…”

Section: Details Of Algorithm Instancesmentioning

confidence: 99%

Application of an Improved A* Algorithm for the Path Analysis of Urban Multi-Type Transportation Systems

Feng,

Zhang,

Zhu

2023

Applied Sciences

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The modern urban transportation service network could be split into unrestricted and restricted networks depending on whether travelers face limitations in route selection. Along with the continuous expansion of the city, it is difficult for travelers to find a more reasonable travel solution when confronted with such a complex transportation service network, which combines both unrestricted and restricted networks, especially for the park-and-ride (P&R) travel mode. This paper addresses the issue of route analysis in modern urban transportation service systems to provide travelers with reasonable travel solutions based on multiple types of transportation services. An improved A* algorithm is proposed to address the optimal path analysis for restricted networks to provide reasonable travel solutions for public transportation trips. Furthermore, by establishing the topological relationship between restricted and unrestricted networks, this paper presented an improved A* algorithm based on hybrid networks that solves the optimal path analysis problem for P&R trips, bringing convenience to many urban travelers.

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Section: Details Of Algorithm Instancesmentioning

confidence: 99%

Application of an Improved A* Algorithm for the Path Analysis of Urban Multi-Type Transportation Systems

Feng,

Zhang,

Zhu

2023

Applied Sciences

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“…Thus, SVR has received wide attention in SOH estimation. Although convex optimization problems [44] are able to solve large-scale practical engineering problems [9], random forest algorithm [53], not only has its unique merit in reducing the overfitting problems [55], but also has been widely used in feature screening [22]. In considering the nature and structure of the health of lithium-ion batteries, random forests are employed in this study.…”

Section: Literature Reviewmentioning

confidence: 99%

A state of health estimation method for electric vehicle Li-ion batteries using GA-PSO-SVR

Zhi

Wang

2022

Complex Intell. Syst.

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State of health (SOH) is the ratio of the currently available maximum capacity of the battery to the rated capacity. It is an important index to describe the degradation state of a pure electric vehicle battery and has an important reference value in evaluating the health level of the retired battery and estimating the driving range. In this study, the random forest algorithm is first used to find the most important health factors to lithium-ion batteries based on the dataset released by National Aeronautics and Space Administration (NASA). Then the support vector regression (SVR) algorithm is developed to predict the SOH of a lithium-ion battery. The genetic algorithm-particle swarm optimization (GA-PSO) algorithm is brought forward to optimize the parameter values of the SVR, which could improve the estimation accuracy and convergence speed. The proposed SOH estimation method is applied to four batteries and gets a root mean square error (RMSE) of 0.40% and an average absolute percentage error (MAPE) of 0.56%. In addition, the method is also compared with genetic algorithm-support vector regression (GA-SVR) and particle swarm optimization-support vector regression (PSO-SVR), respectively. The results show that (i) compared with the PSO-SVR method, the proposed method can decrease the average RMSE by 0.10%, and the average MAPE by 0.17%; (ii) compared with the GA-PSO method, number of iterations under the proposed method can be reduced by 7 generations.

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“…Demand is closely related to public transport for those who regularly use the P&R service. The existence of good public transport connectivity is essential when using the P&R system [57][58][59]. Also, large differences have been found between the impact on the demand of introducing a parking fee and the impact on reducing the use of the parking system [60].…”

Section: Pandr Potential Demand and Acceptancementioning

confidence: 99%

Planning a Park and Ride System: A Literature Review

Ortega

Tóth

Péter

2021

Future Transportation

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The Park and Ride (P&R) system is integrated into the transport infrastructure of a city’s urban environment. P&R is an intermodal connection point between private vehicles and public transport, and therefore is considered a fundamental element in transport planning. The planning of a P&R system is linked to numerous parameters related to transport planning, such as origin and purpose of travel in the P&R system, P&R location problem, P&R and potential demand, P&R and catchment area, P&R and public transport, and P&R in the future transportation (autonomous, electric vehicles). Thus, the planning process becomes essential for the successful implementation of the P&R system. However, most studies have shown each part of the planning process separately. Therefore, the researchers in this paper have conducted a comprehensive analysis of the available literature on P&R system planning, and studies that consider the planning sections separately are to be part of the complete research. In conclusion, the planning of P&R facilities should not be regarded as a separate mobility design element. Instead, it should be viewed as an essential component integrated into the city’s urban environment.

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Modeling a Distance-Based Preferential Fare Scheme for Park-and-Ride Services in a Multimodal Transport Network

Cited by 7 publications

References 33 publications

Application of an Improved A* Algorithm for the Path Analysis of Urban Multi-Type Transportation Systems

Application of an Improved A* Algorithm for the Path Analysis of Urban Multi-Type Transportation Systems

A state of health estimation method for electric vehicle Li-ion batteries using GA-PSO-SVR

Planning a Park and Ride System: A Literature Review

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