Operating electric taxi fleets: A new dispatching strategy with charging plans

Lu, Junli; Yeh, Mi-Yen; Hsu, Yi‐Cheng; Yang, Shun-Neng; Gan, Chai-Hien; Chen, Ming-Syan

doi:10.1109/ievc.2012.6183233

Cited by 38 publications

(19 citation statements)

References 2 publications

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“…In [ 11 , 12 ], according to the charging characteristics of PHEV taxis, a backward induction optimization algorithm to select charging time slots was proposed based on the time-of-use (TOU) electricity price and additional charging fees. In [ 13 ], a scheduling strategy for a taxi fleet, which included charging plans, was proposed based on clients' demands of taxi reservations to reduce the effect of the charging time and battery swapping on the operational time and revenue.…”

Section: Related Workmentioning

confidence: 99%

Charging Guidance of Electric Taxis Based on Adaptive Particle Swarm Optimization

Niu

Zhang

2015

The Scientific World Journal

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Electric taxis are playing an important role in the application of electric vehicles. The actual operational data of electric taxis in Shenzhen, China, is analyzed, and, in allusion to the unbalanced time availability of the charging station equipment, the electric taxis charging guidance system is proposed basing on the charging station information and vehicle information. An electric taxis charging guidance model is established and guides the charging based on the positions of taxis and charging stations with adaptive mutation particle swarm optimization. The simulation is based on the actual data of Shenzhen charging stations, and the results show that electric taxis can be evenly distributed to the appropriate charging stations according to the charging pile numbers in charging stations after the charging guidance. The even distribution among the charging stations in the area will be achieved and the utilization of charging equipment will be improved, so the proposed charging guidance method is verified to be feasible. The improved utilization of charging equipment can save public charging infrastructure resources greatly.

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Section: Related Workmentioning

confidence: 99%

Charging Guidance of Electric Taxis Based on Adaptive Particle Swarm Optimization

Niu

Zhang

2015

The Scientific World Journal

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“…Taxi service, which is an alternative urban transportation mode, is one of the most common personalized modes of transportation in many cities. The expansion of EVs to taxi fleets could be intriguing since EVs exhibit significant environmental benefits over ICE (internal combustion engine) based taxis 2 . As the operation of taxi fleets are mainly preferred in highly dense urban areas, 3 the deployment of EV taxi fleets could significantly reduce CO 2 emission and air pollution.…”

Section: Introductionmentioning

confidence: 99%

“…Issues related to CAEV taxis have acquired growing attention from researchers and automotive industries around the world. Though still the deployment of CAEV taxi fleets is in the early stage, several studies have been accomplished examining the feasibility of CAEV taxi fleets and their acceptability by the riders 2,10,11,12 . For instance, Lu et al 2 have proposed a dispatching strategy with charging plans for electric taxi considering whether such an electric taxi can reach the destination location.…”

Section: Introductionmentioning

confidence: 99%

Dynamic wireless charging for CAEV taxi fleet in urban environment

Vaidya

Mouftah

2020

Internet Technology Letters

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Advent of emerging technologies in the transportation shall led to expansion of electric vehicles (EVs) to urban taxi fleets. In future, Connected and Autonomous Electric Vehicle (CAEV) could likely be the next transportation revolution, especially in taxi fleets. With adoption of CAEVs, it is expected to improve road safety, optimize traffic flow, reduce fuel consumption, and minimize carbon emission in urban environment. However, limited driving range and longer recharging time would be key limitations for widespread deployment of CAEVs. Even though range anxiety caused by limited driving range can be minimized by recharging CAEVs with Dynamic Wireless Charging (DWC) that uses inductive power transfer (IPT) technology. However, due to the sparsely deployed DWC infrastructure, charging CAEV taxi using roadway IPT might be challenging. In this paper, we propose a taxi dispatching solution with DWC plan for urban CAEV taxi fleet in the DWC system using roadway IPT charging technique. Objectives are to minimize waiting time for rider and curtail arrival delay due to detour. Compared to primal dispatching strategy, the proposed strategy can perform better.

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“…Over the past decade, online management of taxis has become standard, and nowadays the focus is on operating a taxi fleet both at the microscopic level of detail and in real time. Due to advances in information and communications technology (ICT), various innovative solutions, such as shared taxis [4], electric taxis [5,6], and shared autonomous vehicles [7], have reshaped the traditional taxi service.…”

Section: Introductionmentioning

confidence: 99%