Analysis of Urban Electric Vehicle Adoption Based on Operating Costs in Urban Transportation Network

Ma, Jie; Zhu, Yu; Chen, Dawei; Zhang, Chenhao; Song, Maocan; Zhang, Honggang; Chen, Jingxu; Zhang, Kai

doi:10.3390/systems11030149

Cited by 3 publications

(2 citation statements)

References 51 publications

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“…The existing scientific landscape indicates that, for the moment, researchers place more emphasis on immediate concerns and challenges, such as functionality and accuracy, rather than delving into the complexities of energy-related aspects, as agricultural robotics, especially in the context of electric vehicles, is still in its nascent stages. In contrast, considerable attention is already paid to the energy efficiency of autonomous vehicles designed for urban environments [49][50][51][52], a fact that further highlights the identified research gap and the need for studies providing a deeper investigation of the energy performance of agricultural robotic systems. Therefore, works focused on the energy dynamics, consumption patterns and the overall performance of the agricultural robotic systems are expected to increase soon.…”

Section: Introductionmentioning

confidence: 99%

Power Consumption Analysis of a Prototype Lightweight Autonomous Electric Cargo Robot in Agricultural Field Operation Scenarios

Loukatos,

Arapostathis,

Karavas

et al. 2024

Energies

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The continuous growth of the urban electric vehicles market and the rapid progress of the electronics industry create positive prospects towards fostering the development of autonomous robotic solutions for covering critical production sectors. Agriculture can be seen as such, as its digital transformation is a promising necessity for protecting the environment, and for tackling the degradation of natural resources and increasing nutritional needs of the population on Earth. Many studies focus on the potential of agricultural robotic vehicles to perform operations of increased intelligence. In parallel, the study of the activity footprint of these vehicles can be the basis for supervising, detecting the malfunctions, scaling up, modeling, or optimizing the related operations. In this regard, this work, employing a prototype lightweight autonomous electric cargo vehicle, outlines a simple and cost-effective mechanism for a detailed robot’s power consumption logging. This process is conducted at a fine time granularity, allowing for detailed tracking. The study also discusses the robot’s energy performance across various typical agricultural field operation scenarios. In addition, a comparative analysis has been conducted to evaluate the performance of two different types of batteries for powering the robot for all the operation scenarios. Even non-expert users can conduct the field operation experiments, while directions are provided for the potential use of the data being collected. Given the linear relationship between the size and the consumption of electric robotic vehicles, the energy performance of the prototype agricultural cargo robot can serve as a basis for various studies in the area.

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Section: Introductionmentioning

confidence: 99%

Power Consumption Analysis of a Prototype Lightweight Autonomous Electric Cargo Robot in Agricultural Field Operation Scenarios

Loukatos,

Arapostathis,

Karavas

et al. 2024

Energies

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show abstract

“…Ahn et al developed and investigated the impact of a multiobjective user equilibrium on a large-scale city network considering the difference in energy consumption of EVs and GVs [21]. Ma et al proposed a stochastic user equilibrium model considering the different operation costs of EVs and GVs to analyse the adoption of EVs in an urban transportation network [22]. These studies have been conducted on urban transportation networks for EVs' intra-city travel, and EVs' driving range limits and recharging requirements are not considered.…”

Section: Introductionmentioning

confidence: 99%

A Reliability-Based Network Equilibrium Model with Electric Vehicles and Gasoline Vehicles

Tu,

Li,

2024

PROMTT

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With the popularity of electric vehicles, they have become an indispensable part of traffic flow on the road network. This paper presents a reliability-based network equilibrium model to realise the traffic flow pattern prediction on the road network with electric vehicles and gasoline vehicles, which incorporates travel time reliability, electric vehicles’ driving range and recharge requirement. The mathematical expression of reliable path travel time is derived, and the reliability-based network equilibrium model is formulated as a variational inequality problem. Then a multi-criterion labelling algorithm is proposed to solve the reliable shortest path problem, and a column-generation-based method of the successive average algorithm is proposed to solve the reliability-based network equilibrium model. The applicability and efficiency of the proposed model and algorithm are verified on the Nguyen-Dupuis network and the real road network of Sioux Falls City. The proposed model and algorithm can be extended to other road networks and help traffic managers analyse traffic conditions and make sustainable traffic policies.

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Identifying Critical Links in Degradable Road Networks Using a Traffic Demand-Based Indicator

Tu,

He,

Lai

et al. 2024

Sustainability

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The primary traffic-based indicators for identifying critical links account for travel time, transportation efficiency, and traffic demand. These indicators are seldom applied to scenarios in which link capacity degradation occurs across the entire network. In addition, the commonly used traffic demand-based indicator, known as unsatisfied demand, can only work when there are disconnected origin–destination (OD) pairs in the network. In this context, this study incorporates the concept of a degradable road network to represent such scenarios and introduces a new network-wide traffic demand-based indicator, defined as late arrival demand (LAD), to identify critical links. Specifically, we built a late arrival rate (LAR)-based user equilibrium (UE) model to capture travel behavior and estimate the LAD in degradable road networks. Then, LAD and four other indicators were introduced to identify critical links in the framework of the LAR-based UE model. Finally, the Nguyen–Dupuis and Sioux Falls networks were employed for numerical experiments. The results, under various levels of traffic demand and degradation, demonstrate that LAD is a flexible and effective network-wide traffic demand-based indicator. This new approach provides insights that can help managers assess link criticality in degradable road networks from the perspective of traffic demand.

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Analysis of Urban Electric Vehicle Adoption Based on Operating Costs in Urban Transportation Network

Cited by 3 publications

References 51 publications

Power Consumption Analysis of a Prototype Lightweight Autonomous Electric Cargo Robot in Agricultural Field Operation Scenarios

Power Consumption Analysis of a Prototype Lightweight Autonomous Electric Cargo Robot in Agricultural Field Operation Scenarios

A Reliability-Based Network Equilibrium Model with Electric Vehicles and Gasoline Vehicles

Identifying Critical Links in Degradable Road Networks Using a Traffic Demand-Based Indicator

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