Routing aspects of electric vehicle drivers and their effects on network performance

Agrawal, Shubham; Zheng, Hong; Peeta, Srinivas; Kumar, Amit

doi:10.1016/j.trd.2016.04.002

Cited by 40 publications

(23 citation statements)

References 27 publications

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“…In this section, the distance range of capacitor powered EVs is set to be within 30 miles (Jiang and Xie, ; Xie and Jiang, ; Jing et al., ). The ICEV is also considered, the distance range of which is assumed to be infinity (Jiang et al., ; Agrawal et al., ).…”

Section: Resultsmentioning

confidence: 99%

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Multitype Recharge Facility Location for Electric Vehicles

Zhang

Rey

Waller

2018

Computer aided Civil Eng

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The motivation of this study is to minimize the system-level travel time costs and greenhouse emissions, which include tailpipe emissions by internal combustion engine vehicles (ICEVs) and smokestack emissions indirectly caused by electric vehicles (EVs), while satisfying EVs' replenishment need in transport networks subject to financial restraints for infrastructure development. In this study, we address recharge facility locations of EVs, where two types of recharge services are taken into account, that is, traditional charging stations and modern charging lanes. The multitype recharge facility location problem is formulated by employing the bilevel framework of the network design problem. In the lower-level program, the mixed-vehicular traffic assignment problem with en-route multitype recharge is employed, which accounts for both ICEVs and EVs with various driving ranges. The upper-level program aims to minimize the total system travel costs by selecting the optimal solution from a set of infrastructure design options considering both expansions of road capacities and provisions of multitype recharge facilities for EVs. In the algorithmic framework, we propose a tailored metaheuristic to solve medium to large instances. Systematic evaluation is conducted to test the efficacy of the proposed approach. The results highlight the impacts of traffic composition, distance ranges of EVs, budget levels and facility expenses on the project selection and evaluation. The results indicate that the two design objectives, to respectively minimize the network-wide travel time and greenhouse emissions, are conflicting for certain scenarios. Additionally, the results demonstrate the advantages of the network design problem (NDP) considering both multitype recharge service provision and road capacity

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Section: Resultsmentioning

confidence: 99%

“…Agrawal et al. () analyzed the differences between the route selection of battery EVs and conventional ICEVs, considering speed‐dependent energy consumption, and explored their influences on the outcomes of traffic assignment. Xie et al.…”

Section: Literature Reviewmentioning

confidence: 99%

Multitype Recharge Facility Location for Electric Vehicles

Zhang

Rey

Waller

2018

Computer aided Civil Eng

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“…AIMSUM simulation framework has proved its capability in the modelling of dynamic vehicle assessment. Various researchers utilised AIMSUM for modelling and calibrating individual vehicle dynamics in urban roadways consisting of homogeneous traffic [132][133][134]. However, for the mixed traffic scenario, Lenorzer et al [41] came up with a new model using the AIMSUM simulator.…”

Section: Simulation Software Developed From Safe Distancementioning

confidence: 99%

Simulation Strategies for Mixed Traffic Conditions: A Review of Car-Following Models and Simulation Frameworks

Matcha

Namasivayam

Fouladi

et al. 2020

Journal of Engineering

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The area of traffic flow modelling and analysis that bridges civil engineering, computer science, and mathematics has gained significant momentum in the urban areas due to increasing vehicular population causing traffic congestion and accidents. Notably, the existence of mixed traffic conditions has been proven to be a significant contributor to road accidents and congestion. The interaction of vehicles takes place in both lateral and longitudinal directions, giving rise to a two-dimensional (2D) traffic behaviour. This behaviour contradicts with the traditional car-following (CF) or one-dimensional (1D) lane-based traffic flow. Existing one-dimensional CF models did the inclusion of lane changing and overtaking behaviour of the mixed traffic stream with specific alterations. However, these parameters cannot describe the continuous lateral manoeuvre of mixed traffic flow. This review focuses on all the significant contributions made by 2D models in evaluating the lateral and longitudinal vehicle behaviour simultaneously. The accommodation of vehicle heterogeneity into the car-following models (homogeneous traffic models) is discussed in detail, along with their shortcomings and research gaps. Also, the review of commercially existing microscopic traffic simulation frameworks built to evaluate real-world traffic scenario are presented. This review identified various vehicle parameters adopted by existing CF models and whether the current 2D traffic models developed from CF models effectively captured the vehicle behaviour in mixed traffic conditions. Findings of this study are outlined at the end.

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“…Transportation is a series link of energy consumption and environmental pollution. Based on the characteristics of urban vehicle, EV is being popularized and applied in the field of urban traffic with the stimulation of various policy subsidies and demonstration operations (e.g., [3,4]). Electric vehicle has become an important technical direction to promote the energy saving and emission reduction of vehicles [5].…”

Section: Introductionmentioning

confidence: 99%

The Energy-Efficient Dynamic Route Planning for Electric Vehicles

Zhou

Wang

2019

Journal of Advanced Transportation

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Aiming to provide an approach for finding energy-efficient routes in dynamic and stochastic transportation networks for electric vehicles, this paper addresses the route planning problem in dynamic transportation network where the link travel times are assumed to be random variables to minimize total energy consumption and travel time. The changeable signals are introduced to establish state-space-time network to describe the realistic dynamic traffic network and also used to adjust the travel time according to the signal information (signal cycle, green time, and red time). By adjusting the travel time, the electric vehicle can achieve a nonstop driving mode during the traveling. Further, the nonstop driving mode could avoid frequent acceleration and deceleration at the signal intersections so as to reduce the energy consumption. Therefore, the dynamically adjusted travel time can save the energy and eliminate the waiting time. A multiobjective 0-1 integer programming model is formulated to find the optimal routes. Two methods are presented to transform the multiobjective optimization problem into a single objective problem. To verify the validity of the model, a specific simulation is conducted on a test network. The results indicate that the shortest travel time and the energy consumption of the planning route can be significantly reduced, demonstrating the effectiveness of the proposed approaches.

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Routing aspects of electric vehicle drivers and their effects on network performance

Cited by 40 publications

References 27 publications

Multitype Recharge Facility Location for Electric Vehicles

Multitype Recharge Facility Location for Electric Vehicles

Simulation Strategies for Mixed Traffic Conditions: A Review of Car-Following Models and Simulation Frameworks

The Energy-Efficient Dynamic Route Planning for Electric Vehicles

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