Krol, Jakub;
Anvari, Bani;
Rafter, C;
Fleming, J;
Yan, X;
Lot, R;
(2024)
Modelling different penetration rates of automated eco-driving electric vehicles in an urban area.
IEEE Transactions on Intelligent Transportation Systems
(In press).
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Abstract
Eco-driving strategies have proven to be effective in providing energy savings for the vehicle that is utilising them. This paper explores the underinvestigated impact of eco-driving vehicles on other network participants adhering to conventional driving styles. An eco-driving strategy designed for an electric vehicle that trades off energy savings with naturalistic driving without relying on vehicle-to-infrastructure or vehicle-to-vehicle communication is extended using Gaussian Process Regression for real-time predictive speed optimization. It enables the assessment of its network effects in two scenarios: 1) a platoon and 2) an urban network simulation with mixed-mode traffic and varying demand levels. Initial validation involves an eco-driving vehicle responding to a platoon leader, influencing following vehicles governed by the Intelligent Driver Model (IDM). Further analysis introduces eco-vehicles into an IDM-governed network under different traffic conditions. Energy savings of up to 21% were achieved in cars following a vehicle that prioritises energy savings and, of up to 13% if they followed a vehicle that attempts to balance energy savings and conventional driving style. In the urban scenario, positive effects on other users are observed in high density traffic even if only a small number of eco-vehicles are present in the network. The largest energy savings achieved in conventional vehicles were 5.1% and were obtained for highdensity traffic and a network consisting of 25% of eco-vehicles.
| Type: | Article |
|---|---|
| Title: | Modelling different penetration rates of automated eco-driving electric vehicles in an urban area |
| Open access status: | An open access version is available from UCL Discovery |
| Publisher version: | https://ieeexplore.ieee.org/Xplore/home.jsp |
| Language: | English |
| Additional information: | This version is the author accepted manuscript. For information on re-use, please refer to the publisher's terms and conditions. |
| Keywords: | Eco-driving, Electric vehicles, ADAS, Energy efficiency, Driver satisfaction, Speed optimisation |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Civil, Environ and Geomatic Eng |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10196445 |
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