A route choice model for capturing driver preferences when driving electric and conventional vehicles

Research output: Contribution to journalJournal articleResearchpeer-review

58 Downloads (Orbit)

Abstract

Battery Electric Vehicles (BEVs) play an important role in the needed transition away from fossil fuels and Internal Combustion Engine Vehicles (ICEVs). Although transport planning models and routing problem solutions exist for BEVs, the assumption that BEV drivers search for the shortest path while constraining energy consumption does not have any empirical basis. This study presents a study of actual route choice behavior of drivers from 107 Danish households participating in a large-scale experiment with BEVs and at the same time driving their ICEVs. GPS traces from 8968 BEV and 6678 ICEV routes were map matched to a detailed road network to construct observed routes, and a route choice model was specified and estimated to capture behavioral differences related to the vehicle type. The results reveal that drivers had a higher sensitivity to travel time and trip length when driving BEVs, and to route directness after receiving the BEV, regardless of vehicle type. The results suggest the need to revise the assumptions of transport planning models and routing problems for BEVs in order not to fail to predict what drivers will do by ignoring differences and similarities related to vehicle type.
Original languageEnglish
Article number1149
JournalSustainability (Switzerland)
Volume12
Issue number3
ISSN2071-1050
DOIs
Publication statusPublished - 2020

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 7 - Affordable and Clean Energy
    SDG 7 Affordable and Clean Energy

Fingerprint

Dive into the research topics of 'A route choice model for capturing driver preferences when driving electric and conventional vehicles'. Together they form a unique fingerprint.

Cite this