1. A route choice model for capturing driver preferences when driving electric and conventional vehicles
- Author
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Thomas Kjær Rasmussen, Carlo Giacomo Prato, and Anders Fjendbo Jensen
- Subjects
Operations research ,Computer science ,direct routes ,020209 energy ,Geography, Planning and Development ,TJ807-830 ,utility maximization ,02 engineering and technology ,Management, Monitoring, Policy and Law ,TD194-195 ,Renewable energy sources ,0502 economics and business ,0202 electrical engineering, electronic engineering, information engineering ,GE1-350 ,SDG 7 - Affordable and Clean Energy ,route choice behavior ,050210 logistics & transportation ,Transportation planning ,Environmental effects of industries and plants ,internal combustion engine vehicles ,Renewable Energy, Sustainability and the Environment ,business.industry ,05 social sciences ,Trip length ,battery electric vehicles ,Energy consumption ,discrete choice models ,Environmental sciences ,driver preferences ,Shortest path problem ,Global Positioning System ,driving behavior ,Routing (electronic design automation) ,business - 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.
- Published
- 2020
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