A Route Choice Model for Capturing Driver Preferences When Driving Electric and Conventional Vehicles

Anders F Jensen,Carlo G Prato,Thomas K Rasmussen

doi:10.3390/su12031149

Anders F Jensen, Carlo G Prato + Show 1 more

Open Access

https://doi.org/10.3390/su12031149

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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.

Highlights

The growing need to reduce emissions from the transport sector and the dependence on fossil fuels is driving the significant efforts of governments to incentivize the market diffusion of Battery Electric Vehicles (BEVs)
As there is no study about the actual behavior of BEV drivers, its underlying factors, and possible differences with respect to the route choice behavior of Internal Combustion Engine Vehicles (ICEVs) drivers, this study addresses this gap by proposing a route choice model that captures the preferences of drivers who had the opportunity of driving both ICEVs and BEVs within a large-scale revealed preferences (RP) experiment
When considering that most electric vehicle routing problems were solved under the assumption that BEV drivers minimize energy consumption [38,39,40,42,43,44], and that transport planning models followed similar assumptions [52,53,54,55,56], this is not a trivial finding, since it suggests that it is more a matter of vehicle choice rather than route cost minimization according to a cost function that depends on the vehicle type

Summary

Introduction

The growing need to reduce emissions from the transport sector and the dependence on fossil fuels is driving the significant efforts of governments to incentivize the market diffusion of Battery Electric Vehicles (BEVs). BEVs use chemical energy stored in rechargeable battery packs for propulsion, while Internal Combustion Engine Vehicles (ICEVs) transform the energy from the combustion of fuel (e.g., petrol, diesel) to propel their engine. Governments have promoted BEVs by designing investment programs, legislation pieces and taxation policies [1,2,3,4,5,6,7,8], while manufacturers have innovated battery technology to improve performance and reduce the range anxiety that relates to the poor adoption of BEVs [9,10,11,12,13]. The market penetration of BEVs has been lethargic because of high costs [9,19,20,21], significant limits in driving range [22,23], anxiety and uncertainty related to the driving range [10,24,25,26], notable deficiencies in public charging infrastructure [27,28,29,30], and specific battery issues such as limited charge cycle and questionable stability [31,32,33,34]

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