In-car usage-based insurance feedback strategies. A comparative driving simulator study

Abstract Usage-Based Insurances (UBI) enable policyholders to actively reduce the impact of vehicle insurance costs by adopting a safer and more eco-friendly driving style. UBI is especially relevant for younger drivers, who are a high-risk population. The effectiveness of UBI should be enhanced by providing in-car feedback optimised for individual drivers. Thirty young novice drivers were therefore invited to complete six experimental drives with an in-car interface that provided real-time information on rewards gained, their driving behaviour and the speed limit. Reward size was either displayed directly in euro, indirectly as a relatively large amount of credits, or as a percentage of the maximum available bonus. Also, interfaces were investigated that provided partial information to reduce the potential for driver distraction. Compared to a control no-UBI condition, behaviour improved similarly across interfaces, suggesting that interface personalisation after an initial familiarisation period could be feasible without compromising feedback effectiveness. Practitioner Summary: User experiences and effects on driving behaviour of six in-car interfaces were compared. The interface provided information on driving behaviour and rewards in a UBI setting. Results suggest that some personalisation of interfaces may be an option after an initial familiarisation period as driving behaviour improved similarly across interfaces.

[1]  Karel Brookhuis,et al.  Univé customer survey: Pay-As-You-Drive (PAYD) insurance : Report PAYD-2. Feedback from Pay-As-You-Drive insurance, both outside and inside the car , 2013 .

[2]  E T Verhoef,et al.  Effects of Pay-As-You-Drive vehicle insurance on young drivers' speed choice: results of a Dutch field experiment. , 2011, Accident; analysis and prevention.

[3]  Maja Fischer,et al.  Psychological predictors of eco-driving: a longitudinal study , 2015 .

[4]  Karel Brookhuis,et al.  The simulator studies : Report PAYD-4. Feedback from Pay-As-You-Drive insurance, both outside and inside the car. , 2014 .

[5]  R Elvik,et al.  Can road traffic law enforcement permanently reduce the number of accidents? , 1992, Accident; analysis and prevention.

[6]  D. Zaal.  TRAFFIC LAW ENFORCEMENT: A REVIEW OF THE LITERATURE. , 1994 .

[7]  Ben Lewis-Evans,et al.  Crash involvement during the different phases of the New Zealand Graduated Driver Licensing System (GDLS). , 2010, Journal of safety research.

[8]  Bruce Simons-Morton,et al.  The observed effects of teenage passengers on the risky driving behavior of teenage drivers. , 2005, Accident; analysis and prevention.

[9]  Natasha Merat,et al.  Surrogate in-vehicle information systems and driver behaviour: effects of visual and cognitive load in simulated rural driving , 2005 .

[10]  L. Steg,et al.  Comparing the effectiveness of monetary versus moral motives in environmental campaigning , 2013 .

[11]  J. Barkenbus.  Eco-driving: An overlooked climate change initiative , 2010 .

[12]  T. Dingus,et al.  Crash and risky driving involvement among novice adolescent drivers and their parents. , 2011, American journal of public health.

[13]  Thomas J Triggs,et al.  Driver distraction: the effects of concurrent in-vehicle tasks, road environment complexity and age on driving performance. , 2006, Accident; analysis and prevention.

[14]  Bryan Reimer,et al.  Glance analysis of driver eye movements to evaluate distraction , 2002, Behavior research methods, instruments, & computers : a journal of the Psychonomic Society, Inc.

[15]  Todd Litman,et al.  Pay-As-You-Drive Pricing and Insurance Regulatory Objectives , 2007 .

[16]  John A. Groeger.  PAY AS YOU LEARN : THE POTENTIAL OF USING VEHICLE ELECTRONICS DATA FOR A PAY AS YOU LEARN APPROACH FOR LONG TERM IMPROVEMENTS IN DRIVING SKILL , 2006 .

[17]  Katja Kircher,et al.  Interface design of eco-driving support systems – Truck drivers’ preferences and behavioural compliance , 2015 .

[18]  Neville A Stanton,et al.  Safe driving in a green world: a review of driver performance benchmarks and technologies to support 'smart' driving. , 2011, Applied ergonomics.

[19]  J. Alba,et al.  Irrelevant Information and Mediated Intertemporal Choice , 2004 .

[20]  P Delhomme,et al.  Reducing air-pollution: a new argument for getting drivers to abide by the speed limit? , 2010, Accident; analysis and prevention.

[21]  David D Clarke,et al.  Killer crashes: fatal road traffic accidents in the UK. , 2010, Accident; analysis and prevention.

[22]  C. Vlek,et al.  A review of intervention studies aimed at household energy conservation , 2005 .

[23]  Johan Engström,et al.  Sensitivity of eye-movement measures to in-vehicle task difficulty , 2005 .

[24]  Neil Thorpe,et al.  Attitudes towards and perceptions of eco-driving and the role of feedback systems , 2013, Ergonomics.

[25]  A. Tversky,et al.  Prospect theory: analysis of decision under risk , 1979 .

[26]  Keith T. Adkins.  Two essays in applied economics: pay-as-you-go auto insurance and privatized military housing , 2004 .

[27]  Jason E. Bordoff,et al.  Pay-As-You-Drive Auto Insurance: A Simple Way to Reduce Driving-Related Harms and Increase Equity , 2008 .

[28]  A. Pradhan,et al.  The effect on teenage risky driving of feedback from a safety monitoring system: a randomized controlled trial. , 2013, The Journal of adolescent health : official publication of the Society for Adolescent Medicine.

[29]  Karel A. Brookhuis,et al.  Effects of MDMA (ecstasy), and multiple drugs use on (simulated) driving performance and traffic safety , 2004, Psychopharmacology.

[30]  R. Bagchi,et al.  Illusionary Progress in Loyalty Programs: Magnitudes, Reward Distances, and Step-Size Ambiguity , 2011 .

[31]  A. Tversky,et al.  Prospect theory: an analysis of decision under risk — Source link , 2007 .

[32]  Dick de Waard,et al.  The impact of immediate or delayed feedback on driving behaviour in a simulated Pay-As-You-Drive system. , 2015, Accident; analysis and prevention.

[33]  R. Cialdini.  Influence: Science and Practice , 1984 .

[34]  Todd Litman.  Pay-As-You-Drive Pricing For Insurance Affordability , 2011 .

[35]  Samantha Jamson,et al.  The design of an in-vehicle assistance system to support eco-driving , 2015 .

[36]  Yan Zhang,et al.  Medium Maximization , 2003 .

[37]  Allan F Williams,et al.  Teenage drivers: patterns of risk. , 2003, Journal of safety research.

[38]  Anders af Wåhlberg,et al.  Driver celeration behaviour and accidents - an analysis , 2008 .

[39]  Peter Bonsall,et al.  Modelling safety-related driving behaviour: impact of parameter values , 2005 .

[40]  Andry Rakotonirainy,et al.  Examining the effects of an eco-driving message on driver distraction. , 2013, Accident; analysis and prevention.

[41]  Neville A Stanton,et al.  Driver behaviour with adaptive cruise control , 2005, Ergonomics.

[42]  Niels Agerholm,et al.  Pay as You Speed, ISA with incentives for not speeding: a case of test driver recruitment. , 2012, Accident; analysis and prevention.

[43]  Julie Hatfield,et al.  The role of risk-propensity in the risky driving of younger drivers. , 2009, Accident; analysis and prevention.

[44]  Dot Hs,et al.  The 100-Car Naturalistic Driving Study Phase II - Results of the 100-Car Field Experiment , 2006 .

[45]  Paul A. Jennings,et al.  Effect of Using an In-Vehicle Smart Driving Aid on Real-World Driver Performance , 2014, IEEE Transactions on Intelligent Transportation Systems.

[46]  E. Scott Geller,et al.  Behavior Analysis and Environmental Protection: Accomplishments and Potential for More , 2004 .