Exploring Factors that Influence Connected Drivers to (Not) Use or Follow Recommended Optimal Routes

Recommender System UXPublic Transit & Trip PlanningPublic Transit OperatorsFood Delivery Riders & Ride-Hailing Drivers

Navigation applications are becoming ubiquitous in our daily navigation experiences. With the intention to circumnavigate congested roads, their route guidance always follows the basic assumption that drivers always want the fastest route. However, it is unclear how their recommendations are followed and what factors affect their adoption. We present the results of a semi-structured qualitative study with 17 drivers, mostly from the Philippines and Japan. We recorded their daily commutes and occasional trips, and inquired into their navigation practices, route choices and on-the-fly decision-making. We found that while drivers choose a recommended route in urgent situations, many still preferred to follow familiar routes. Drivers deviated because of a recommendation's use of unfamiliar roads, lack of local context, perceived driving unsuitability, and inconsistencies with realized navigation experiences. Our findings and implications emphasize their personalization needs, and how the right amount of algorithmic sophistication can encourage behavioral adaptation.

Quick Actions

Share

Share this page

ios_share

https://hci.top/en/papers/chi/3800/2019

AdRecommended

Learn AI Coding at CodeNow

At a Glance

Paper Snapshot

fact_check
dataset
Source
CHI
calendar_month
Year
2019
emoji_events
Award
No award tagged
group
Authors
2 authors
sell
Subtopics
Recommender System UX, Public Transit & Trip Planning
work
Professions
Public Transit Operators, Food Delivery Riders & Ride-Hailing Drivers
article
Content Status
Abstract only
hub
Related Papers
0 related papers