Naturalistic Evaluation of a Narrow Navigation System - A longitudinal Study on Bus Drivers’ and Passengers’ Experience and Acceptance of an Automated Docking Support System
Report, 2025

​Executive Summary  
Introduction 
An evaluation of an advanced driver assistance system in buses called the Narrow Navigation (NN) System, developed by Volvo Buses, was carried out and co-financed within the EU project eBRT-2030 (European Bus Rapid Transit 2030) in collaboration with Volvo Buses, VL and Svealandstrafiken AB. This naturalistic, longitudinal study investigated real-world use and acceptance of the NN system, which automates aspects of the docking process, a task often described as stressful and cognitively demanding. The study examined how drivers’ experience and acceptance evolve over time and evaluates passenger comfort during automated dockings using the NN system.

​Method 
A Volvo 7900 electric bus equipped with the NN system operated along a 13 km public bus route in Västerås, Sweden. Five professional drivers participated in a 3.5-month trial following a three-day training. Data were collected via interviews, questionnaires, and driving logs. Passenger comfort was assessed through questionnaires comparing automated and manual dockings. 

​Findings 
Drivers’ experiences with the NN system evolved over time, shaped by technical performance and context. Initial experience varied, but all drivers reported increased trust and acceptance over timeas they learned how to interact with the system. This increase in trust and acceptance was temporarily disrupted in the middle of the test period due to experiences often technical issues (e.g., positioning errors, interface lag) that caused frustration but were not seen as safety-critical. After, drivers adapted their behavior to the NN system; user trust stabilized but did not fully return to initial peak levels. 
 
The NN system was highly valued during docking for its precision and consistency, reducing driver stress and improving passenger comfort significantly compared to manually operated buses. However, departures were problematic due to slow, indecisive acceleration, making it less suitable for merging into traffic.

​Control transitions improved with experience, though drivers desired smoother handovers and more adaptive system behavior. LED indicators were preferred over audio due to ambient noise.

​Conclusion 
The NN system shows strong potential for improving docking consistency, driver ergonomics, and passenger comfort. However, its performance during departures and control transitions highlights the need for further refinement.

​Future Research Directions 
Future research should therefore:

(i) Investigate the potential benefits of automated docking systems using a larger sample size and examine in greater detail how driving behavior influences user experience and acceptance at both national and international levels.

(ii) Explore how an NN system with enhanced functionality—such as advanced object detection, auto-braking, and adaptive driving behavior—would be perceived in real public transport operations.

(iii) Assess the potential economic benefits of an NN system, including reduced tire and wheel axle wear and tear, and/or fewer sick leaves due to upper body aches and pains. 

longitudinal study

mobility

automation

automated docking

advanced driver assistance system (ADAS)

comfort

naturalistic study

Narrow Navigation System

bus drivers

user acceptance

public transport

automated buses

user experience

bus passengers

Author

Mikael Johansson

Chalmers, Industrial and Materials Science, Design & Human Factors

Fredrick Ekman

Chalmers, Industrial and Materials Science, Design & Human Factors

Naturalistic Evaluation of a Narrow Navigation System​ - A longitudinal Study on Bus Drivers’ and Passengers’ Experience and Acceptance of an Automated Docking Support System

European Commission (EC) (Part of UITP EBRT2030 Grant agreement ID: 101095882), 2024-02-01 -- 2025-06-30.

Driving Forces

Sustainable development

Innovation and entrepreneurship

Areas of Advance

Transport

Subject Categories (SSIF 2025)

Transport Systems and Logistics

Psychology

Vehicle and Aerospace Engineering

Design

Work Sciences

More information

Created

11/20/2025