Design of a rich multimodal interface for mobile spoken route guidance

2007 ◽  
Author(s):  
Markku Turunen ◽  
Jaakko Hakulinen ◽  
Anssi Kainulainen ◽  
Aleksi Melto ◽  
Topi Hurtig
Keyword(s):  
Route Guidance ◽  
Multimodal Interface

A Study on Route Guidance of a Car Navigation System Based on Augmented Reality

2011 ◽  
Vol 131 (7) ◽  
pp. 897-906
Author(s):  
Kengo Akaho ◽  
Takashi Nakagawa ◽  
Yoshihisa Yamaguchi ◽  
Katsuya Kawai ◽  
Hirokazu Kato ◽  
...  
Keyword(s):  
Augmented Reality ◽  
Navigation System ◽  
Route Guidance ◽  
Car Navigation System ◽  
Car Navigation

scholarly journals An Eco-Friendly Multimodal Route Guidance System for Urban Areas Using Multi-Agent Technology

2021 ◽  
Vol 11 (5) ◽  
pp. 2057
Author(s):  
Abdallah Namoun ◽  
Ali Tufail ◽  
Nikolay Mehandjiev ◽  
Ahmed Alrehaili ◽  
Javad Akhlaghinia ◽  
...  
Keyword(s):  
Traffic Flow ◽  
Urban Areas ◽  
Urban Environments ◽  
Ease Of Use ◽  
Transport Infrastructure ◽  
Guidance System ◽  
Planning System ◽  
Flow Density ◽  
Route Guidance ◽  
Agent Based

The use and coordination of multiple modes of travel efficiently, although beneficial, remains an overarching challenge for urban cities. This paper implements a distributed architecture of an eco-friendly transport guidance system by employing the agent-based paradigm. The paradigm uses software agents to model and represent the complex transport infrastructure of urban environments, including roads, buses, trolleybuses, metros, trams, bicycles, and walking. The system exploits live traffic data (e.g., traffic flow, density, and CO2 emissions) collected from multiple data sources (e.g., road sensors and SCOOT) to provide multimodal route recommendations for travelers through a dedicated application. Moreover, the proposed system empowers the transport management authorities to monitor the traffic flow and conditions of a city in real-time through a dedicated web visualization. We exhibit the advantages of using different types of agents to represent the versatile nature of transport networks and realize the concept of smart transportation. Commuters are supplied with multimodal routes that endeavor to reduce travel times and transport carbon footprint. A technical simulation was executed using various parameters to demonstrate the scalability of our multimodal traffic management architecture. Subsequently, two real user trials were carried out in Nottingham (United Kingdom) and Sofia (Bulgaria) to show the practicality and ease of use of our multimodal travel information system in providing eco-friendly route guidance. Our validation results demonstrate the effectiveness of personalized multimodal route guidance in inducing a positive travel behavior change and the ability of the agent-based route planning system to scale to satisfy the requirements of traffic infrastructure in diverse urban environments.

scholarly journals Modular Approach for Odometry Localization Method for Vehicles with Increased Maneuverability

Sensors ◽  
2020 ◽  
Vol 21 (1) ◽  
pp. 79
Author(s):  
Chenlei Han ◽  
Michael Frey ◽  
Frank Gauterin
Keyword(s):  
Steering System ◽  
Vehicle Control ◽  
Modular Approach ◽  
Route Guidance ◽  
State Variables ◽  
Simulation Environment ◽  
Localization Method ◽  
State Estimators ◽  
Position And Orientation ◽  
Guidance Information

Localization and navigation not only serve to provide positioning and route guidance information for users, but also are important inputs for vehicle control. This paper investigates the possibility of using odometry to estimate the position and orientation of a vehicle with a wheel individual steering system in omnidirectional parking maneuvers. Vehicle models and sensors have been identified for this application. Several odometry versions are designed using a modular approach, which was developed in this paper to help users to design state estimators. Different odometry versions have been implemented and validated both in the simulation environment and in real driving tests. The evaluated results show that the versions using more models and using state variables in models provide both more accurate and more robust estimation.

scholarly journals Hybrid Vehicle-Centric Route Guidance 1

2003 ◽  
Vol 36 (14) ◽  
pp. 149-154 ◽  
Author(s):  
Jennifer Farver ◽  
Ismail Chabini
Keyword(s):  
Hybrid Vehicle ◽  
Route Guidance
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