A FUZZY ROUTE GUIDANCE MODEL FOR INTELLIGENT IN-VEHICLE NAVIGATION SYSTEMS

1999 ◽  
Vol 08 (02) ◽  
pp. 229-237
Author(s):  
JUNG-HSIEN CHIANG
Keyword(s):  
Fuzzy Clustering ◽  
Guidance System ◽  
Vehicle Navigation ◽  
Navigation Systems ◽  
Route Guidance ◽  
Fixed Costs ◽  
Adaptive Fuzzy ◽  
Clustering Model ◽  
Efficient Alternative ◽  
Guidance Model

This paper presents an adaptive fuzzy clustering model that can be used to identify nature subgroups of links as well as priority memberships in a route guidance system. The fuzzy route guidance model, inspired by the fuzzy clustering technique, provides an adaptive and efficient alternative to traditional fixed costs route guidance methods. Three specific objectives underlie the presentation of the fuzzy route guidance model in this paper. The first is to describe a general overview of the in-vehicle navigation system, and the second is to introduce the fuzzy route guidance model based on adaptive fuzzy clustering and least cost problem. The third part is to demonstrate that the proposed model is able to perform route guidance in road test.

Advanced Vehicle Navigation applied in the BMW Real Time Light Simulation

2000 ◽  
Vol 53 (1) ◽  
pp. 30-41 ◽  
Author(s):  
J. P. Löwenau ◽  
P. J. Th. Venhovens ◽  
J. H. Bernasch
Keyword(s):  
Real Time ◽  
Traffic Safety ◽  
Driving Simulator ◽  
Vehicle Navigation ◽  
Navigation Systems ◽  
Route Guidance ◽  
Differential Gps ◽  
Night Time ◽  
Cd Rom ◽  
Positioning Systems

Advanced vehicle navigation based on the US Global Positioning Systems (GPS) will play a major role in future vehicle control systems. Contemporary vehicle navigation systems generally consist of vehicle positioning using satellites and location and orientation of the vehicle with respect to the roadway geometry using a digitised map on a CD-ROM. The standard GPS (with Selective Availability) enables positioning with an accuracy of at least 100 m and is sufficiently accurate for most route guidance tasks. More accurate, precision navigation can be obtained by Differential GPS techniques. A new light concept called Adaptive Light Control (ALC) has been developed with the aim to improve night-time traffic safety. ALC improves the headlamp illumination by means of continuous adaptation of the headlamps according to the current driving situation and current environment. In order to ensure rapid prototyping and early testing, the step from offline to online (real-time) simulation of light distributions has been successfully completed in the driving simulator. The solutions are directly ported to real vehicles to allow further testing with natural road conditions.

Lane-Level Positioning Method for 3D In-Vehicle Navigation System

2013 ◽  
Vol 340 ◽  
pp. 767-772
Author(s):  
Lin Zhang ◽  
Bin Wang ◽  
Xue Yu Mi ◽  
Li Fen Yi
Keyword(s):  
Navigation System ◽  
Vehicle Navigation ◽  
Navigation Systems ◽  
Route Guidance ◽  
Map Matching ◽  
Differential Gps ◽  
Vehicle Navigation System ◽  
Detection Technology ◽  
Positioning Method ◽  
The Way

The objective of this study is to find an effective way to realize lane-level route guidance for vehicle navigation system. Based on the modeling of 3D map, a lane-level positioning method was presented by the way of combination of virtual differential GPS, height aiding, and collision detecting technique. GPS parameters were amended through virtual differential technology and height aiding technology by the way of elevation interpolation and least squares estimation in order to improve the output precision. Then a method of lane-level map matching was implemented in 3D digital map based on the collision detection technology. Tested by RTK technique, the method was proven to fulfill the demands of vehicle navigation systems.

When Should Auditory Guidance Systems Tell Drivers to Turn?

1995 ◽  
Vol 39 (17) ◽  
pp. 1072-1076 ◽  
Author(s):  
Paul Green ◽  
Kellie George
Keyword(s):  
Regression Analysis ◽  
Navigation System ◽  
Traffic Signal ◽  
Guidance System ◽  
Vehicle Navigation ◽  
Route Guidance ◽  
Vehicle Navigation System ◽  
Guidance Systems ◽  
Turn Direction

This two-part experiment examined how far from an intersection an auditory route-guidance system should present the final turn instructions (e.g., “Turn right.”). In part 1, 48 drivers followed instructions from a simulated in-vehicle navigation system (“In approximately 2 miles, turn right at the traffic signal”), responding “Is this it?” when they thought they had reached the desired intersection. In response, the computer gave the appropriate guidance (“No, continue…” or “Turn…”). In part 2, they repeatedly approached 2 different intersections. Feedback from previous trials (“too far,” “too close,” “OK”) was used to adjust when messages (e.g., “Turn left.”) were presented. Regression analysis revealed that last turn messages should be provided approximately 450 feet before an intersection (approached at 40 mi/h), with that value being adjusted 15 feet for each mile per hour change. Adjustments are also made for gender (plus or minus 56 feet), age (plus or minus 60 feet), and turn direction (plus or minus 48 feet).

Augmenting Landmarks During the Head-Up Provision of In-Vehicle Navigation Advice

2017 ◽  
Vol 9 (2) ◽  
pp. 18-38 ◽  
Author(s):  
David R. Large ◽  
Gary Burnett ◽  
Adam Bolton
Keyword(s):  
Driving Simulator ◽  
Response Times ◽  
Vehicle Navigation ◽  
Navigation Systems ◽  
Route Guidance ◽  
Success Rates ◽  
The Road ◽  
Performance Improvements ◽  
Significant Performance ◽  
Verbal Messages

The use of landmarks during the provision of directions can greatly improve drivers' route-following performance. However, the successful integration of landmarks within in-vehicle navigation systems is predicated on the acquisition and deployment of good quality landmarks, as defined by their visibility, uniqueness, permanence, location etc., and their accurate and succinct depiction on in-vehicle displays and during accompanying verbal messages. Notwithstanding the inherent variability in the quality and propensity of landmarks within the driving environment, attending to in-vehicle displays and verbal messages while driving can distract drivers and heighten their visual and cognitive workload. Furthermore, vocal utterances are transient and can be littered with paralinguistic cues that can influence a driver's interpretation of what is said. In this paper, a driving simulator study is described aiming to investigate the augmentation of landmarks during the head up provision of route guidance advice – a potential solution to some of these problems. Twenty participants undertook four drives utilising a navigation system presented on a head up display (HUD) in which navigational instructions were presented as either: conventional distance-to-turn information; on-road arrows; or augmented landmarks (either an arrow pointing to the landmark or a box enclosing the landmark adjacent to the required turning). Participants demonstrated significant performance improvements while using the augmented landmark 'box' compared to the conventional distance-to-turn information, with response times and success rates enhanced by 43.1% and 26.2%, respectively. Moreover, there were significant reductions in eyes off-the-road time when using this approach, and it also attracted the lowest subjective ratings of workload. The authors conclude that there are significant benefits to augmenting landmarks during the head-up provision of in-car navigation advice.

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.

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