scholarly journals PREFERENCE FOR MAP SCALE OF IN-CAR ROUTE GUIDANCE AND NAVIGATION SYSTEM

2016 ◽  
Vol 22 (3) ◽  
pp. 472-491 ◽  
Author(s):  
Ana Paula Marques Ramos ◽  
Mônica Modesta Santos Decanini ◽  
Edmur Azevedo Pugliesi ◽  
Vilma Mayumi Tachibana ◽  
Renan Furlan De Oliveira ◽  
...  
Keyword(s):  
Traffic Safety ◽  
Navigation System ◽  
User Satisfaction ◽  
Important Variable ◽  
Route Guidance ◽  
Map Design ◽  
Driving Task ◽  
Appropriate Scale ◽  
Map Scale

Usability issues of maps presented in-car Route Guidance and Navigation System (RGNS) may result in serious impacts on traffic safety. To obtain effective RGNS, evaluation of 'user satisfaction' with the system has played a prominent role, since designers can quantify drivers' acceptance about presented information. An important variable related to design of RGNS interfaces refers to select appropriate scale for maps, since it interferes on legibility of maps. Map with good legibility may support drivers comprehend information easily and take decisions during driving task quickly. This paper evaluates drivers' preference for scales used in maps of RGNS. A total of 52 subjects participated of an experiment performed in a parked car. Maps were designed at four different scales 1:1,000, 1:3,000, 1:6,000 and 1:10,000 for a route composed of 13 junctions. Map design was based on cartographic communication principles, such as perceptive grouping and figure-ground segregation. Based on studies cases, we conclude intermediate scales (1:6,000 and 1:3,000) were more acceptable among drivers compared to large scales (1:1,000) and small (1:10,000). RGNS should select scales for maps which supports drivers to quickly identify direction of the maneuver and, simultaneously, get information about surroundings of route. More results are presented and implications discussed

scholarly journals EVALUATION OF USABILITY OF MAPS OF DIFFERENT SCALES PRESENTED IN AN IN-CAR ROUTE GUIDANCE AND NAVIGATION SYSTEM

2018 ◽  
Vol 24 (3) ◽  
pp. 383-406
Author(s):  
Ana Paula Marques Ramos ◽  
Edmur Azevedo Pugliesi ◽  
Renan Furlan de Oliveira ◽  
Vilma Mayumi Tachibana ◽  
Mônica Modesta Santos Decanini
Keyword(s):  
Cognitive Processing ◽  
Navigation System ◽  
Traffic Accidents ◽  
Driving Simulator ◽  
Mental Workload ◽  
Communication Process ◽  
Navigation Systems ◽  
Route Guidance ◽  
And Gender ◽  
Map Scale

Abstract Noise from the information communication process produced by the interfaces of navigation systems has overloaded drivers' cognitive processing systems and increased the probability of traffic accidents. This work evaluates the usability of maps of different scales in a prototype route guidance and navigation system. The maps were designed on basic cartographic communication principles, such as perceptive grouping and figure-ground segregation, as well drivers’ requirements for performing a tactical task. Two different scales were adopted, 1:3,000 and 1:6,000, and the maps implemented in the prototype. A total of 52 subjects (26 males and 26 females) participated in an experiment performed in a driving simulator. The maps describe an urban route composed of 13 simple and complex maneuvers. The drivers’ mental workload was measured in terms of visual demand, navigational error and subjective preference. Results reveal that the usability of maps is influenced by map scale variation, and this is related to maneuver complexity. Also, an association between drivers’ visual demand and gender was found, and this was related to drivers’ spatial ability. More implications are presented and discussed.

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

Safety Enhancement by Automated Driving: What are the Relevant Scenarios?

2020 ◽  
Vol 64 (1) ◽  
pp. 1686-1690
Author(s):  
Niklas Grabbe ◽  
Michael Höcher ◽  
Alexander Thanos ◽  
Klaus Bengler
Keyword(s):  
Traffic Safety ◽  
Road Traffic ◽  
Test Cases ◽  
Automated Driving ◽  
Road Traffic Safety ◽  
Human Driver ◽  
Driving Task ◽  
Promising Solution ◽  
Vehicle Automation ◽  
Safety Enhancement

Automated driving offers great possibilities in traffic safety advancement. However, evidence of safety cannot be provided by current validation methods. One promising solution to overcome the approval trap (Winner, 2015) could be the scenario-based approach. Unfortunately, this approach still results in a huge number of test cases. One possible way out is to show the current, incorrect path in the argumentation and strategy of vehicle automation, and focus on the systemic mechanisms of road traffic safety. This paper therefore argues the case for defining relevant scenarios and analysing them systemically in order to ultimately reduce the test cases. The relevant scenarios are based on the strengths and weaknesses, in terms of the driving task, for both the human driver and automation. Finally, scenarios as criteria for exclusion are being proposed in order to systemically assess the contribution of the human driver and automation to road safety.

Route guidance by a car navigation system based on augmented reality

2012 ◽  
Vol 180 (2) ◽  
pp. 43-54 ◽  
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 Indoor path visualization method based on the spatial characteristics of indoor environment

2019 ◽  
Vol 1 ◽  
pp. 1-2
Author(s):  
Jiafeng Shi ◽  
Jie Shen ◽  
Zdeněk Stachoň ◽  
Yawei Chen
Keyword(s):  
Indoor Environment ◽  
Design Method ◽  
Three Dimensional ◽  
Indoor Environments ◽  
Route Guidance ◽  
Visualization Method ◽  
Continuous Space ◽  
Indoor Location ◽  
Indoor Space ◽  
Map Design

<p><strong>Abstract.</strong> With the increasing number of large buildings and more frequent indoor activities, indoor location-based service has expanded. Due to the complicated internal passages of large public buildings and the three-dimensional interlacing, it is difficult for users to quickly reach the destination, the demand of indoor paths visualization increases. Isikdag (2013), Zhang Shaoping (2017), Huang Kejia (2018) provided navigation services for users based on path planning algorithm. In terms of indoor path visualization, Nossum (2011) proposed a “Tubes” map design method, which superimposed the channel information of different floors on the same plane by simplifying the indoor corridor and the room. Lorenz et al (2013) focused on map perspective (2D/3D) and landmarks, developed and investigated cartographic methods for effective route guidance in indoor environments. Holscher et al (2007) emphasized using the landmark objects at the important decision points of the route in indoor map design. The existing studies mainly focused on two-dimensional plane to visualize the indoor path, lacking the analysis of three-dimensional connectivity in indoor space, which makes the intuitiveness and interactivity of path visualization greatly compromised. Therefore, it is difficult to satisfy the wayfinding requirements of the indoor multi-layer continuous space. In order to solve this problem, this paper aims to study the characteristics of the indoor environment and propose a path visualization method. The following questions are addressed in this study: 1) What are the key characteristics of the indoor environment compared to the outdoor space? 2) How to visualize the indoor paths to satisfy the users’ wayfinding needs?</p>

scholarly journals Measuring effective map design for route guidance: An experiment comparing electronic map display principles

2008 ◽  
Vol 16 (3) ◽  
pp. 190-201 ◽  
Author(s):  
Thomas Porathe
Keyword(s):  
Decision Making ◽  
Route Guidance ◽  
Effective Strategy ◽  
Electronic Map ◽  
The World ◽  
Map Design ◽  
Guidance Systems

Route guidance systems in vehicles has started to use an oblique, slanted view of the map, mimicking something of the egocentric perspective the driver sees through the windscreen. Is this an effective strategy? What is the most effective map design to convey route guidance to drivers, and how can this be measured? In an experiment with four different modes of map displays the speed of decision making and accuracy of navigation have been tested. The four map types were: the traditional paper map, the northup electronic map with position plotting (the symbol of the vehicle moving in the static map), the head-up electronic map (map moving, the position of the vehicle static and facing up) and the egocentric view map display, a 3-D scenery mimicking the world outside the wind screen. The experiment showed clearly that the egocentric 3-D view was the most effective.

Effect of Driving Duration and Work Schedules on Vigilance Level and Driving Performance of Bus Drivers

2013 ◽  
Vol 321-324 ◽  
pp. 1518-1521 ◽  
Author(s):  
Yu Long Pei ◽  
Lian Zhen Wang
Keyword(s):  
Traffic Safety ◽  
Driving Performance ◽  
Work Schedules ◽  
Bus Drivers ◽  
Driving Task ◽  
Stanford Sleepiness Scale ◽  
Driving Fatigue ◽  
Positive Correlations ◽  
One Way Anova ◽  
Very High

The bus drivers have to suffer from very high labor intensity every day. Driving fatigue among the bus drivers is very common and has very dangerous risk for traffic safety. Fourteen male bus drivers, divided into two groups according to two kinds of work schedules, participated in a control experiment. The driving session was performed in the real road scene. Each driver was asked to finish a five-laps driving task. The Stanford Sleepiness Scale score was recorded to measure the subjective fatigue feelings of the bus drivers. Choice reaction time and PECLOS indicators were used to assess the driving performance. One-way ANOVA was used to examine significance of data variations with SPSS. Person’s correlation coefficient was employed to explore the correlations among the three indicators. The results reveal that driving duration has a significant effect on the vigilance level of the bus drivers. There are evident positive correlations between the three indicators. And the two kinds of work schedules have different effect on the bus drivers’ prevention of driving fatigue.

MACHINE LEARNING ON CONGESTION ANALYSIS BASED REAL-TIME NAVIGATION SYSTEM

2011 ◽  
Vol 20 (04) ◽  
pp. 753-781
Author(s):  
KAI CHEN ◽  
KIA MAKKI ◽  
NIKI PISSINOU
Keyword(s):  
Machine Learning ◽  
Travel Time ◽  
Real Time ◽  
Navigation System ◽  
Prediction Models ◽  
Urban Traffic ◽  
Route Guidance ◽  
Highway Traffic ◽  
Data Set ◽  
Guidance Systems

In the metropolitan region, most congestion or traffic jams are caused by the uneven distribution of traffic flow that creates bottleneck points where the traffic volume exceeds the road capacity. Additionally, unexpected incidents are the next most probable cause of these bottleneck regions. Moreover, most drivers are driving based on their empirical experience without awareness of real-time traffic situations. This unintelligent traffic behavior can make the congestion problem worse. Prediction based route guidance systems show great improvements in solving the inefficient diversion strategy problem by estimating future travel time when calculating accurate travel time is difficult. However, performances of machine learning based prediction models that are based on the historical data set degrade sharply during a congestion situation. This paper develops a new navigation system for reducing travel time of an individual driver and distributing the flow of urban traffic efficiently in order to reduce the occurrence of congestion. Compared with previous route guidance systems, the results reveal that our system, applying the advanced multi-lane prediction based real-time fastest path (AMPRFP) algorithm, can significantly reduce the travel time especially when drivers travel in a complex route environment and face frequent congestion problems. Unlike the previous system,1 it can be applied either for single lane or multi-lane urban traffic networks where the reason for congestion is significantly complex. We also demonstrate the advantages of this system and verify the results using real highway traffic data and a synthetic experiment.

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.

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