A team of US researchers has developed a micro-navigation smartphone app to provide assistance to those who are blind or visually impaired (BVI) in finding their bus stops.
A new study published in the journal Translational Vision Science and Technology (TVST) found the success rate of the app was substantially higher than that of Google Maps.
Current GPS systems have sufficient macro-navigation for planning routes using public transport.
However, micro-navigation, such as finding the exact locations of bus stops and destinations, remains an issue for people who are BVI, as GPS-based localisation for this is less accurate.
To tackle this problem, the researchers developed a mobile app called All_Aboard, which is meant to be used in conjunction with mainstream GPS systems and focuses on improving micro-navigation.
When a GPS indicates that a BVI user is nearing their destination, that is when the app should be opened.
It uses the phones’ camera to detect street signs from 30 to 50 feet away and then uses auditory cues to direct the user towards their destination, with the frequency of the sounds changing as they approach the end point.
The app is powered by AI, using a deep learning neural network trained on about 10,000 images of bus stops collected in a given city or region.
All_Aboard is currently capable of recognising bus stops in 10 major cities/regions around the world.
Gang Luo, PhD of the Schepens Eye Research Institute of Mass Eye and Ear, said:
“Our findings suggest that the All_Aboard app could help travelers with visual impairments in navigation by accurately detecting the bus stop, and therefore greatly reducing their chance of missing buses due to standing too far from the bus stops.”
In the study, 24 BVI individuals used All_Aboard along with Google Maps to navigate a set route with 10 bus stops at an urban (Boston) and suburban site (Newton, Massacusetts).
The results of the study were measured in terms of localisation error and rate of successful localisation.
Localisation error, or gap distance, is defined as the distance between the desired destination and maps marked end point.
The rate of successful localisation is the probability of getting close enough to the bus stops.
The researchers found that in both urban and suburban locations, All_Aboard had a success rate of 93 per cent, whereas Google Maps had a 52 per cent success rate.
Additionally, the average gap distance with Google Maps was 6.62 metres and 1.54 metres with All_Aboard.
GPS accuracy is supposed to be acceptable in suburban areas, said Luo, who added it was not initially expected that the performance with Google Maps in Newton, Mass. would be so low.
Previous research from Luo and his colleagues found this problem may be due to widespread errors in bus stop location mapping data in Google Maps.
Luo said: “This study indicates that computer vision-based object recognition capabilities can be used in a complementary way and provide added benefit to purely mapping-based, macro-navigation services in real-world settings.
Image: TVST/Mass Eye and Ear
