Outdoor Localization Using BLE RSSI and Accessible Pedestrian Signals for the Visually Impaired at Intersections

One of the major challenges for blind and visually impaired (BVI) people is traveling safely to cross intersections on foot. Many countries are now generating audible signals at crossings for visually impaired people to help with this problem. However, these accessible pedestrian signals can result in confusion for visually impaired people as they do not know which signal must be interpreted for traveling multiple crosses in complex road architecture. To solve this problem, we propose an assistive system called CAS (Crossing Assistance System) which extends the principle of the BLE (Bluetooth Low Energy) RSSI (Received Signal Strength Indicator) signal for outdoor and indoor location tracking and overcomes the intrinsic limitation of outdoor noise to enable us to locate the user effectively. We installed the system on a real-world intersection and collected a set of data for demonstrating the feasibility of outdoor RSSI tracking in a series of two studies. In the first study, our goal was to show the feasibility of using outdoor RSSI on the localization of four zones. We used a k-nearest neighbors (kNN) method and showed it led to 99.8% accuracy. In the second study, we extended our work to a more complex setup with nine zones, evaluated both the kNN and an additional method, a Support Vector Machine (SVM) with various RSSI features for classification. We found that the SVM performed best using the RSSI average, standard deviation, median, interquartile range (IQR) of the RSSI over a 5 s window. The best method can localize people with 97.7% accuracy. We conclude this paper by discussing how our system can impact navigation for BVI users in outdoor and indoor setups and what are the implications of these findings on the design of both wearable and traffic assistive technology for blind pedestrian navigation.

Virtual Guide Dog: Next-generation pedestrian signal for the visually impaired

Accessible pedestrian signal was proposed as a mean to achieve the same level of service that is set forth by the Americans with Disabilities Act for the visually impaired. One of the major issues of existing accessible pedestrian signals is the failure to deliver adequate crossing information for the visually impaired. This article presents a mobile-based accessible pedestrian signal application, namely, Virtual Guide Dog. Integrating intersection information and onboard sensors (e.g. GPS, compass, accelerometer, and gyroscope sensor) of modern smartphones, the Virtual Guide Dog application can notify the visually impaired: (1) the close proximity of an intersection and (2) the street information for crossing. By employing a screen tapping interface, Virtual Guide Dog can remotely place a pedestrian crossing call to the controller, without the need of using a pushbutton. In addition, Virtual Guide Dog informs VIs the start of a crossing phase using text-to-speech technology. The proof-of-concept test shows that Virtual Guide Dog keeps the users informed about the remaining distance as they are approaching the intersection. It was also found that the GPS-only mode is accompanied by greater distance deviation compared to the mode jointly operating with both GPS and cellular positioning.

The Effect of Countdown Pedestrian Signals on Pedestrian Behavior in Various Weather Conditions - Case Study in Banja Luka

Pedestrians represent the most vulnerable category of participants in traffic. More and more complex traffic conditions in cities across Europe, and therefore BiH, threaten traffic to become a challenge for pedestrians, and pedestrians often experience traffic as a challenge. Studies of behavior of pedestrians at signalized pedestrian crossings conclude that there is a high level of insecurity and a high percentage of unsafe crossings by pedestrians. Timers that add pedestrian signals indicate the length of the red light, the remaining time to the beginning of the green light for the safe crossing of pedestrians across the street. This paper analyzes the effect of the countdown pedestrian signals - CPSs in different weather conditions, ie the comparison of pedestrian behavior (switching to red light) without CPSs and with CPSs in different weather conditions (sun, snow, rain, no precipitation with a temperature of 0 degrees) was performed. The paper analyzes a traffic light pedestrian crossing over the road that consists of four traffic lanes in Banja Luka, BiH.

Determining Confusion for Traditional and Experimental Pedestrian Signals in Rural and Suburban Areas in the United States

Walking is a mode of travel used by billions of people daily. Facilities that promote walking such as crosswalks often involve sharing space with conflicting vehicular traffic. These areas are not immune to receiving pedestrians that either do not obey or do not understand today’s pedestrian signals, which are used to communicate periods of safe crossing. Therefore, improving comprehension would subsequently improve safety and crash rates. The Traditional Pedestrian Signal in the United States displays an illuminated man and a hand to indicate a cautionary-crossing period, a transition period, and a crossing-prohibited period. This signal type was evaluated and compared to a relatively new Experimental Pedestrian Signal. The Experimental Pedestrian Signal presented in this paper utilized the figure of a walking man changing only by the colors green, yellow, and red. Both signals were analyzed to identify the phases that best communicated the intended action. Video files depicting a Traditional and Experimental Signal were administered with a questionnaire to test the comprehension of rural and suburban participants. The results indicated that the Experimental Pedestrian Signal was not better understood than the current Traditional Signal, although a vast majority of participants preferred the Experimental Signal. The lowest comprehension occurred during the transition phase for both pedestrian signal types. The results also suggest that the interpretation of the yellow color varies by location and may invoke mixed responses if incorporated in pedestrian signals. A more appropriate solution may be to combine both symbolic and color cues into future pedestrian signals.

Using Difference Images to Detect Pedestrian Signal Changes

This paper describes a method of using camera images to detect changes in the display status of pedestrian traffic signals. In much of the research previously done on signal detection, the color or shape of images or machine learning has been used to estimate the signal status. However, it is known that these methods are greatly affected by occlusion and changes in illumination. We propose a method of detecting, using multiple image sequences captured over time, changes in appearance that occur when a signal changes. If this method is used, the position and the status of the traffic light can be accurately detected as long as it appears in the image, even if its relative position or the lighting conditions in the area changes. In this paper, we first describe how pedestrian signals are seen when difference images are used, and we propose an algorithm for detecting when a signal changes. Then, the effectiveness of the proposed method is confirmed through verification tests.