Harnessing Mobile Ad hoc Network (MANET) to Improve Vulnerable Road User Safety
Our goal is to investigate, implement, and demonstrate a mobile ad hoc network (MANET)-based, practical, infrastructure-free and secure framework that improves the safety of vulnerable road users such as pedestrians and cyclists in the situations when their safety is most threatened, e.g.,non-intersection crossings, lightly-lit areas, evening and late-night situations, and jaywalking.
Data Collection APP
The first step of the project is building a data collection platform to collect data from the road users. We first developed the flow of the data collection framework. This framework includes an Android app that runs on the client side and a server component that handles the collected data. The app encrypts the collected data on the client-side for privacy protection and automatically uploads to our Amazon “Simple Storage Service” (S3) server for temporary storage. The data is stored in encrypted format on S3 storage and we download the data to our local servers for further processing/analysis after decryption. Automatic labeling of data is performed locally on our server. Processed data will later be used in predicting pedestrian’s road crossing behavior.
Multi-hop Packet Transmission on Android
We developed an Android App for multi-hop communication between vehicles and pedestrians on road. Multi-hop communication can solve the problem of high communication delay in None-Line-of-Sight scenario and communication beyond range.
Thus we designed and implemented our distance based data forwarding algorithms based on Wi-Fi Aware in commodity Android smartphones. This can extend the range of communication compared to single hop communication and reduce the communication delay caused by network congestion at the same time.
Vehicle to Pedestrian Authentication
Currently, we are working on the authentication of the source of the message in our MANET-based framework. With the absence of a centralized entity managing node identities, a malicious entity can inject fake messages into our framework to impede traffic flows.
This research is funded by Federal HighWay Administration (FHWA).