Citation:
Li, C.-Y., Salinas, G., Huang, P.-H., Tu, G.-H., Hsu, G.-H., Hsieh, T.- Y. (2018). V2PSense: Enabling Cellular-based V2P Collision Warning Service Through Mobile Sensing. Paper submitted in 2018 IEEE International Conference on Communications (ICC), Kansas City.
Sponsor:
This work was partially supported by the Ministry of Science and Tech-nology, Taiwan, under grant numbers 106-2622-8-009-017 and 106-2218-E-009-018, and by the H2020 collaborative Europe/Taiwan research project 5G-CORAL (grant num. 761586)
The C-V2X (Cellular Vehicle-to-Everything) technology
is developing in full swing. One of its mainstream services
can be the Vehicle-to-Pedestrian (V2P) service. It can protect
pedestrians who are mostly vulnerable on the road. In this
work, we seek to enaThe C-V2X (Cellular Vehicle-to-Everything) technology
is developing in full swing. One of its mainstream services
can be the Vehicle-to-Pedestrian (V2P) service. It can protect
pedestrians who are mostly vulnerable on the road. In this
work, we seek to enable a V2P service that can identify which
pedestrians may be nearby a dangerous driving event and then
notify them of warning messages. To enable this V2P service,
there are two major challenges. First, a low-latency V2P message
transport is required for this infrastructure-based service.
Second, the pedestrian’s smartphone requires an energy-efficient
outdoor positioning method instead of power-hungry GPS due
to its limited battery life. We thus propose a novel solution,
V2PSense, which trades off positioning precision for energy
savings while achieving low-latency message transport with LTE
high-priority bearers. It does a coarse-grained positioning by
leveraging intermittent GPS information and mobile sensing data,
which includes step count from the pedometer and cellular signal
strength changes. Though the V2PSense’s positioning is not as
precise as the GPS, it can still ensure that all the pedestrians
nearby dangerous spots can be notified. Our results show that
it can achieve the average precision ratio 92.6% for estimating
where the pedestrian is while saving 20.8% energy, compared
with the GPS always-on case.[+][-]