Extensions to Bluetooth/WiFi for Vehicular and Pedestrian Traffic Monitoring

之前的一笔GEOCT拨款给了莫尔探索推断车辆交通的技术的机会 通过监测与智能手机、消费类和车载等个人设备相关的信号 配饰。研究了商业上可用的系统，如Libelium的Meshlium以及 定制平台(内部)开发。通过这项初步研究，发现了缺点和机会 暴露于广泛的数据收集和解释。具体地说，估计流量的困难 遇到了流量/速度以及实际交通量的外推百分比。此外, 发现了车辆交通监控以外的机会。Engage Plus将允许Morr 进一步扩展设备发现系统，以缓解与可变范围 已扫描当前部署和设备。此外，Morr还有机会扩展蓝牙的作用 WiFi数据收集通过推断动态流量以及相关的独特机会 由于交通延误造成了城市内不可预见的延误和拥堵。使用低成本的原型 由Morr开发的它也可以解决从移动探测器收集数据的问题，并集成 网络中的数据。后一种将固定式探头与移动式探头集成在一起的方法 将有助于增加总体上可以众包的数据量，以及提供 速度和流量推断的参考或基线。Engage Plus将有两名研究生参加 并且允许将数据收集缩放到真实环境或交通走廊。

A previous Engage grant afforded MORR the opportunity to explore technologies for inferring vehicular traffic through the monitoring of signals related to personal devices such as Smartphones, consumer and vehicular accessories. Commercially available systems such as Libelium's Meshlium were investigated as well as a custom platform (in-house) developed. Through this initial study, shortcomings and opportunities were exposed to extend data collection and interpretation. Specifically, difficulties in estimating traffic flow/velocities as well as extrapolating percentages of actual traffic were encountered. In addition, opportunities outside of vehicular traffic monitoring were identified. The Engage Plus will allow MORR to further scale the device discovery system to mitigate against uncertainties associated with the variable range of current deployments and devices scanned. In addition, MORR has the opportunity to extend the role Bluetooth and WiFi data collection has through inferring ambulatory traffic as well as unique opportunities associated with traffic delays caused unforeseen delays and congestion within the city. With the low cost prototype developed by MORR it is also feasible to address data collection from mobile probes and integration of that data within the network. This latter method of integrating stationary probes with the inclusion of mobile probes would serve to increase the amount of data that could be crowdsourced in general as well as providing references or baselines to velocity and flow inferencing. The Engage Plus will involve two research students and allow scaling of the data collection to a real environment or traffic corridor.