I-Corps: RoadsInDB: Customer Discovery in the Logistics, Delivery, Ride Sharing, Location-based Services and Analytics Verticals

该项目解决与管理大型车队部署相关的物流问题，包括：Uber、Lyft和Ola等出租车共享服务；Hub GRUB等送餐服务；以及Google Shopping和Amazon等零售送货服务，涉及管理和优化成百上千辆汽车的运营。快递网络一度由少数几家大公司和许多小公司主导。然而，新的模式正在演变。例如，纽约市街道上有1.4万辆出租车，优步现在是纽约市最大的出租车服务公司。这些公司必须近乎实时地运行，并依赖于对道路网络上的车辆进行的历史分析，以保持其运营效率。特别是，企业在供需之间进行实时匹配时，会不断计算公路网上的网络距离。该项目所涉及的技术能够以非常高的吞吐速度在道路网络上计算数十万个网络距离。该项目的技术不同于Google Maps、Here Maps和其他在线地图服务，因为它们提供了API来计算源和目标顶点之间的最短路径。该项目的技术仅专注于在数据库中以非常高的吞吐量计算网络距离，这使得这项技术对于对道路网络执行广泛分析查询的公司至关重要。这种方法将对食品递送公司、包裹递送公司(UPS、联邦快递、USPS)、出租车/豪华轿车服务和拼车服务(Uber、Lyft、Ola Cabs)具有吸引力。提供地图服务的公司，如谷歌、微软或ESRI，可能也会发现这项技术很有吸引力，因为使用它，他们可以通过提供网络距离来改善他们的本地搜索服务，而不是像目前这样求助于“如乌鸦飞”的距离。该团队目前的业务模式将是为每个客户定制系统，要求按机器或按站点购买许可证。该团队的计划是专注于几个垂直市场(即具有特定、迫切需求的利基市场)，并了解他们的需求。该团队将开发应用程序，以迎合每一个垂直市场。

This project addresses logistics issues related to managing the deployment of large fleets of vehicles ranging from: Cab sharing services like Uber, Lyft, and Ola; food delivery services like Hub Grub; and retail delivery services like Google Shopping and Amazon, involving managing and optimizing the operation of hundreds and thousands of vehicles. Delivery networks were once dominated by a few large players and many small players. However, new models are evolving. For example, with 14k taxis on the streets of New York City (NYC), Uber is now is the single largest taxi service in NYC. Such companies must perform near real-time and rely on historical analytics on vehicles on road networks to keep their operations running efficiently. In particular, companies constantly compute network distances on road networks as they perform real time matchmaking between supply and demand. The technology involved in this project enables computing hundreds of thousands of network distances on road network at a very high throughput rate. This project's technology is different from Google Maps, Here Maps, and other online map services in the sense that they provide APIs to compute the shortest path between a source and destination vertex. This project's technology only focuses on computing network distances at a very high throughput inside a database, which makes this technology essential for companies that perform extensive analytical queries on road networks. This approach will be attractive to food delivery companies, package delivery companies (UPS, FedEx, USPS), taxi/limousine services, and ride sharing services (Uber, Lyft, Ola Cabs). Companies that provide map services such as Google, Microsoft, or ESRI may also find this technology attractive since using it they can improve their local search service by providing network distances instead of resorting to "as the crow flies" distances which is currently the case. The team's current business model would be to customize the system for each customer, requiring the purchase of licenses on a per-machine or per-site basis. This team's plan is to concentrate on several verticals (i.e., niche markets with specific, compelling needs) and understand their requirements. The team will develop applications to cater to each of the verticals.