A dynamic pricing and revenue management algorithm for a ride-share commuting system

城市街道和高速公路上的交通拥堵导致生产力、压力、社会和环境成本的重大损失。扩大日常通勤的共乘提供了一种减少交通拥堵的手段，同时为用户保持可接受的出行时间和成本。该项目旨在设计多维模型和算法，以动态计算通勤者的商业乘车共享系统的定制票价。将开发模型和算法，以分析乘客需求、车辆利用率、车辆供应、运输时间、路线信息、车辆运营成本等的历史、真实的时间和预测数据，并根据若干服务质量约束规定每个乘车请求的票价。

Traffic congestion on city streets and highways leads to major loss of productivity, stress, societal and environmental costs. The expansion of ride-sharing for daily commuting offers a means to reduce traffic congestion, while maintaining acceptable travel times and cost for the users. The proposed project aims to design multidimensional models and algorithms to dynamically calculate customized fares for a commercial ride-sharing system for commuters. Models and algorithms algorithm(s) will be developed to analyze historical, real time and projected data for passenger demand, vehicle utilization, vehicle supply, transit times, route information, vehicle operating costs etc. and specifies fares for each ride request, subject to several quality of service constraints.