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了生产力、压力、社会和环境成本的重大损失。将拼车扩展为日常通勤提供了一种手段，可以在保持用户可接受的出行时间和成本的同时减少交通拥堵。拟议的项目旨在设计多维模型和算法，为通勤者的商业拼车系统动态计算定制车费。将开发模型和算法算法(S)，以分析乘客需求、车辆使用、车辆供应、过境时间、路线信息、车辆运营成本等的历史、实时和预测数据，并根据几个服务质量限制指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.