Texas A&M University Transit: Addressing Efficiency and Customer Service Needs
公司规模
Large Corporate
地区
- America
国家
- United States
产品
- TripSpark CAD/AVL
- TripSpark Scheduling Software
- TripSpark MDTs
- TripSpark Automatic Passenger Counters
技术栈
- CAD/AVL
- Scheduling Software
- MDTs
- Automatic Passenger Counters
实施规模
- Enterprise-wide Deployment
影响指标
- Customer Satisfaction
- Cost Savings
- Productivity Improvements
技术
- 功能应用 - 车队管理系统 (FMS)
- 分析与建模 - 实时分析
- 功能应用 - 远程监控系统
适用行业
- 运输
- 教育
适用功能
- 物流运输
- 商业运营
用例
- 车队管理
- 实时定位系统 (RTLS)
- 预测性维护
服务
- 系统集成
- 软件设计与工程服务
关于客户
Texas A&M University is one of the largest universities in America, covering over 5,000 acres and hosting over 63,000 students. The university’s College Station campus operates a transit system that serves not only students and staff but also the general population of College Station. With 97 buses running on 18 routes both on and off campus, the transit system is the 6th largest in Texas. The university uses advanced technologies to manage its fixed route operations and transport an average of 50,000 passengers on a typical fall or spring semester day.
挑战
Texas A&M University faced several challenges with its transit system, including the need to adjust services to avoid running empty buses, splitting shifts on short notice, and reducing complaints from riders. The university needed a solution to maximize route efficiency, manage real-time rostering changes, and improve on-time performance to enhance rider satisfaction.
解决方案
Texas A&M University implemented TripSpark’s CAD/AVL and scheduling software, MDTs, and automatic passenger counters to manage their transit operations. By using ridership data, the university intelligently adjusted evening, weekend, and holiday services to reduce driver hours without negatively impacting ridership. The flexible rostering system allowed for easy management of real-time rostering changes, and real-time dispatching improved on-time performance. Riders were provided with real-time bus location information, reducing wait times and complaints.
运营影响
数量效益
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