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How Demand Response Software Improved Vehicle Utilization Ratio
Technology Category
- Functional Applications - Fleet Management Systems (FMS)
- Functional Applications - Remote Monitoring & Control Systems
Applicable Industries
- Cities & Municipalities
- Transportation
Applicable Functions
- Business Operation
- Logistics & Transportation
Use Cases
- Fleet Management
- Predictive Maintenance
- Remote Asset Management
Services
- Software Design & Engineering Services
- System Integration
- Training
The Challenge
The City of Whitehorse faced significant inefficiencies in their transit system due to the limitations of their in-house developed software. The software could not handle multiple pickups, leading to under-utilized buses and a cumbersome manual process for ridership data collection. This inefficiency resulted in unreliable and slow service, causing numerous customer complaints. Dispatchers and management staff spent excessive time managing these complaints and manually inputting performance data into spreadsheets.
About The Customer
Whitehorse Transit (WT) is the public transportation provider for Whitehorse, Yukon, accommodating the city's 26,000+ population. The Handy-Bus system, a demand response service, is jointly funded by the City and the Government of the Yukon Territory. WT operates a single vehicle providing around 25-35 trips per day, serving individuals who have difficulty using regular transit services. Despite its small scale, WT is dedicated to offering safe and reliable transportation, especially given the harsh winter conditions in the region.
The Solution
To address the inefficiencies, WT implemented TripSpark's demand response software. This powerful software allowed for automated scheduling, enabling multiple pickups and optimal routing. The browser-based solution facilitated quick and efficient in-the-moment changes to the schedule, significantly reducing the workload on dispatchers. The software's reporting feature provided real-time performance and overview reports, enhancing the ability to monitor service quality and address customer complaints promptly. Automated ridership data collection further streamlined operations, allowing managers to see service quality in real-time.
Operational Impact
Quantitative Benefit
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