On-Demand Transport Dispatch for Transit Egress Congestion
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Solution Overview
Problem
Public transport riders often face increased delays and traffic congestion at fixed stations due to a lack of preemptive planning for additional transport needs, especially when many riders disembark simultaneously from transit means like trains or buses.
Innovation Solution
A computing system identifies user intent to use on-demand transport services before the actual request is made by analyzing location data and historical patterns, preemptively configuring and optimizing transport options at egress locations, including carpooling, ridesharing, and use of electric scooters or bicycles, to minimize wait times and congestion.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If fixed stations are used for public transport, then transport infrastructure is simplified, but riders experience increased delays and traffic congestion when disembarking simultaneously
Solution Approach 1:
The system performs preliminary actions by detecting user intent to use on-demand transport services before the actual request is made. The computing system analyzes location data and historical patterns to identify users who will need additional transport upon arriving at fixed stations, and preemptively configures and optimizes transport options (carpooling, ridesharing, electric scooters, bicycles) before the mass outflow occurs, thereby reducing wait times and congestion at egress locations
2Ease of operation
If on-demand transport is provided at fixed stations, then rider mobility is improved, but traffic congestion and confusion increase during mass outflow
Solution Approach 1:
The system preemptively identifies users who will need additional transport and configures transport options before the mass outflow occurs. By analyzing location data and historical patterns in advance, the system optimizes the deployment of on-demand transport services, electric scooters, and bicycles at egress locations before riders arrive, thereby improving rider mobility while avoiding traffic congestion and confusion during peak discharge periods
Solution Approach 2:
The system dynamically adapts transport supply based on real-time conditions. The computing system continuously monitors user intent, location data, and transport availability to dynamically adjust and optimize transport options at egress locations. This dynamic approach allows the system to respond to changing conditions and optimize resource allocation, improving rider mobility while minimizing traffic congestion during mass outflow events
Data Source
AI summary
A computing system can receive utilization data from computing devices of requesting users. Based on the utilization data, the system can determine, for each requesting user, an intent of the requesting user, the intent corresponding to a probability that the requesting user will utilize the transport service upon arrival at an arrival location of a transit vehicle. The system may determine a destination for the requesting user that requires additional transport from the arrival location of the transit vehicle. Based on the destination of the requesting user, the system can transmit a set of transport requests to computing devices of a set of the transport providers to facilitate transport for the requesting users at the arrival location of the transit vehicle.