Timetable Generator for Autonomous Vehicle Service Management
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Solution Overview
Problem
Existing transportation systems face high congestion issues due to delayed buses, which lead to overcrowding and passenger inconvenience, as current technologies only optimize service intervals after congestion is noted, not proactively addressing delays.
Innovation Solution
A transportation system with autonomous vehicles and a service management device that generates timetables based on real-time passenger information, adjusting average speed and dwell time to prevent delays and congestion by calculating boarding and alighting times, and responding to disabled vehicles to ensure efficient passenger transfer.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the bus delays are allowed to occur, then the service intervals can be optimized after congestion is noted, but the congestion becomes excessively high temporarily and passenger convenience deteriorates
Solution Approach 1:
The system performs preliminary action by proactively adjusting the timetable before congestion occurs. The timetable generator calculates boarding and alighting time estimates and adjusts dwell times and average speeds in advance to prevent delays, rather than reacting after congestion is noted. This ensures passengers are not subjected to excessive congestion while maintaining schedule reliability.
Solution Approach 2:
The system applies dynamics by making the timetable adjustable and flexible. The timetable generator dynamically adjusts dwell times at stops and average speeds between stops based on real-time passenger information and calculated boarding/alighting time estimates. This dynamic adjustment allows the system to optimize service intervals while preventing congestion from becoming excessively high.
2Ease of operation
If the dwell time is increased to accommodate more passengers, then the boarding and alighting can be completed, but the vehicle delay increases and congestion occurs
Solution Approach 1:
The system changes parameters by adjusting dwell time and average speed based on calculated boarding and alighting time estimates. Rather than using fixed dwell times, the timetable generator dynamically modifies these parameters to match actual passenger flow requirements, ensuring complete boarding and alighting without excessive vehicle delays.
Solution Approach 2:
The system uses feedback by continuously monitoring passenger information and adjusting the timetable accordingly. The timetable generator receives passenger information, calculates boarding and alighting time estimates, and uses this feedback to optimize dwell times and average speeds, preventing both incomplete passenger handling and excessive delays.
3Ease of operation
If the average speed is reduced to allow more time for boarding and alighting, then passenger convenience is improved, but the vehicle delay increases and service intervals are disrupted
Solution Approach 1:
The system changes parameters by dynamically adjusting average speed and dwell time based on calculated boarding and alighting time estimates. Rather than uniformly reducing speed, the timetable generator selectively modifies these parameters at specific stops and time intervals, improving passenger convenience while maintaining overall service efficiency and minimizing delays.
Data Source
AI summary
A transportation system includes a traveling route, vehicles, and a service management device. The service management device includes a timetable generator that generates a timetable for each of the vehicles, and a communication device that is configured to receive passenger information at least from the vehicles or stops. The timetable generator calculates a boarding and alighting time estimate of the vehicle at the stop based on at least the passenger information such that a higher average speed of the vehicle between the stops and a longer dwell time of the vehicle at the stop are set for a longer boarding and alighting time estimate.


