Bus Network Control System for Dynamic Passenger Load Distribution
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Solution Overview
Problem
Bus networks face challenges in maintaining scheduled arrival times due to congestion, road closures, and high passenger demand, leading to delays and the 'bus bunching' phenomenon, where buses converge, resulting in uneven passenger distribution and increased wait times for passengers.
Innovation Solution
A bus network control system that utilizes demand prediction and arrival time prediction units to identify unscheduled buses that can arrive earlier at stops, allowing them to take over and distribute passenger loads more evenly, thereby reducing wait times and alleviating congestion.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If buses operate according to fixed schedules on shared roads, then route stability is maintained, but buses are delayed due to congestion, roadworks, and passenger boarding/alighting times
Solution Approach 1:
The system dynamically adjusts bus schedules in real-time based on actual traffic conditions and passenger demand. Instead of rigid fixed schedules, the system continuously monitors bus positions, traffic congestion, and passenger waiting times to optimize arrival times and spacing between buses, allowing the schedule to adapt to changing conditions while maintaining reliability
Solution Approach 2:
The system implements real-time feedback loops by monitoring bus positions, traffic conditions, and passenger demand, then using this information to adjust schedules dynamically. The control system receives continuous data from buses and stops, processes this information to predict arrival times and identify delays, and sends corrective instructions back to buses to maintain optimal scheduling
2Productivity
If buses are spaced apart on the road, then coverage is improved, but delays cause buses to converge and bunch together, resulting in uneven passenger distribution
Solution Approach 1:
The system dynamically controls the spacing between buses by adjusting their schedules in real-time. When a leading bus is delayed, the system automatically adjusts the schedule of following buses to maintain optimal spacing, preventing bunching and ensuring even passenger distribution across the fleet while maintaining comprehensive network coverage
Solution Approach 2:
The system takes preliminary action by predicting potential bus bunching scenarios before they occur. By monitoring real-time conditions and predicting arrival times, the system proactively adjusts schedules to prevent delays from causing bus convergence, thereby maintaining stable spacing and even passenger distribution before the problem manifests
3Ease of manufacture
If premeditated timetable optimisation is used, then initial scheduling is improved, but it cannot remedy dynamic congestion conditions and changing passenger demand
Solution Approach 1:
The system transitions from static premeditated timetables to dynamic real-time scheduling. While initial schedules provide a baseline framework, the system continuously adapts to changing conditions by monitoring traffic congestion, roadworks, and passenger demand, adjusting bus schedules dynamically to maintain optimal performance throughout the day
Solution Approach 2:
The system implements continuous feedback loops that monitor real-time conditions and automatically adjust schedules accordingly. The control system receives ongoing data from buses and stops, processes this information to identify deviations from optimal scheduling, and sends corrective instructions to maintain adaptability to changing congestion conditions and passenger demand throughout the operational day
Data Source
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AI summary
A bus network control system (200) for controlling a plurality of buses (110, 120) operating as at least a part of a bus network (100); wherein the bus network (100) comprises: one or more scheduled buses (110), operating according to respective schedules; one or more unscheduled buses (120); and one or more lines (130), each line being formed from a plurality of sequentially connected stops (131, 132, 133, 134, 135, 136), wherein the schedule of the or each scheduled bus indicates one or more stops corresponding to a section of a respective line; the bus network control system comprising: a demand prediction unit (1101) configured to: obtain demand data pertaining to one or more of the scheduled buses; and predict a number of passengers boarding and/or alighting a given scheduled bus at one or more of the stops on that scheduled bus's schedule based on the demand data; an arrival time prediction unit (1102) configured to: obtain operating data pertaining to one or more buses; and predict respective arrival times of a given scheduled bus at one or more of the stops on that scheduled bus's schedule based on the operating data; and a schedule management unit (1103) that, for a given stop, S, that a given scheduled bus, B, is scheduled to stop at, is configured to: obtain the predicted number of passengers boarding and/or alighting buses at stop S from the demand prediction unit (1101); obtain the predicted arrival time of bus B at stop S from the arrival time prediction unit (1102); predict an average wait time of passengers at stop S to board a bus travelling on the line L of bus B at the time bus B is predicted to arrive at stop S, based on the predicted number of passengers boarding and/or alighting buses at stop S and the predicted arrival time of bus B at stop S; and identify whether there is an unscheduled bus, U, that can arrive at stop S at an earlier time than bus B, and if so, instruct bus U to travel to stop S and assign the unscheduled bus U a schedule of stops.