A SUMO analysis of the railway traffic flow on the SOWETO corridor : Factors influencing train operation
Bibliographic record
Abstract
40% of public transport users in the Johannesburg Metropolitan use the train as a preferred mode of transport for home to work journeys. Out of the 40% train users in Johannesburg, 35% travel from Johannesburg South to the East of Johannesburg and the 5% travel to the North side of Johannesburg.There are three main interconnecting stations in Johannesburg that is the Johannesburg Park Station (Central Johannesburg), Germiston Station (East of Johannesburg) and New Canada Station (South of Johannesburg). The study investigates the traffic from the South as it has massive patronage, and it experiences overcrowded trains, congestions, and delays. New Canada Station is the interconnection for traffic in these following routes, Vereeniging/Oberholzer- New Canada – Johannesburg- George Goch (Red Route), Naledi – New Canada – Johannesburg (Yellow Route) and Naledi – New Canada – George Goch (Blue Route). The red route experiences heavy delays and overcrowding, due to several factors like the distance between Johannesburg and Vereeniging, minimum headway of approximately 20 mins and the overcrowding which is a consequence of new townships developing around the railway lines.Three plans or scenarios were implemented on the SOWETO corridor traffic evaluation. The first plan uses the timeslots from the operator’s timetable, which had varying headways. The second plan evaluates the traffic when the headway has equal intervals, and the last plan assesses the introduction of route(s) given the results from the first and second plan. Dwell time, vehicle type are variables used to analyse the train traffic on the SOWETO corridors, a simulation using SUMO in conjunction with Python was implemented. The older train set specifications (5M2A called TYPE A) and the newer train set specifications (Xtrapolis called TYPE B) were used in the simulation.The headway influences the manner passengers arrive at the stations. Passengers arrive in large amounts when the headways are longer as most passengers turn to be reliant on the timetable. Varying headways experienced more delays than equal interval headways. TYPE A vehicles have longer travel time in comparison to TYPE B vehicles, the travel time is longer by (1-2) minutes. TYPE B vehicles have lesser dwell time due to the arrangement of their doors. Routing, assignment of vehicles to routes, design of a vehicle, passenger arrival rate and the headway are essential parts of a well performing network, as they influence the dwell time, delays, and congestion.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".