Traffic simulation-emission modelling to evaluate impact of signal cycle on automobile emissions
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Summary
This study investigates the impact of traffic signal control strategies on vehicular exhaust emissions at urban intersections, specifically addressing the problem of high pollution concentrations caused by congestion and speed fluctuations in heterogeneous traffic conditions. The research focuses on the Malhar intersection in Vadodara, India, a high-volume arterial road characterized by mixed vehicle types and lack of lane discipline. The primary objective is to evaluate how optimizing signal cycle lengths and phase systems can reduce emissions by minimizing vehicle idling and frequent acceleration-deceleration cycles. The methodology employs an integrated microscopic traffic simulation and emission modeling approach using VISSIM and its add-on module, EnViVer (VERSIT+micro). Field data, including traffic volumes and speed-time profiles for motorcycles, motorized three-wheelers, and cars, were collected using video cameras and V-box instruments during peak hours. The VISSIM model was calibrated to reflect Indian driving behaviors, adjusting parameters such as look-ahead distance and lane-changing behavior. Model validation was performed using the GEH statistic for traffic volume and Root Mean Square Error (RMSE) and Mean Absolute Error (MAE) for speed profiles, confirming the model’s accuracy with GEH values below 5 and MAE values under 10. Two optimization scenarios were tested against a base model with a 120-second signal cycle. Case-1 involved reducing the cycle length to 90 seconds while maintaining a four-phase system. Case-2 further reduced the cycle to 60 seconds and modified the signal phasing to a three-phase system. Results indicated that both modifications significantly lowered emissions. Case-1 reduced CO2, NOx, and PM10 emissions by 22.08%, 27.35%, and 13.47%, respectively. Case-2 achieved greater reductions, decreasing CO2 by 27.00%, NOx by 32.17%, and PM10 by 18.89% compared to the base model. Spatial analysis of pollutant concentrations confirmed that the three-phase system in Case-2 yielded the lowest emission levels across the network. The findings demonstrate that optimizing traffic signal operations is an effective strategy for mitigating urban air pollution. The study concludes that reducing signal cycle lengths and adjusting phase systems can significantly decrease vehicle idling and stop-and-go behaviors, thereby lowering exhaust emissions. This approach offers a practical tool for traffic engineers to design signal timings that balance traffic flow efficiency with environmental sustainability in metropolitan areas with heterogeneous traffic.
Provenance
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| Stage | Outcome | Tool | Model | Prompt | Attempts | Completed |
|---|---|---|---|---|---|---|
| discover | success | OpenAlex-citations | — | — | 1 | 2026-06-20 |
| archive | success | unpaywall | — | — | 2 | 2026-06-26 |
| extract | success | cached | — | — | 2 | 2026-06-26 |
| clean | success | clean | — | — | 1 | 2026-06-20 |
| chunk | success | chunk | — | — | 1 | 2026-06-20 |
| embed | success | embed | Qwen/Qwen3-Embedding-8B | — | 1 | 2026-06-20 |
| promote | success | — | — | — | 1 | 2026-06-20 |
| summarize | success | llm | qwen3.6-27b-prismaquant | summ-v5 | 1 | 2026-06-26 |
| tag | success | vector_similarity | — | — | 6 | 2026-06-20 |
| verify | success | — | — | — | 1 | 2026-06-26 |
Summary generated by qwen3.6-27b-prismaquant on 2026-06-26; verification: verified.
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