Publication: Scheduling of traffic lights
| dc.contributor.authors | Unal I., Tumantozlu H.C., Ak E.M., Turkoglu E., Bulkan S., Calis B. | |
| dc.date.accessioned | 2022-03-28T15:09:00Z | |
| dc.date.accessioned | 2026-01-11T07:03:09Z | |
| dc.date.available | 2022-03-28T15:09:00Z | |
| dc.date.issued | 2018 | |
| dc.description.abstract | Big and highly populated cities face traffic congestion problems in almost every country. There are four standard driving modes which are acceleration, cruising, deceleration and idling. Vehicle fuel consumption is being used unnecessarily during idling and acceleration modes instead of steady-speed driving. To minimize the fuel consumption, it will be helpful to reorganize traffic lights with the help of green-wave strategy. In this paper, the traffic light signalization in a crowded city is studied by the help of simulation. The timing of signalization is obtained by using production order quantity model and compared to other signalization techniques through simulation. The results show that production order quantity model can be successfully used to determine timing of traffic lights. Data used are obtained from Istanbul Municipality. © IEOM Society International. | |
| dc.identifier.issn | 21698767 | |
| dc.identifier.uri | https://hdl.handle.net/11424/257304 | |
| dc.language.iso | eng | |
| dc.publisher | IEOM Society | |
| dc.relation.ispartof | Proceedings of the International Conference on Industrial Engineering and Operations Management | |
| dc.rights | info:eu-repo/semantics/closedAccess | |
| dc.subject | Green-wave strategy | |
| dc.subject | Production order quantity model | |
| dc.subject | Simulation | |
| dc.subject | Timing schedule | |
| dc.subject | Traffic signalization | |
| dc.title | Scheduling of traffic lights | |
| dc.type | conferenceObject | |
| dspace.entity.type | Publication | |
| oaire.citation.endPage | 2066 | |
| oaire.citation.issue | JUL | |
| oaire.citation.startPage | 2065 | |
| oaire.citation.title | Proceedings of the International Conference on Industrial Engineering and Operations Management | |
| oaire.citation.volume | 2018 |
