Abstract
Efficient traffic enforcement is an essential, yet complex, component in preventing road accidents. In this paper, we present a novel model and an optimizing algorithm for mitigating some of the computational challenges of real-world traffic enforcement allocation in large road networks. Our approach allows for scalable, coupled and non-Markovian optimization of multiple police units and guarantees optimality. In an extensive empirical evaluation we show that our approach favorably compares to several baseline solutions achieving a significant speed-up, using both synthetic and real-world road networks.
| Original language | English |
|---|---|
| Title of host publication | 26th International Joint Conference on Artificial Intelligence, IJCAI 2017 |
| Editors | Carles Sierra |
| Publisher | International Joint Conferences on Artificial Intelligence |
| Pages | 3814-3822 |
| Number of pages | 9 |
| ISBN (Electronic) | 9780999241103 |
| DOIs | |
| State | Published - 2017 |
| Event | 26th International Joint Conference on Artificial Intelligence, IJCAI 2017 - Melbourne, Australia Duration: 19 Aug 2017 → 25 Aug 2017 |
Publication series
| Name | IJCAI International Joint Conference on Artificial Intelligence |
|---|---|
| Volume | 0 |
| ISSN (Print) | 1045-0823 |
Conference
| Conference | 26th International Joint Conference on Artificial Intelligence, IJCAI 2017 |
|---|---|
| Country/Territory | Australia |
| City | Melbourne |
| Period | 19/08/17 → 25/08/17 |
Bibliographical note
Funding Information:This work was supported in part by the LAW-TRAIN project that has received funding from the European Union Horizon 2020 research and innovation program under grant agreement 653587 and in part by by a grant from the Ministry of Science & Technology, Israel & the Japan Science and Technology Agency (jst), Japan.
Funding
This work was supported in part by the LAW-TRAIN project that has received funding from the European Union Horizon 2020 research and innovation program under grant agreement 653587 and in part by by a grant from the Ministry of Science & Technology, Israel & the Japan Science and Technology Agency (jst), Japan.
| Funders | Funder number |
|---|---|
| European Union Horizon 2020 research and innovation program | |
| Ministry of Science & Technology, Israel & the Japan Science and Technology Agency | |
| Horizon 2020 Framework Programme | 653587 |