Abstract
Road accidents are the leading causes of death among youths and young adults worldwide. Efficient traffic enforcement is an essential, yet complex, component in preventing road accidents. In this article, we present a novel model, an optimizing algorithm and a deployed system which together mitigate many of the computational and real-world challenges of traffic enforcement allocation in large road networks. Our approach allows for scalable, coupled and non-Markovian optimization of multiple police units and guarantees optimality. Our deployed system, which utilizes the proposed approach, is used by the Israeli traffic police and is shown to provide meaningful benefits compared to existing standard traffic police enforcement practices.
| Original language | English |
|---|---|
| Article number | 103381 |
| Journal | Artificial Intelligence |
| Volume | 289 |
| DOIs | |
| State | Published - Dec 2020 |
Bibliographical note
Publisher Copyright:© 2020 Elsevier B.V.
Funding
This work was supported in part by the LAW-TRAIN project which received funding from the European Union Horizon 2020 research and innovation program under grant agreement 653587 and in part by a grant from the Ministry of Science & Technology, Israel & the Japan Science and Technology Agency (JST), Japan.
| Funders | Funder number |
|---|---|
| Ministry of Science & Technology, Israel & the Japan Science and Technology Agency | |
| Horizon 2020 Framework Programme | |
| Japan Science and Technology Agency | |
| Horizon 2020 | 653587 |
Keywords
- Deployed system
- Security
- Traffic enforcement