With technology such as in-vehicle data collection systems, driving data including mileage, speed, acceleration can be collected and analyzed by many researchers. However, in these studies, data could be collected only from a few selected drivers. In addition, drivers knowing that they were participating experiments might drive differently from natural. Furthermore, few researches took advantage of headway, which requires data from not only objective vehicles but also vehicles nearby. Many urban traffic surveillance systems built in recent years have brought new opportunities for researches. In this paper, urban traffic surveillance data at both intersections and road segments were used, so that data of numerous vehicles including objective vehicles and vehicles nearby could be collected, and indicators such as headway of vehicles could be calculated. The differences of driving behavior between crash-involved and crash-not-involved drivers were then analyzed. It was found that crash-involved drivers tended to keep less headways than crash-not-involved drivers when driving through intersections in everyday driving behavior. In the days before the crashes, this tendency of male drivers was stronger than female drivers. For road segments, compared with crash-not-involved drivers, crash-involved drivers' headways were seen less, and crash-involved drivers' speeds under free flow condition were seen larger at certain time frames. The result suggests that there is a great potential to taking advantage of urban traffic surveillance data to identify at-risk drivers.
|Original language||English (US)|
|Title of host publication||Proceedings - 2016 IEEE International Conference on Service Operations and Logistics, and Informatics, SOLI 2016|
|Publisher||Institute of Electrical and Electronics Engineers Inc.|
|Number of pages||6|
|State||Published - Aug 24 2016|
|Event||2016 IEEE International Conference on Service Operations and Logistics, and Informatics, SOLI 2016 - Beijing, China|
Duration: Jul 10 2016 → Jul 12 2016
|Name||Proceedings - 2016 IEEE International Conference on Service Operations and Logistics, and Informatics, SOLI 2016|
|Other||2016 IEEE International Conference on Service Operations and Logistics, and Informatics, SOLI 2016|
|Period||7/10/16 → 7/12/16|
Bibliographical noteFunding Information:
The work described in this paper was supported by grants from the National Natural Science Foundation of China (Grant No. 71301083), the National Basic Research Program of China (973 Project; No.2012CB725405), and the Research Funds of Tsinghua University (No. 20151080412).
- driving behavior
- time headway