Analysis of Pedestrian Street-Crossing Decision-Making Based on Vehicle Deceleration-Safety Gap

Hongjia Zhang, Yingshi Guo, Yunxing Chen, Qinyu Sun and Chang Wang
Additional contact information
Hongjia Zhang: School of Automobile, Chang’an University, Xi’an 710064, China
Yingshi Guo: School of Automobile, Chang’an University, Xi’an 710064, China
Yunxing Chen: School of Automobile, Chang’an University, Xi’an 710064, China
Qinyu Sun: School of Automobile, Chang’an University, Xi’an 710064, China
Chang Wang: School of Automobile, Chang’an University, Xi’an 710064, China

IJERPH, 2020, vol. 17, issue 24, 1-13

Abstract: Numerous traffic crashes occur every year on zebra crossings in China. Pedestrians are vulnerable road users who are usually injured severely or fatally during human-vehicle collisions. The development of an effective pedestrian street-crossing decision-making model is essential to improving pedestrian street-crossing safety. For this purpose, this paper carried out a naturalistic field experiment to collect a large number of vehicle and pedestrian motion data. Through interviewed with many pedestrians, it is found that they pay more attention to whether the driver can safely brake the vehicle before reaching the zebra crossing. Therefore, this work established a novel decision-making model based on the vehicle deceleration-safety gap (VD-SGM). The deceleration threshold of VD-SGM was determined based on signal detection theory (SDT). To verify the performance of VD-SGM proposed in this work, the model was compared with the Raff model. The results show that the VD-SGM performs better and the false alarm rate is lower. The VD-SGM proposed in this work is of great significance to improve pedestrians’ safety. Meanwhile, the model can also increase the efficiency of autonomous vehicles.

Keywords: pedestrian; zebra crossings; decision-making model; vehicle deceleration; signal detection theory; autonomous vehicles (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
https://www.mdpi.com/1660-4601/17/24/9247/pdf (application/pdf)
https://www.mdpi.com/1660-4601/17/24/9247/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jijerp:v:17:y:2020:i:24:p:9247-:d:459986

Access Statistics for this article

IJERPH is currently edited by Ms. Jenna Liu

More articles in IJERPH from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().