Title

Crash Risk Analysis Of Different Designs Of Toll Plazas

Keywords

All-electronic toll collection; And toll by plate; Cashless toll; Hybrid toll plaza; Log linear; Open road tolling; Traditional toll plaza

Abstract

The Expressways (toll roads) offer a high level of service, and the Global Electronic Toll Collection market has exceeded the expectation. However, finding optimal designs for toll plazas is an issue with world-wide relevance, and this study makes a significant contribution towards this end. The main goal of this study is to examine for the first time the traffic safety impact of using different designs of the Hybrid Toll Plaza (HTP). In addition to that, this study helps understand the relationship between the crash frequency and several important crash-related factors and circumstances of these facilities. Crash data from a seven-year period was investigated, and a hundred mainline toll plazas in Florida were evaluated. The results of this study proved that there is a significant difference between the different designs of the HTP. And there is an indication that the majority of crashes occurred at diverge-and-merge areas before and after the plaza. Moreover, the results indicated significant relationships between the crash frequency and toll plaza types, annual average daily traffic, and driver-age. This study has also proved that the HTP and the All-Electronic Toll Collection (AETC) were associated with less number of crashes than the Traditional Toll Plazas by 44.7 and 72.6 percent, respectively. Also, one of the findings with interesting safety implications is the interaction between design type and percentage of prepaid transponder vs. manual payment users regarding crash rate. Overall, for those agencies who cannot adopt the AETC system, improving traffic safety at toll plazas should take a priority.

Publication Date

8-1-2018

Publication Title

Safety Science

Volume

107

Number of Pages

77-84

Document Type

Article

Personal Identifier

scopus

DOI Link

https://doi.org/10.1016/j.ssci.2018.02.024

Socpus ID

85045640358 (Scopus)

Source API URL

https://api.elsevier.com/content/abstract/scopus_id/85045640358

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