Full Record

Author | Sahaji, Rajib |

Title | BOTTOM-UP NETWORK SCREENING TO IDENTIFY HIGH COLLISION LOCATIONS FOR THE CITY OF SASKATOON |

URL | http://hdl.handle.net/10388/ETD-2012-06-546 |

Publication Date | 2012 |

Date Available | 2013-01-03 00:00:00 |

University/Publisher | University of Saskatchewan |

Abstract | Safety network screening is used to identify roadway locations (e.g., intersections and roadway segments) for potential safety improvements. Currently, one of the most commonly used network screening methods in practice is the safety performance function (SPF) based method that uses traffic volume data as an essential input for the screening process. However, the lack of traffic volume data for target roadway locations restricts the applicability of SPF-based network screening methods. The primary objective of this study is to screen Saskatoon’s roadway networks using two existing network screening methods (i.e., the binomial test and the beta-binomial (BB) test) that do not require traffic volume as an input. Previous studies have applied the binomial test and/or the BB test without explicitly defining the particular circumstances that indicate which test is preferable. This study introduced a formal statistical test known as the overdispersion test (i.e., “C(α) Test”) to determine which network screening method – the binomial test or the BB test – should be used to screen a given study dataset. The “C(α) Test” was applied to a total of 36 study collision datasets, including 26 segment collision datasets, and 10 intersection collision datasets. (“C (α) Test” results showed that 15 of 26 (58%) segment collision datasets, and all of 10 intersection collision datasets contained statistically significant overdispersion at the 95% confidence level (P-value < 0.05). The BB test was selected as an appropriate network screening method for 15 segment collision datasets and 10 intersection collision datasets. The remaining 11 segment collision datasets that did not contain statistically significant overdispersion (P-value ≥ 0.05) were screened using the binomial test. The network screening results for each study location (i.e., a segment or an intersection) in all 36 study datasets were presented in terms of the estimated probability obtained from either the binomial test or the BB test. The estimated probability values were used as a ranking measure to select the top 10 or top 30 riskiest locations for both roadway segments and intersections. The network screening results (estimated probability) for each study segment or intersection in all 36 study collision datasets were then visually displayed in a set of 36 collision maps that were developed using ArcGIS. The developed GIS-based collision maps are expected to help engineers in the City of Saskatoon to efficiently select potential locations for deploying specific safety countermeasures that will result in the reduction of a certain configuration of collisions at the screened locations. As a final component of this thesis, a diagnosis study was performed to identify the most dominant collision configurations at the top 30 riskiest signalized intersections (among a total of 154 signalized intersections) in Saskatoon. This study quantitatively compared the performance of two existing collision diagnosis methods (i.e., descriptive data analysis and BB test), and the… |

Subjects/Keywords | Bottom-up Network Screening, Beta-binomial Test, Collision Diagnosis, GIS Collision Maps |

Contributors | Park, Peter Y.; Hawkes, Christopher D.; Sparks, Gordon A.; Berthelot, Curtis; Gardiner, Angela |

Language | en |

Country of Publication | ca |

Record ID | handle:10388/ETD-2012-06-546 |

Other Identifiers | TC-SSU-201206546 |

Repository | sask |

Date Retrieved | 2020-07-15 |

Date Indexed | 2020-07-20 |

Sample Search Hits | Sample Images

…133
Table 4.48 Summary of descriptive data analysis of study *collision* databases, 2005-2009....... 142
Table 4.49 Summary of “C(α) *Test*” results, 2005-2009. ......................................................... 143
Table 5.1 Top 30…

…149
Table 5.4 Results of descriptive data analysis and BB *test* for four most frequent *collision*
configurations at top 10 signalized intersections, 2005-2009. ................................... 152
Table 5.5 Number and percentage of top 30 riskiest…

…signalized intersections for the four
most frequent *collision* configurations based on the BB *test* results, 2005-2009. ...... 155
x
LIST OF FIGURES
Figure 1.1 Trend of PDO, injury, and fatal collisions per 100,000 people in Saskatoon,
2005-2009…

…5.3 Top 10 riskiest signalized intersections showing probability of top four *collision*
configurations based on the BB *test* results, 2005-2009. ......................................... 157
xiv
LIST OF SYMBOLS
Observed number of collisions for a…

…histograms, and
*collision* diagrams as main tools to identify the most frequent dominant *collision* configurations at
hotspots. The HSM also proposed the BB *test* as a supplementary diagnosis tool when the
descriptive data analysis fails to identify the most…

…screening methods (binomial *test*
and/or BB *test*) for identifying and ranking high *collision* locations with and without traffic
volume data in the City of Saskatoon;
2. To introduce a statistical *test* to quantitatively justify the circumstances when…

…the BB *test* is a
more appropriate network screening method than the binomial *test*;
3. To develop a set of GIS *collision* maps as a tool of communication to more efficiently visualize
the network screening results; and
4. To quantitatively compare the…

…outcomes from two different *collision* diagnosis methods
(descriptive data analysis and BB *test*) to determine the method that could be regarded as a
more rigorous diagnosis method.
1.4.
Scope of the Study
The roadway network in Saskatoon is the…