Details:

Creators:
Mitra, Sudeshna
Corporate Creators:
California Polytechnic State University, San Luis Obispo. College of Engineering. Dept. of Civil & Environmental Engineering
Subject/TRT Terms:
[+]
Geographic Information Systems--California--Inland Empire
Traffic Accidents--California--Inland Empire
Traffic Safety--California--Inland Empire
Accidents
Collisions
Geographic Information Systems
Traffic Accidents
Traffic Safety

Resource Type:
Tech Report
Geographical Coverage:
California
OCLC Number:
681772058
Corporate Publisher:
Leonard Transportation Center
NTL Classification:
NTL-GEOGRAPHIC INFORMATION SYSTEMS-GEOGRAPHIC INFORMATION SYSTEMS ; NTL-SAFETY AND SECURITY-Accidents ; NTL-SAFETY AND SECURITY-SAFETY AND SECURITY ;
Abstract:
It is well known that the major goal of the transportation system is to enhance

mobility and crashes are unwanted by-products which have to be minimized

while achieving the primary goal. Although general people value travel time more

than any other outcomes of transportation system, traffic accidents impose huge

economic burden on the society. A detail investigation of the State of California

crash statistics showed overrepresentation of fatal, injury, alcohol related crashes,

road departure crashes, speeding related crashes in Inland Empire and identified

as one of the major transportation issues affecting this region. This seed-grant

proposal aimed to investigate the reason behind the high crash statistics in

Inland Empire by developing methodologies to identify crash hotspots and

detecting the potential areas of safety improvements using Geographic

Information System (GIS). However, significant challenges were faced during the

research to obtain relevant crash data from Caltrans district 8. Hence the GIS

based methodology was developed using data from another real city in the

United States. The result of this study showed that spatial dependence plays a

strong role in the analysis of road traffic injury crashes. These spatial

dependences, accounted through the spatial autocorrelation helped detecting

statistically significant clusters of fatal, severe and minor injury as well as

pedestrian crashes. These clusters are overlaid with socioeconomic and road

network layers to investigate if certain spatial, socioeconomic and traffic related

factors are present near statistically significant crash clusters. Once this

reconnaissance is completed, a more detailed site investigation is easier to find

the contributory factors for fatal, injury and pedestrian crash occurrences.


Format:
PDF
Collection(s):
US Transportation Collection
University Transportation Centers
Main Document Checksum:
[+]
urn:sha256:098fde23b438faacba4d46ccd812ae7235191ea2efb1813a38cd4a03450a38a9
File Type:

Supporting Files

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