Evaluation

Modeling Secondary Accidents Identified by Traffic Shock Waves

Wang, Junhua
Liu, Boya
Lanfang, Zhang
Ragland, David R.
2015

The high potential for occurrence and the negative consequences of secondary accidents make them an issue of great concern affecting freeway safety. Using accident records from a three-year period together with California interstate freeway loop data, a dynamic method for more accurate classification based on the traffic shock wave detecting method was used to identify secondary accidents. Spatio-temporal gaps between the primary and secondary accident were proven be fit via a mixture of Weibull and normal distribution. A logistic regression model was developed to investigate major factors...

Identification of Freeway Secondary Accidents with Traffic Shock Wave Detected by Loop Detectors

Wang, Junhua
Xie, Wenjing
Liu, Boya
Fang, Shou'en
Ragland, David R.
2016

Secondary traffic accidents are generally recorded without being specifically noted as such in the accident database, leading to difficulty in the study of such accidents. Previous research generally classified secondary incidents by predefining fixed spatio-temporal boundaries—a method that can be very subjective. Using 10,762 accident records gathered from 2012 upstream loop detector data on a California interstate freeway, this paper proposes a dynamic method for more convincing and accurate classification based on traffic shock waves detected by the loop detectors. This method...

Utilizing the Eigenvectors of Freeway Loop Data Spatiotemporal Schematic for Real Time Crash Prediction

Fang, Shou'en
Xie, Wenjing
Wang, Junhua
Ragland, David R.
2016

The concept of crash precursor identification is gaining more practicality due to the recent advancements in Advanced Transportation Management and Information Systems. Investigating the shortcomings of the existing models, this paper proposes a new method to model the real time crash likelihood based on loop data through schematic eigenvectors. Firstly, traffic volume, occupancy and density spatiotemporal schematics in certain duration before an accident occurrence were constructed to describe the traffic flow status. Secondly, eigenvectors and eigenvalues of the spatiotemporal schematics...

Safety Assessment of Uncontrolled Intersections Using Both Conflict Probability and Severity

Ma, Yingying
Qin, Xiaoran
Grembek, Offer
Chen, Zhiwei
2016

This paper presents a method to assess the safety of uncontrolled intersections considering both conflict probability and severity, which are two major properties of traffic conflicts. This method provides not only the safety level of the entire intersection but also the distribution of safety within intersections. Intersections are modelled by a two-dimensional Cartesian coordinate system and the internal space of intersections is divided into cells. Firstly, vehicle movement characteristics of at uncontrolled intersections are modelled. Secondly, conflict probability of each cell within...

The 2026 CSSA Peer Exchange Series launches this month!

April 6, 2026
Submitted by Kris Leckie
UC Berkeley SafeTREC is excited to announce our 2026 virtual two-part Peer Exchange series: “Advancing safety through the CSSA.” The series, part of the Complete Streets Safety Assessment (CSSA) program, will feature two former participant communities as they reflect on their experiences with the program – from their initial application to the real-world safety impacts of their comprehensive safety reports.

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Community Trainings at Work: An Evaluation of Community Pedestrian and Bicycle Safety Trainings

Beck, Kate M.
2019

The Community Pedestrian Bicycle Safety Training (CPBST) program trains and mobilizes communities to address pedestrian and bicycle safety and strengthens collaboration with local officials and agency staff. This research brief summarizes an evaluation of the CPBST program completed in 2018.

Impact of the Community Pedestrian and Bicycle Safety Training Program: Insights from the 2022 Follow-Up Survey

Aqshems Nichols
Chen, Katherine L.
Jill F. Cooper
2022

The Community Pedestrian Bicycle Safety Training (CPBST) program is a collaborative project between UC Berkeley Safe Transportation Research and Education Center (SafeTREC) and California Walks (Cal Walks) that seeks to assist communities with three goals:

Identifying and better understanding their local transportation safety needs; Developing and strengthening local partnerships between various stakeholders in their community; and Generating a community-specific action plan for improving the safety of active transportation in their area.

These objectives are pursued through...

Sites chosen for 2026 Complete Streets Safety Assessments program

March 23, 2026
Submitted by Katherine Chen
UC Berkeley SafeTREC and Fehr & Peers are excited to announce the selection of 16 communities throughout California for our 2026 Complete Streets Safety Assessment (CSSA) program! These sites represent a diverse range of cities, counties, and tribal lands committed to eliminating traffic fatalities and improving mobility for all road users.

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Impact of the Community Pedestrian and Bicycle Safety Training: Program Insights from the 2023 Follow-Up Survey

Lekshmy Hirandas
2023

The Community Pedestrian and Bicycle Safety Training Program (CPBST) is a collaborative effort between the Safe Transportation Research and Education Center (SafeTREC) at the University of California Berkeley and California Walks (Cal Walks), established in 2009, with funding from the California Office of Traffic Safety. Its main objective is to promote pedestrian and bicycle safety by educating...

Pedestrian Crash Risk on Boundary Roadways University Campus Case Study

Schneider, Robert J.
Grembek, Offer
Braughton, Matthew
2013

Prominent pedestrian trip attractors, such as college campuses and major urban parks, are often surrounded by roadways with high volumes of motor vehicle traffic. Although many pedestrians cross busy boundary roadways, relatively little is known about the pedestrian crash risk along these types of facilities. This study quantifies pedestrian crash risk at roadway intersections on the boundary of the University of California, Berkeley, campus during typical spring and fall semester weekdays. Manual pedestrian counts were extrapolated with data from three automated counter locations to...