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Related Concept Videos

Survival Tree01:19

Survival Tree

Survival trees are a non-parametric method used in survival analysis to model the relationship between a set of covariates and the time until an event of interest occurs, often referred to as the "time-to-event" or "survival time." This method is particularly useful when dealing with censored data, where the event has not occurred for some individuals by the end of the study period, or when the exact time of the event is unknown.
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Classification of Systems-I01:26

Classification of Systems-I

Linearity is a system property characterized by a direct input-output relationship, combining homogeneity and additivity.
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Classification of Systems-II01:31

Classification of Systems-II

Continuous-time systems have continuous input and output signals, with time measured continuously. These systems are generally defined by differential or algebraic equations. For instance, in an RC circuit, the relationship between input and output voltage is expressed through a differential equation derived from Ohm's law and the capacitor relation,
Aggregates Classification01:29

Aggregates Classification

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Structural Classification of Joints01:20

Structural Classification of Joints

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Design Example: Alignment of a Road Line Using GIS01:17

Design Example: Alignment of a Road Line Using GIS

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Related Experiment Video

Updated: Jun 6, 2026

Evaluating the Effect of Roadside Parking on a Dual-Direction Urban Street
14:55

Evaluating the Effect of Roadside Parking on a Dual-Direction Urban Street

Published on: January 20, 2023

A classification tree based modeling approach for segment related crashes on multilane highways.

Anurag Pande1, Mohamed Abdel-Aty, Abhishek Das

  • 1Department of Civil & Environmental Engineering, California Polytechnic State University, San Luis Obispo, CA 93407, USA. apande@calpoly.edu

Journal of Safety Research
|November 10, 2010
PubMed
Summary
This summary is machine-generated.

This study introduces a classification tree method for analyzing multilane arterial crashes, offering a new tool for safety analysis without arbitrary segment lengths. It identifies key factors influencing crash types and times.

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Last Updated: Jun 6, 2026

Evaluating the Effect of Roadside Parking on a Dual-Direction Urban Street
14:55

Evaluating the Effect of Roadside Parking on a Dual-Direction Urban Street

Published on: January 20, 2023

Area of Science:

  • Traffic Safety Engineering
  • Transportation Planning
  • Data Science in Transportation

Background:

  • Traditional crash frequency analysis struggles with mid-block segments due to arbitrary length requirements.
  • Existing methods are less suitable for analyzing crashes on arterial corridors compared to intersections.

Purpose of the Study:

  • To present a classification tree-based alternative for analyzing crashes on mid-block segments of multilane arterials.
  • To develop a method for assessing roadway safety without segmenting corridors into arbitrary lengths.

Main Methods:

  • Utilized random sampling of time, day of week, and location (milepost) for crash and non-crash data.
  • Derived geometric design, roadside, and traffic characteristics based on milepost locations.
  • Developed classification tree models comparing all crashes and specific crash types (rear-end, lane-change, pedestrian, single-vehicle/off-road) against non-crash data.

Main Results:

  • Classification tree models identified significant variables and provided a means to classify crashes.
  • Average Daily Traffic (ADT), time of day, and day of week were significantly related to all crash types.
  • Different crash types exhibited distinct temporal patterns, with varying likelihoods at different times.

Conclusions:

  • Classification tree models offer a valuable tool for safety analysis, avoiding arbitrary data aggregation.
  • Non-event specific information may be less suitable for analyzing single-vehicle/off-road crashes.