Aims and Scope
Recent Articles
The Effects of Picking Up Primary School Pupils on Surrounding Street’s Traffic: A Case Study in Hanoi
Dinh Hiep, Vu V. Huy, Teppei Kato, Aya Kojima, Hisashi Kubota
Introduction:
One of the significant characteristics of schools in Vietnam is that almost all parents send their children to school and/or pick up their children from school using private vehicles (motorcycles). The parents usually stop and park their vehicle on streets outside the school gates, which can lead to serious congestion and increases the likelihood of traffic accidents.
Methods:
The objective of this study is to find out factors affecting the picking up of pupils at primary school by evaluating the typical primary schools in Hanoi city. A binary logistic regression model was used to determine factors that influence the decision of picking up pupils and the waiting duration of parents. The behavior of motorcyclists during the process of picking up pupils at the primary school gate has been identified and analyzed in detail by the Kinovea software.
Results and Discussion:
The study showed that, on the way back home, almost all parents use motorbikes (89.15%) to pick up their children. During their waiting time (8.48 minutes in average), they made a lot of illegal parking actions on the street there by, causing a lot of “cognitive” errors and “crash” points surrounding in front of the primary school entrance gate. Risky picking-up behaviors were significantly observed, i.e. picking-up on opposite side of the school, making a U-turn, backing-up dangerously, parking on the middle of street, and parking on the street next to sidewalk).
Conclusion:
Based on the analyzed results, several traffic management measures have been suggested to enhance traffic safety and reduce traffic congestion in front of school gates. In addition, the results of the study will provide a useful reference for policymakers and authorities.
December 31, 2020
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- December 21, 2020
The Extent of Capacity Loss Caused by Rainfall at Signalised Intersections
November 25, 2020
Adaptive Frame of Universal Vehicle Course
August 25, 2020Application of Geographical Information System Techniques to Determine High Crash-Prone Areas in the Fort Peck Indian Reservation
July 30, 2020
Comparisons Between Braking Experiments and Longitudinal Train Dynamics Using Friction Coefficient and Braking Pressure Modeling in a Freight Train
July 14, 2020
The Strategic Positioning of Moroccan Seaports: An Application of the Boston Consulting Group Growth-share Matrix
July 03, 2020
Crowdsourcing as a Social Interaction Tool to Stimulate Sustainable Transportation Mode Use
Editor's Choice
Travel-time Prediction Using K-nearest Neighbor Method with Distance Metric of Correlation Coefficient
Jinhwan Jang
Background:
Real-time Travel Time (TT) information has become an essential component of daily life in modern society. With reliable TT information, road users can increase their productivity by choosing less congested routes or adjusting their trip schedules. Drivers normally prefer departure time-based TT, but most agencies in Korea still provide arrival time-based TT with probe data from Dedicated Short-Range Communications (DSRC) scanners due to a lack of robust prediction techniques. Recently, interest has focused on the conventional k-nearest neighbor (k-NN) method that uses the Euclidean distance for real-time TT prediction. However, conventional k-NN still shows some deficiencies under certain conditions.
Methods:
This article identifies the cases where conventional k-NN has shortcomings and proposes an improved k-NN method that employs a correlation coefficient as a measure of distance and applies a regression equation to compensate for the difference between current and historical TT.
Results:
The superiority of the suggested method over conventional k-NN was verified using DSRC probe data gathered on a signalized suburban arterial in Korea, resulting in a decrease in TT prediction error of 3.7 percent points on average. Performance during transition periods where TTs are falling immediately after rising exhibited statistically significant differences by paired t-tests at a significance level of 0.05, yielding p-values of 0.03 and 0.003 for two-day data.
Conclusion:
The method presented in this study can enhance the accuracy of real-time TT information and consequently improve the productivity of road users.
September 30, 2019
Other Post
- January 18, 2018
Effect of Traffic Flow, Proportion of Motorcycle, Speed, Lane Width, and the Availabilities of Median and Shoulder on Motorcycle Accidents at Urban Roads in Indonesia
January 22, 2018
A Simulation Model to Determine the Capacity of a Y-Type Waterway Intersection for a Real Seaport
January 29, 2018
Effectiveness of Experimental Left-Turn Sign Usage in Terms of Crashes and Analyzing Severity of Left Turn Crashes in Alaska
January 29, 2018
Collisions Between Pedestrians and Reversing Vehicles in Public Settings in France
February 28, 2017
Impact of Integrated Multimodal Traveler Information on Auto Commuter’s Mode Switching Propensity
March 23, 2017
From Macro to Microscopic Trip Generation: Representing Heterogeneous Travel Behavior
