scholarly journals Influence of Winter Road Conditions and Signal Delay on Pedestrian Route Choice in Japan's Snowiest Metropolis

2005 ◽  
Vol 1939 (1) ◽  
pp. 145-153
Author(s):  
Thambiah Muraleetharan ◽  
Kunio Meguro ◽  
Takeo Adachi ◽  
Toru Hagiwara ◽  
Sei'ichi Kagaya
Keyword(s):  
Questionnaire Survey ◽  
Choice Behavior ◽  
Field Survey ◽  
Surface Condition ◽  
Route Choice ◽  
Road Surface ◽  
Field Surveys ◽  
Surface Conditions ◽  
The Road ◽  
Route Choice Behavior

Investigation of pedestrian route choice behavior on icy surfaces is important for the effective improvement of walkways in winter. The objective of this research was to investigate pedestrian route choice behavior in winter. Field surveys and questionnaire surveys were conducted to fulfill this objective. Video cameras were used in the field surveys to clarify the movements of pedestrians. How pedestrians chose their routes was investigated by observing their movements. According to the field survey, when the signal was green, the probability that the pedestrian would cross became extremely high, regardless of the road surface conditions. However, when the walkway surface was icy, the probability that the pedestrian would wait for a green signal decreased by a considerable value. This indicates that when the wait becomes long, the probability that the pedestrian will cross becomes low during the snowy season. A questionnaire survey was also conducted to clarify the factors affecting pedestrian route choice behavior. The questionnaire asked about different road surface conditions. The results from the survey indicate that even if part of a road section has a good surface condition, it has a strong influence on route choice behavior. It indicates that pedestrians feel uncomfortable in walking on slippery walkways and they prefer to choose bare walkways. On the basis of the data from the field survey and questionnaire survey, logit models were developed to express quantitatively the route choice behaviors of pedestrians. These models can be used to predict the probability that a pedestrian will select a route as a function of pedestrian delay at signalized intersections and the road surface conditions in winter.

scholarly journals Road Surface Condition Forecasting in France

2009 ◽  
Vol 48 (12) ◽  
pp. 2513-2527 ◽  
Author(s):  
L. Bouilloud ◽  
E. Martin ◽  
F. Habets ◽  
A. Boone ◽  
P. Le Moigne ◽  
...  
Keyword(s):  
Surface Temperature ◽  
Initial Conditions ◽  
Meteorological Data ◽  
Surface Condition ◽  
Road Surface ◽  
Snow Layer ◽  
Surface Conditions ◽  
The Road ◽  
Road Surface Temperature ◽  
On The Road

Abstract A numerical model designed to simulate the evolution of a snow layer on a road surface was forced by meteorological forecasts so as to assess its potential for use within an operational suite for road management in winter. The suite is intended for use throughout France, even in areas where no observations of surface conditions are available. It relies on short-term meteorological forecasts and long-term simulations of surface conditions using spatialized meteorological data to provide the initial conditions. The prediction of road surface conditions (road surface temperature and presence of snow on the road) was tested at an experimental site using data from a comprehensive experimental field campaign. The results were satisfactory, with detection of the majority of snow and negative road surface temperature events. The model was then extended to all of France with an 8-km grid resolution, using forcing data from a real-time meteorological analysis system. Many events with snow on the roads were simulated for the 2004/05 winter. Results for road surface temperature were checked against road station data from several highways, and results for the presence of snow on the road were checked against measurements from the Météo-France weather station network.

scholarly journals Introducing Road Surface Conditions into a Microscopic Traffic Simulation

10.29007/cqps ◽  
2019 ◽  
Author(s):  
Thomas Weber ◽  
Patrick Driesch ◽  
Dieter Schramm
Keyword(s):  
Traffic Simulation ◽  
Surface Condition ◽  
Road Surface ◽  
Automated Driving ◽  
Microscopic Traffic Simulation ◽  
Surface Conditions ◽  
Main Research ◽  
Car Following ◽  
The Road ◽  
Car Following Model

The introduction of highly automated driving functions is one of the main research and development efforts in the automotive industry worldwide. In the early stages of the development process, suppliers and manufacturers often wonder whether and to what extend the potential of the systems under development can be estimated in a cheap and timely manner. In the context of a current research project, a sensor system for the detection of the road surface condition is to be developed and it is to be investigated how such a system can be used to improve higher level driving functions. This paper presents how road surface conditions are introduced in various elements of the microscopic traffic simulation such as the actual network, the network editor, a device for detection, and an adaptation of the standard Krauß car following model. It is also shown how the adaptations can subsequently affect traffic scenarios. Furthermore, a summary is given how this preliminary work integrates into the larger scope of using SUMO as a tool in the process of analyzing the effectiveness of a road surface condition sensor.

AN ANALYSIS OF TRUCKS' ROUTE CHOICE BEHAVIOR CONSIDERING VEHICLE TYPE AND TRIP LENGTH

2018 ◽  
Vol 74 (5) ◽  
pp. I_657-I_666
Author(s):  
Hideki OKA ◽  
Makoto CHIKARAISHI ◽  
Jun TANABE ◽  
Daisuke FUKUDA ◽  
Takashi OGUCHI
Keyword(s):  
Choice Behavior ◽  
Route Choice ◽  
Trip Length ◽  
Vehicle Type ◽  
Route Choice Behavior

scholarly journals Design of an artificial simulator for analyzing route choice behavior in the presence of information system

1995 ◽  
Vol 22 (4-7) ◽  
pp. 119-147 ◽  
Author(s):  
P.D.V.G. Reddy ◽  
H. Yang ◽  
K.M. Vaughn ◽  
M.A. Abdel-Aty ◽  
R. Kitamura ◽  
...  
Keyword(s):  
Information System ◽  
Choice Behavior ◽  
Route Choice ◽  
Route Choice Behavior

A geostatistical approach to winter road surface condition estimation using mobile RWIS data

2019 ◽  
Vol 46 (6) ◽  
pp. 511-521
Author(s):  
Lian Gu ◽  
Tae J. Kwon ◽  
Tony Z. Qiu
Keyword(s):  
Robust Regression ◽  
Surface Condition ◽  
Road Surface ◽  
Road Maintenance ◽  
Surface Conditions ◽  
Modelling Framework ◽  
Geostatistical Approach ◽  
Winter Road ◽  
Systematic Framework

In winter, it is critical for cold regions to have a full understanding of the spatial variation of road surface conditions such that hot spots (e.g., black ice) can be identified for an effective mobilization of winter road maintenance operations. Acknowledging the limitations in present study, this paper proposes a systematic framework to estimate road surface temperature (RST) via the geographic information system (GIS). The proposed method uses a robust regression kriging method to take account for various geographical factors that may affect the variation of RST. A case study of highway segments in Alberta, Canada is used to demonstrate the feasibility and applicability of the method proposed herein. The findings of this study suggest that the geostatistical modelling framework proposed in this paper can accurately estimate RST with help of various covariates included in the model and further promote the possibility of continuous monitoring and visualization of road surface conditions.

scholarly journals Road Hazard Assessment Using Pothole and Traffic Data in South Korea

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Choong Heon Yang ◽  
Jin Guk Kim ◽  
Sung Pil Shin
Keyword(s):  
Hazard Assessment ◽  
Traffic Safety ◽  
Hazard Index ◽  
Surface Damage ◽  
Road Surface ◽  
Risk Level ◽  
Traffic Data ◽  
Surface Conditions ◽  
The Road ◽  
Damage Data

Road surface conditions have a direct effect on the quality of driving, which in turn affects overall traffic flow. Many studies have been conducted to accurately identify road surface conditions using diverse technologies. However, these previously proposed methods may still be insufficient to estimate actual risks along the roads because the exact road risk levels cannot be determined from only road surface damage data. The actual risk level of the road must be derived by considering both the road surface damage data as well as other factors such as speed. In this study, the road hazard index is proposed using smartphone-obtained pothole and traffic data to represent the level of risk due to road surface conditions. The relevant algorithm and its operating system are developed to produce the estimated index values that are classified into four levels of road risk. This road hazard index can assist road agencies in establishing road maintenance plans and budgets and will allow drivers to minimize the risk of accidents by adjusting their driving speeds in advance of dangerous road conditions. To demonstrate the proposed risk hazard assessment methodology, road hazards were assessed along specific test road sections based on observed pothole and historical travel speed data. It was found that the proposed methodology provides a rational method for improving traffic safety.

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