INJURY PREDICTION MODELS FOR ONSHORE ROAD NETWORK DEVELOPMENT

被引:5
|
作者
Kustra, Wojciech [1 ]
Zukowska, Joanna [1 ]
Budzynski, Marcin [1 ]
Jamroz, Kazimierz [1 ]
机构
[1] Gdansk Univ Technol, Fac Civil & Environm Engn, Narutowicza 11, PL-80233 Gdansk, Poland
关键词
Road safety; Polish national roads; density of injuries; log logistic and gamma distribution; risk management; MOTOR-VEHICLE CRASHES; POISSON-GAMMA MODELS; ACCIDENT; SAFETY; SEVERITY; REGRESSION; INTERSECTION; PARAMETERS; CHINA; FIT;
D O I
10.2478/pomr-2019-0029
中图分类号
U6 [水路运输]; P75 [海洋工程];
学科分类号
0814 ; 081505 ; 0824 ; 082401 ;
摘要
Integrating different modes of transport (road, rail, air and water) is important for port cities. To accommodate this need, new transport hubs must be built such as airports or sea ports. If ports are to grow, they must be accessible, a feature which is best achieved by building new roads, including fast roads. Poland must develop a network of fast roads that will provide good access to ports. What is equally important is to upgrade the network of national roads to complement fast roads. A key criterion in this case is to ensure that the roads are efficient to minimise time lost for road users and safe. With safety standards and safety management practices varying vastly across the EU, Directive 2008/96/EC of the European Parliament and of the Council was a way to ensure that countries follow procedures for assessing the impact of road projects on road safety and conduct road safety audits, road safety management and road safety inspections. The main goal of the research was to build mathematical models to combine road safety measures, i.e. injury density (DI) and accident density (DA), with road and traffic factors on longer sections, all based on risk analysis. The practical objective is to use these models to develop tools for assessing how new road projects will impact road safety. Because previous research on models to help estimate injuries (I) or injury density (DI) on long sections was scarce, the authors addressed that problem in their work. The idea goes back to how Poland is introducing procedures for assessing the effects of infrastructure on safety and developing a method to estimate accident indicators to support economic analysis for new roads, a solution applied in JASPERS. Another reason for the research was Poland's insufficient and ineffective pool of road safety management tools in Poland. The paper presents analyses of several models which achieved satisfactory results. They are consistent with the work of other researchers and the outcomes of previous research conducted by the authors. The authors built the models based on a segmentation of national roads into sections from 10 to 50 km, making sure that they feature consistent cross-sections and average daily traffic volumes. Models were built based on the method described by Jamroz (Jamroz, 2011). Using the available road traffic volume data, each section was assigned variables defining geometric and traffic features. Based on studies conducted on road sections, the variables were either averaged over the entire length of the section or calculated as a percentage of the variable occurring over the entire length: related to traffic volume, roadside environment or cross section
引用
收藏
页码:93 / 103
页数:11
相关论文
共 50 条
  • [31] DEVELOPMENT AND UPGRADING OF TWO-LANE SINGLE ROAD NETWORK IN POLAND
    Tracz, Marian
    Kiec, Mariusz
    ROADS AND BRIDGES-DROGI I MOSTY, 2016, 15 (03): : 191 - 206
  • [32] Multivariable Prediction Models for Traumatic Spinal Cord Injury: A Systematic Review
    Hakimjavadi, Ramtin
    Basiratzadeh, Shahin
    Wai, Eugene K.
    Baddour, Natalie
    Kingwell, Stephen
    Michalowski, Wojtek
    Stratton, Alexandra
    Tsai, Eve
    Viktor, Herna
    Phan, Philippe
    TOPICS IN SPINAL CORD INJURY REHABILITATION, 2024, 30 (01) : 1 - 44
  • [33] Comparison of supervised machine learning algorithms for road traffic crash prediction models in Rwanda
    de Dieu, Gatesi Jean
    Bin, Shuai
    Huang, Wencheng
    Mathieu, Ntakiyemungu
    PROCEEDINGS OF THE INSTITUTION OF CIVIL ENGINEERS-TRANSPORT, 2023, : 83 - 98
  • [34] Accident Prediction Models for Winter Road Safety Does Temporal Aggregation of Data Matter?
    Usman, Taimur
    Fu, Liping
    Miranda-Moreno, Luis F.
    TRANSPORTATION RESEARCH RECORD, 2011, (2237) : 144 - 151
  • [35] Pedestrian Road Safety Analysis Based on Macro-Level Collision Prediction Models
    Tian, Zhun
    Zhang, Shengrui
    CICTP 2021: ADVANCED TRANSPORTATION, ENHANCED CONNECTION, 2021, : 1771 - 1780
  • [36] Road traffic accident prediction for mixed traffic flow using artificial neural network
    Yeole M.
    Jain R.K.
    Menon R.
    Materials Today: Proceedings, 2023, 77 : 832 - 837
  • [37] The Fuzzy Regression Prediction of the City Road Traffic Accident
    Luo Yong
    Zhang Shibo
    2009 INTERNATIONAL CONFERENCE ON INDUSTRIAL MECHATRONICS AND AUTOMATION, 2009, : 121 - 124
  • [38] Collision prediction models using multivariate Poisson-lognormal regression
    El-Basyouny, Karim
    Sayed, Tarek
    ACCIDENT ANALYSIS AND PREVENTION, 2009, 41 (04) : 820 - 828
  • [39] Predicting Road Accident Counts in Poland and the Czech Republic Using Neural Network Models
    Gorzelanczyk, Piotr
    Lizbetinova, Lenka
    Pecman, Jan
    ROCZNIK OCHRONA SRODOWISKA, 2024, 26 : 603 - 615
  • [40] Development and validation of prediction models for endometrial cancer in postmenopausal bleeding
    Wong, Alyssa Sze-Wai
    Cheung, Chun Wai
    Fung, Linda Wen-Ying
    Lao, Terence Tzu-Hsi
    Mol, Ben Willem J.
    Sahota, Daljit Singh
    EUROPEAN JOURNAL OF OBSTETRICS & GYNECOLOGY AND REPRODUCTIVE BIOLOGY, 2016, 203 : 220 - 224