Abstract

This paper provides a system dynamic model for reducing the number of motorway accidents due to wrong-way driving. Motorway accidents are often fatal due to high speeds. It is therefore necessary to carry out all the possible countermeasures in order to achieve adequate traffic management. One of the reasons for motorway accidents is driving in the wrong direction. Based on the analysis of the data on motorway accidents caused by driving in the wrong direction and based on the knowledge of individual project elements of junctions and slip roads, this paper will focus on this area. The possible countermeasures, presented here for preventing drivers from driving in the wrong direction on motorways drastically reduce the number of U-turn maneuvers that result in driving in the wrong direction and influence the level of safety on motorways. With the help of this model of system dynamics the countermeasures for reducing the number of such drivers will be confirmed and their effects will be shown. Članek podaja model zniževanja prometnih nesreč zaradi nepravilne smeri vožnje na avtocestah. Prometne nesreče na avtocestah so zaradi velike hitrosti vožnje velikokrat tragične, zato je potrebno izvesti vse možne ukrepe za ustrezno upravljanja prometa. Eden od vzrokov nastanka prometnih nesreč na avtocesti je nepravilna smer vožnje. Na podlagi analiz podatkov o prometnih nesrečah zaradi nepravilne smeri vožnje na avtocestah ter na osnovi poznavanja posameznih projektnih elementov vozlišč in priključkov se pričujoče delo usmerja na to področje. Predstavljeni možni ukrepi za preprečevanje nepravilne smeri vožnje na avtocestah v veliki meri znižujejo število nepravilnih prometnih manevrov, ki imajo za posledico nepravilno smer vožnje in s tem pozitivno vplivajo na raven prometne varnosti na avtocestah. S pomočjo modela sistemske dinamike bo potrjena upravičenost ukrepov za zmanjševanje števila primerov nepravilne smeri vožnje in prikazani njihovi učinki.

Abstract

Increasing mobility and congestion results in an increase in travel time variability and in a decrease in reliability. Reliability becomes an important performance measure for transportation facilities. A variety of performance measures have been proposed to quantify it. Many of these indicators are based on percentiles of travel time. The knowledge of the distribution of travel time is needed to properly estimate these values. Congestion distorts the distribution and particular statistical distributions are needed. Different distributions have been proposed in the literature. In a previous paper, we presented a comparison of six statistical distributions used to model travel time. These six distributions are the Lognormal, Gamma, Burr (extended by Singh-Maddala), Weibull, a mixture of two Normal distributions and a mixture of two Gamma distributions. In this paper a probabilistic modeling of travel time which takes into account the levels-of-service is given. Levels of service are identified, then travel time distributions are modeled by level of service. This results in a very good fit between the empirical and modeled distributions Moreover, the adjustment was improved, thanks to the calibration of “Bureau of Public Roads” functions, linking the travel time to the traffic flow by level of service. The superiority of the Singh-Maddala distribution appears in many cases. This has been validated, thanks to travel time data from the same site at another period. However the parameters of the distributions vary from one year to another, due to changes in infrastructure. The transferability of the approach, not performed, will be based on travel time data on another site. Document type: Conference object

Abstract

© Copyright 2016 by SCITEPRESS - Science and Technology Publications, Lda. All rights reserved.The urbanized mankind is faced with vulnerability of urban systems, migration and concentration of population, low quality of habitat, loss of fertile land, and necessity of waste disposal. In large cities, a significant contribution to atmospheric pollution with sulphur dioxide, nitrogen and carbon oxides, and industrial dust comes from the motor transport. The motor traffic growth inevitably affects the human health by causing road and transport traumatism, respiratory diseases and diseases caused by physical inactivity. The proposed solution is based on optimization of a city transport system parameters. This was achieved by via simulation modelling taking into account a large number of parameters, both within and outside the system, many of the latter being stochastic. The recommendations include rearranging of the public transport routes and changing over to vehicles running on gas motor fuel.

Abstract

"jats:title"Objective"/jats:title" "jats:p"The emphasis of the study presented in this paper was to identify the attributes of drivers who are prone to cause a motorway crash. It was induced byambitions to enhance the effectiveness of traffic safety campaigns by identifying subgroups of drivers more precisely."/jats:p" "/jats:sec""jats:sec" "jats:title"Method"/jats:title" "jats:p"For this purpose we conducted an accident data analysis of all injury crashes 2012–2014 on Austrian motorways. Since 2012 it is possible for the police to label the “mainly responsible person” for the crash in the Austrian electronic accident recording system. It turned out that the quality of the data had some limitations, which required considerable pre-processing. The analysis by comparing the proportions of “mainly responsible” and “not responsible” drivers was done using descriptive statistics and logistic regression models. The binary characteristic, if a person was, according to the police, mainly responsible for the crash served as response variable. It was regressed on various personal and vehicle characteristics in order to identify their influence on the probability of causing a crash."/jats:p" "/jats:sec""jats:sec" "jats:title"Results/Conclusions"/jats:title" "jats:p"The results yield apparent tendencies, some of which support well-known pattern, e.g., the disproportionally high risk of motorcyclists and - to a lesser extent - young and elderly car drivers to cause an accident. Other results were less expected, e.g., the higher risk of foreign car drivers (compared to Austrian drivers) as well as drivers of light trucks, whereas drivers of heavy trucks revealed a below-average risk of causing a crash. The differences between male and female car drivers were small from young to middle age and fully disappeared in the high age group. There is some evidence that the frequency and experience of driving on a motorway have more influence on the risk of causing a crash than the driver’s gender. From this we conclude that motorway safety campaigns should on the one hand focus on the abovementioned groups of high risk drivers and on the other hand, in terms of car drivers, equally address both male and female drivers."/jats:p" "/jats:sec Document type: Article