When planning their transport policy, cities usually focus on developing sustainable transport systems and reducing the negative consequences of transport. One way to deliver transport policies is to use the Sustainable Urban Mobility Plan (SUMP), a strategic document designed to meet the demand for mobility whilst ensuring adequate quality of life for the residents. The process of Sustainable Urban Mobility Planning (SUMP process) can be supported by using a transport model. The objective of this article is to analyse the efficacy of the Multilevel Model of Transport Systems—referred to by its acronym, MST—for the SUMP process. With its ability to represent the transport system’s behaviour depending on the level of detail, the MST can significantly benefit the SUMP process. The proposed concept of integration of the MST into the SUMP process has already been tested and applied in delivering Gdynia’s (Poland) SUMP. The paper suggests ways to use the MST at different levels of planning and modelling and describes the outcomes. Using the multilevel structure helps to fully realise the transport model’s potential to improve the effectiveness of urban mobility planning. The conclusions show that the methods proposed in the article are worthwhile and cities should consider them when planning the SUMP process.

The fundamental relationship of traffic flow and bivariate relations between speed and flow, speed and density, and flow and density are of great importance in transportation engineering. Fundamental relationship models may be applied to assess and forecast traffic conditions at uninterrupted traffic flow facilities. The objective of the article was to analyze and compare existing models of the fundamental relationship. To that end, we proposed a universal and quantitative method for assessing models of the fundamental relationship based on real traffic data from a Polish expressway. The proposed methodology seeks to address the problem of finding the best deterministic model to describe the empirical relationship between fundamental traffic flow parameters: average speed, flow, and density based on simple and transparent criteria. Both single and multi-regime models were considered: a total of 17 models. For the given data, the results helped to identify the best performing models that meet the boundary conditions and ensure simplicity, empirical accuracy, and good estimation of traffic flow parameters.

According to the UN, road safety is the key to achieving sustainable development goals, yet the complexity of how road accidents happen makes this a difficult challenge leaving many countries struggling with the problem. For years, Poland has infamously been one of the EU’s top countries for road-accident fatality rates. Despite that, it has made significant progress in the last thirty years with a fatality reduction of more than 60%. A number of factors have contributed to this result: improving the socioeconomic situation, improving road safety measures, changing road user behaviour and changing national road safety programmes. This article presents Poland’s approach to road safety and, in particular, Vision Zero, adopted in 2005. Poland’s road safety changed over the years as the country learned from its successes and failures. Tools for forecasting fatalities were developed and used to identify the main factors that have helped to reduce deaths. An assessment was conducted on how Poland could implement Vision Zero until 2050 under different road safety scenarios. It was found that in order to achieve the EU’s goal for 2030, Poland must reduce fatalities to 1200. While it is an ambitious goal, it is also an important step towards zero fatalities in 2050.

Adverse weather such as rain, snow, and fog may significantly reduce visibility or change adhesion properties and, as a consequence, affect drivers’ sense of safety, driving comfort, and their reaction to a changing driving environment (i.e., lower speed and increased headways). The changed behavior of individual drivers affects both traffic flow characteristics, that is, average speed and headways, and parameters related to highway performance such as free-flow speed and capacity. Thus, understanding the impact may be important in the context of predicting and assessing traffic conditions on planned or existing road facilities. The paper discusses the effects of adverse weather conditions and time of day on traffic flow characteristics and the parameters related to highway performance. Using real traffic and weather data from a Polish expressway, the paper aims to identify factors related to weather and time of day that significantly influence traffic flow parameters and traffic conditions and to analyze and quantify this impact. The results of the study may help to develop coefficients of weather-related adjustment factors that will make it possible to estimate, for example, average speed of vehicles in the nighttime or in conditions of rain or limited visibility. The results of the study may contribute to a new Polish method for capacity estimation and traffic conditions assessment for uninterrupted traffic facilities.

An important challenge to achieving sustainable university campuses is ensuring that the academic community makes sustainable transport choices. The objective of this study was to investigate the daily commuting patterns, identify the potential for change, and determine the factors and criteria affecting the transport decisions of academic communities of two universities located in Gdansk, Poland. This paper summarizes the results of trip generation measurements and a comprehensive online survey of 3678 respondents, including the universities’ staff and students. Analysis of survey results revealed clear differences between students and university staff in terms of travel patterns and factors that influence their choices. Staff usually (57%) choose the car for daily commutes with students opting for public transport (59%). The choice of travel mode in particular groups is determined mostly by car availability, trip origin location, and accessibility. The choices also depend on transport user individual requirements such as trip quality, costs, or ecology. With approximately 1400 trips daily per 1000 students, the universities are large traffic generators. Thus, how the staff and students behave determines the effect the universities have on the urban transport system. Understanding the behaviour can help to estimate whether it can be changed and how.