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"Traffic engineering Germany."
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Urbanism and transport in Germany : building blocks for architects and city and transport planners
\"Helmut Holzapfel's Urbanism and Transport in Germany, a bestseller in its own country, now available in English, examines the history and the future of urban design for transport in major European cities. Holzapfel shows the social impact of the automobile throughout German and European history, and the cultural, political, and economic processes that promoted it. From the unlikely birth of the automobile in Germany, and its shared history with the fascist government of 1933-1945, to new models of \"shared space\" and street and settlement networks, Holzapfel shows how the car has shaped the urban fabric of Europe, from roads, to neighborhoods and houses, to the city at large. Focusing not just on planning, but on historical, architectural, and economic factors, Urbanism and Transport in Germany offers new vistas and solutions to problems of urban sprawl and automobile-centric urban design\"--Provided by publisher.
Book
Quantitative and qualitative changes in substance-related administrative offences in road traffic during the SARS-CoV-2 pandemic in Munich
The SARS-CoV-2 pandemic beginning in 2020 led to significant restrictions on social life and mobility, raising concerns about increased substance use across the general population. To investigate whether the pandemic resulted in quantitative or qualitative changes in alcohol and/or drug use in the context of road traffic, a retrospective analysis of toxicological findings was conducted in the city of Munich, considering the local pandemic-related restrictions.
A total of 6,210 blood samples were analyzed from individuals suspected of committing substance-related administrative traffic offences under §24a of the German Road Traffic Act between January 1, 2019, and July 31, 2021. Samples were examined for the presence of substances, their concentrations, and the type of vehicle involved. The cohort was stratified into pre-pandemic and pandemic periods, with March 16, 2020 set as the cut-off date. The pandemic period was further subdivided based on the severity of imposed restrictions. Statistical comparisons were performed using Fisher's exact test, t-tests, ANOVA, and logistic regression.
Cannabis was the most frequently detected substance (66.2% pre-pandemic; 67.4% during the pandemic), followed by alcohol (11.7% vs. 10.8%) and cocaine (5.7% vs. 5.2%). Only minor differences were observed between the pre-pandemic and pandemic periods, as well as across phases of mild versus severe restrictions. Notably, THC-COOH concentrations were higher during the pandemic. Alcohol levels were elevated during phases of light restrictions and reduced during periods of strict lockdown. Cannabis was most commonly detected in car drivers, whereas alcohol was more frequently found in e-scooter riders, particularly during less restrictive phases.
Substance detection patterns among drivers in Munich showed overall stability during the COVID-19 pandemic, with cannabis remaining the most commonly identified drug. However, shifts in substance concentrations and differences by vehicle type and restriction severity suggest subtle changes in consumption behavior. These findings underscore the need for continued surveillance and context-specific traffic safety measures.
Journal Article
Automated vehicles and sustainability when considering rebound effects
While automated vehicles are expected to lower energy consumption, improve traffic flow and enhance road safety, their deployment may increase traffic volume, leading to a rebound effect. Addressing this issue, we develop a framework to assess the environmental, social and time costs of private and of shared automated vehicle usage in urban and rural areas in Germany. When comparing the status quo and automated vehicle usage, we show that 34–47% of additional traffic volume could emerge without deteriorating current conditions, depending on the area and usage concept. Shared automated vehicles in rural areas constitute the most distinct case, as they are the most beneficial for the environment and society but are the least attractive with respect to the time costs of passengers. Policymakers and system providers should strive to mitigate this dichotomy.
Journal Article
Modeling hourly weather-related road traffic variations for different vehicle types in Germany
Weather has a substantial influence on people’s travel behavior. In this study we analyze if meteorological variables can improve predictions of hourly traffic counts at 1400 stations on federal roads and highways in Germany. Motorbikes, cars, vans and trucks are distinguished. It is evaluated in how far the mean squared error of Poisson regression models for hourly traffic counts is reduced by using precipitation, temperature, cloud cover and wind speed data. It is shown that in particular motorbike counts are strongly weather-dependent. On federal roads the mean squared error is reduced by up to 60% in models with meteorological predictor variables, when compared to models without meteorological variables. A detailed analysis of the models for motorbike counts reveals non-linear relationships between the meteorological variables and motorbike counts. Car counts are shown to be specifically sensitive to weather in touristic regions like seaside resorts and nature parks. The findings allow for several potential applications like improvements of route planning in navigation systems, implementations in traffic management systems, day-ahead planning of visitor numbers in touristic areas or the usage in road crash modelling.
Journal Article
Simultaneous internalization of traffic congestion and noise exposure costs
This study elaborates on the interrelation of external effects, in particular road traffic congestion and noise. An agent-based simulation framework is used to compute and internalize user-specific external congestion effects and noise exposures. The resulting user equilibrium corresponds to an approximation of the system optimum. For traffic congestion and noise, single objective optimization is compared with multiple objective optimization. The simulation-based optimization approach is applied to the real-world case study of the Greater Berlin area. The results reveal a negative correlation between congestion and noise. Nevertheless, the multiple objective optimization yields a simultaneous reduction in congestion and noise. During peak times, congestion is the more relevant external effect, whereas, during the evening, night and morning, noise is the more relevant externality. Thus, a key element for policy making is to follow a dynamic approach, i.e. to temporally change the incentives. During off-peak times, noise should be reduced by concentrating traffic flows along main roads, i.e. inner-city motorways. In contrast, during peak times, congestion is reduced by shifting transport users from the inner-city motorway to smaller roads which, however, may have an effect on other externalities.
Journal Article
Influence of an Automated Vehicle with Predictive Longitudinal Control on Mixed Urban Traffic Using SUMO
In this paper, an approach to quantify the area of influence of an intelligent longitudinally controlled autonomous vehicle in an urban, mixed-traffic environment is proposed. The intelligent vehicle is executed with a predictive longitudinal control, which anticipates the future traffic scenario in order to reduce unnecessary acceleration. The shown investigations are conducted within a simulated traffic environment of the city center of Darmstadt, Germany, which is carried out in the traffic simulation software “Simulation of Urban Mobility” (SUMO). The longitudinal dynamics of the not automated vehicles are considered with the Extended Intelligent Driver Model, which is an approach to simulate real human driver behavior. The results show that, in addition to the energy saving caused by a predictive longitudinal control of the ego vehicle, this system can also reduce the consumption of surrounding traffic participants significantly. The area of influence can be quantified to four vehicles and up to 250 m behind.
Journal Article
Cell-Based Optimization of Air Traffic Control Sector Boundaries Using Traffic Complexity
The increasing demand for air travel has intensified the need for more efficient air traffic management (ATM) solutions. One of the key challenges in this domain is the optimal sectorization of airspace to ensure balanced controller workload and operational efficiency. Traditional airspace sectors, typically static and based on historical flow patterns, often fail to adapt to evolving traffic complexity, resulting in imbalanced workload distribution and reduced system performance. This study introduces a novel methodology for optimizing ATC sector geometries based on air traffic complexity indicators, aiming to enhance the balance of operational workload across sectors. The proposed optimization is formulated in the horizontal plane using a two-dimensional cell-based airspace representation. A graph-partitioning optimization model with spatial and operational constraints is applied, along with a refinement step using adjacent-cell pairs to improve geometric coherence. Tested on real data from Madrid North ACC, the model achieved significant complexity balancing while preserving sector shapes in a real-world case study based on a Spanish ACC. This work provides a methodological basis to support static and dynamic airspace design and has the potential to enhance ATC efficiency through data-driven optimization.
Journal Article
Do citizens support the transformation of urban transport? Evidence for the acceptability of parking management, car lane conversion and road closures from a German case study
Facing the challenges of motorised traffic, many cities around the globe started implementing measures to transform their urban transport systems. One of the major challenges for the success of adequate policies is not only their effectiveness but also whether they are accepted by city residents. With a quantitative case study in four neighbourhoods in Frankfurt am Main (N = 821), this article investigates the acceptability of three measures: (i) parking management, (ii) the conversion of car lanes into cycle lanes and (iii) the closure of an inner city arterial road to car traffic. The results show a surprisingly high acceptability for all measures if the benefits for local residents are tangible. Thus, successful policy packages may combine push measures with either pull measures, as suggested frequently in the literature, or with improvements for other land uses (e.g. re-using former car-parking spaces for non-transport purposes, such as greenery or seating areas). Furthermore, the perceived effectiveness, daily travel practices and intentions to reduce car use, the built environment and, to a lesser degree, socio-demographics explain differences in acceptability by population group.
Journal Article
Noise Annoyance Is Associated with Depression and Anxiety in the General Population- The Contribution of Aircraft Noise
While noise annoyance has become recognized as an important environmental stressor, its association to mental health has hardly been studied. We therefore determined the association of noise annoyance to anxiety and depression and explored the contribution of diverse environmental sources to overall noise annoyance.
We investigated cross-sectional data of n = 15.010 participants of the Gutenberg Health Study (GHS), a population-based, prospective, single-center cohort study in Mid-Germany (age 35 to 74 years). Noise annoyance was assessed separately for road traffic, aircraft, railways, industrial, neighborhood indoor and outdoor noise (\"during the day\"; \"in your sleep\") on 5-point scales (\"not at all\" to \"extremely\"); depression and anxiety were assessed by the PHQ-9, resp. GAD-2.
Depression and anxiety increased with the degree of overall noise annoyance. Compared to no annoyance, prevalence ratios for depression, respectively anxiety increased from moderate (PR depression 1.20; 95%CI 1.00 to 1.45; PR anxiety 1.42; 95% CI 1.15 to 1.74) to extreme annoyance (PR depression 1.97; 95%CI 1.62 to 2.39; PR anxiety 2.14; 95% CI 1.71 to 2.67). Compared to other sources, aircraft noise annoyance was prominent affecting almost 60% of the population.
Strong noise annoyance was associated with a two-fold higher prevalence of depression and anxiety in the general population. While we could not relate annoyance due to aircraft noise directly to depression and anxiety, we established that it was the major source of annoyance in the sample, exceeding the other sources in those strongly annoyed. Prospective follow-up data will address the issue of causal relationships between annoyance and mental health.
Journal Article
Association between Source-Specific Particulate Matter Air Pollution and hs-CRP: Local Traffic and Industrial Emissions
Long-term exposures to particulate matter air pollution (PM2.5 and PM10) and high traffic load have been associated with markers of systemic inflammation. Epidemiological investigations have focused primarily on total PM, which represents a mixture of pollutants originating from different sources.
We investigated associations between source-specific PM and high-sensitive C-reactive protein (hs-CRP), an independent predictor of cardiovascular disease.
We used data from the first (2000-2003) and second examination (2006-2008) of the Heinz Nixdorf Recall study, a prospective population-based German cohort of initially 4,814 participants (45-75 years of age). We estimated residential long-term exposure to local traffic- and industry-specific fine particulate matter (PM2.5) at participants' residences using a chemistry transport model. We used a linear mixed model with a random participant intercept to estimate associations of source-specific PM and natural log-transformed hs-CRP, controlling for age, sex, education, body mass index, low- and high-density lipoprotein cholesterol, smoking variables, physical activity, season, humidity, and city (8,204 total observations).
A 1-μg/m3 increase in total PM2.5 was associated with a 4.53% increase in hs-CRP concentration (95% CI: 2.76, 6.33%). hs-CRP was 17.89% (95% CI: 7.66, 29.09%) and 7.96% (95% CI: 3.45, 12.67%) higher in association with 1-μg/m3 increases in traffic- and industry-specific PM2.5, respectively. RESULTS for PM10 were similar.
Long-term exposure to local traffic-specific PM (PM2.5, PM10) was more strongly associated with systemic inflammation than total PM. Associations of local industry-specific PM were slightly stronger but not significantly different from associations with total PM.
Journal Article