A velocidade elevada e a sua variabilidade são consideradas fatores determinantes na causa de acidentes e gravidade dos mesmos. A freqüência dos acidentes decresce quando os limites de velocidade estabelecidos são apropriados ou realísticos. O limite estabelecido deve estar de acordo com as velocidades praticadas pela média dos condutores ditos prudentes, ou este limite não será considerado. No presente estudo é elaborado um método para estabelecimento de limites de velocidade básicos para rodovias de pista simples do Estado do Rio Grande do Sul. O método parte das velocidades operacionais da via e de seus graus de mobilidade e acessibilidade, sugerindo um limite de velocidade único para os dois sentidos da via. Também são sugeridas velocidades de advertência em curvas do alinhamento horizontal. Seis rodovias do Estado do Rio Grande do Sul foram selecionadas para um estudo de caso. A seleção procura englobar rodovias de classes de projeto e região diferentes, para que se possa fazer uma análise ampla de projetos de rodovias. As rodovias, a partir de suas velocidades operacionais e dados de geometria, têm seus limites de velocidade calculados. Na seqüência, as velocidades de advertência são calculadas. Os resultados são apresentados em forma de gráficos para facilitar a compreensão da distribuição das velocidades ao longo da extensão do trecho. Os resultados de cada trecho são analisados e comparados. / High speed and its variability are considered determining factors in the cause of accidents and its severity. The frequency of accidents decreases when the speed limits established are appropriate or realistic. The limit must be established in accordance with the speeds practiced by the average conservative drivers, or this limit will not be considered. In the present study a method is developed to establish basic speed limits for two-lane highways of the state of Rio Grande do Sul. The method relies on the operational speed of the track and its degrees of mobility and accessibility, suggesting one speed limit for both ways of the road. It is also suggested warning speeds for curves in the horizontal alignment. Six two-lane highways of the state of Rio Grande do Sul were selected for a case study. The selection was made so all classes of project and different regions were included, in a way that analysis of different projects could be done. The two-lane highways have their limits of speed calculated, from their operating speeds and geometry data. Next, the warning speeds are calculated. The results are presented in the form of graphs to facilitate the understanding of the distribution of velocities along the length of the segment. The results of each different segment are analyzed and compared.

O objetivo desta pesquisa foi recalibrar um modelo de simulação de rodovias de pista simples a fim de seja possível usá-lo no estudo de estradas do Estado de São Paulo. O modelo escolhido para recalibração é o TRARR (TRAffic on Rural Roads) versão 4.0, desenvolvido na Austrália pelo ARRB Transport Research Ltd. A recalibração do modelo consistiu em alterar parâmetros referentes ao desempenho (relação potência/massa) e características (massa, comprimento) dos veículos pesados e um parâmetro relativo ao comportamento dos veículos quando viajando em pelotões, de tal modo que os resultados da simulação ficassem compatíveis com os observados em campo. As medidas de desempenho escolhidas para a recalibração foram: a porcentagem de veículos trafegando em pelotões, a velocidade média dos veículos e a taxa de ultrapassagens. Os dados para a recalibração do modelo foram coletados num trecho de 2,8 km de extensão, na rodovia SP 255, entre as cidades paulistas de Araraquara e Ribeirão Preto. No processo de recalibração, as medidas de desempenho observadas no campo foram comparadas com as produzidas pelas versões recalibrada e original do simulador. Ao final da recalibração, pôde-se concluir que as duas versões do modelo são capazes de simular adequadamente o trecho estudado, sendo que o modelo recalibrado produz resultados ligeiramente melhores que os da versão original. O modelo recalibrado foi validado simulando-se um trecho de 10 km de extensão da SP 255 e comparando-se os valores medidos no trecho para as medidas de desempenho escolhidas com os valores produzidos pela versão recalibrada do simulador. Os resultados dessa comparação indicam que o modelo pode ser considerado capaz de simular adequadamente a operação de rodovias de pista simples no Estado de São Paulo. Os resultados do estudo também sugerem que a precisão pode ser melhorada com um ajuste fino de alguns dos parâmetros não modificados durante a recalibração. / The objective of this research is to recalibrate a two-lane highway simulation model to allow its employment within the context of the São Paulo state highways, Brazil. The model chosen for this recalibration is TRARR (TRAffic on Rural Roads) version 4.0, originally developed a in Australia by ARRB Transport Research Ltd. The procedure used for the model recalibration consisted in modifying input parameters related to heavy vehicle dimensions and performance characteristics (power/mass ratio, weight and length) as well as to the behavior of vehicles in platoons, in such a way that the model outputs are compatible with real traffic behavior. Three measures of performance were chosen for recalibration of the model: percent of jouney time spent following, average speed and overtaking rate. Data for model recalibration were collected at a 2.8 km rural section of SP 225, a highway which connects the cities of Ribeirão Preto and Araraquara in the state of São Paulo (Brazil). The recalibration procedure was based on comparisons of the measures of performance observed on the real highway with those produced by the simulator\'s recalibrated and original versions. At the end of the recalibration process, both the recalibrated and the original models were considered capable of reproducing the traffic behavior on a two-lane highway similar to the ones in the state of São Paulo. Furthermore, it was concluded that the recalibrated model is capable of producing results slightly better than the original one. The recalibrated model was submitted to a validation procedure in which a 10 km section of SP 255 was simulated and the measures of perfomance obtained with the model were compared to field observations. The results of the validation procedure indicate that recalibrated version of TRARR is capable of simulating traffic operations on rural two-lane highways in the state of São Paulo. The results of the research also suggest that the model results may be improved with fine-tuning of some of the parameters that were not modified during the recalibration procedure.

Number of lanes is a basic roadway attribute that is widely used in many transportation applications. Traditionally, number of lanes is collected and updated through field surveys, which is expensive especially for large coverage areas with a high volume of road segments. One alternative is through manual data extraction from high-resolution aerial images. However, this is feasible only for smaller areas. For large areas that may involve tens of thousands of aerial images and millions of road segments, an automatic extraction is a more feasible approach. This dissertation aims to improve the existing process of extracting number of lanes from aerial images automatically by making improvements in three specific areas: (1) performance of lane model, (2) automatic acquisition of external knowledge, and (3) automatic lane location identification and reliability estimation. In this dissertation, a framework was developed to automatically recognize and extract number of lanes from geo-rectified aerial images. In order to address the external knowledge acquisition problem in this framework, a mapping technique was developed to automatically estimate the approximate pixel locations of road segments and the travel direction of the target roads in aerial images. A lane model was developed based on the typical appearance features of travel lanes in color aerial images. It provides more resistance to “noise” such as presence of vehicle occlusions and sidewalks. Multi-class classification test results based on the K-nearest neighbor, logistic regression, and Support Vector Machine (SVM) classification algorithms showed that the new model provides a high level of prediction accuracy. Two optimization algorithms based on fixed and flexible lane widths, respectively, were then developed to extract number of lanes from the lane model output. The flexible lane-width approach was recommended because it solved the problems of error-tolerant pixel mapping and reliability estimation. The approach was tested using a lane model with two SVM classifiers, i.e., the Polynomial kernel and the Radial Basis Function (RBF) kernel. The results showed that the framework yielded good performance in a general test scenario with mixed types of road segments and another test scenario with heavy plant occlusions.

This master thesis describes transport projects in Orlikoústecko region. At the first part it concerns on the general history of transport and actual trends in road, railway and cycle transport in European Union and Czech republic. In next part it characterizes Pardubice region and describes chosen transport projects in Orlickoustecko region. It focuses especially on legislation, financing methods and complete description of each project.

Advanced Driving Assistance Systems (ADAS) has the potential to decrease the number of fatal accidents in traffic. However, in some cases, drivers with the systems in their car are resistant against using them. Exploring the underlying reasons and factors of the low-usage of ADAS was the purpose of this thesis. The thesis consists of Study I, an exploratory interview study with ten drivers who had cars with ADAS. The goal of Study I was to highlight the possible reasons behind the low usage of ADAS. The results of Study I were used to design Study II, which consisted of a survey targeted to drivers who had access to the ADAS adaptive cruise control and lane keep assist (N = 49). The results indicate that the factors or circumstances that affect usage depend on the ADAS and the user groups. Some identified underlying factors for low usage behavior of ADAS are the need to monitor the vehicle more when ADAS is activated and lack of trust in own ability when using ADAS compared to the high usage group. / Advanced Driving Assistance Systems (ADAS) har potential att förhindra antalet dödsfall i trafiken. Det förekommer att förare som har systemen i sin bil, väljer bort att använda dem. Syftet med den här uppsatsen var att undersöka underliggande orsaker och faktorer till låg användningsgrad av ADAS. Uppsatsen består av två studier. Studie I är en explorativ intervjustudie med tio förare som hade bilar med ADAS. Målet med Studie I var att ringa in de möjliga bakomliggande faktorerna för låg användningsgrad av ADAS. Resultaten från Studie I användes för att utforma en enkätstudie till Studie II som var riktad till förare som hade bilar med förarstödsystemen adaptiv farthållare och körfältsassistans (N = 49). Resultaten pekar på att de underliggande orsakerna och faktorerna beror på vilken ADAS som avses samt vilket användargrupp föraren tillhör. Några underliggande faktorer för låg användingsgruppen tycks vara känsla av att behöva övervaka fordonet samt lägre grad av tilltro till den egna förmågan än vad höganvändingsgrupper rapporterade.

The Indiana Department of Transportation (INDOT) manages and maintains over 3,000 miles of interstates across the state. Assessing lane marking quality is an important part of agency asset tracking and typically occurs annually. The current process requires agency staff to travel the road and collect representative measurements. This is quite challenging for high volume multi-lane facilities. Furthermore, it does not scale well to the additional 5,200 centerline miles of non-interstate routes. <div><br></div><div>Modern vehicles now have technology on them called “Lane Keep Assist” or LKA, that monitor lane markings and notify the driver if they are deviating from the lane. This thesis evaluates the feasibility of monitoring when the LKA systems can and cannot detect lane markings as an alternative to traditional pavement marking asset management techniques. This information could also provide guidance on what corridors are prepared for level 3 autonomous vehicle travel and which locations need additional attention. </div><div><br></div><div>In this study, a 2019 Subaru Legacy with LKA technology was utilized to detect pavement markings in both directions along Interstates I-64, I-65, I-69, I-70, I-74, I90, I-94 and I-465 in Indiana during the summer of 2020. The data was collected in the right most lane for all interstates except for work zones that required temporary lane changes. The data was collected utilizing two go-pro cameras, one facing the dashboard collecting LKA information and one facing the roadway collecting photos of the user’s experience. Images were taken at 0.5 second frequency and were GPS tagged. Data collection occurred on over 2,500 miles and approximately 280,000 images were analyzed. The data provided outputs of: No Data, Excluded, Both Lanes Not Detected, Right Lane Not Detected, Left Lane Not Detected, and Both Lanes Detected. </div><div><br></div><div>The data was processed and analyzed to create spatial plots signifying locations where markings were detectable and locations where markings were undetected. Overall, across 2,500 miles of travel (right lane only), 77.6% of the pavement markings were classified as both detected. The study found</div><div><br></div><div>• 2.6% the lane miles were not detected on both the left and right side </div><div>• 5.2% the lane miles were not detected on the left side </div><div>• 2.0% the lane miles were not detected on the right side 8 </div><div><br></div><div>Lane changes, inclement weather, and congestion caused 12.5% of the right travel lane miles to be excluded. The methodology utilized in this study provides an opportunity to complement the current methods of evaluating pavement marking quality by transportation agencies. </div><div><br></div><div>The thesis concludes by recommending large scale harvesting of LKA from a variety of vendors so that complete lane coverage during all weather and light conditions can be collected so agencies have an accurate assessment of how their pavement markings perform with modern LKA technology. Not only will this assist in identifying areas in need of pavement marking maintenance, but it will also provide a framework for agencies and vehicle OEM’s to initiate dialog on best practices for marking lines and exchanging information.</div>

In lane departure warning systems (LDWS) it is important that the auditory warning triggers a fast and appropriate reaction from the driver. The rumble strip noise is a suitable warning to alert the driver of an imminent lane departure. A short reaction time is important in lane departure scenarios, where a late response may have fatal consequences. For abstract sounds an increase in intensity can influence the perceived urgency level of the warning, which may also trigger a faster reaction from the listener. In this thesis, the effect of a rumble strip warning with looming (increasing) intensity was analyzed by letting test persons drive a driving simulator and measuring how quickly they reacted to the auditory warning. These results were compared with those for a rumble strip warning with a constant intensity, and two versions of an abstract warning; constant intensity and looming intensity. A survey regarding the perceived urgency, annoyance and acceptance of the warnings was also carried out. The results show no differences in reaction time between the four warning signals. This may be because the test persons expected the warnings, or because of their limited experience. The survey suggests that adding a looming intensity to the rumble strip warning results in a higher urgency, while keeping the annoyance low, which could be of importance to avoid unwanted reactions from the driver. / I varningssystem för personbilar används ofta ett system som signalerar ett stundande ofrivilligt lämnande av körfältet, s.k. lane departure warning systems (LDWS), genom att en varningssignal ljuder. Det är viktigt att en sådan akustisk varningssignal frammanar en snabb och lämplig reaktion från föraren. Ljudet av en bullerräffla är en lämplig varningssignal för detta ändamål. En kort reaktionstid är viktig när fordon är på väg att ofrivilligt lämna körfältet, då en långsam reaktion kan ha förödande konsekvenser. Studier på abstrakta akustiska varningssignaler har visat att en ökande intensitet kan få en varning att verka mer brådskande, vilket i sin tur kan leda till att lyssnaren reagerar snabbare. I denna rapport analyseras hur ett bullerräffleljuds ökande intensitet påverkar förarens reaktionstid. Analysen gjordes genom att mäta reaktionstiden hos testpersoner som körde en bilsimulator med fyra olika varningssignaler; en bullerräffleljudsvarning och en abstrakt varning, båda med konstant intensitet och ökande intensitet. Reaktionstiderna för de olika signalerna jämfördes, varpå en enkät utfärdades där testpersonerna uppgav hur brådskande och irriterande de uppfattade varningarna, samt till vilken grad de skulle acceptera varningarna i ett verkligt körscenario. Resultaten visar inga skillnader i reaktionstid mellan varningarna, vilket kan bero på att testpersonerna förutsåg när varningarna skulle komma, eller på grund av deras begränsade erfarenhet av bullerräffleljud. Enkätens utfall antyder att bullerräffleljudsvarningen med ökande intensitet är mer brådskande än versionen med konstant intensitet, men att irritationsnivån inte påverkas när intensiteten ökar, vilket kan vara viktigt för att inte framkalla oönskade reaktioner hos föraren.

This thesis proposes changes to the Golden Lane Estate in central London to integrate the public spaces within the estate with the surrounding city[M1] .   The Golden[M2]  Lane Estate is a modernist housing complex consisting of nine residential buildings with 564 flats. It was built as a council house project in 1952-1962 to satisfy the housing need after the Second World War.   Current observations show that the public spaces at the Golden Lane Estate are mostly empty and spread over different levels increasing the spatial separation. Residents use the large open spaces for transit to or from their flats and visitors are rarely attracted. The modernist layout, where few people share space in front of the entrances to their flats, have affected the perceived ownership of public space at Golden Lane. It is neither perceived as private nor fully public.   I have assumed that the residential buildings should stay intact. They are architecturally and historically valuable and serve their purpose well. The flats are popular and the estate was listed in 1992.   The Golden Lane Leisure Centre is situated in the middle of the estate. In the listing record it is described as a chief example of the architects’ belief that a housing development should not just be a collection of flats but a real part of the city; it provides welcome facilities for those who live outside the estate as well as for residents.   By reviving the Leisure Centre and turning unused garages into offices the two western public spaces are activated and restructured to be attractive to residents and visitors again. The revenue from the commercial spaces can finance an upgrade of the eastern public spaces to be a calm oasis where residents can realise their gardening dreams or office workers have their lunch. Today’s Golden Lane Estate can become a real part of the city with four attractive places adding value for residents, workers and visitors.

<p>Unsafe lane changes have been identified as a common factor in motor vehicle accidents. It would be helpful, particularly for automated vehicles, to know if there are behaviors of vehicles, beyond a directional signal, or characteristics of the traffic environment that correlated with a higher probability of an unsafe lane change (lane changes without a directional signal). This work investigates what the observable cues are that drivers use to determine the relative safety when overtaking front vehicles, and if drivers make more lane changes under certain conditions on highways. This study utilizes interviews, surveys, 3D animation software, and highway driving public footage for data collection and experiments. It is found that a side-to-side motion of the front vehicle or a factor that might trigger a side-to-side motion of the front vehicle in the environment is the key marker that indicates a possible unsafe lane change, and it is also found that traffic speed, time of day, traffic flow, and a combination of traffic density & number of lanes & vehicle count all have effects on drive’s decision on making lane changes on different levels.</p>

A self-driven car is a vehicle that can drive without human intervention by making correct decisions based on the environmental conditions. Since the innovation is in its beginning periods, totally moving beyond the human inclusion is still a long shot. However, rapid technological advancements are being made towards the safety of the driver and the passengers. One such safety feature is a Lane Detection System that empowers vehicle to detect road lane lines in various climate conditions. This research provides a feasible and economical solution to detect the road lane lines while driving in a sunny, rainy, or snowy weather condition. An algorithm is designed to perform real time road lane line detection on a low voltage computer that can be easily powered in a regular auto vehicle. The algorithm runs on a RaspberryPi computer placed inside the car. A camera, attached to the vehicle’s windshield, captures the real time images and passes them to the RaspberryPi for processing. The algorithm processes each frame and determines the lane lines. The detected lane lines can be viewed on a 7 inch display screen connected to the Raspberry Pi. The entire system is mounted inside a Jeep Wrangler to conduct the experiments and is powered by the vehicle’s standard charger of 12V-15V power supply. The algorithm provides approximately 97% accurate detection of road lane lines in all weather conditions.