Comparison of free flow speed estimation models

Free flow speed (FFS) is the drivers’ desired speed on roadways at low traffic volume and absence of traffic control devices whose determination is a fundamental step in the analysis of two-lane highways. FFS can either be estimated using either analytical model or based on field measurement. Regarding the former approach; the Malaysian Highway Capacity Manual (MHCM) established a model for estimating FFS based on base-free-flow-speed (BFFS), roadway’s geometric features and fraction of motorcycles in the traffic stream. On the other hand, the Highway Capacity Manual (HCM) suggested an approach for field measurement of FFS; preferably at a two-way flow rate not exceeding 200 veh/h. For many highways, observing a two-way flow rate of 200 veh/h or less is seldom met or impossible. In such situations, mean speed could be observed at higher flow rates and adjusted accordingly using a model provided by the HCM. This study describes the application of the two approaches for measuring FFS. Moving car observer (MCO) method was used for collecting the relevant data related to travel time, speed, flow rate, and traffic composition with using a video recording instrumented test vehicle while the roadway geometric features were measured manually. Data for the study were collected on four directional segments of rural two-lane highways with varying geometric features and traffic composition in Johor, Malaysia. Field data obtained were analyzed to estimate the FFS using the two approaches. Results obtained from both methods were compared to ascertain the degree of their consistency or otherwise. Statistical analysis using student t-test indicates that there is no statistically significant difference between the FFS estimates from the two approaches

Traffic monitoring using image processing : a thesis presented in partial fulfillment of the requirements for the degree of Master of Engineering in Information and Telecommunications Engineering at Massey University, Palmerston North, New Zealand

Traffic monitoring involves the collection of data describing the characteristics of vehicles and their movements. Such data may be used for automatic tolls, congestion and incident detection, law enforcement, and road capacity planning etc. With the recent advances in Computer Vision technology, videos can be analysed automatically and relevant information can be extracted for particular applications. Automatic surveillance using video cameras with image processing technique is becoming a powerful and useful technology for traffic monitoring. In this research project, a video image processing system that has the potential to be developed for real-time application is developed for traffic monitoring including vehicle tracking, counting, and classification. A heuristic approach is applied in developing this system. The system is divided into several parts, and several different functional components have been built and tested using some traffic video sequences. Evaluations are carried out to show that this system is robust and can be developed towards real-time applications

Pedestrian behaviour in urban area

The pedestrian behavior is influenced by several factors, including: characteristics of the user, numerousness of group, road infrastructures and environmental factors. These factors were studied by means the collection of data carried out in the city of Oristano (Sardinia-Italy) on eleven sidewalks and five crosswalks. The objective was to study the pedestrians behavior, researching the link between independent variables and the dependent variables that, for sidewalks was only the pedestrian speed while for crosswalks were the speed of crossing, the crossing time, the waiting time and the total time. The regression models were constructed by using ten sidewalks and four crosswalks so ignoring one for each. In the construction, were considered more variables that gradually were excluded on the basis of the p-value. The models thus detected were deemed significant according to their coefficient of determination and were validated with data from the sidewalk or crosswalk excluded from the construction of the same. Both for sidewalks that crosswalks were found some reliable models. The models construction is useful to improve the understanding of the pedestrians behavior and then obtain useful indications to design pedestrian infrastructures with characteristics closer to the real pedestrians behavior. The present study aims to give greater importance to pedestrians, analyzing how they relate with the urban context in which they live and how it conditions their behavior, so as to design infrastructure in which they feel an integral part and main actors of the urban scene, giving them the respect they deserve and a new sense of belonging to the city in which they live

Wide area detection system: Conceptual design study

An integrated sensor for traffic surveillance on mainline sections of urban freeways is described. Applicable imaging and processor technology is surveyed and the functional requirements for the sensors and the conceptual design of the breadboard sensors are given. Parameters measured by the sensors include lane density, speed, and volume. The freeway image is also used for incident diagnosis