561 resultados para Real-world scenarios
Resumo:
This paper describes an application of decoupled probabilistic world modeling to achieve team planning. The research is based on the principle that the action selection mechanism of a member in a robot team can select an effective action if a global world model is available to all team members. In the real world, the sensors are imprecise, and are individual to each robot, hence providing each robot a partial and unique view about the environment. We address this problem by creating a probabilistic global view on each agent by combining the perceptual information from each robot. This probabilistic view forms the basis for selecting actions to achieve the team goal in a dynamic environment. Experiments have been carried out to investigate the effectiveness of this principle using custom-built robots for real world performance, in addition, to extensive simulation results. The results show an improvement in team effectiveness when using probabilistic world modeling based on perception sharing for team planning.
Resumo:
Ideas of 'how we learn' in formal academic settings have changed markedly in recent decades. The primary position that universities once held on shaping what constitutes learning has come into question from a range of experience-led and situated learning models. Drawing on findings from a study conducted across three Australian universities, the article focuses on the multifarious learning experiences indicative of practice-based learning exchanges such as student placements. Building on both experiential and situated learning theories, the authors found that students can experience transformative and emotional elucidations of learning, that can challenge tacit assumptions and transform the ways they understand the world. It was found that all participants (hosts, students, academics) both teach and learn in these educative scenarios and that, contrary to common (mis)perceptions that academics live in 'ivory towers', they play a crucial role in contributing to learning that takes place in the so-called 'real world'.
Resumo:
Continuous biometric authentication schemes (CBAS) are built around the biometrics supplied by user behavioural characteristics and continuously check the identity of the user throughout the session. The current literature for CBAS primarily focuses on the accuracy of the system in order to reduce false alarms. However, these attempts do not consider various issues that might affect practicality in real world applications and continuous authentication scenarios. One of the main issues is that the presented CBAS are based on several samples of training data either of both intruder and valid users or only the valid users' profile. This means that historical profiles for either the legitimate users or possible attackers should be available or collected before prediction time. However, in some cases it is impractical to gain the biometric data of the user in advance (before detection time). Another issue is the variability of the behaviour of the user between the registered profile obtained during enrollment, and the profile from the testing phase. The aim of this paper is to identify the limitations in current CBAS in order to make them more practical for real world applications. Also, the paper discusses a new application for CBAS not requiring any training data either from intruders or from valid users.
Resumo:
This paper demonstrates the application of a robust form of pose estimation and scene reconstruction using data from camera images. We demonstrate results that suggest the ability of the algorithm to rival methods of RANSAC based pose estimation polished by bundle adjustment in terms of solution robustness, speed and accuracy, even when given poor initialisations. Our simulated results show the behaviour of the algorithm in a number of novel simulated scenarios reflective of real world cases that show the ability of the algorithm to handle large observation noise and difficult reconstruction scenes. These results have a number of implications for the vision and robotics community, and show that the application of visual motion estimation on robotic platforms in an online fashion is approaching real-world feasibility.
Resumo:
Vehicle emitted particles are of significant concern based on their potential to influence local air quality and human health. Transport microenvironments usually contain higher vehicle emission concentrations compared to other environments, and people spend a substantial amount of time in these microenvironments when commuting. Currently there is limited scientific knowledge on particle concentration, passenger exposure and the distribution of vehicle emissions in transport microenvironments, partially due to the fact that the instrumentation required to conduct such measurements is not available in many research centres. Information on passenger waiting time and location in such microenvironments has also not been investigated, which makes it difficult to evaluate a passenger’s spatial-temporal exposure to vehicle emissions. Furthermore, current emission models are incapable of rapidly predicting emission distribution, given the complexity of variations in emission rates that result from changes in driving conditions, as well as the time spent in driving condition within the transport microenvironment. In order to address these scientific gaps in knowledge, this work conducted, for the first time, a comprehensive statistical analysis of experimental data, along with multi-parameter assessment, exposure evaluation and comparison, and emission model development and application, in relation to traffic interrupted transport microenvironments. The work aimed to quantify and characterise particle emissions and human exposure in the transport microenvironments, with bus stations and a pedestrian crossing identified as suitable research locations representing a typical transport microenvironment. Firstly, two bus stations in Brisbane, Australia, with different designs, were selected to conduct measurements of particle number size distributions, particle number and PM2.5 concentrations during two different seasons. Simultaneous traffic and meteorological parameters were also monitored, aiming to quantify particle characteristics and investigate the impact of bus flow rate, station design and meteorological conditions on particle characteristics at stations. The results showed higher concentrations of PN20-30 at the station situated in an open area (open station), which is likely to be attributed to the lower average daily temperature compared to the station with a canyon structure (canyon station). During precipitation events, it was found that particle number concentration in the size range 25-250 nm decreased greatly, and that the average daily reduction in PM2.5 concentration on rainy days compared to fine days was 44.2 % and 22.6 % at the open and canyon station, respectively. The effect of ambient wind speeds on particle number concentrations was also examined, and no relationship was found between particle number concentration and wind speed for the entire measurement period. In addition, 33 pairs of average half-hourly PN7-3000 concentrations were calculated and identified at the two stations, during the same time of a day, and with the same ambient wind speeds and precipitation conditions. The results of a paired t-test showed that the average half-hourly PN7-3000 concentrations at the two stations were not significantly different at the 5% confidence level (t = 0.06, p = 0.96), which indicates that the different station designs were not a crucial factor for influencing PN7-3000 concentrations. A further assessment of passenger exposure to bus emissions on a platform was evaluated at another bus station in Brisbane, Australia. The sampling was conducted over seven weekdays to investigate spatial-temporal variations in size-fractionated particle number and PM2.5 concentrations, as well as human exposure on the platform. For the whole day, the average PN13-800 concentration was 1.3 x 104 and 1.0 x 104 particle/cm3 at the centre and end of the platform, respectively, of which PN50-100 accounted for the largest proportion to the total count. Furthermore, the contribution of exposure at the bus station to the overall daily exposure was assessed using two assumed scenarios of a school student and an office worker. It was found that, although the daily time fraction (the percentage of time spend at a location in a whole day) at the station was only 0.8 %, the daily exposure fractions (the percentage of exposures at a location accounting for the daily exposure) at the station were 2.7% and 2.8 % for exposure to PN13-800 and 2.7% and 3.5% for exposure to PM2.5 for the school student and the office worker, respectively. A new parameter, “exposure intensity” (the ratio of daily exposure fraction and the daily time fraction) was also defined and calculated at the station, with values of 3.3 and 3.4 for exposure to PN13-880, and 3.3 and 4.2 for exposure to PM2.5, for the school student and the office worker, respectively. In order to quantify the enhanced emissions at critical locations and define the emission distribution in further dispersion models for traffic interrupted transport microenvironments, a composite line source emission (CLSE) model was developed to specifically quantify exposure levels and describe the spatial variability of vehicle emissions in traffic interrupted microenvironments. This model took into account the complexity of vehicle movements in the queue, as well as different emission rates relevant to various driving conditions (cruise, decelerate, idle and accelerate), and it utilised multi-representative segments to capture the accurate emission distribution for real vehicle flow. This model does not only helped to quantify the enhanced emissions at critical locations, but it also helped to define the emission source distribution of the disrupted steady flow for further dispersion modelling. The model then was applied to estimate particle number emissions at a bidirectional bus station used by diesel and compressed natural gas fuelled buses. It was found that the acceleration distance was of critical importance when estimating particle number emission, since the highest emissions occurred in sections where most of the buses were accelerating and no significant increases were observed at locations where they idled. It was also shown that emissions at the front end of the platform were 43 times greater than at the rear of the platform. The CLSE model was also applied at a signalled pedestrian crossing, in order to assess increased particle number emissions from motor vehicles when forced to stop and accelerate from rest. The CLSE model was used to calculate the total emissions produced by a specific number and mix of light petrol cars and diesel passenger buses including 1 car travelling in 1 direction (/1 direction), 14 cars / 1 direction, 1 bus / 1 direction, 28 cars / 2 directions, 24 cars and 2 buses / 2 directions, and 20 cars and 4 buses / 2 directions. It was found that the total emissions produced during stopping on a red signal were significantly higher than when the traffic moved at a steady speed. Overall, total emissions due to the interruption of the traffic increased by a factor of 13, 11, 45, 11, 41, and 43 for the above 6 cases, respectively. In summary, this PhD thesis presents the results of a comprehensive study on particle number and mass concentration, together with particle size distribution, in a bus station transport microenvironment, influenced by bus flow rates, meteorological conditions and station design. Passenger spatial-temporal exposure to bus emitted particles was also assessed according to waiting time and location along the platform, as well as the contribution of exposure at the bus station to overall daily exposure. Due to the complexity of the interrupted traffic flow within the transport microenvironments, a unique CLSE model was also developed, which is capable of quantifying emission levels at critical locations within the transport microenvironment, for the purpose of evaluating passenger exposure and conducting simulations of vehicle emission dispersion. The application of the CLSE model at a pedestrian crossing also proved its applicability and simplicity for use in a real-world transport microenvironment.
Resumo:
Adolescents are indeed bothered by the complexities of the present and future and are concerned with making sense out of the multiple demands of parents, teachers, and peers while trying to develop identities as autonomous individuals. In this confused world, contemporary school science does not fit their view of desirable world as evident in the findings of the ROSE study. However, there are bright spots where teachers, community, parents and youth do engage with STEM. This paper will report on initiatives drawn from a decade of research in schools that have attempted to reconcile the interests of youth and the contemporary world of science. The aim is to identify those factors that do stimulate student interest. These case studies were conducted generally using both qualitative and quantitative data and findings analysed in terms of program outcomes and student engagement. The key finding is that the formation of relationships and partnerships in which students have high degree of autonomy and sense of responsibility is paramount to positive dispositions towards STEM. The findings raise some hope that innovative schools and partnerships can foster innovation and connect youth with the real world.
Resumo:
The development of text classification techniques has been largely promoted in the past decade due to the increasing availability and widespread use of digital documents. Usually, the performance of text classification relies on the quality of categories and the accuracy of classifiers learned from samples. When training samples are unavailable or categories are unqualified, text classification performance would be degraded. In this paper, we propose an unsupervised multi-label text classification method to classify documents using a large set of categories stored in a world ontology. The approach has been promisingly evaluated by compared with typical text classification methods, using a real-world document collection and based on the ground truth encoded by human experts.
Resumo:
Billing Mediation Platform (BMP) in telecommunication industry is used to process real-time streams of Call Detail Records (CDRs) which can be a massive number a day. The generated records by BMP can be deployed for billing purposes, fraud detection, spam filtering, traffic analysis, and churn forecast. Several of these applications are distinguished by real-time processing requiring low-latency analysis of CDRs. Testing of such a platform carries diverse aspects like stress testing of analytics for scalability and what-if scenarios which require generating of CDRs with realistic volumetric and appropriate properties. The approach of this project is to build user friendly and flexible application which assists the development department to test their billing solution occasionally. These generators projects have been around for a while the only difference are the potions they cover and the purpose they will be used for. This paper proposes to use a simulator application to test the BMPs with simulating CDRs. The Simulated CDRs are modifiable based on the user requirements and represent real world data.
Resumo:
Rapid urbanisation and resulting continuous increase in traffic has been recognised as key factors in the contribution of increased pollutant loads to urban stormwater and in turn to receiving waters. Urbanisation primarily increases anthropogenic activities and the percentage of impervious surfaces in urban areas. These processes are collectively responsible for urban stormwater pollution. In this regard, urban traffic and land use related activities have been recognised as the primary pollutant sources. This is primarily due to the generation of a range of key pollutants such as solids, heavy metals and PAHs. Appropriate treatment system design is the most viable approach to mitigate stormwater pollution. However, limited understanding of the pollutant process and transport pathways constrains effective treatment design. This highlights necessity for the detailed understanding of traffic and other land use related pollutants processes and pathways in relation to urban stormwater pollution. This study has created new knowledge in relation to pollutant processes and transport pathways encompassing atmospheric pollutants, atmospheric deposition and build-up on ground surfaces of traffic generated key pollutants. The research study was primarily based on in-depth experimental investigations. This thesis describes the extensive knowledge created relating to the processes of atmospheric pollutant build-up, atmospheric deposition and road surface build-up and establishing their relationships as a chain of processes. The analysis of atmospheric deposition revealed that both traffic and land use related sources contribute total suspended particulate matter (TSP) to the atmosphere. Traffic sources become dominant during weekdays whereas land use related sources become dominant during weekends due to the reduction in traffic sources. The analysis further concluded that atmospheric TSP, polycyclic aromatic hydrocarbons (PAHs) and heavy metals (HMs) concentrations are highly influenced by total average daily heavy duty traffic, traffic congestion and the fraction of commercial and industrial land uses. A set of mathematical equation were developed to predict TSP, PAHs and HMs concentrations in the atmosphere based on the influential traffic and land use related parameters. Dry deposition samples were collected for different antecedent dry days and wet deposition samples were collected immediately after rainfall events. The dry deposition was found to increase with the antecedent dry days and consisted of relatively coarser particles (greater than 1.4 ìm) when compared to wet deposition. The wet deposition showed a strong affinity to rainfall depth, but was not related to the antecedent dry period. It was also found that smaller size particles (less than 1.4 ìm) travel much longer distances from the source and deposit mainly with the wet deposition. Pollutants in wet deposition are less sensitive to the source characteristics compared to dry deposition. Atmospheric deposition of HMs is not directly influenced by land use but rather by proximity to high emission sources such as highways. Therefore, it is important to consider atmospheric deposition as a key pollutant source to urban stormwater in the vicinity of these types of sources. Build-up was analysed for five different particle size fractions, namely, <1 ìm, 1-75 ìm, 75-150 ìm, 150-300 ìm and >300 ìm for solids, PAHs and HMs. The outcomes of the study indicated that PAHs and HMs in the <75 ìm size fraction are generated mainly by traffic related activities whereas the > 150 ìm size fraction is generated by both traffic and land use related sources. Atmospheric deposition is an important source for HMs build-up on roads, whereas the contribution of PAHs from atmospheric sources is limited. A comprehensive approach was developed to predict traffic and other land use related pollutants in urban stormwater based on traffic and other land use characteristics. This approach primarily included the development of a set of mathematical equations to predict traffic generated pollutants by linking traffic and land use characteristics to stormwater quality through mathematical modelling. The outcomes of this research will contribute to the design of appropriate treatment systems to safeguard urban receiving water quality for future traffic growth scenarios. The „real world. application of knowledge generated was demonstrated through mathematical modelling of solids in urban stormwater, accounting for the variability in traffic and land use characteristics.
Resumo:
Background: Foot ulcers are a frequent reason for diabetes-related hospitalisation. Clinical training is known to have a beneficial impact on foot ulcer outcomes. Clinical training using simulation techniques has rarely been used in the management of diabetes-related foot complications or chronic wounds. Simulation can be defined as a device or environment that attempts to replicate the real world. The few non-web-based foot-related simulation courses have focused solely on training for a single skill or “part task” (for example, practicing ingrown toenail procedures on models). This pilot study aimed to primarily investigate the effect of a training program using multiple methods of simulation on participants’ clinical confidence in the management of foot ulcers. Methods: Sixteen podiatrists participated in a two-day Foot Ulcer Simulation Training (FUST) course. The course included pre-requisite web-based learning modules, practicing individual foot ulcer management part tasks (for example, debriding a model foot ulcer), and participating in replicated clinical consultation scenarios (for example, treating a standardised patient (actor) with a model foot ulcer). The primary outcome measure of the course was participants’ pre- and post completion of confidence surveys, using a five-point Likert scale (1 = Unacceptable-5 = Proficient). Participants’ knowledge, satisfaction and their perception of the relevance and fidelity (realism) of a range of course elements were also investigated. Parametric statistics were used to analyse the data. Pearson’s r was used for correlation, ANOVA for testing the differences between groups, and a paired-sample t-test to determine the significance between pre- and post-workshop scores. A minimum significance level of p < 0.05 was used. Results: An overall 42% improvement in clinical confidence was observed following completion of FUST (mean scores 3.10 compared to 4.40, p < 0.05). The lack of an overall significant change in knowledge scores reflected the participant populations’ high baseline knowledge and pre-requisite completion of web-based modules. Satisfaction, relevance and fidelity of all course elements were rated highly. Conclusions: This pilot study suggests simulation training programs can improve participants’ clinical confidence in the management of foot ulcers. The approach has the potential to enhance clinical training in diabetes-related foot complications and chronic wounds in general.
Resumo:
Most current computer systems authorise the user at the start of a session and do not detect whether the current user is still the initial authorised user, a substitute user, or an intruder pretending to be a valid user. Therefore, a system that continuously checks the identity of the user throughout the session is necessary without being intrusive to end-user and/or effectively doing this. Such a system is called a continuous authentication system (CAS). Researchers have applied several approaches for CAS and most of these techniques are based on biometrics. These continuous biometric authentication systems (CBAS) are supplied by user traits and characteristics. One of the main types of biometric is keystroke dynamics which has been widely tried and accepted for providing continuous user authentication. Keystroke dynamics is appealing for many reasons. First, it is less obtrusive, since users will be typing on the computer keyboard anyway. Second, it does not require extra hardware. Finally, keystroke dynamics will be available after the authentication step at the start of the computer session. Currently, there is insufficient research in the CBAS with keystroke dynamics field. To date, most of the existing schemes ignore the continuous authentication scenarios which might affect their practicality in different real world applications. Also, the contemporary CBAS with keystroke dynamics approaches use characters sequences as features that are representative of user typing behavior but their selected features criteria do not guarantee features with strong statistical significance which may cause less accurate statistical user-representation. Furthermore, their selected features do not inherently incorporate user typing behavior. Finally, the existing CBAS that are based on keystroke dynamics are typically dependent on pre-defined user-typing models for continuous authentication. This dependency restricts the systems to authenticate only known users whose typing samples are modelled. This research addresses the previous limitations associated with the existing CBAS schemes by developing a generic model to better identify and understand the characteristics and requirements of each type of CBAS and continuous authentication scenario. Also, the research proposes four statistical-based feature selection techniques that have highest statistical significance and encompasses different user typing behaviors which represent user typing patterns effectively. Finally, the research proposes the user-independent threshold approach that is able to authenticate a user accurately without needing any predefined user typing model a-priori. Also, we enhance the technique to detect the impostor or intruder who may take over during the entire computer session.
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The existence of the Macroscopic Fundamental Diagram (MFD), which relates network space-mean density and flow, has been shown in urban networks under homogeneous traffic conditions. Since the MFD represents the area-wide network traffic performances, studies on perimeter control strategies and an area traffic state estimation utilizing the MFD concept has been reported. The key requirements for the well-defined MFD is the homogeneity of the area wide traffic condition, which is not universally expected in real world. For the practical application of the MFD concept, several researchers have identified the influencing factors for network homogeneity. However, they did not explicitly take drivers’ behaviour under real time information provision into account, which has a significant impact on the shape of the MFD. This research aims to demonstrate the impact of drivers’ route choice behaviour on network performance by employing the MFD as a measurement. A microscopic simulation is chosen as an experimental platform. By changing the ratio of en-route informed drivers and pre-trip informed drivers as well as by taking different route choice parameters, various scenarios are simulated in order to investigate how drivers’ adaptation to the traffic congestion influences the network performance and the MFD shape. This study confirmed and addressed the impact of information provision on the MFD shape and highlighted the significance of the route choice parameter setting as an influencing factor in the MFD analysis.
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Driver distraction has recently been defined by Regan as "the diversion of attention away from activities critical for safe driving toward a competing activity, which may result in insufficient or no attention to activities critical for safe driving (Regan, Hallett & Gordon, 2011, p.1780)". One source of distraction is in-vehicle devices, even though they might provide other benefits, e.g. navigation systems. Currently, eco-driving systems have been growing rapidly in popularity. These systems send messages to drivers so that driving performance can be improved in terms of fuel efficiency. However, there remain unanswered questions about whether eco-driving systems endanger drivers by distracting them. In this research, the CARRS-Q advanced driving simulator was used in order to provide safety for participants and meanwhile simulate real world driving. The distraction effects of tasks involving three different in-vehicle systems were investigated: changing a CD, entering a five digit number as a part of navigation task and responding to an eco-driving task. Driving in these scenarios was compared with driving in the absence of these distractions, and while drivers engaged in critical manoeuvres. In order to account for practice effects, the same scenarios were duplicated on a second day. The three in-vehicle systems were not the exact facsimiles of any particular existing system, but were designed to have similar characteristics to those of system available. In general, the results show that drivers’ mental workloads are significantly higher in navigation and CD changing scenarios in comparison to the two other scenarios, which implies that these two tasks impose more visual/manual and cognitive demands. However, eco-driving mental workload is still high enough to be called marginally significant (p ~ .05) across manoeuvres. Similarly, event detection tasks show that drivers miss significantly more events in the navigation and CD changing scenarios in comparison to both the baseline and eco-driving scenario across manoeuvres. Analysis of the practice effect shows that drivers’ baseline scenario and navigation scenario exhibit significantly less demand on the second day. However, the number of missed events across manoeuvres confirmed that drivers can detect significantly more events on the second day for all scenarios. Distraction was also examined separately for five groups of manoeuvres (straight, lane changing, overtaking, braking for intersections and braking for roundabouts), in two locations for each condition. Repeated measures mixed ANOVA results show that reading an eco-driving message can potentially impair driving performance. When comparing the three in–vehicle distractions tested, attending to an eco-driving message is similar in effect to the CD changing task. The navigation task degraded driver performance much more than these other sources of distraction. In lane changing manoeuvres, drivers’ missed response counts degraded when they engaged in reading eco-driving messages at the first location. However, drivers’ event detection abilities deteriorated less at the second lane changing location. In baseline manoeuvres (driving straight), participants’ mean minimum speed degraded more in the CD changing scenario. Drivers’ lateral position shifted more in both CD changing and navigation tasks in comparison with both eco-driving and baseline scenarios, so they were more visually distracting. Participants were better at event detection in baseline manoeuvres in comparison with other manoeuvres. When approaching an intersection, the navigation task caused more events to be missed by participants, whereas eco-driving messages seemed to make drivers less distracted. The eco-driving message scenario was significantly less distracting than the navigation system scenario (fewer missed responses) when participants commenced braking for roundabouts. To sum up, in spite of the finding that two other in-vehicle tasks are more distracting than the eco-driving task, the results indicate that even reading a simple message while driving could potentially lead to missing an important event, especially when executing critical manoeuvres. This suggests that in-vehicle eco-driving systems have the potential to contribute to increased crash risk through distraction. However, there is some evidence of a practice effect which suggests that future research should focus on performance with habitual rather than novel tasks. It is recommended that eco-driving messages be delivered to drivers off-line when possible.
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This paper investigates engaging experienced birders, as volunteer citizen scientists, to analyze large recorded audio datasets gathered through environmental acoustic monitoring. Although audio data is straightforward to gather, automated analysis remains a challenging task; the existing expertise, local knowledge and motivation of the birder community can complement computational approaches and provide distinct benefits. We explored both the culture and practice of birders, and paradigms for interacting with recorded audio data. A variety of candidate design elements were tested with birders. This study contributes an understanding of how virtual interactions and practices can be developed to complement existing practices of experienced birders in the physical world. In so doing this study contributes a new approach to engagement in e-science. Whereas most citizen science projects task lay participants with discrete real world or artificial activities, sometimes using extrinsic motivators, this approach builds on existing intrinsically satisfying practices.
Resumo:
Vehicular accidents are one of the deadliest safety hazards and accordingly an immense concern of individuals and governments. Although, a wide range of active autonomous safety systems, such as advanced driving assistance and lane keeping support, are introduced to facilitate safer driving experience, these stand-alone systems have limited capabilities in providing safety. Therefore, cooperative vehicular systems were proposed to fulfill more safety requirements. Most cooperative vehicle-to-vehicle safety applications require relative positioning accuracy of decimeter level with an update rate of at least 10 Hz. These requirements cannot be met via direct navigation or differential positioning techniques. This paper studies a cooperative vehicle platform that aims to facilitate real-time relative positioning (RRP) among adjacent vehicles. The developed system is capable of exchanging both GPS position solutions and raw observations using RTCM-104 format over vehicular dedicated short range communication (DSRC) links. Real-time kinematic (RTK) positioning technique is integrated into the system to enable RRP to be served as an embedded real-time warning system. The 5.9 GHz DSRC technology is adopted as the communication channel among road-side units (RSUs) and on-board units (OBUs) to distribute GPS corrections data received from a nearby reference station via the Internet using cellular technologies, by means of RSUs, as well as to exchange the vehicular real-time GPS raw observation data. Ultimately, each receiving vehicle calculates relative positions of its neighbors to attain a RRP map. A series of real-world data collection experiments was conducted to explore the synergies of both DSRC and positioning systems. The results demonstrate a significant enhancement in precision and availability of relative positioning at mobile vehicles.