Development of the Sungkyunkwan University Driving Simulator (SKUD) for Human-Machine Interface studies of Car Navigation Systems

Driving simulators are useful tools that can be used not only to test the components of future cars, but also to evaluate the telematics service and HMI (Human-Machine Interface). However, driving simulators that are currently available cannot be implemented to test and evaluate a real commercial telematics service system because the GPS (Global Positioning System), which contains basic functional support for the telematics module, does not work in the VR (virtual reality) environment. A driving simulator, together with the GPS simulator, can be used to study the HMI to evaluate commercial CNS (Car Navigation Systems). In this paper, Sungkyunkwan University Driving Simulator (SKUD) is developed with a GPS simulator that is able to emulate GPS satellite signals and includes the NMEA-0183 protocol and RS232C communication standards. Furthermore, using the SKUD, the HMI of the real commercial CNS could be investigated with driver workload assessment methods.     

License plate location method unaffected by variation in size and aspect ratio

License plate location is a challenging task that is necessary for automatic vehicle identification. This paper presents a new method for locating a license plate when its size and aspect ratio are highly variable. The proposed method begins with an assumption that a license plate exists in a region where dense edges are located. We define an edge region as an area containing rich edges. The edge regions are created by dilating vertical edges, and they are classified into one of four types: left fragment type, right fragment type, whole type, and undefined type. The candidates for a license plate region are constructed by merging edge regions. Knowing what type of edge region is being examined is useful in the merging process. Finally, we verify whether each candidate contains a license plate or not by using the character arrangement information. The arrangement pattern is determined by the size of connected components and by the vertical overlap or horizontal distance between two neighboring components. Experimental results show that the proposed method gives robust results regardless of any variation in the size and aspect ratio of license plates.     

浅埋暗挖地铁车站的安全风险控制技术

为了控制暗挖施工带来的环境风险,提出了以控制地层变形为核心,以保证既有结构安全为目的的风险管理体系.该体系包括：既有结构现状评估、施工影响预测、控制方案制定、监测反馈及工后评估与恢复,在目前国内最大的暗挖地铁换乘车站——北京地铁黄庄站得到了应用,从技术上保证了环境安全.根据监测数据,10号线双层段最终地表沉降全部控制在80 mm以内,其中控制在64 mm以内的测点占总测点数的93.6%;管线测点沉降值全部小于30 mm,最大差异沉降为1.123‰.表明风险控制中制定的控制标准是合理的,施工中采取的措施是有效的.     

The motion analysis of fire video images based on moment features and flicker frequency

In this paper, motion analysis methods based on the moment features and flicker frequency features for early fire flame from ordinary CCD video camera were proposed, and in order to describe the changing of flame and disturbance of non-flame phenomena further more, the average changing pixel number of the first-order moments of consecutive flames has been defined in the moment analysis as well. The first-order moments of all kinds of flames used in our experiments present irregularly flickering, and their average changing pixel numbers of first-order moments are greater than fire-like disturbances. For the analysis of flicker frequency of flame, which is extracted and calculated in spatial domain, and therefore it is computational simple and fast. The method of extracting flicker frequency from video images is not affected by the catalogues of combustion material and distance. In experiments, we adopted two kinds of flames, i.e. , fixed flame and movable flame. Many comparing and disturbing experiments were done and verified that the methods can be used as criteria for early fire detection.     

An analysis of bicycle route choice preferences in Texas,US

In the US, the rise in motorized vehicle travel has contributed to serious societal, environmental, economic, and public health problems. These problems have increased the interest in encouraging non-motorized modes of travel (walking and bicycling). The current study contributes toward this objective by identifying and evaluating the importance of attributes influencing bicyclists’ route choice preferences. Specifically, the paper examines a comprehensive set of attributes that influence bicycle route choice, including: (1) bicyclists’ characteristics, (2) on-street parking, (3) bicycle facility type and amenities, (4) roadway physical characteristics, (5) roadway functional characteristics, and (6) roadway operational characteristics. The data used in the analysis is drawn from a web-based stated preference survey of Texas bicyclists. The results of the study emphasize the importance of a comprehensive evaluation of both route-related attributes and bicyclists’ demographics in bicycle route choice decisions. The empirical results indicate that travel time (for commuters) and motorized traffic volume are the most important attributes in bicycle route choice. Other route attributes with a high impact include number of stop signs, red light, and cross-streets, speed limits, on-street parking characteristics, and whether there exists a continuous bicycle facility on the route.

A traffic analysis zone definition: a new methodology and algorithm

This paper develops a comprehensive approach to the definition of transportation analysis zones (TAZ), and therein, presents a new methodology and algorithm for the definition of TAZ embedded in geographic information systems software, improves the base algorithm with several local algorithms, and comprehensively analyses the obtained results. The results obtained are then compared to these presently used in the transportation analysis process of the Lisbon Metropolitan Area. The proposed algorithm presents a new methodology for TAZ design based on a smoothed density surface of geocoded travel demand data. The algorithm aims to minimise the loss of information when moving from a continuous representation of the origin and destination of each trip to their discrete representations through zones, and focuses on the trade-off between the statistical precision, geographical error, and the percentage of intra-zonal trips of the resulting OD matrix. The results for the Lisbon Metropolitan Area case study suggest a significant improvement in OD matrix estimates compared to current transportation analysis practises based on administrative units.

A copula-based joint multinomial discrete–continuous model of vehicle type choice and miles of travel

In this paper, a joint model of vehicle type choice and utilization is formulated and estimated on a data set of vehicles drawn from the 2000 San Francisco Bay Area Travel Survey. The joint discrete–continuous model system formulated in this study explicitly accounts for common unobserved factors that may affect the choice and utilization of a certain vehicle type (i.e., self-selection effects). A new copula-based methodology is adopted to facilitate model estimation without imposing restrictive distribution assumptions on the dependency structures between the errors in the discrete and continuous choice components. The copula-based methodology is found to provide statistically superior goodness-of-fit when compared with previous estimation approaches for joint discrete–continuous model systems. The model system, when applied to simulate the impacts of a doubling in fuel price, shows that individuals are more likely to shift vehicle type choices than vehicle usage patterns.

Traveled distance,stock and fuel efficiency of private vehicles in Canada: price elasticities and rebound effect

This paper presents estimates of the rebound effect and other elasticities for the Canadian light-duty vehicle fleet using panel data at the provincial level from 1990 to 2004. We estimate a simultaneous three-equation model of aggregate demand for vehicle kilometers traveled, vehicle stock and fuel efficiency. Price and income elasticities obtained are broadly consistent with those reported in the literature. Among other results, an increase in the fuel price of 10% would reduce driving by ~2% in the long term and by 1% the average fuel consumption rate. Estimates of the short- and long-term rebound effects are ~8 and 20%, respectively. We also find that an increase in the gross domestic product per capita of 10% would cause an increase in driving distance of 2–3% and an increase of up to 4% in vehicle stock per adult. In terms of policy implications, our results suggest that: (1) the effectiveness of new fuel efficiency standards will be somewhat mitigated by the rebound effect and (2) fuel price increases have limited impacts on gasoline demand.

<Emphasis Type="Italic">Not</Emphasis> driving alone? American commuting in the twenty-first century

This paper investigates recent commuting trends by American workers. Unlike most studies of commuting that rely on data from the American Community Survey this study utilizes the American Time Use Survey to detail the complex commuting patterns of modern-day workers. Changes in the price of gasoline in recent years suggest that the incidence of “driving alone” should be on the decline. Indeed, results show that the sensitivity of modal commuting with respect to changes in gasoline prices appears to be relatively large. We estimate the gasoline-price elasticity of driving alone to be 0.057 and the gasoline-price elasticity of carpooling to be 0.502. Additional factors also affect commuting, including socio-economic characteristics and social desires. However, it is changes in gasoline prices that appear to account for nearly all of the recent variation in the mode chosen for commuting.     

Modeling the spatial and temporal dimensions of recreational activity participation with a focus on physical activities

This study presents a unified framework to understand the weekday recreational activity participation time-use of adults, with an emphasis on the time expended in physically active recreation pursuits by location and by time-of-day. Such an analysis is important for a better understanding of how individuals incorporate physical activity into their daily activities on a typical weekday, and can inform the development of effective policy interventions to facilitate physical activity. Furthermore, such a study of participation and time use in recreational activity episodes contributes to activity-based travel demand modeling, since recreational activity participation comprises a substantial share of individuals’ total non-work activity participation. The methodology employed here is the multiple discrete continuous extreme value (MDCEV) model, which provides a unified framework to explicitly and endogenously examine time use by type, location, and timing. The data for the empirical analysis is drawn from the 2000 Bay Area Travel Survey (BATS), supplemented with other secondary sources that provide information on physical environment variables. To our knowledge, this is the first study to jointly address the issues of ‘where’, ‘when’ and ‘how much’ individuals choose to participate in ‘what type of (recreational) activity’.