Siamak Ardekani

Urban Network-Wide Traffic Variables and Their Relations

Time-lapse aerial photography over the Central Business Districts (CBD) of Austin and Dallas, Texas, has been employed to determine the averages of concentration, speed and fraction of vehicles stopped and to examine the relations among such network-wide averages including the flow which was measured on the ground simultaneously. The results have indicated that the average flow in a street network may indeed be expressed as the product of the space mean speed and concentration. Simultaneous ground experiments have also been conducted in the Austin CBD to investigate the reasonableness of the assumptions of the “two-fluid model,” a curvilinear relation between the trip time and stop time per unit distance, which may be used in characterizing the quality of traffic service in urban street networks. As a result of these simultaneous ground experiments and aerial observations, the assumptions of the model have been verified. Moreover, relations between the fraction of vehicles stopped and concentration as well as between speed and concentration have allowed the two-fluid model to be used to compare the quality of traffic service in various street networks under the same level of concentration. The two-fluid model may then be used to predict, for a given change in vehicular concentration in a street network, the resulting changes in the averages of speed, fraction of vehicles stopped, flow, etc. This is particularly useful as a performance model in urban planning where for a given concentration it is desirable to predict the resulting traffic conditions.

Characterizing Traffic Conditions in Urban Areas

A series of vehicular traffic experiments conducted in Austin, Texas, shows the reasonableness of the two assumptions in the two-fluid (moving and stopped vehicles) model of town traffic. The observational data support the assumption that the average speed in an urban street network is proportional to the fraction of the vehicles moving raised to a power and is also in agreement with the supposition that during relatively uniform periods the traffic is ergodic. An important consequence is that the average of the fraction of time stopped for a test vehicle circulating in a street network is approximately equal to the average fraction of the vehicles stopped in the system during the same test period. The parameters of the two-fluid model and the observed ranges of trip time and stop time per unit distance have been shown to be effective in assessing or rank ordering the relative quality of traffic service in a number of Texas cities; comparisons are made with various cities around the world. The two-fluid methodology appears to be useful in a preliminary “before”/“after” study during which signal timing changes were made. Finally, a preliminary analysis of aerial photographic data in two cities allows the determination of an additional two-fluid model parameter, p , in the relation stating that the fraction of vehicles stopped is given by the ratio of concentration to the jam or maximum concentration raised to a power, p . It is suggested that this parameter may be useful in describing the relative quality of various traffic systems.

The Influence of Stops on Vehicle Fuel Consumption in Urban Traffic

A simple linear relation between fuel consumption per unit distance, (phi) and trip time per unit distance T , (phi) = k 1 + k 2 T is established for the fuel data collected in Austin and Dallas, Texas, and Matamoros, Mexico. The qualities of traffic service in these cities are compared through the study of the spread of the data points along the (phi), T trend, showing that the Matamoros data in general have higher (phi) and T values. The fuel consumption model (phi) = k 1 + k 2 T is improved by the addition of a term proportional to (Delta) N s ( T ), the deviation of the number of stops for a given datum point from the average number of stops associated with the trip time interval into which the datum point falls. It is shown in the resulting new model, (phi) = k 1 + k 2 T + k 3 (Delta) N s , that since T and (Delta) N s are virtually uncorrected, the values of k 1 and k 2 in the simpler model remain unchanged. A discussion of the physical interpretation of the model parameters is presented. In addition, an analysis of data obtained in central London shows that k 1 depends almost entirely on vehicle mass. It is also shown that the value of the parameter k 3 is approximately given by the product of the warmed-up idle fuel flow and the average stop duration.

Trip time-stop time studies of extreme driver behaviors

The focus of the present study has been to investigate the extent to which drivers with “extreme” modes of behavior deviate from the “normal” (chase-car) trend in a given city. The experiment consisted of collecting trip time-stop time data in the Central Business District (CBD) of Roanoke, Virginia, using three vehicles circulating simultaneously in the area. While one of the three vehicles was engaged in the chase-car mode, the other two vehicles were driven aggressively or conservatively. Similar data were also collected in the Austin, Texas, CBD. Using the data for each driver type, three two-fluid trends are established for the Roanoke CBD: an aggressive, a normal (chase-car), and a conservative trend. On a trip time-stop time diagram, while the conservative and aggressive trends are essentially parallel, the conservative trend approaches the normal trend at off-peak periods. The aggressive trend, on the other hand, approaches the normal trend at peak periods. The differences among the trends, however, are by and large statistically significant. Similar results have been obtained in Austin—despite uncertainties at high levels of demand, where the normal trend may cross the aggressive trend. The results also underline the importance of common data collection techniques when comparing the quality of traffic service of various cities using the two-fluid model approach. In assessing the statistical significance of differences among the two-fluid trends of various city networks, the potential impact of driver behavioral variations must be considered.

Comparison of quality of service in two central business districts two-fluid model approach in Texas

In 2003-2004, the City of Fort Worth, Texas, undertook an exercise to retime traffic signals, to convert several one-way streets to two-way streets, and to make significant changes to the land use in the downtown area. Those changes were expected to have a significant impact on the quality of service of the downtown street network. After an urban street network undergoes modifications of its control system or geometric configuration as in Fort Worth, there is a need to have quantifiable tools to perform before-and-after studies on network quality of service. The purpose of this study was to use the two-fluid model to compare network performance over time and after a recent major modification. In 1983 and 1994, the two-fluid model was calibrated for the Dallas and Arlington, Texas, networks. The model was then recalibrated for the two networks with data collected in 2003; this allowed comparisons of the quality of traffic service in these networks over a long time. To assess the changes in Fort Worth, a new model was calibrated with data collected in 2004 and was then compared with the previous model calibrated in 1999. This comparison helped determine the success of signal retiming strategies as well as modifications in street geometry and land use. As expected, changes occurred in the system over time, but those changes, both positive and negative, differed, depending on the city.

AN OBSERVATIONAL STUDY OF THE NETWORK-LEVEL TRAFFIC VARIABLES

Simultaneous ground measurements of traffic variables including speed, concentration, and flow over the Central Business District of Tehran have been made to examine the relations among network-wide averages of such variables. The two-fluid model, a curvilinear relation between the trip time and stop time per unit distance, has been calibrated to characterize the quality of traffic service in the study network. In addition, relations between the fraction of vehicles stopped and the average concentration, as well as between the averages of speed and concentration, are derived to describe interrupted traffic flow conditions in urban networks.

Management of urban road networks following man-made or natural disasters

Lessons learned from post-disaster conditions after major urban earthquakes are used to develop roadway management strategies for other man-made or natural disasters. Events considered are those which cause major disruptions to the roadway network but would not necessarily require evacuation of the population. These include terrorist attacks, earthquakes, tornadoes, widespread flooding, etc. Events such as nuclear or chemical incidents or approaching hurricanes, which require evacuation of communities, are not considered. Key management functions of an Emergency Operations Center such as damage inventory and detour plans are addressed. The main objectives are to mitigate the impact of such disasters on the population while accelerating the return to normalcy. The findings are incorporated into a GIS decision tool which allows editing of the roadway network to reflect roadway closures and capacity reductions. The updated network information is then used to determine optimal traffic detour and diversion strategies to best utilize the remaining network capacity.

A Transportation Sustainability Index for Urban Communities

A Transportation Sustainability Index has been developed to assess the extent of transportation sustainability in an urban development. The index is based on sustainability indicators in six categories, namely: 1) Pedestrian infrastructure; 2) Bicycle infrastructure; 3) Transit infrastructure; 4) Mixed-use and transit-oriented developments; 5) Traffic calming measures; and 6) Sustainable operations. The procedure has been applied to three city developments in north Texas. The index can be used as a sustainability audit tool to assist communities in assessing where they stand in terms of sustainability of their transportation systems and what additional steps they can take to become more transportation sustainable.

A PC‐Based Decision Tool for Roadway Incident Management

A quick-response PC tool has been developed to address a number of crucial transportation needs following major road incidents or urban disasters. Known as TEMPO (Transportation Emergency Management of Post-Incident Operations), the tool is capable of instantaneously identifying near-optimal traffic-diversion strategies around disruptions in an urban traffic network. TEMPO utilizes heuristic approaches to estimating the origin-destination (O-D) of the traffic on the closed links and reassigning the estimated O-D to the remainder of the network. This article describes the following features of TEMPO: (1) the GIS-based data structure that allows graphic user interaction and network editing, including closed street links, changes in number of lanes, cordoned off areas, changes in street directionality, speed limits, and parking regulations, and (2) the algorithm for traffic diversion around the incident based on cordoning the affected region around the closure, estimation of the O-D matrix for the traffic on the closed links, and reassignment of the O-D to the network. Finally, a simulation-based calibration procedure is conducted to compare the TEMPO results with those generated by a popular planning software, TRANPLAN. Thirty-three incident scenarios in a generic test network are simulated by both TEMPO and TRANPLAN, and the results are compared statistically.

A Simulation Study of the Operational Performance of Left-Turn Phasing and Indication Sequences

In this paper, the operational performance of left-turn phasing and indication sequence is presented. The study contributes to the selection of an optimal left-turn phasing and indication sequence. Presently, there are no comprehensive guidelines to assist traffic engineers in this task. The operational performance of six different phase patterns and three intersection geometries are addressed using simulations. The threshold values to identify traffic conditions under which each phase pattern performs best and beyond which another phase pattern should be considered are also formulated. The efficiency of leading and lagging sequences are addressed. The study shows that when some left-turn protection is needed, the less restrictive protected/permissive phase should be used unless there is a severe safety problem which necessitates the use of protected only phase. The permissive only phase is recommended for low left-turn and opposing volumes.