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From page 47... ... 45 3 COMPUTATIONAL METHODS The computational methods used by a travel time reliability monitoring system (TTRMS) need to be designed to generate information about the ways in which travel times and rates vary during system operation and the reasons why these variations occur. Read the entire page →
From page 48... ... 46 GUIDE TO ESTABLISHING MONITORING PROGRAMS FOR TRAVEL TIME RELIABILITY • Imputation: how the TTRMS should impute estimates for missing or invalid data. • Segment travel time calculations: the steps and computations that transform raw sensor data into observations of segment travel times. Read the entire page →
From page 49... ... 47 GUIDE TO ESTABLISHING MONITORING PROGRAMS FOR TRAVEL TIME RELIABILITY NETWORK CONCEPTS The first task in establishing a TTRMS is to define a network topology that can be used to study the system's travel time variability. Notions of monuments, passage times, segments, and routes need to be created. Read the entire page →
From page 50... ... 48 GUIDE TO ESTABLISHING MONITORING PROGRAMS FOR TRAVEL TIME RELIABILITY Passage Times The second concept is a passage time, which indicates when a vehicle has passed a given monument. When the monument is at the location of a detector (e.g., a loop in the pavement or an AVI reader) Read the entire page →
From page 51... ... 49 GUIDE TO ESTABLISHING MONITORING PROGRAMS FOR TRAVEL TIME RELIABILITY Figure 3.2. Turning segments connecting monuments. Read the entire page →
From page 52... ... 50 GUIDE TO ESTABLISHING MONITORING PROGRAMS FOR TRAVEL TIME RELIABILITY Users In this context, users are people (or packages) making trips across the network. Read the entire page →
From page 53... ... 51 GUIDE TO ESTABLISHING MONITORING PROGRAMS FOR TRAVEL TIME RELIABILITY Markets A market is formed by a set of users in combination with a route bundle. An example would be commuters who have toll tag–equipped vehicles (user group) Read the entire page →
From page 54... ... 52 GUIDE TO ESTABLISHING MONITORING PROGRAMS FOR TRAVEL TIME RELIABILITY impacts of "insufficient base capacity" are captured by the nominal congestion condition categories described above (i.e., situations in which the demand-to-capacity ratio is high enough that sustained queuing occurs) Read the entire page →
From page 55... ... 53 GUIDE TO ESTABLISHING MONITORING PROGRAMS FOR TRAVEL TIME RELIABILITY Readers should recognize that the right set of regimes for a given segment, route, or system will be site specific. Care should be taken in identifying these regimes so that they represent the smallest set of categories that clearly describe how the system operates and performs. Read the entire page →
From page 56... ... 54 GUIDE TO ESTABLISHING MONITORING PROGRAMS FOR TRAVEL TIME RELIABILITY inverse, spot rates) Read the entire page →
From page 57... ... 55 GUIDE TO ESTABLISHING MONITORING PROGRAMS FOR TRAVEL TIME RELIABILITY characteristics. The best practice is to implement a series of imputation methods in the order of the accuracy of their estimates. Read the entire page →
From page 58... ... 56 GUIDE TO ESTABLISHING MONITORING PROGRAMS FOR TRAVEL TIME RELIABILITY qi(t) Read the entire page →
From page 59... ... 57 GUIDE TO ESTABLISHING MONITORING PROGRAMS FOR TRAVEL TIME RELIABILITY the downtown area of a city. These detectors would have comparable macroscopic patterns in that the a.m. Read the entire page →
From page 60... ... 58 GUIDE TO ESTABLISHING MONITORING PROGRAMS FOR TRAVEL TIME RELIABILITY There are three scenarios for which a vehicle-based sensor pair would report no travel time data: 1. Either Sensor A or Sensor B, or both, are malfunctioning. Read the entire page →
From page 61... ... 59 GUIDE TO ESTABLISHING MONITORING PROGRAMS FOR TRAVEL TIME RELIABILITY Figure 3.7. Super segment examples. Read the entire page →
From page 62... ... 60 GUIDE TO ESTABLISHING MONITORING PROGRAMS FOR TRAVEL TIME RELIABILITY Estimating Spot (Time-Mean) Speeds for Single-Loop Detectors In the case of many point sensors, the speeds are directly observed and averages of those speeds are periodically reported by the device. Read the entire page →
From page 63... ... 61 GUIDE TO ESTABLISHING MONITORING PROGRAMS FOR TRAVEL TIME RELIABILITY Using the assumed free-flow speeds, g-factors can be calculated for all free-flow time periods according to Equation 3.7: g t k t T q t Vfree( ) Read the entire page →
From page 64... ... 62 GUIDE TO ESTABLISHING MONITORING PROGRAMS FOR TRAVEL TIME RELIABILITY Figure 3.8. Example of 5-minute g-factor estimates at a detector. Read the entire page →
From page 65... ... 63 GUIDE TO ESTABLISHING MONITORING PROGRAMS FOR TRAVEL TIME RELIABILITY These g-factors should be updated periodically to account for seasonal variations in vehicle lengths or changes to truck traffic patterns. It is recommended that new g-factors be generated at least every 3 months. Read the entire page →
From page 66... ... 64 GUIDE TO ESTABLISHING MONITORING PROGRAMS FOR TRAVEL TIME RELIABILITY across a segment. To do this, separate field observations of the individual vehicle speeds have to be obtained or an assumption must be made (based on similar facilities) Read the entire page →
From page 67... ... 65 GUIDE TO ESTABLISHING MONITORING PROGRAMS FOR TRAVEL TIME RELIABILITY about 10th from the beginning. If the sensor can record two stamps, then the first and the last could be reported. Read the entire page →
From page 68... ... 66 GUIDE TO ESTABLISHING MONITORING PROGRAMS FOR TRAVEL TIME RELIABILITY The challenge of extracting useful data is illustrated by Figure 3.13, which shows the raw Bluetooth data collected for westbound trips made on US-50 between South Lake Tahoe and Placerville. Obviously present are trip times up to 400 minutes: the upper bound of the linking program used by the data processor. Read the entire page →
From page 69... ... 67 GUIDE TO ESTABLISHING MONITORING PROGRAMS FOR TRAVEL TIME RELIABILITY case here. Hence, a simpler technique was selected, one that can be described easily and implemented by practitioners. Read the entire page →
From page 70... ... 68 GUIDE TO ESTABLISHING MONITORING PROGRAMS FOR TRAVEL TIME RELIABILITY Computing Automated Vehicle Identification–Based Segment Travel Times Given the nature of the data, computing segment travel times from vehicle-based data is straightforward, at least in principle. For trips between Readers A and B (i.e., for Segment A–B) Read the entire page →
From page 71... ... 69 GUIDE TO ESTABLISHING MONITORING PROGRAMS FOR TRAVEL TIME RELIABILITY These same data can be summarized in cumulative density functions (CDFs) , an example of which is shown in Figure 3.16. Read the entire page →
From page 72... ... 70 GUIDE TO ESTABLISHING MONITORING PROGRAMS FOR TRAVEL TIME RELIABILITY 0 5 10 15 20 25 30 35 40 40000 41000 42000 43000 44000 45000 46000 47000 48000 49000 50000 Tr av el T im e (m in ) Chronological Observation Number Individual Vehicle Travel Times / I-5 Southbound Figure 3.17. Read the entire page →
From page 73... ... 71 GUIDE TO ESTABLISHING MONITORING PROGRAMS FOR TRAVEL TIME RELIABILITY another incident (about Observation 46,500) , which also had no impact on the travel times. Read the entire page →
From page 74... ... 72 GUIDE TO ESTABLISHING MONITORING PROGRAMS FOR TRAVEL TIME RELIABILITY Understanding Automated Vehicle Location Data AVL technologies track vehicles as they travel. Hence, entire trips can be observed, including the path employed. Read the entire page →
From page 75... ... 73 GUIDE TO ESTABLISHING MONITORING PROGRAMS FOR TRAVEL TIME RELIABILITY In many cases, as shown in Figure 3.21 (and in Figure 3.20) , for a few data points there are multiple possibilities for the map-matching results. Read the entire page →
From page 76... ... 74 GUIDE TO ESTABLISHING MONITORING PROGRAMS FOR TRAVEL TIME RELIABILITY Generating Segment Travel Times from Automated Vehicle Location Data Computing segment travel times from AVL data is straightforward. Four steps are involved, the first two of which have already implicitly been described. Read the entire page →
From page 77... ... 75 GUIDE TO ESTABLISHING MONITORING PROGRAMS FOR TRAVEL TIME RELIABILITY time estimates will either underestimate the actual average travel times (as congestion grows) or overestimate the travel times (as congestion recedes) Read the entire page →
From page 78... ... 76 GUIDE TO ESTABLISHING MONITORING PROGRAMS FOR TRAVEL TIME RELIABILITY between the time stamp for the last monument in the route and the first. If this is the case, vehicle-specific travel times can be obtained and from them, the average travel time can be computed. Read the entire page →
From page 79... ... 77 GUIDE TO ESTABLISHING MONITORING PROGRAMS FOR TRAVEL TIME RELIABILITY 5. Macro-level network flow dynamics determine how the evolving conditions on upstream segments (e.g., increasing or decreasing congestion) Read the entire page →
From page 80... ... 78 GUIDE TO ESTABLISHING MONITORING PROGRAMS FOR TRAVEL TIME RELIABILITY Figure 3.23. Example of distribution of simulated versus actual (ac) Read the entire page →
From page 81... ... 79 GUIDE TO ESTABLISHING MONITORING PROGRAMS FOR TRAVEL TIME RELIABILITY Figure 3.24. Example of a network simulated using the point queue–based model. Read the entire page →
From page 82... ... 80 GUIDE TO ESTABLISHING MONITORING PROGRAMS FOR TRAVEL TIME RELIABILITY Route Travel Time Distributions from Vehicle-Based Data This is the easier task. If enough AVI- or AVL-based observations are available, it may be possible to develop the distribution of vehicular travel times directly from the raw data. Read the entire page →
From page 83... ... 81 GUIDE TO ESTABLISHING MONITORING PROGRAMS FOR TRAVEL TIME RELIABILITY perform geometrical or exponential smoothing over the current and previous time periods to smooth the trend over time, giving more weight to the most recent Tj, as well as those Tj values with larger sample sizes, and thus higher accuracy. The drawback of this method is that if the current time period has too few data points, then the median value could still be affected by the outliers. Read the entire page →
From page 84... ... 82 GUIDE TO ESTABLISHING MONITORING PROGRAMS FOR TRAVEL TIME RELIABILITY to a day's worth of FasTrak toll tag data in Oakland. As can be seen in the top part of Figure 3.26 (hourly median travel times) Read the entire page →
From page 85... ... 83 GUIDE TO ESTABLISHING MONITORING PROGRAMS FOR TRAVEL TIME RELIABILITY Once Steps 1–6 have been completed, further analysis can be performed for a variety of purposes using the following steps: 7. Prioritize facilities on the basis of relative impacts. Read the entire page →
From page 86... ... 84 GUIDE TO ESTABLISHING MONITORING PROGRAMS FOR TRAVEL TIME RELIABILITY demand. Data points not falling into any one of these categories should be classified as being normal. Read the entire page →
From page 87... ... 85 GUIDE TO ESTABLISHING MONITORING PROGRAMS FOR TRAVEL TIME RELIABILITY Step 6. Develop TR-CDFs The sixth step is to develop TR-CDFs for each combination of recurring congestion that would normally occur (from the analysis above) Read the entire page →
From page 88... ... 86 GUIDE TO ESTABLISHING MONITORING PROGRAMS FOR TRAVEL TIME RELIABILITY Step 9. Use Reliability Analysis for Planning and Programming Decisions In Step 9, the results of the semivariance analysis can be used as inputs into decision making associated with future agency planning and programming decisions. Read the entire page →
From page 89... ... 87 GUIDE TO ESTABLISHING MONITORING PROGRAMS FOR TRAVEL TIME RELIABILITY 4. Quddus, M Read the entire page →

From page 47...

... 45 3 COMPUTATIONAL METHODS The computational methods used by a travel time reliability monitoring system (TTRMS) need to be designed to generate information about the ways in which travel times and rates vary during system operation and the reasons why these variations occur.