Various types of data were collected from the surveyed sites. The data is summarised under four main headings as shown below and also summarised for each site in Table 3.4. A detailed description of the methods used for data extraction and the definition of each type is provided below and a full analysis is presented in Chapter 4.
Traffic characteristics: arrival traffic flow, traffic composition, time headway, site throughput, directional split, MUT (Move-up Time), MUD (Move-up Delay) and queues.
Roadworks site characteristics: site length, operation type and signage.
Drivers’ behaviours: close following “tailgating”, amber crossing and red light violations.
Signals settings: signals timing (i.e. green time and all-red period), signals type (i.e. FT and VA).
3.4.1 Flow level, profile and composition
Traffic flow information (i.e. flow by vehicle type, directional split and HGVs percentage) was collected for each site and each direction separately for each 5-minutes interval in order to create accurate flow profiles. Vehicles in each traffic stream were classified into two
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vehicle types (i.e. cars and HGVs). Bicycles and motorcycles were ignored, because their number was negligible. Observed flow levels, profiles and composition will be used as input into the developed micro-simulation model.
Table 3.4: Summary of studied parameters through site categories
Site Selection
Historical shuttle-lane roadworks sites Current shuttle- lane roadworks sites (full surveys)Current shuttle- lane roadworks sites (partial surveys) Post-removal of shuttle-lane roadworks sites Normal signalised intersections MUT Signals compliance Signage Flow levels Following time headway MUT MUD Signals Timings Queuing Drivers behaviour Signals compliance Signage Site dimensions Signage Arrival headway distribution MUT Signals compliance
(Sites 2 to 7) (Sites 11 to 19) (Sites 20 to 23) (Sites 11,16, 19) (Sites 1, 15) 3.4.2 Throughput
The number of vehicles passing the shuttle-lane site was counted every cycle (for sites operated by temporary traffic signals) and also for every 5-minutes interval and by vehicle type and for each direction separately. Observed system throughput will be used to compare with the micro-simulation model output for validation purposes.
3.4.3 Time headway
Time Headway (TH) is defined as the time elapsed between the front of the leading vehicle (n-1) passing an imaginary datum line (x) on the road (or on the playback screen) and the front of the following vehicle (n) passing the same point, as illustrated in Figure 3.3 and shown in Equation 3.1 (Evans and Wasielewski, 1982; Evans, 1991). Observed TH (before approaching the roadworks) will be used to compare with the micro-simulation model output for validation purposes.
TH B, D Et B − t B − 1 G Equation 3.1
Where,
t is the time when the vehicle (n-1, n) crosses the datum line
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Figure 3.3: Illustration of time headway 3.4.4 Move-up Time (MUT)
Move-up Time (departure headway or discharge headway) at traffic signals is a fundamental parameter used to measure the capacity of an intersection and timing the traffic signals. MUT is usually defined as the time elapsed between successive vehicles (in a queue) when they start to cross the stop line at a signalised junction, after the traffic lights turn green (Jin et al., 2009; Briggs, 1977 and Michael et al., 2000). The MUT can be calculated using Equation 3.2. Observed MUT for each site and direction will be used to compare with micro- simulation model output for validation purposes.
MUT B Et B t B 1 G Equation 3.2
3.4.5 Move-up Delay (MUD)
Following a stopping situation at traffic signals the driver (queue leader) will spend time preparing to move when the light shows green (move-up delay or start-up time). The move- up delay was captured from the time the signals sequence shows red-amber until the first vehicle in the queue starts to move. Observed MUD for each stream will be used as an input into the developed micro-simulation model.
3.4.6 Drivers’ behaviour
Drivers’ behaviour was also observed on site and from video playback to capture the statistics of vehicles following too closely “tailgating”. Also drivers’ behaviour in terms of number of vehicles (cycles) crossing the stop line at the onset of amber and red light violations.
Headway
Datum line
n n-1
51 3.4.7 Roadworks sites characteristics
Various measurements such as site length and the location of roadworks signs were collected on site using a measuring wheel.
3.4.8 Signals settings
Detailed signals settings such as green time (minimum and maximum for VA sites), all-red period, amber and red-amber were collected on site and from video playbacks. Also the type of signals operation was identified on site and from video playbacks.
3.5
Summary
This chapter described the data collection stages, available methods and the difficult issues related to data collection. In total, data from six different categories have been collected (data from 23 different sites with over 54 hours of video recording). Furthermore, description of each type of the collected data was also provided.
The collected data will be analysed in details as shown in the next chapter and will be used as inputs/outputs for the developed S-Paramics simulation model as explained in the following chapters.
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CHAPTER FOUR:
DATA ANALYSIS
4.1
Introduction
The aim of this chapter is to present the work that was undertaken in analysing the field data which will be used in developing, calibrating and validating the micro-simulation model. Data collection and analysis is a critical part of the current research in capturing the characteristics of various types of shuttle-lane roadworks and also in understanding drivers’ behaviour through urban roadworks.
Data collected on roadworks sites were used to capture vehicles following time headways, departure headways at temporary traffic signals, move-up delays, queuing information, signing and drivers’ compliance with temporary traffic signals. Data collected from the same sites (post the removal of roadworks) were used to capture the arrival headway without the effect of the roadworks. Other data were collected on normal signalised junctions, which were used to compare drivers’ behaviour with temporary traffic signals at roadworks.