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- 2020 Fit Speed Dating Colesberg (South Africa)
It is unsurprising then that some species of birds, including 19 raptors, are often spotted here. It is a particularly scenic reserve with an amazingly mountainous landscape and a consequent collection of deep, shady kloofs grown over with olive, buffalo-thorn and sweet thorn trees. Doornkloof Nature Reserve is wonderful for hiking.
There is a two to three day hiking trail, but hikers can also apply to walk anywhere in the reserve and either sleep in the hiking hut provided, or anywhere in the veld. There are basic camping facilities available, and there are also picnic and braai areas on the Seekoei River bank at Roodewal.
In Italy an evaluation of all enforcement routes was conducted in After the first year, average speeds reduced further by 9. Fatalities also reduced by For crash outcomes, eight-month pre-installation and post-installation periods were compared. In , a series of evaluations were conducted by relevant stakeholders at 13 locations in England data was provided by stakeholder consultation. Speed profiles three years before enforcement were compared with speed profiles for three years during enforcement.
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Posted speed limits of enforcement routes were between 30 mph and 50 mph. The 85 th percentile speed dropped by about Average speed reduced by an average of Across all routes, crashes reduced by an average of In , a macroscopic evaluation of the system was conducted on the R61 by using only data captured through the ASE system. Prior to enforcement a total of crashes had been reported, 75 of which involved fatalities. The specific time frame before ASE implementation, during which these crashes occurred, was not reported.
During enforcement, between November and November , no fatal crashes were reported. Contribution of this work. Although much research exists for ASE implementations in the developed world, the impact of ITS safety interventions vary from region to region Sussman Moreover, to the best of the authors' knowledge, no research exists that considers the impact of ASE on different modes of transport with differentiated speed limits. Furthermore, existing literature on ASE does not evaluate the impact on adjacent road segments, or compare the results with control routes.
Anker Guesthouse, Philippolis, South Africa - www.wellnesselek.hu
This paper examines the impact of ASE on speeding patterns and crash rates on the R61 in South Africa - a bidirectional single carriageway with no central reservation. Time differentiation and spatial differentiation analyses were performed to establish the impact on the ASE route, and also on control routes at various distances from the enforcement route. Crash outcomes fatalities, serious and minor injuries are also analysed on the enforcement route by comparing two years of pre- and postinstallation effects of the ASE system.
The investigation transcends macroscopic effects presented by local authorities Safely Home to address microscopic effects such as reductions in average speed and speed variability. Quantitative analysis. The aim of the quantitative analysis was to investigate the impact of ASE systems on speed limit compliance and crashes for two modes of transport. This section focuses on the compliance, while methods pertaining to the crashes are presented in a subsequent section.
CR I was chosen since it shares similar characteristics with the enforcement route, while CRs II and III were chosen to observe speeding patterns further away from the enforcement route, and were frequently used by passenger vehicles equipped with TomTom devices. Figure 2 shows the enforcement and the control routes, while Table I shows the geometric and traffic characteristics of each route. Evaluation dates ran from June to June before enforcement, and from December to December during enforcement. With regard to the state of enforcement on these routes before ASE, it should be noted that there were no permanent ITS interventions, and speed enforcement was carried out exclusively by mobile police units.
Time differentiation was performed on the enforcement and control routes. This involved a 'before' and 'during' enforcement analysis for each route. Results from time differentiation on the enforcement route were expected to show reduction in travel speeds during enforcement.
Spatial differentiation was also performed with the aim of determining the impact of the system on control routes relative to the enforcement route. This involved 'in' and 'out' of ASE section analysis before and during enforcement. Comparing the enforcement route and CR I, results from spatial differentiation before enforcement were expected to be similar, while results during enforcement were expected to be slightly different.
Between the enforcement route and CR II, spatial differentiation results were expected to be similar before implementation, but different after implementation. It was well understood that, despite these expectations, the riding quality, general traffic patterns of the routes over time, policing, etc, could lead to different results. Two independent data sets were considered for the quantitative study. Firstly, TomTom traffic statistics obtained from tracking devices, TomTom navigation devices and TomTom fleet management devices were used. This data set represented fleet monitoring for passenger vehicles mainly used for private transportation.
TomTom devices are uncommon in minibus taxis, since these devices are considered a luxury item. Tracking devices were installed in the taxis, each of which were programmed to provide time stamps, location and speed information at a nominal frequency of 1Hz. A total of trips between Cape Town and the Eastern Cape were obtained between November and May , these covering a total distance of more than 50 km. There was no data for minibus taxis before ASE. Due to this data availability constraint, only spatial differentiation analysis during enforcement was performed for the minibus taxis.
Data capturing and validation, with further analysis. Although the tracking devices were programmed at a minimum transmission frequency of 1Hz, not all consecutive records were captured at this frequency, due to filtering and data loss. Despite the accuracy of the GPS as a measurement device, it is still subject to systematic and random errors, which could be out by as much as 15 m per sample Gates et al The reasons for this include the following:.
On the other hand, the effects of random error were difficult to address. Statistical smoothing techniques or visual inspection of data can be used to identify random errors Jun et al Polygons surrounding each route were used to minimise the effects of random error.
Only records within the polygons were used. To validate the minibus tracking data, average speeds captured by the ASE system were compared with average speeds calculated from the GPS traces. The ASE system's speeds were obtained from twelve fines levied on minibus taxi drivers between December and March A maximum percentage error of 0. Two GPS reference records closest to the entry and exit cabinets respectively were selected from the list of GPS records defining a trip.
For each trip, a 2 km radius was defined around each camera to minimise wide variations in the location of reference records. Trips with no GPS records in the specified radius were excluded from the analysis.
2020 Fit Speed Dating Colesberg (South Africa)
This ensured a maximum deviation of 4 km in travel distance from the fixed travel distance of The GPS average speed for each trip was calculated using the known distance and travel time between the reference records. Average speeds calculated from reference records were also used to conduct further analyses on minibus taxis. These were used to detect if a given trip violated the ASE system. The valid trips through the enforcement route were identified and analysed. Each taxi was examined separately. Crash risk and injury severity. High crash rates on a particular road are often the reason behind ASE system deployment.
Reduction in crash rates due to ASE rest on the assumption that their effect on vehicle speed is equally worthwhile. It is therefore necessary to investigate their impact on crash rates. To this end, crash data within the enforcement route between January and September was provided for analysis by the Western Cape Department of Transport.
Time-based analysis around the enforcement date of November was applied with pre-implementation and post-implementation periods of two years. The analysis was conducted for minibus taxis and passenger vehicles for crashes primarily linked to human error due to speeding. Qualitative analysis. Although the trips in the study were captured from nine vehicles, multiple taxi drivers were involved, as more than one taxi driver is employed to drive each vehicle. In all, a total of 20 minibus taxi drivers were interviewed to determine their level of understanding of ASE.
Only those drivers who frequently drive through the R61 enforcement routes between Cape Town and the Eastern Cape Province were interviewed. Based on their understanding of ASE, taxi drivers were grouped into three categories. The first category represented drivers who understood how the ASE system operates and where it had been deployed along the route. The second category represented drivers who understood how the system operates, but were unaware of its location along the route.
The third category represented drivers who neither understood how the system operates nor where it had been deployed along the route. Speed compliance results. More than 6 vehicles were identified from TomTom traffic queries making complete trips through the respective evaluation routes in the time frames considered. For minibus taxis, trips identified from GPS records were analysed. Passenger vehicles. These results indicate an improvement after introduction of the ASE, but similar improvements in the adjacent and farther away control sections.
Together with Table 3 , Figure 3 also gives insight into spatial differentiation results. Before enforcement, however, these margins were lower and inconsistent, suggesting a higher degree of similarity and the absence of average speed-related enforcement. Coupled with observations from time differentiation results, it was observed that the ASE system appeared to have influenced passenger vehicle drivers to comply with speed limits along the enforcement route and on CR I, but not on control routes further away, such as CR II and CR III.
Two concerns arise from the time and spatial differentiation results. Firstly, between the enforcement route and CR I, it was observed that during enforcement CR I showed a slightly better level of compliance with the speed limit. Its mean and 85 th percentile speeds were 3. Speed profiles on CR I were expected to improve, but not to the point where they would be better than the enforcement route. This unexpected result may be due to routine maintenance during the enforcement period on CR I.
This could be due to road safety campaigns carried out across the country on roads with high death tolls. Following this trend, factors responsible for this could to some extent be responsible for reduction in speeds along the enforcement route, which may have nothing to do with the ASE system. Nevertheless, the reduction in speed along the enforcement route was better than that on CR II and III, and was in line with the results mentioned in the "Related Work" section above all of which did not consider control sections , suggesting that the ASE system has a measurable effect.
Passenger vehicles and minibus taxis. The spatial differentiation results after introduction of ASE are presented in Figure 4 and Table 3 , for both passenger vehicles and minibus taxis.