Monitoring and analysis of travel speeds on the national road network using floating car technologies Shlomo Bekhor Transportation Research Institute Technion – Israel Institute of Technology The road network used for the analysis includes the 2011 Israel TMC road network. This network contains most interurban roads and major arterial streets in metropolitan areas (Haifa, Tel Aviv and Jerusalem). The network comprises 1,593 road segments with an overall length of about 8,960 Km. Out of the 1,593 segments, 1,383 relate to interurban roads and 210 to urban arterials. Speed is considered a leading cause and contributing factor that affect injuries from road crashes. There are numerous studies linking travel speeds and road crashes. Hence an essential part of every road safety plan is speed management. In order to manage speed, it has to be systematically and consistently monitored and analyzed. In this study we present a system for the collection and analysis of travel speeds at the nationwide level. The current research provides a comprehensive speed database in space and time. This analysis can identify the road sections with significant excesses of travel speeds relative to the speed limit. It can also serve as baseline to evaluate current counter-measures employed to reduce speed. The project was sponsored by Or Yarok (NGO). The conventional methods to measure speed are based on the deployment of equipment in the measured road sections, whether temporary or permanent (OECD, 2006). Due to relatively high cost of the equipment and the deployment/installation, speed measurements are typically conducted at a low frequency in road locations that are selected for different considerations, and constitute only a very small part of the road network. These methods allow performing targeted tests, but they do not supply systematic data bases for evaluation of actual speeds distributions in time and space. Vast penetration of GPS devices and cellular phones. Speed assessment of equipped vehicles by cellular phones and by GPS to characterize speeds in the road network. Focus was on average speed in congested conditions, often for navigation purposes. Similar methods can be used to receive estimates of speed distribution during free flow conditions, which are needed to monitor, analyze and manage road safety. The advantage of these methods stems from the availability of the data, without a need to install or deploy equipment of any sort. The travel speeds used in this study were provided by Decell Technologies (a private company). To assess the reliability of the GPS speed data, it is needed to compare it to an independent data source. The Ayalon Highway, a North-South highway crossing the Tel Aviv Metropolitan Area, was selected for the comparison. Magnetic loop detectors permanently installed in the highway provide speed and occupancy data every five minutes, for each lane and direction. Ayalon speed data is obtained from averages taken in five minutes intervals. The data are classified into five categories of different vehicles. The average speed is calculated for each vehicle category. South North Directio n From Junction To Junction Kibutz Galuyot La Guardia La Guardia Hashalom Hashalom Harakevet Harakevet Halacha Halacha Rokach Rokach Kakal Kakal Glilot Glilot Shevat Hakochavim Shevat Hakochavim Glilot Glilot Kakal Kakal Rokach Rokach Halacha Halacha Harakevet Harakevet Hashalom Hashalom La Guardia La Guardia Kibutz Galuyot Average Loop Detector speeds GPS speeds Average (km/h) Std. dev. (km/h) Average (km/h) Std. dev. (km/h) 92.8 6.9 92.8 7.0 99.5 5.8 98.7 5.3 96.0 3.9 95.7 6.2 99.3 3.3 99.6 4.8 103.2 2.4 103.4 7.0 100.7 3.0 98.4 9.8 104.8 5.2 102.6 3.7 103.8 1.5 100.2 1.6 104.5 2.8 98.2 4.6 107.3 2.2 102.0 4.0 108.9 2.8 101.5 3.6 105.0 4.3 95.3 4.4 103.0 4.3 94.4 4.7 95.2 4.3 93.8 5.4 100.7 3.9 91.4 4.2 94.1 4.3 93.9 11.2 101.2 3.8 97.6 5.5 Relative diff. 0.0% -0.8% -0.3% 0.4% 0.2% -2.3% -2.1% -3.5% -6.1% -5.0% -6.9% -9.2% -8.4% -1.6% -9.2% -0.2% -3.5% Results from the comparative analysis of GPS data based on floating sources with sensor data on fixed locations show that there is a good fit. Since the average segment length is about 6.0 km, and a GPS reading is recorded every 30 seconds on average, this means that a vehicle traveling at 90 km/h will give on average 4 GPS readings per segment. At free-flow conditions, there are not many cars passing, so the only way to collect sufficient information is to gather them for a large period of time (in this study, 6 months). In order to reduce variance and receive representative estimates it is recommended to gather at least 300 observations for every road section. The raw data was collected for 6 months, from 01‐Feb‐2011 until 28‐Jul‐2011, and after filtering included over 30 million GPS free-flow speed observations. More than 90% of the 1,593 road segments have more than 1,000 observations. For privacy reasons, there is no information about the driver or the vehicle, so the same segment might contain more than one observation for the same vehicle. The data file contains the distribution of the speed for each road section at 5 km/h intervals. mean speed standard deviation percentage observations over the allowed speed the 85th percentile the excess speed (the difference between the 85th percentile speed and allowed speed). A total of 6 different periods were defined: 3 typical days: Workdays (Sunday to Thursday), Friday and Saturday 2 time periods: day (from 06:00 to 22:00) and night (from 22:00 to 06:00).