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).