EVALUATION OF AHS EFFECT ON MEAN SPEED
BY STATIC METHOD
Toshiyuki YOKOTA
Senior Researcher, ITS Division,
Public Works Research Institute, Ministry of Construction 3050804 Asahi-1, Tsukuba-city, Ibaraki, Japan Phone: ++81-298-64-4496 Fax: ++81-298-64-0178
e-mail : [email protected]
Satoshi UEDA, Shigeo MURATA
ITS Division, Public Works Research Institute, Ministry of Construction
The present paper describes the functionality and the expected effect of longitudinal control (acceleration and deceleration) in the Advanced Cruise-Assist Highway Systems (AHS) for the mixed traffic of AHS and non-AHS vehicles, and presents quantitative analysis of the effect of AHS on traffic efficiency improvement.
The functionality and the expected effect of longitudinal control in AHS were first identified. The expected effect was then quantified by evaluating the improvement of traffic capacity with different settings of headway and other parameters. Finally, the improvement of travel speed due to the improvement of traffic capacity was quantitatively analyzed on a macroscopic scale by using a generalized
QUALITATIVE ANALYSIS OF Q-V VARIATION IN AHS
Traffic capacity, which is generally affected by regional traffic situations and geographical factors, is mainly determined by such road characteristics as uninterrupted sections (single lane, multilane), intersections, and interchanges. Although Q-V characteristics have conventionally been considered as unchanged, they can vary with such parameters as headway and the percentage of AHS vehicles if the use of AHS vehicles, which adjust their headway by the automatic control of acceleration and deceleration, becomes widespread.
A conceptual model showing the relationship between headway and Q-V curves is presented in Figure 1. Here, the magnitude of headway (greater or smaller) is relative to
non-AHS vehicles. In the case of AHS with a greater headway, as shown in the figure, the Q-V curve is scaled down (maximum Q-value is increased) as the percentage of AHS vehicles is increased. In AHS with a smaller headway, on the other hand, the Q-V curve is scaled up as the percentage of AHS vehicles is increased.
The results of the analysis of qualitative characteristics of traffic based on an AHS traffic stream simulator are schematically shown in the Headway-QV model diagram. When the percentage of AHS vehicles in congested traffic is increased, traffic capacity changes significantly but speed and its variation remain nearly the same (O1 -> T1). When the percentage of AHS vehicles in free-stream traffic is increased, speed increases and its standard deviation decreases while traffic capacity remains the same (O2 -> T2). The above results indicate that speed tends to be maintained in a congested zone, while traffic demand tends to be maintained in a free-stream zone. Further analysis with varying settings is still needed for the qualitative evaluation of traffic.
RELATIONSHIP BETWEEN SPACING (HEADWAY) AND V (SPEED) IN AHS
In the relationship between AHS vehicle spacing and speed, constant headway is V
Q-V including AHS vehicles that decrease headway T2” Q Q-V excluding AHS vehicles Q-V including AHS vehicles that increase headway
Figure 1. Headway - QV model O1
T1’
T1” O2
consideration. Here, traffic capacity Q for each headway is given by the reciprocal of the gradient of the corresponding S-V line. Spacing becomes a constant value of d if speed is below a certain level, above which a linear relationship is assumed between spacing and speed.
IMPROVEMENT OF TRAFFIC CAPACITY BY AHS
Traffic capacity in an uninterrupted multilane section was calculated for different headway of AHS vehicles (0.5, 0.9, and 1.6 s) and different percentages, d (%), of AHS vehicles. Each AHS vehicle is assumed to keep a target headway regardless of whether the preceding vehicle is AHS or non-AHS vehicle. The capacity of the mixed traffic of AHS and non-AHS vehicles is given by the following equation:
Qd=3600 / ( hid + hmanual ( 1-d )) (1)
Qd : capacity of the mixed traffic when the percentage of AHS vehicles is d (%)
hi: target headway of AHS vehicle
hmanual: average headway of non-AHS vehicle
d: Extension rate of AHS
Shown in Table 1 are traffic capacities, as deduced from equation (1), when the percentage of AHS vehicles is 100%.
Likewise, traffic capacity at an intersection when the percentage of AHS vehicles is d (%) was calculated based on the elementary flow rate at the intersection. Saturated flow rates when the percentage of AHS vehicles is 100% are shown in Table 2.
Q
Target headway 1.6 s Target headway 0.9s Target headway 0.5s
Figure 2. S-V figure considering minimum distance headway d d
Table 1 Target headway of AHS and traffic capacity
System Target
headway
Uninterrupted section
(multiple lanes) Magnification
Non-AHS vehicle - 2,200/h/lane
-1.6 s 2,200/h/lane 1.0
AHS-c ACC
0.9 s 4,000/h/lane 1.8
AHS-a
Automatic traveling (platoon) 0.5 s 7,200/h/lane 3.3
Table 2 Target headway of AHS and traffic flow rate at junction
System Target
headway
Uninterrupted section
(multiple lanes) Magnification
Non-AHS vehicle - 2,000/h/lane
-1.6 s 2,200/h/lane 1.1
AHS-c ACC
0.9 s 4,000/h/lane 2.0
AHS-a
Automatic traveling (platoon) 0.5 s 7,200/h/lane 3.6
EVALUATION OF MACROSCOPIC EFFECT OF AHS ON TRAVEL-TIME REDUCTION
FROM A GENERALIZED AGGREGATED Q-V EQUATION
The improvement of travel speed due to the improvement of traffic capacity was quantitatively analyzed on a macroscopic scale by using equation (2), which is a generalized aggregated Q-V equation providing the average travel speed in an area from the total road length (converted to per-lane length) within the area and cumulative vehicle-kilometer. The generalized aggregated Q-V equation takes into consideration the effect of AHS on the increase of traffic volume and starting flow rate. The parameters used were estimated from the regional data of the road traffic census.
Rb
V = a (2)
For expressways, (a, b, c) = (33.6, 0.28, 0.19), multiple correlation coefficient = 0.83 For national highways, (a, b, c) = (24.6, 0.42, 0.43), multiple correlation coefficient = 0.93
Assuming that the increase of traffic volume by AHS is reflected in the total road length, estimation was made for three different target headway (1.6, 0.9, and 0.5 s) and for national highways and expressways as shown in Table 3. Traffic volume (cumulative vehicle-kilometer) was assumed to be unchanged from the present traffic demand.
Table 3. Different cases of estimation
National
highway Expressway
Target headway = 1.6s Case 1 Case 4
Target headway = 0.9s Case 2 Case 5
Target headway = 0.5s Case 3 Case 6
The results of the estimation are shown in Table 4. When the percentage of AHS vehicles is 100%, target headway of 1.6, 0.9, and 0.5 s result in increase in travel speed by factors of 1.03, 1.32, and 1.67, respectively, in the case of national highways, and 1.00, 1.18, and 1.39, respectively, in the case of expressways.
Table-4 Evaluation of macroscopic effect on travel time reduction
AHS extension rate Type of road Case Target
Headway 0% 20% 40% 60% 80% 100% Speed Vm 35.2 35.5 35.7 35.9 36.2 36.4 Case 1 1.6 s Ratio rmd 1.00 1.01 1.01 1.02 1.03 1.03 Speed Vm 35.2 36.8 38.6 40.7 43.3 46.5 Case 2 0.9 s Ratio rmd 1.00 1.04 1.09 1.15 1.23 1.32 Speed Vm 35.2 37.6 40.5 44.4 49.9 58.8 National Highway Case 3 0.5 s Ratio rmd 1.00 1.07 1.15 1.26 1.42 1.67 Speed Vm 72.6 72.6 72.6 72.6 72.6 72.6 Case 4 1.6 s Ratio rmd 1.00 1.00 1.00 1.00 1.00 1.00 Speed Vm 72.6 74.6 76.8 79.3 82.3 85.9 Case 5 0.9 s Ratio rmd 1.00 1.03 1.06 1.09 1.13 1.18 Speed Vm 72.6 75.7 79.6 84.5 91.1 101.2 Expressway Case 6 0.5 s Ratio rmd 1.00 1.04 1.10 1.16 1.25 1.39
FINAL REMARKS
In the present study, expected effect of the longitudinal control of AHS on traffic capacity improvement was quantitatively analyzed on a macroscopic scale by using a generalized aggregated Q-V equation. More detailed analysis of the functionality of AHS will be conducted in accordance with the development of AHS design.
REFERENCES
1) Japan Road Association: Highway Capacity Manual, pp.19, September, 1992
2) Japan Road Association: The explanation and application of Road Structure Ordinance, pp.254-255, 1983
3) FHWA: Precursor Systems Analysis of Automated Highway Systems, Volume Four, Lateral and Longitudinal Control Analysis, pp.18, April, 1995
Figure 3. AHS mixture rate and the change of travel speed
0 10 20 30 40 50 60 70 80 90 100 110 0 20 40 60 80 100
AHS extension rate(%) Speed(km/h) Expressway h=0.5 Expressway h=0.9 Expressway h=1.6 National highway h=0.5 National highway h=0.9 National highway h=1.6
