Page 41 - Proceeding of Atrans Young Researcher's Forum 2019_Neat

“Transportation for A Better Life:
Smart Mobility for Now and Then”

23 August 2019, Bangkok, Thailand

The approaching speed is calculated from 2.4 Data analysis
the time taken to cross the reference line at the The descriptive statistic and the binary
distance of 100-150 m from the stop line. logistic regression model are used to identify the
factors and reveled their influences on the driver's
stop/go decision. The indecision zones (Dilemma
Table 2 A data extraction in the model
Factors Type of code zone type II) are found in term of the distances and
variable the travel time to stopping line. A probability of
A decision categorical 0 Stop, 1 Go stopping 10% and 90% is a position of ending and
Vehicle type 0 Motorcycle, 1 Passenger beginning of the indecision zone, respectively.
categorical
car
Distance from continuous Meter
stopping line 3. Results and discussion
Gender* categorical 0 Female,1 Male 3.1 Descriptive statistic of the driver
Driver's age* categorical 0 >25 years ,1 <25years behavior
A passenger* categorical 0 Not have,1 Have At the onset of yellow, the distribution of the
Use a helmet* categorical 0 Not use, 1 Use approach speed, the distance from the stop line, and
Front vehicle If NFV : W1 = 1, W2 = 0,
in the same W3 = 0, W4 = 0, W5 = 0 the stop/go decision of drivers are shown in Fig. 3
lane If FVSS : W1 = 0, W2 = 1, and Fig. 4 and their descriptive statistics are as
W3 = 0, W4 = 0, W5 = 0 shown in Table 3.
If FVSG : W1 = 0, W2 = 0,
categorical As expected, the vehicles near to the stop
W3 = 1, W4 = 0, W5 = 0 line with higher speed tend to proceed through the
If FVDS : W1 = 0, W2 = 0,
W3 = 0, W4 = 1, W5 = 0 intersection where the vehicle positioned far away
If FVDG : W1 = 0, W2 = 0, from the stop line with lower speed tends to stop.
W3 = 0, W4 = 0, W5 = 1 However, there is a boundary that certain drivers
Back vehicle If NBV : W6 = 1, W7 = 0, choose to stop or go which will be presented in the
in the same W8 = 0
lane If BVS : W6 = 0, W7 = 1, next section.
categorical
W8 = 0 The comparison of distance and speed
If BVD : W6 = 0, W7 = 0, reveal certain differences among the passenger car
W8 = 1 and motorcyclist behavior. For both stop and go
Front vehicle If NFVA : W9 = 1, W10 = 0, group, it was found that the mean position of the
in adjacent W11 = 0, W12 = 0, W13 = 0
lane If FVASS: W9 = 0, W10 = passenger car (95.8 m, 33.8 m) is nearer to the stop
1, W11 = 0, W12 = 0, W13 line than those of the motorcyclist (100.7 m., 42.5
= 0 m.). Moreover, their mean speed (62.2 kph, 69.6
If FVASG: W9 = 0, W10 = kph) are also higher than those of the motorcyclist
0, W11 = 1, W12 = 0, W13
categorical (55.9 kph, 64.4 kph).
= 0
If FVADS: W9 = 0, W10 =
0, W11 = 0, W12 = 1, W13 PC
= 0 120
If FVADG: W9 = 0, W10 = 110
0, W11 = 0, W12 = 0, W13 100
= 1 90
Speed continuous Kilometer per hour 80 Stop
*only for the motorcycle Speed (Kph) 70 Go
60
50
According to the afore-mentioned method, a 40
total of 40 hr. traffics were monitored and a total of 30
593 passenger cars and 231 motorcycles were 20 0 10 20 30 40 50 60 70 80 90 100 110 120 130 140 150
extracted and coded. Among the observed Distance from stopping line (m)
motorcyclists, 71% and 29% are male and female,
respectively. The majority of the observed rider are Fig. 3 The passenger car stop/go decision at the
adults (93 %) and only 7 % is a young rider. There onset of yellow light
are 79 % of rider that driving alone where 21 % have
pillion passenger. For the safety equipment use,
there are 87% of driver that wear a safety helmet.

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