Construction of Driving Condition Based on Discrete Fourier Transform and Improved K-Means Clustering Algorithm

Figures & Tables

Clustering categories	v_a	T_c	v_x	a_a	T	T_i
Class 1	6.23	0.12	11.06	0.16	26.15	0.59
Class 2	16.25	0.25	18.26	0.59	35.56	0.23
Class 3	23.03	0.49	30.51	0.45	48.12	0.18

Characteristic parameters	Overall sample data	k-means		k-means++		Grid-K-means
Characteristic parameters	Overall sample data	Fitted value	Relative error/%	Fitted value	Relative error/%	Fitted value	Relative error/%
v_a	18.91	18.11	4.23	18.34	3.01	18.60	1.64
a_a	1.85	1.95	5.41	1.88	1.62	1.86	0.54
a_d	-2.36	-2.45	3.81	-2.43	2.97	-2.39	1.27
T_i	0.52	0.58	11.54	0.55	5.77	0.53	1.92
T_a	0.49	0.41	16.32	0.44	10.20	0.47	4.08
T_d	0.26	0.31	19.23	0.29	11.54	0.28	7.69
E_s			10.09		5.85		2.86

Characteristic parameters	M₁	M₂	M₃
Segment duration T	0.132	0.231	0.745
distance S	0.293	0.134	0.045
Average speed V_a	0.719	0.463	-0.025
Average driving speed V_x	0.478	0.615	0.112
Idle time ratio T_i	0.125	-0.351	0.843
Acceleration time ratio T_a	0.694	-0.156	0.060
Deceleration time ratio T_d	0.923	0.341	-0.123
Cruising time ratio T_c	0.641	0.435	-0.045
Mean acceleration a_a	0.014	0.623	0.033
Mean deceleration a_d	0.366	-0.433	-0.052
Standard deviation of acceleration a_std	0.445	0.267	-0.067
Standard deviation of speed V_std	0.387	0.215	0.034

Category		Eigenvalue
Primary component	principal M₁	average speed, acceleration time ratio, deceleration time ratio, cruising time ratio
Secondary component	principal M₂	average speed, acceleration time ratio, deceleration time ratio, cruising time ratio
Third component	principal M₃	segment duration, idle time ratio

Fragment number	T	S	V_a	V_x	T_i	T_a	T_d	T_c	a_a	a_d	a_std	V_std
1	119	203.29	6.15	7.60	0.06	0.17	0.08	0.03	0.42	-0.66	0.48	5.05
2	319	2320.7	26.19	33.63	0.14	0.26	0.19	0.11	0.30	-0.34	0.37	17.5
⋮	⋮	⋮	⋮	⋮	⋮	⋮	⋮	⋮	⋮	⋮	⋮	⋮
78	243	346	7.03	12.23	0.04	0.21	0.08	0.04	0.38	-0.61	0.39	5.01
79	167	459.12	5.97	8.04	0.06	0.19	0.05	0.05	0.44	-0.59	0.28	4.91
⋮	⋮	⋮	⋮	⋮	⋮	⋮	⋮	⋮	⋮	⋮	⋮	⋮
1584	169	829.04	17.66	23.65	0.13	0.19	0.09	0.07	0.36	-0.50	0.48	14.8
1585	486	6799.9	50.37	52.65	0.02	0.18	0.13	0.30	0.19	-0.20	0.29	16.5

Data set	k-means		k-means++		Grid-K-means
Data set	Accuracy	Elapsed time	Accuracy	Elapsed time	Accuracy	Elapsed time
20000	92.76%	25.82s	93.16%	34.86s	95.78%	25.83s
80000	88.32%	43.83s	89.32%	49.16s	92.36%	40.69s
100000	87.24%	58.12s	87.65%	67.94s	90.12%	50.38s

Method		Acceleration distribution (m/s2)
Method		(-∞,-0.64)	[-0.64,0.64]	(0.64,+∞)
Grid-K-means	K-S value	0.68	0.57	0.53
Grid-K-means	Similarity level	0.89	0.96	0.99
k-means++	K-S value	0.71	0.26	0.45
k-means++	Similarity level	0.79	0.44	0.82

Serial number	eigenvalue	contribution/%	Cumulative contribution/%
1	5.5605	43.23	43.23
2	3.2315	26.83	70.06
3	1.9901	16.14	86.20
4	1.0434	6.14	92.34
5	0.53476	3.11	95.45
6	0.45796	2.01	97.46
7	0.38341	1.22	98.68
8	0.21525	0.78	99.46
9	0.17450	0.23	99.69
10	0.10126	0.19	99.88
11	0.09324	0.08	99.96
12	0.02532	0.04	100