Journal of Jilin University(Engineering and Technology Edition) ›› 2021, Vol. 51 ›› Issue (4): 1331-1341.doi: 10.13229/j.cnki.jdxbgxb20200246

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Speed behavior characteristic on typical driving scenarios and along switched scenarios

Jin XU1,2(),Cun-shu PAN2,Jing-hou FU2,Jun LIU2,Dan-qi WANG2   

  1. 1.Chongqing Key Laboratory of “Human-Vehicle-Road” Cooperation & Safety for Mountain Complex Environment，Chongqing Jiaotong University，Chongqing 400074，China
    2.College of Traffic and Transportation，Chongqing Jiaotong University，Chongqing 400074，China
  • Received:2020-04-15 Online:2021-07-01 Published:2021-07-14

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Abstract:

To clarify the speed behavior on typical scenes and speed variation when driving scenes switching, three road sections were selected in Chongqing, field driving experiments with more than 70 subjects were carries out. The vehicle operation data under the natural state were collected through on-board instruments, and the speed change characteristics when driving scenes alternate was analyzed, as well as the restraint of roadway condition on the speed behavior for various driving scenes. The results show that the driver's selection behavior on the main line of river-spanning bridge is highly discrete, that is, the road environment has little restraint on the driver's behavior, and the probability of rear end collision is higher on the bridge. When driving from the main line of the bridge into a ramp with small radius of the interchange, the driver will slow down on the bridge in advance, and the sharp ramps have stronger binding on the driving behavior than the bridge. The driver will continue the deceleration behavior to a certain distance in the tunnel, and the dispersion of speed amplitude will be weakened at the same time, indicating that the change of environment at tunnel entrance will significantly affect the driver's speed choice behavior. When driving into a ramp with a small radius, the driver's deceleration behavior will continue into the range of circular curve, and higher speed will lead to greater deceleration. For a ramp with a relative longer circular, only a few drivers will keep a constant speed near the middle of the circular curve. When the circular curve of the ramp is shorter, no driver would drive at a constant speed within the circular curve. The driving speed is constant in the range of multi-layer helical ramps. Speed amplitude of 70 percent drivers is distributed in a narrow range. Therefore, adjusting the design parameters in a small range can take care of most drivers' behavior habits.

Key words: traffic engineering, driving behavior, road condition, driving scenario, speed, interchange ramp, river-spanning bridge, tunnel

CLC Number: 

  • U491.25

Fig.1

Test sites： road I - road III"

Table 1

Switch of alignment （scenario） types of each test route"

序号试验地点构成单元（场景组成）
单元#1［主要参数］单元#2［主要参数］单元#3［主要参数］单元#4［主要参数］
道路I

涪陵长江一桥-

南桥头立交

大桥主线［直线段］回头曲线匝道［R=35 m］螺旋匝道［内圈半径39.525 m， 外圈半径50 m， 坡度4.5%］/
道路II

苏家坝立交O匝

道?菜园坝大桥

同向连续曲线匝道［R1=200 m， R2=100 m］同向曲线隧道［R3=60 m， R4=90 m］

曲线匝道［R4=90 m，

长度160 m］

过江大桥主线

［直线段］

苏家坝立交M

匝道

大桥主线出口［分流点］螺旋匝道（右转）［R1=100 m， R2=60 mm， R3=100 mm］S型曲线匝道［R4=65 m，R5=300 m］/
道路III

江南立交?向

黄路

小半径回头曲线匝道/R=60 m向黄路/大半径曲线

向黄隧道

［直线段，长度890 m］

/

Fig.2

Test vehicles and onboard instruments"

Table 2

Information of drivers participated field driving test"

试验地点被试数量男/人女/人

年龄分布

/岁

平均年龄

/岁

驾龄分布

/年

平均驾龄

/年

行驶里程

/万公里

平均行驶里程

/万公里

道路I106423~5733.21~317.70.2~80098.1
道路II3021922~4733.22~229.41~6017.7
道路III33171626~5138.44~2410.61~10025.9

Fig.3

Driving speed measured on test road I and their variation characteristics"

Fig.4

Driving speed measured on test road II and their variation characteristics"

Fig.5

Speed distribution on three spots of Caiyuanba Bridge， Test Road II"

Fig.6

Driving speed measured on test road III and their variation characteristics"

Fig.7

Speed pattern on sharp ramp with radii of 60 m in test road III"

Fig.8

Speed pattern on sharp ramp with radii of 35 m in test road I"

Fig.9

Driving speed measured on M ramp of Fuling Yangtze River Bridge and their variation characteristics"

Fig.10

Three parameters used to describe discreteness of drivers′ speed behavior"

1 Shallam R D K, Venthuruthiyil S P, Chunchu M, et al. Empirical analysis of operating speed performance on undivided hilly roads[J]. Journal of Transportation Engineering, Part A: Systems, 2019, 145(8): 04019034.
2 Xu J, Lin W, Wang X, et al. Acceleration and deceleration calibration of operating speed prediction models for two-lane mountain highways[J]. Journal of Transportation Engineering, Part A: Systems, 2017, 143(7): 1-13.
3 Jacob A, Anjaneyulu M V L R. Operating speed of different classes of vehicles at horizontal curves on two-lane rural highways[J]. Journal of Transportation Engineering, 2013, 139(3): 287-294.
4 Fitzpatrick K, Miaou S, Marcus B, et al. Exploration of the relationships between operating speed and roadway features on tangent sections[J]. Journal of Transportation Engineering, 2005, 131(4): 261-269.
5 Semeida A M. Application of artificial neural networks for operating speed prediction at horizontal curves: a case study in Egypt[J]. Transportation in Developing Economies, 2019, 5(14): 1-8.
6 Sekhar C R, Nataraju J, Velmurugan S, et al. Free flow speed analysis of two lane inter urban highways[J]. Transportation Research Procedia, 2016 17: 664 -673.
7 刘硕, 王俊骅, 张兰芳, 等. 城市地下道路车速特征及运行车速模型[J]. 同济大学学报:自然科学版, 2015, 43(11): 1677-1683.
Liu Shuo, Wang Jun-hua, Zhang Lan-fang, et al. Characteristic and prediction model for operating speed model in urban underground road[J]. Journal of Tongji University(Natural Science):2015, 43(11): 1677-1683.
8 徐进,邵毅明,赵军,等. 山区道路弯坡组合路段重载车辆行驶速度模型[J]. 长安大学学报, 2015, 35(2): 67-74.
Xu Jin, Shao Yi-ming, Zhao Jun, et al. Speed prediction model of heavy truck driving on curved segment with a slope of mountainous highway[J]. Journal of Chang'an University(Natural Science Edition), 2015, 35(2): 67-74.
9 王志新, 余强, 赵轩, 等. 长大下坡路段载货汽车行驶速度预测研究[J]. 公路交通科技, 2017, 34(7): 130-135.
Wang Zhi-xin, Yu Qiang, Zhao Xuan, et al. Study on truck speed prediction in long and steep downhill sections[J]. Journal of Highway and Transportation Research and Development, 2017, 34(7): 130-135.
10 徐进, 邵毅明, 杨奎, 等. 基于人-车-路协同仿真的山区道路大型车辆行驶适应性分析[J]. 中国公路学报, 2015, 28(2): 14-25.
Xu Jin, Shao Yi-ming, Yang Kui, et al. Analysis of adaptability of large vehicles on mountainous highways based on driver-vehicle-road collaborative simulation[J]. China Journal of Highway and Transport, 2015, 28(2): 14-25.
11 Choudhari T, Maji A. Effect of horizontal curve geometry on the maximum speed reduction: a driving simulator‑based study[J]. Transportation in Developing Economies, 2019, 5(14): 1-8.
12 Bassani M, Catani L, Salussolia A, et al. A driving simulation study to examine the impact of available sight distance on driver behavior along rural highways[J]. Accident Analysis and Prevention, 2019, 131: 200-212.
13 Deng Z, Chu D, Wu C, et al. Curve safe speed model considering driving style based on driver behaviour questionnaire[J]. Transportation Research Part F, 2019, 65: 536-547.
14 Zhao X, Xu W, Ma J, et al. Effects of connected vehicle-based variable speed limit under different foggy conditions based on simulated driving[J]. Accident Analysis & Prevention, 2019, 128: 206-216.
15 Bassani M, Catani L, Cirillo C, et al. Night-time and daytime operating speed distribution in urban arterials[J]. Transportation Research Part F, 2016 42: 56-69.
16 Yang Q, Overton R, Han L D, et al. The influence of curbs on driver behaviors in four-lane rural highways—a driving simulator based study[J]. Accident Analysis and Prevention, 2013, 50: 1289-1297.
17 Larocca A P C, Ribeiro R L, Figueira A C, et al. Analysis of perception of vertical signaling of highways by drivers in a simulated driving environment[J]. Transportation Research Part F, 2018, 58: 471-487.
18 Schneidereit T, Petzoldt T, Keinath A, et al. Using SHRP 2 naturalistic driving data to assess drivers' speed choice while being engaged in different secondary tasks[J]. Journal of Safety Research, 2017, 62: 33-42.
19 Dhahir B, Hassan Y. Using horizontal curve speed reduction extracted from the naturalistic driving study to predict curve collision frequency[J]. Accident Analysis and Prevention, 2019, 123: 190-199.
20 Al-Sahili K, Dwaikat M, Abu-Eisheh S, et al. Effectiveness of consistency measures in crash prediction models for two-lane highways in palestine[J]. Arabian Journal for Science and Engineering, 2018, 43(10): 5645-5656.
21 Borsati M, Cascarano M, Bazzana F. On the impact of average speed enforcement systems in reducing highway accidents: evidence from the Italian safety tutor[J]. Economics of Transportation, 2019, 20: 100123.
22 Sayed T, Sacchi E. Evaluating the safety impact of increased speed limits on rural highways in British Columbia[J]. Accident Analysis and Prevention, 2016: 95: 172-177.
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