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Effect of Information Provision to Following Vehicle on Reducing Amount of CO2 Emissions and Safety Drive
Available online at www.sciencedirect.com
ScienceDirect Available online at www.sciencedirect.com
Transportation Research Procedia 00 (2017) 000–000
ScienceDirect
www.elsevier.com/locate/procedia
Transportation Research Procedia 27 (2017) 93–100 www.elsevier.com/locate/procedia
20th EURO Working Group on Transportation Meeting, EWGT 2017, 4-6 September 2017, Budapest, Hungary
Effect of Information Provision to Following Vehicle on Reducing Amount of CO2 Emissions and Safety Drive Yukimasa MATSUMOTO a, *, Shogo ISHIGURO a a
Department of Civil Engineering, Meijo University, Nagoya 468-8502, Japan
Abstract For reducing the amount of CO2 emissions from vehicles approaching a signalized intersection in car-following situation, the information provision system to a driver is proposed in this paper. The system provides mainly the accelerator-off indication, in which the vehicle could pass through the intersection or shorten the idling time if it would follow the information. In carfollowing situation, the distance between the lead vehicle and the following vehicle might become shorter by the information provision so that risk of traffic collisions may be raised. Therefore, the influence of the information provision on driving behavior in car-following situation is grasped using a driving simulator in this paper. The risk of traffic collisions is measured by the TTC (time to collision) inverse when the information is provided, and the effectiveness in reducing the amount of CO2 emissions from vehicle is also evaluated quantitatively. From results of the experiments with 25 participants, although the information provision only to the lead vehicle might raise the risk of traffic collision, it can be seen that the information provision to the following vehicle can contribute to reduce the risk of traffic collision even under car-following situations. Moreover, it can be seen that the information provision to both vehicles reduces the amount of CO2 emissions from the following vehicle most effectively. © 2017 The Authors. Published by Elsevier B.V. © 2017 The Authors. Published by Elsevier B.V. Peer-review EURO Working Working Group Group on on Transportation Transportation Meeting. Meeting. Peer-review under under responsibility responsibility of of the the scientific scientific committee committee of of the the 20th 20th EURO Keywords: CO2; Signalized intersection; Driving simulator; Accelerator-off; Traffic signal information; Car-following
1. Introduction Various information on traffic conditions such as the level of traffic congestion, a travel time of each vehicle and also vehicle movements has been available by the advantage of the ITS technologies. In Japan, the Driving Safety
* Corresponding author. Tel.: +81-52-832-1151; fax: +81-52-832-1179. E-mail address: [email protected] 2214-241X © 2017 The Authors. Published by Elsevier B.V. Peer-review under responsibility of the scientific committee of the 20th EURO Working Group on Transportation Meeting.
2352-1465 © 2017 The Authors. Published by Elsevier B.V. Peer-review under responsibility of the scientific committee of the 20th EURO Working Group on Transportation Meeting. 10.1016/j.trpro.2017.12.137
94 2
Yukimasa Matsumoto et al. / Transportation Research Procedia 27 (2017) 93–100 Author name / Transportation Research Procedia 00 (2017) 000–000
Support System (DSSS) based on the vehicle-to-infrastructure communication system (V2I) has been actually put into operation in 2011, aiming to prevent traffic accidents by delivering the information on vehicles and pedestrians approaching the upcoming intersection (Koreeda et al., 2013; Taniguchi et al., 2013). The Signal Recognition Enhancement System based on traffic signal information has also been operated, which prevents the driver overlooking the red traffic signal ahead (Sueki et al., 2009). In the U.S., the real-time traffic light information can be sent to a vehicle by the advanced traffic management system from December 2016 as one of the V2I applications. The providing traffic signal information has the potential for improving traffic congestion and traffic accidents. Moreover, smoothing traffic flow is expected to contribute for reducing the amount of CO2 emissions from vehicles. Information provision based on upcoming traffic signal information to a driver has attracted attention from many researchers. Asadi and Vahidi (2010) propose an algorithm to schedule an optimal speed trajectory for reducing idling time at stop line using upcoming traffic signal information. Tielert et al. (2010) evaluated traffic-light-tovehicle communication for reducing fuel consumption and emissions by large-scale simulations. Rakha and Kamalanathsharma (2011) present a framework to enhance vehicle fuel consumption efficiency while approaching a signalized intersection through the provision of signal phase and timing information. Matsumoto et al. (2014) simulated vehicle movements approaching a signalized intersection under information provision using a microscopic traffic simulation based on observed actual vehicle movements. While a microscopic traffic flow simulation evaluates the effectiveness of the information provision based on the upcoming traffic signal to a driver, the responses by each driver are also grasped using a driving simulator when the traffic signal information is provided. Niu and Sun (2013) evaluated the effectiveness of the green wave guidance strategy and the eco-driving speed guidance strategy with a multi-vehicle driving simulator. Kircher et al. (2014) investigated the difference of effects between intermittent and continuous eco-driving speed information with a truck driving simulator. Brouwer et al. (2015) tailored different types of the display to present eco-driving speed feedback with a truck driving simulator. These studies indicate that providing the speed information is significantly efficient to reduce the amount of CO2 emissions. Matsumoto and Peng (2015) also showed that providing the information had a significant effect on reducing CO2 emissions from vehicles approaching a signalized intersection. Especially, it was also found that more effective information was the accelerator-off indication than the recommended speed information from the experiments with a driving simulator. However, these studies mainly analyze the individual behavior of the driver regardless the interaction between the lead and the following vehicles. Kondoh and Yamamura (2006) clarified that drivers' perception of proximity risk in car-following situation was strongly correlated with the time headway and the time to collision using a driving simulator. Broughtona et al. (2007) employed a driving simulator to measure the behavior of drivers following a lead vehicle under three visibility conditions. Yoshizawa et al. (2012) analyzed the influence of road alignments and the lead vehicle behavior on car-following behavior in a driving simulator experiment. These studies suggest that a driving simulator is useful and efficient for measuring driving behavior in car-following situation. Therefore, we use a fixed-base 3D driving simulator for exploring the information provision in car-following situation. By previous research (Matsumoto and Peng, 2015), we developed the information provision system for reducing the amount of CO2 emissions from a vehicle approaching a signalized intersection and clarified that the accelerator-off indication is more effective for reducing it than the recommended speed information. Thus, the accelerator-off indication is mainly provided to the lead and following vehicles in this study and the influence of the information provision on driving behaviour in car-following situation is grasped using a driving simulator. Especially the risk of traffic collisions is measured when the information is provided to a driver and the effectiveness in reducing the amount of CO2 emissions from vehicle is also clarified quantitatively. 2. Information Provision System 2.1. Outline of information provision system For decreasing unnecessary vehicle movements such as rapid deceleration and long idling, two types of the provided information are designed in this study. One is the accelerator-off indication, which informs a driver of releasing the accelerator pedal for passing through the upcoming signalized intersection or for shortening the idling time during a red signal at the intersection. Another is the recommended speed information.
Yukimasa Matsumoto et al. / Transportation Research Procedia 27 (2017) 93–100 Author name / Transportation Research Procedia 00 (2017) 000–000
95 3
Speed
G Y R
0 Red
tgr
trd
Green
Red
af
vs
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vr G Y R
0 dm
td
tr tc
tgr
tf
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ds
C1 C2 C3 Distance from intersection
Fig. 1. Time-space diagram of vehicle approaching intersection
ds Distance from intersection
Fig. 2. Vehicle movement with information provision
A vehicle can pass through the upcoming signalized intersection as long as the vehicle runs at the recommended speed provided by the system. The recommended speed which is equal to the current speed is only provided when the vehicle can pass through the upcoming intersection with the current running speed in this study. 2.2. Concept to provide information to reduce unnecessary vehicle movement Fig. 1 shows a time-space diagram of vehicles approaching a signalized intersection, in which the horizontal axis of this figure denotes the time elapse and the vertical axis denotes the distance from the upcoming signalized intersection. The color bar on the horizontal axis indicates the signal status. The background color shows the signal state when the vehicle arrives at the intersection with a constant speed. In this study, for convenience, a yellow phase is regarded as same as a red phase so that vehicles stop when the traffic signal is yellow. In this figure, the vehicle C1 stops at the intersection if the vehicle runs at the constant speed. A green signal starts after tgr from the time when the vehicle passes the distance ds from the intersection and the next red signal starts after trd. For this case, the information to reduce the current speed is provided at ds. If the vehicle C1 would follow the information, it could pass through the intersection without stopping at red signal like a broken line. The vehicle C2 approaches the intersection at the constant speed and will pass through the intersection during green time. For this case, no information is provided. On the other hand, the vehicle C3 approaches the intersection during green signal and will stop at the intersection due to a red signal. For this case, the vehicle C3 could pass through the intersection like a dashed line if it would accelerate. However, such behavior may raise a risk of traffic accidents. Therefore, the vehicle is informed of reducing the current speed in advance by the proposed system like a broken line so that it will shorten the idling time at the intersection during a red signal. 2.3. Method of information provision The lower part of Fig. 2 shows a time-space diagram when the vehicle approaches the signalized intersection from the distance ds with/without information. The upper part shows the speed of the vehicle. The vehicle running at ds will reach the upcoming intersection after time tc during red signal without decelerating like a dotted line. However, if the vehicle would decelerate by releasing the accelerator pedal, it could pass through the intersection at tf during green signal like a broken line. In this figure, ds, tc and tf denote the location of the vehicle from the upcoming signalized intersection, the forecasted arrival time with the current running speed vs and the forecasted arrival time at the intersection with releasing the accelerator pedal, respectively. The deceleration rate during releasing the accelerator pedal is assumed to be a constant of af and td is the reaction time. The dm is a marginal distance, which mainly includes the queue length of the vehicles during red signal and a marginal distance which corresponds to a time lag between the start of a green signal and the arrival time at the intersection. This marginal distance helps the vehicle pass through the intersection safely because the traffic signal turns to green slightly prior to the vehicle arrival at the intersection. If this is set to be 0, the traffic signal sometimes turns to green from red at the moment the vehicle reaches the intersection, which leads to heavy braking. From this figure, tf is calculated as:
Author name / Transportation Procedia 00 (2017) 000–000 Yukimasa Matsumoto et al. / Research Transportation Research Procedia 27 (2017) 93–100
496
40km/h (a) Accelerator-off Upcoming intersection is passable at green signal
(b) Accelerator-off Idling time at upcoming intersection is shortened
(c) Recommended speed Upcoming intersection is passable at green signal
Fig. 3. Information displayed on the screen
tf =
a f t d − vs + vs2 + 2a f (d s − d m − t a vs ) af
.
(1)
For passing through the intersection by the accelerator-off, tf must be larger than tgr, where tgr means the remaining red time until the signal will turn to green, and then the following relations can be obtained:
t c < t gr < t f .
(2)
Even if tf is less than tgr, the accelerator-off indication is also provided for shortening the idling time during red signal in this study. If the accelerator-off indication is provided to the vehicle running at enough low speed, the vehicle reaches the intersection much later than the time the signal turns to green, tgr. This movement is also regarded as unnecessary because the vehicle continues to decelerate by releasing the accelerator pedal in spite of green signal ahead. Therefore, the current speed of the vehicle is provided as the recommended speed at the moment the vehicle can pass through the intersection with the current speed like the solid curved line in Fig. 2. 2.4. Information provision to following vehicle The vehicle receiving the information begins to decelerate from ds which has a certain distance from the upcoming intersection. In this case, the driver of the following vehicle might be surprised by unexpected deceleration of the lead vehicle without an advance notice. Moreover, the distance between the lead vehicle and the following vehicle becomes shorter so that risk of traffic collisions may be raised. Therefore, the information is also provided to the following vehicle by the same method explained above in this study. However, when the distance between the lead vehicle and the following vehicle is short naturally, the risk of traffic collisions may be raised. Furthermore, when the following vehicle runs with higher speed than the lead vehicle, the distance between the two vehicles becomes shorter even if the accelerator-off indication is provided to the following vehicle. Therefore, when the time headway between two vehicles is shorter than 2 sec., any information is disappeared in the proposed information system. The vehicles with the same speed and the lower speed of the lead vehicle are provided the information as same as the way for the lead vehicle. 3. Experiments using fixed-base 3D driving simulator 3.1. Experimental course and design of information The information provision system proposed in this study is introduced in a fixed-base 3D driving simulator which is composed of a seat, a steering wheel, pedals, speakers and three 42” monitors having 120° field of view including side view of mirror images. The 3D virtual driving environment is generated by UC-Win/Road. The course of about 4,500m created for this driving experiment includes 6 signalized intersections and 1 gentle curve section for
Yukimasa Matsumoto et al. / Transportation Research Procedia 27 (2017) 93–100 Author name / Transportation Research Procedia 00 (2017) 000–000
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generating driving unmonotonous. The course is flat having two lanes for both directions in which the lane width is set to be 3.25 m. A speed limit of the course is set to be 40 km/h. The information provision system displays the information on the screen of the driving simulator based on the location and the speed of the current vehicle, and the remaining time of the current signal phase. Fig. 3 shows the 3 types of the displayed information on the screen during the driving experiment. The left image signifies the accelerator-off indication, which is displayed when the upcoming intersection can be passable at green signal by just releasing the accelerator pedal. The middle image signifies the accelerator-off indication, which is displayed when the vehicle cannot pass through the upcoming intersection by releasing the accelerator pedal but can shorten the idling time. The right image signifies the recommended speed, which is appeared at the moment when the running speed is decreased enough to pass through the upcoming intersection with the current running speed. The displayed recommended speed is rounded off in unit of 5 km/h by the system considering driver’s recognition time and safety. At every time when any information is provided, the notice tone of “dingdong” is sounded and makes a driver noticed that any information is provided on the screen. 3.2. Using recorded vehicle as lead vehicle The driving experiments in this study are designed under the situation where a lead vehicle and the following vehicle run simultaneously in order to grasp the differences of the following driving behaviors with/without information provision to a lead vehicle and the following vehicle. The vehicle movements of the lead vehicle for all participants are therefore desired to be identical to eliminate the influence of the difference of the lead vehicle movements. Thus the vehicle movements recorded by the previous experiment where only one vehicle runs on the same course are used as the lead vehicle movements. There are two types of the lead vehicle movement, the movements with information provision and without information provision. 3.3. Driving experiment of vehicle following The participants were 25 people with a driving license ranging from 20 to 60 years old. Driving operation of the 3D driving simulator seems to be different from the actual vehicle driving. Therefore, each participant was asked to practice the driving on a simpler course for about 3 minutes to get used to the simulator operation. After that, each participant started to drive after the lead vehicle and follow it. Each participant drove on the experimental course 4 times. The experiments include 4 scenarios combined by the information provision (with/without information provision) and the vehicle types to be provided the information (the lead vehicle and the following). The participants were instructed to 1) drive as if they normally drove an actual road, 2) obey strictly the traffic signals unless they judged not to stop safely at yellow signal, 3) go straight at the intersection and 4) follow the provided information. The speed limit of 40 km/h was also informed in advance. The participants were asked to redo the driving experiment if they failed to comply with these instructions. 4. Results of driving experiment of following vehicle The influences of the information provision on the driving behavior of the following vehicle are grasped here. Especially, in the case where the information is provided to the lead vehicle, it is conceivable that the headway between the lead vehicle and the following vehicle is shortened due to unexpected speed change of the lead vehicle by the provided information and it is likely to raise the risk of traffic collisions. Therefore, it is clarified whether traffic safety is maintained with enough headway even if the information is provided to the lead vehicle. Moreover, the influence of the information provision on CO2 emissions from the vehicle is quantitatively evaluated based on the results of the driving experiments. 4.1. Comparing vehicle behavior of following vehicle
Yukimasa Matsumoto et al. / Transportation Research Procedia 27 (2017) 93–100 Author name / Transportation Research Procedia 00 (2017) 000–000 Average Running speed (km/h)
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1500 2000 2500 3000 Distance from last intersection (m)
Lead vehicle without information & Following vehicle without information Lead vehicle with information & Following vehicle without information
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Lead vehicle without information & Following vehicle with information Lead vehicle with information & Following vehicle with information
0.1
0.1
0.08
0.08 Average 1/TTC(1/s)
Average 1/TTC(1/s)
Fig. 4. Average running speed of following vehicle by scenario
0.06 0.04 0.02 0
0.06 0.04 0.02 0
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1000 1500 2000 2500 3000 3500 4000 4500 Distance from last intersection (m)
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Fig. 5. Average 1/TTC when following vehicle without information
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500 1000 1500 2000 2500 3000 3500 4000 4500 Distance from last intersection (m)
Lead vehicle with information & Following vehicle without information
lead vehicle with information & Following vehicle with information
Fig. 6. Average 1/TTC when lead vehicle with information
Fig. 4 shows the average running speed of all participants of the following vehicles for the entire course by each scenario. In this figure, the horizontal axis denotes the distance from the last signalized intersection (m) and the vertical axis denotes the average vehicle running speed (km/h) of the following vehicle. It is obvious that the running speed is reduced more as the vehicle approaches the signalized intersection in all scenarios where the information is provided to any vehicle than the running speed without the information provision to two vehicles. However, in the case where the information is provided to the lead vehicle, there is a possibility to shorten the headway between the lead vehicle and the following vehicle. Therefore, it is clarified whether the behavior of the following vehicle is safe by TTC (time to collision) index in the next section. 4.2. TTC inverse The TTC index defined by Hayward (1972) is an index indicating the time required for two vehicles to collide if they continue at their present speed and the same path. In this study, the TTC inverse is used to express unsafety level because the TTC index sometimes takes infinity. The smaller TTC inverse means the traffic state between the lead and the following vehicles is safer. 4.3. Collision risk evaluation by TTC inverse The TTC inverse is used for evaluating the unsafety of traffic state between the lead and the following vehicles under different scenarios with/without the information provision. Fig. 5 and Fig. 6 show the average TTC inverse of all participants by the scenarios, in which the horizontal axis of this figure denotes the distance from the last intersection and the vertical axis denotes the average TTC inverse. In two figures, 6 points where the TTC inverse becomes larger sharply present the place of the signalized intersection.
Author name / Transportation Research Procedia 00 (2017) 000–000 Yukimasa Matsumoto et al. / Transportation Research Procedia 27 (2017) 93–100
997
Average amount of CO2 emission(kg-CO2)
0.78 0.76
5%
0.74
**
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6%
* **
0.7 0.68
Lead vehicle with Lead vehicle with Lead vehicle without Lead vehicle without information & information & information & information & Following vehicle with Following vehicle without Following vehicle with Following vehicle without information information information information *:5% sighnificant, **:1% sighnificant compared with “no information is provided to both vehicles”
Fig. 7. CO2 emissions of following vehicles by information provision scenario
Fig. 5 shows the influence of the information provision to the lead vehicle when the following vehicle does not receive any information. The traffic state when the information is provided only to the lead vehicle becomes more danger than the state when no information is provided to both vehicles. Especially, it can be seen that the risk of traffic collisions rises sharply as the vehicle approaches the intersection. This means the information provision to only the lead vehicle worsens the traffic safety under car-following situations. Fig. 6 shows the influence of the information provision to the following vehicle when the lead vehicle receives the information. The traffic state when the information is provided to the both vehicles becomes safer than the state when the information is provided only to the lead vehicle. Especially, the traffic safety rises higher at near the intersection. From these results of the experiments, although the information provision only to the lead vehicle might raise the risk of traffic collisions, it is found that the information provision to the following vehicle can contribute to reduce the risk even under car following situations. 4.4. Amount of CO2 emission under each scenario The method proposed by Oguchi et al. (2002) is used in this study for calculating the amount of CO2 emissions base on the following vehicle movements. The amount of CO2 emissions is calculated from the data acquired in the driving experiments. Fig. 7 shows the average amounts of CO2 emissions from the following vehicles by each information provision scenario. Results of the Welch’s t-test whether a significant difference of the average amount of CO2 emissions is exists compared with the scenario where no information is provided to both vehicles are also added in the figure, and show all scenarios have significant differences of the amount of CO2 emissions. It can be seen that the mount of CO2 emissions from the following vehicle is reduced 5% when the information is provided only to the following vehicle and 3.5% when the information is provided only to the lead vehicle. Furthermore, the maximum reduction of 6% can be attained when the information is provided to both vehicles. From these results of the experiments, it can be seen that the information provision to any vehicle can reduce the amount of CO2 emissions from the following vehicle and in particular the information provision to both vehicles contribute to reduce the amount of CO2 emissions from the following vehicle most effectively. 5. Conclusions For reducing the amount of CO2 emissions from vehicles approaching a signalized intersection in car-following situation, the information provision system to a driver was proposed in this paper. The system provides mainly the accelerator-off indication, in which the vehicle could pass through the intersection or shorten the idling time if it would follow the information, because the previous study clarified that the accelerator-off indication was more effective for reducing the CO2 emissions than the recommended speed information.
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Yukimasa Matsumoto et al. / Transportation Research Procedia 27 (2017) 93–100 Author name / Transportation Research Procedia 00 (2017) 000–000
In car-following situation, the distance between the lead vehicle and the following vehicle may become shorter by the information provision so that risk of traffic collisions may be raised. Therefore, the influence of the information provision on driving behaviour in car-following situation was grasped using a 3D driving simulator. The risk of traffic collisions was measured when the information was provided and the effectiveness in reducing the amount of CO2 emissions from the following vehicle was also evaluated quantitatively. From results of the experiments with 25 participants, although the information provision only to the lead vehicle might raise the risk of traffic collision, it can be seen that the information provision to the following vehicle can contribute to reduce the risk of traffic collision even under car-following situations. Moreover, it is found that the information provision to any vehicle can reduce the amount of CO2 emissions from the following vehicle and in particular the information provision to both vehicles contributes to reduce the amount of CO2 emissions from the following vehicle most effectively. For future works, it is necessary to evaluate the effectiveness of the information provision on reducing the amount of CO2 emissions and raising traffic safety under the environment where more vehicles than two run simultaneously. 6. Acknowledgement This study has been supported by JSPS KAKENHI Great Number 15K06262. References Asadi, B., Vahidi, A., 2010. Predictive Cruise Control: Utilizing Upcoming Traffic Signal Information for Improving Fuel Economy and Reducing Trip Time. IEEE Transactions on Control Systems Technology 19, 3, 707-714. Broughtona, K. L. M., Switzera, F., Scott, D., 2007. Car Following Decisions under Three Visibility Conditions and Two Speeds Tested with a Driving Simulator. Accident Analysis and Prevention 39, 1, 106–116. Brouwer, R. F. T., Stuiver, A., Hof, T., Kroon, L., Pauwelussen, J., Holleman, B., 2015. Personalised Feedback and Eco-driving: An Explorative Study. Transportation Research C 58, 760-771. Hayward, J. C., 1972. Near-miss determination through use of a social of danger, 51st Annual Meeting of the Highway Research Board. 24-34. Kircher, k., Fors, C., Ahlstrom, C., 2014. Continuous Versus Intermittent Presentation of Visual Eco-driving Advice. Transportation Research F 24, 27-38. Kondoh, T., Yamamura, T., 2008. Identification of Visual Cues and Quantification of Drivers' Perception of Proximity Risk to the Lead Vehicle in Car-Following Situations. Journal of Mechanical Systems for Transportation and Logistics 1, 2, 170-180. Koreeda, Y., Kobayashi, M., Kato, H., 2013. Development of image-processing vehicle detector for DSSS (Driving Safety Support Systems), 20th ITS World Congress. Tokyo, Japan. Matsumoto, Y., Oshima, T., Iwamoto, R., 2014. Effect of Information Provision around Signalized Intersection on Reduction of CO2 Emission from Vehicles. Procedia - Social and Behavioral Sciences 111, 1015-1024. Matsumoto, Y., Peng, G., 2015. Analysis of Driving Behavior with Information for Passing Through Signalized Intersection by Driving Simulator. Transportation Research Procedia 10, 103-112. Niu, D., Sun, J., 2013. Eco-driving Versus Green Wave Speed Guidance for Signalized Highway Traffic: A Multi-Vehicle Driving Simulator Study. Procedia - Social and Behavioral Sciences 96, 1079-1090. Rakha, H., Kamalanathsharma, R. K., 2011. Eco-driving at signalized intersections using V2I communication, 14th International IEEE Conference on Intelligent Transportation Systems. 341-346. Sueki, T., Harada, T., Yamamoto, S., Kamata, K., 2009. The expansion of driving safety support system by utilizing the road waves, 16th World Congress on ITS. Stockholm, Sweden. Taniguchi, Y., Oota, T., Kato, H., 2013. Development and verification tests of driving safety support systems utilizing ITS radio system, 20th ITS World Congress. Tokyo, Japan. Tielert, T., Killat, M., Hartenstein, H., Luz, R., Hausberger, S., Benz, T., 2010. The Impact of traffic-light-to-vehicle communication on fuel consumption and emissions, Internet of Things (IOT), IEEE. 1-8. Yoshizawa, R., Shiomi, Y., Uno, N., Iida, K., Yamaguchi, M., 2012. Analysis of Car-following Behavior on Sag and Curve Sections at Intercity Expressways with Driving Simulator. International Journal of Intelligent Transportation Systems Research 10, 2, 56–65.
ScienceDirect Available online at www.sciencedirect.com
Transportation Research Procedia 00 (2017) 000–000
ScienceDirect
www.elsevier.com/locate/procedia
Transportation Research Procedia 27 (2017) 93–100 www.elsevier.com/locate/procedia
20th EURO Working Group on Transportation Meeting, EWGT 2017, 4-6 September 2017, Budapest, Hungary
Effect of Information Provision to Following Vehicle on Reducing Amount of CO2 Emissions and Safety Drive Yukimasa MATSUMOTO a, *, Shogo ISHIGURO a a
Department of Civil Engineering, Meijo University, Nagoya 468-8502, Japan
Abstract For reducing the amount of CO2 emissions from vehicles approaching a signalized intersection in car-following situation, the information provision system to a driver is proposed in this paper. The system provides mainly the accelerator-off indication, in which the vehicle could pass through the intersection or shorten the idling time if it would follow the information. In carfollowing situation, the distance between the lead vehicle and the following vehicle might become shorter by the information provision so that risk of traffic collisions may be raised. Therefore, the influence of the information provision on driving behavior in car-following situation is grasped using a driving simulator in this paper. The risk of traffic collisions is measured by the TTC (time to collision) inverse when the information is provided, and the effectiveness in reducing the amount of CO2 emissions from vehicle is also evaluated quantitatively. From results of the experiments with 25 participants, although the information provision only to the lead vehicle might raise the risk of traffic collision, it can be seen that the information provision to the following vehicle can contribute to reduce the risk of traffic collision even under car-following situations. Moreover, it can be seen that the information provision to both vehicles reduces the amount of CO2 emissions from the following vehicle most effectively. © 2017 The Authors. Published by Elsevier B.V. © 2017 The Authors. Published by Elsevier B.V. Peer-review EURO Working Working Group Group on on Transportation Transportation Meeting. Meeting. Peer-review under under responsibility responsibility of of the the scientific scientific committee committee of of the the 20th 20th EURO Keywords: CO2; Signalized intersection; Driving simulator; Accelerator-off; Traffic signal information; Car-following
1. Introduction Various information on traffic conditions such as the level of traffic congestion, a travel time of each vehicle and also vehicle movements has been available by the advantage of the ITS technologies. In Japan, the Driving Safety
* Corresponding author. Tel.: +81-52-832-1151; fax: +81-52-832-1179. E-mail address: [email protected] 2214-241X © 2017 The Authors. Published by Elsevier B.V. Peer-review under responsibility of the scientific committee of the 20th EURO Working Group on Transportation Meeting.
2352-1465 © 2017 The Authors. Published by Elsevier B.V. Peer-review under responsibility of the scientific committee of the 20th EURO Working Group on Transportation Meeting. 10.1016/j.trpro.2017.12.137
94 2
Yukimasa Matsumoto et al. / Transportation Research Procedia 27 (2017) 93–100 Author name / Transportation Research Procedia 00 (2017) 000–000
Support System (DSSS) based on the vehicle-to-infrastructure communication system (V2I) has been actually put into operation in 2011, aiming to prevent traffic accidents by delivering the information on vehicles and pedestrians approaching the upcoming intersection (Koreeda et al., 2013; Taniguchi et al., 2013). The Signal Recognition Enhancement System based on traffic signal information has also been operated, which prevents the driver overlooking the red traffic signal ahead (Sueki et al., 2009). In the U.S., the real-time traffic light information can be sent to a vehicle by the advanced traffic management system from December 2016 as one of the V2I applications. The providing traffic signal information has the potential for improving traffic congestion and traffic accidents. Moreover, smoothing traffic flow is expected to contribute for reducing the amount of CO2 emissions from vehicles. Information provision based on upcoming traffic signal information to a driver has attracted attention from many researchers. Asadi and Vahidi (2010) propose an algorithm to schedule an optimal speed trajectory for reducing idling time at stop line using upcoming traffic signal information. Tielert et al. (2010) evaluated traffic-light-tovehicle communication for reducing fuel consumption and emissions by large-scale simulations. Rakha and Kamalanathsharma (2011) present a framework to enhance vehicle fuel consumption efficiency while approaching a signalized intersection through the provision of signal phase and timing information. Matsumoto et al. (2014) simulated vehicle movements approaching a signalized intersection under information provision using a microscopic traffic simulation based on observed actual vehicle movements. While a microscopic traffic flow simulation evaluates the effectiveness of the information provision based on the upcoming traffic signal to a driver, the responses by each driver are also grasped using a driving simulator when the traffic signal information is provided. Niu and Sun (2013) evaluated the effectiveness of the green wave guidance strategy and the eco-driving speed guidance strategy with a multi-vehicle driving simulator. Kircher et al. (2014) investigated the difference of effects between intermittent and continuous eco-driving speed information with a truck driving simulator. Brouwer et al. (2015) tailored different types of the display to present eco-driving speed feedback with a truck driving simulator. These studies indicate that providing the speed information is significantly efficient to reduce the amount of CO2 emissions. Matsumoto and Peng (2015) also showed that providing the information had a significant effect on reducing CO2 emissions from vehicles approaching a signalized intersection. Especially, it was also found that more effective information was the accelerator-off indication than the recommended speed information from the experiments with a driving simulator. However, these studies mainly analyze the individual behavior of the driver regardless the interaction between the lead and the following vehicles. Kondoh and Yamamura (2006) clarified that drivers' perception of proximity risk in car-following situation was strongly correlated with the time headway and the time to collision using a driving simulator. Broughtona et al. (2007) employed a driving simulator to measure the behavior of drivers following a lead vehicle under three visibility conditions. Yoshizawa et al. (2012) analyzed the influence of road alignments and the lead vehicle behavior on car-following behavior in a driving simulator experiment. These studies suggest that a driving simulator is useful and efficient for measuring driving behavior in car-following situation. Therefore, we use a fixed-base 3D driving simulator for exploring the information provision in car-following situation. By previous research (Matsumoto and Peng, 2015), we developed the information provision system for reducing the amount of CO2 emissions from a vehicle approaching a signalized intersection and clarified that the accelerator-off indication is more effective for reducing it than the recommended speed information. Thus, the accelerator-off indication is mainly provided to the lead and following vehicles in this study and the influence of the information provision on driving behaviour in car-following situation is grasped using a driving simulator. Especially the risk of traffic collisions is measured when the information is provided to a driver and the effectiveness in reducing the amount of CO2 emissions from vehicle is also clarified quantitatively. 2. Information Provision System 2.1. Outline of information provision system For decreasing unnecessary vehicle movements such as rapid deceleration and long idling, two types of the provided information are designed in this study. One is the accelerator-off indication, which informs a driver of releasing the accelerator pedal for passing through the upcoming signalized intersection or for shortening the idling time during a red signal at the intersection. Another is the recommended speed information.
Yukimasa Matsumoto et al. / Transportation Research Procedia 27 (2017) 93–100 Author name / Transportation Research Procedia 00 (2017) 000–000
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Fig. 1. Time-space diagram of vehicle approaching intersection
ds Distance from intersection
Fig. 2. Vehicle movement with information provision
A vehicle can pass through the upcoming signalized intersection as long as the vehicle runs at the recommended speed provided by the system. The recommended speed which is equal to the current speed is only provided when the vehicle can pass through the upcoming intersection with the current running speed in this study. 2.2. Concept to provide information to reduce unnecessary vehicle movement Fig. 1 shows a time-space diagram of vehicles approaching a signalized intersection, in which the horizontal axis of this figure denotes the time elapse and the vertical axis denotes the distance from the upcoming signalized intersection. The color bar on the horizontal axis indicates the signal status. The background color shows the signal state when the vehicle arrives at the intersection with a constant speed. In this study, for convenience, a yellow phase is regarded as same as a red phase so that vehicles stop when the traffic signal is yellow. In this figure, the vehicle C1 stops at the intersection if the vehicle runs at the constant speed. A green signal starts after tgr from the time when the vehicle passes the distance ds from the intersection and the next red signal starts after trd. For this case, the information to reduce the current speed is provided at ds. If the vehicle C1 would follow the information, it could pass through the intersection without stopping at red signal like a broken line. The vehicle C2 approaches the intersection at the constant speed and will pass through the intersection during green time. For this case, no information is provided. On the other hand, the vehicle C3 approaches the intersection during green signal and will stop at the intersection due to a red signal. For this case, the vehicle C3 could pass through the intersection like a dashed line if it would accelerate. However, such behavior may raise a risk of traffic accidents. Therefore, the vehicle is informed of reducing the current speed in advance by the proposed system like a broken line so that it will shorten the idling time at the intersection during a red signal. 2.3. Method of information provision The lower part of Fig. 2 shows a time-space diagram when the vehicle approaches the signalized intersection from the distance ds with/without information. The upper part shows the speed of the vehicle. The vehicle running at ds will reach the upcoming intersection after time tc during red signal without decelerating like a dotted line. However, if the vehicle would decelerate by releasing the accelerator pedal, it could pass through the intersection at tf during green signal like a broken line. In this figure, ds, tc and tf denote the location of the vehicle from the upcoming signalized intersection, the forecasted arrival time with the current running speed vs and the forecasted arrival time at the intersection with releasing the accelerator pedal, respectively. The deceleration rate during releasing the accelerator pedal is assumed to be a constant of af and td is the reaction time. The dm is a marginal distance, which mainly includes the queue length of the vehicles during red signal and a marginal distance which corresponds to a time lag between the start of a green signal and the arrival time at the intersection. This marginal distance helps the vehicle pass through the intersection safely because the traffic signal turns to green slightly prior to the vehicle arrival at the intersection. If this is set to be 0, the traffic signal sometimes turns to green from red at the moment the vehicle reaches the intersection, which leads to heavy braking. From this figure, tf is calculated as:
Author name / Transportation Procedia 00 (2017) 000–000 Yukimasa Matsumoto et al. / Research Transportation Research Procedia 27 (2017) 93–100
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40km/h (a) Accelerator-off Upcoming intersection is passable at green signal
(b) Accelerator-off Idling time at upcoming intersection is shortened
(c) Recommended speed Upcoming intersection is passable at green signal
Fig. 3. Information displayed on the screen
tf =
a f t d − vs + vs2 + 2a f (d s − d m − t a vs ) af
.
(1)
For passing through the intersection by the accelerator-off, tf must be larger than tgr, where tgr means the remaining red time until the signal will turn to green, and then the following relations can be obtained:
t c < t gr < t f .
(2)
Even if tf is less than tgr, the accelerator-off indication is also provided for shortening the idling time during red signal in this study. If the accelerator-off indication is provided to the vehicle running at enough low speed, the vehicle reaches the intersection much later than the time the signal turns to green, tgr. This movement is also regarded as unnecessary because the vehicle continues to decelerate by releasing the accelerator pedal in spite of green signal ahead. Therefore, the current speed of the vehicle is provided as the recommended speed at the moment the vehicle can pass through the intersection with the current speed like the solid curved line in Fig. 2. 2.4. Information provision to following vehicle The vehicle receiving the information begins to decelerate from ds which has a certain distance from the upcoming intersection. In this case, the driver of the following vehicle might be surprised by unexpected deceleration of the lead vehicle without an advance notice. Moreover, the distance between the lead vehicle and the following vehicle becomes shorter so that risk of traffic collisions may be raised. Therefore, the information is also provided to the following vehicle by the same method explained above in this study. However, when the distance between the lead vehicle and the following vehicle is short naturally, the risk of traffic collisions may be raised. Furthermore, when the following vehicle runs with higher speed than the lead vehicle, the distance between the two vehicles becomes shorter even if the accelerator-off indication is provided to the following vehicle. Therefore, when the time headway between two vehicles is shorter than 2 sec., any information is disappeared in the proposed information system. The vehicles with the same speed and the lower speed of the lead vehicle are provided the information as same as the way for the lead vehicle. 3. Experiments using fixed-base 3D driving simulator 3.1. Experimental course and design of information The information provision system proposed in this study is introduced in a fixed-base 3D driving simulator which is composed of a seat, a steering wheel, pedals, speakers and three 42” monitors having 120° field of view including side view of mirror images. The 3D virtual driving environment is generated by UC-Win/Road. The course of about 4,500m created for this driving experiment includes 6 signalized intersections and 1 gentle curve section for
Yukimasa Matsumoto et al. / Transportation Research Procedia 27 (2017) 93–100 Author name / Transportation Research Procedia 00 (2017) 000–000
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generating driving unmonotonous. The course is flat having two lanes for both directions in which the lane width is set to be 3.25 m. A speed limit of the course is set to be 40 km/h. The information provision system displays the information on the screen of the driving simulator based on the location and the speed of the current vehicle, and the remaining time of the current signal phase. Fig. 3 shows the 3 types of the displayed information on the screen during the driving experiment. The left image signifies the accelerator-off indication, which is displayed when the upcoming intersection can be passable at green signal by just releasing the accelerator pedal. The middle image signifies the accelerator-off indication, which is displayed when the vehicle cannot pass through the upcoming intersection by releasing the accelerator pedal but can shorten the idling time. The right image signifies the recommended speed, which is appeared at the moment when the running speed is decreased enough to pass through the upcoming intersection with the current running speed. The displayed recommended speed is rounded off in unit of 5 km/h by the system considering driver’s recognition time and safety. At every time when any information is provided, the notice tone of “dingdong” is sounded and makes a driver noticed that any information is provided on the screen. 3.2. Using recorded vehicle as lead vehicle The driving experiments in this study are designed under the situation where a lead vehicle and the following vehicle run simultaneously in order to grasp the differences of the following driving behaviors with/without information provision to a lead vehicle and the following vehicle. The vehicle movements of the lead vehicle for all participants are therefore desired to be identical to eliminate the influence of the difference of the lead vehicle movements. Thus the vehicle movements recorded by the previous experiment where only one vehicle runs on the same course are used as the lead vehicle movements. There are two types of the lead vehicle movement, the movements with information provision and without information provision. 3.3. Driving experiment of vehicle following The participants were 25 people with a driving license ranging from 20 to 60 years old. Driving operation of the 3D driving simulator seems to be different from the actual vehicle driving. Therefore, each participant was asked to practice the driving on a simpler course for about 3 minutes to get used to the simulator operation. After that, each participant started to drive after the lead vehicle and follow it. Each participant drove on the experimental course 4 times. The experiments include 4 scenarios combined by the information provision (with/without information provision) and the vehicle types to be provided the information (the lead vehicle and the following). The participants were instructed to 1) drive as if they normally drove an actual road, 2) obey strictly the traffic signals unless they judged not to stop safely at yellow signal, 3) go straight at the intersection and 4) follow the provided information. The speed limit of 40 km/h was also informed in advance. The participants were asked to redo the driving experiment if they failed to comply with these instructions. 4. Results of driving experiment of following vehicle The influences of the information provision on the driving behavior of the following vehicle are grasped here. Especially, in the case where the information is provided to the lead vehicle, it is conceivable that the headway between the lead vehicle and the following vehicle is shortened due to unexpected speed change of the lead vehicle by the provided information and it is likely to raise the risk of traffic collisions. Therefore, it is clarified whether traffic safety is maintained with enough headway even if the information is provided to the lead vehicle. Moreover, the influence of the information provision on CO2 emissions from the vehicle is quantitatively evaluated based on the results of the driving experiments. 4.1. Comparing vehicle behavior of following vehicle
Yukimasa Matsumoto et al. / Transportation Research Procedia 27 (2017) 93–100 Author name / Transportation Research Procedia 00 (2017) 000–000 Average Running speed (km/h)
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Fig. 4. Average running speed of following vehicle by scenario
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Fig. 5. Average 1/TTC when following vehicle without information
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Fig. 6. Average 1/TTC when lead vehicle with information
Fig. 4 shows the average running speed of all participants of the following vehicles for the entire course by each scenario. In this figure, the horizontal axis denotes the distance from the last signalized intersection (m) and the vertical axis denotes the average vehicle running speed (km/h) of the following vehicle. It is obvious that the running speed is reduced more as the vehicle approaches the signalized intersection in all scenarios where the information is provided to any vehicle than the running speed without the information provision to two vehicles. However, in the case where the information is provided to the lead vehicle, there is a possibility to shorten the headway between the lead vehicle and the following vehicle. Therefore, it is clarified whether the behavior of the following vehicle is safe by TTC (time to collision) index in the next section. 4.2. TTC inverse The TTC index defined by Hayward (1972) is an index indicating the time required for two vehicles to collide if they continue at their present speed and the same path. In this study, the TTC inverse is used to express unsafety level because the TTC index sometimes takes infinity. The smaller TTC inverse means the traffic state between the lead and the following vehicles is safer. 4.3. Collision risk evaluation by TTC inverse The TTC inverse is used for evaluating the unsafety of traffic state between the lead and the following vehicles under different scenarios with/without the information provision. Fig. 5 and Fig. 6 show the average TTC inverse of all participants by the scenarios, in which the horizontal axis of this figure denotes the distance from the last intersection and the vertical axis denotes the average TTC inverse. In two figures, 6 points where the TTC inverse becomes larger sharply present the place of the signalized intersection.
Author name / Transportation Research Procedia 00 (2017) 000–000 Yukimasa Matsumoto et al. / Transportation Research Procedia 27 (2017) 93–100
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Average amount of CO2 emission(kg-CO2)
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Lead vehicle with Lead vehicle with Lead vehicle without Lead vehicle without information & information & information & information & Following vehicle with Following vehicle without Following vehicle with Following vehicle without information information information information *:5% sighnificant, **:1% sighnificant compared with “no information is provided to both vehicles”
Fig. 7. CO2 emissions of following vehicles by information provision scenario
Fig. 5 shows the influence of the information provision to the lead vehicle when the following vehicle does not receive any information. The traffic state when the information is provided only to the lead vehicle becomes more danger than the state when no information is provided to both vehicles. Especially, it can be seen that the risk of traffic collisions rises sharply as the vehicle approaches the intersection. This means the information provision to only the lead vehicle worsens the traffic safety under car-following situations. Fig. 6 shows the influence of the information provision to the following vehicle when the lead vehicle receives the information. The traffic state when the information is provided to the both vehicles becomes safer than the state when the information is provided only to the lead vehicle. Especially, the traffic safety rises higher at near the intersection. From these results of the experiments, although the information provision only to the lead vehicle might raise the risk of traffic collisions, it is found that the information provision to the following vehicle can contribute to reduce the risk even under car following situations. 4.4. Amount of CO2 emission under each scenario The method proposed by Oguchi et al. (2002) is used in this study for calculating the amount of CO2 emissions base on the following vehicle movements. The amount of CO2 emissions is calculated from the data acquired in the driving experiments. Fig. 7 shows the average amounts of CO2 emissions from the following vehicles by each information provision scenario. Results of the Welch’s t-test whether a significant difference of the average amount of CO2 emissions is exists compared with the scenario where no information is provided to both vehicles are also added in the figure, and show all scenarios have significant differences of the amount of CO2 emissions. It can be seen that the mount of CO2 emissions from the following vehicle is reduced 5% when the information is provided only to the following vehicle and 3.5% when the information is provided only to the lead vehicle. Furthermore, the maximum reduction of 6% can be attained when the information is provided to both vehicles. From these results of the experiments, it can be seen that the information provision to any vehicle can reduce the amount of CO2 emissions from the following vehicle and in particular the information provision to both vehicles contribute to reduce the amount of CO2 emissions from the following vehicle most effectively. 5. Conclusions For reducing the amount of CO2 emissions from vehicles approaching a signalized intersection in car-following situation, the information provision system to a driver was proposed in this paper. The system provides mainly the accelerator-off indication, in which the vehicle could pass through the intersection or shorten the idling time if it would follow the information, because the previous study clarified that the accelerator-off indication was more effective for reducing the CO2 emissions than the recommended speed information.
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Yukimasa Matsumoto et al. / Transportation Research Procedia 27 (2017) 93–100 Author name / Transportation Research Procedia 00 (2017) 000–000
In car-following situation, the distance between the lead vehicle and the following vehicle may become shorter by the information provision so that risk of traffic collisions may be raised. Therefore, the influence of the information provision on driving behaviour in car-following situation was grasped using a 3D driving simulator. The risk of traffic collisions was measured when the information was provided and the effectiveness in reducing the amount of CO2 emissions from the following vehicle was also evaluated quantitatively. From results of the experiments with 25 participants, although the information provision only to the lead vehicle might raise the risk of traffic collision, it can be seen that the information provision to the following vehicle can contribute to reduce the risk of traffic collision even under car-following situations. Moreover, it is found that the information provision to any vehicle can reduce the amount of CO2 emissions from the following vehicle and in particular the information provision to both vehicles contributes to reduce the amount of CO2 emissions from the following vehicle most effectively. For future works, it is necessary to evaluate the effectiveness of the information provision on reducing the amount of CO2 emissions and raising traffic safety under the environment where more vehicles than two run simultaneously. 6. Acknowledgement This study has been supported by JSPS KAKENHI Great Number 15K06262. References Asadi, B., Vahidi, A., 2010. Predictive Cruise Control: Utilizing Upcoming Traffic Signal Information for Improving Fuel Economy and Reducing Trip Time. IEEE Transactions on Control Systems Technology 19, 3, 707-714. Broughtona, K. L. M., Switzera, F., Scott, D., 2007. Car Following Decisions under Three Visibility Conditions and Two Speeds Tested with a Driving Simulator. Accident Analysis and Prevention 39, 1, 106–116. Brouwer, R. F. T., Stuiver, A., Hof, T., Kroon, L., Pauwelussen, J., Holleman, B., 2015. Personalised Feedback and Eco-driving: An Explorative Study. Transportation Research C 58, 760-771. Hayward, J. C., 1972. Near-miss determination through use of a social of danger, 51st Annual Meeting of the Highway Research Board. 24-34. Kircher, k., Fors, C., Ahlstrom, C., 2014. Continuous Versus Intermittent Presentation of Visual Eco-driving Advice. Transportation Research F 24, 27-38. Kondoh, T., Yamamura, T., 2008. Identification of Visual Cues and Quantification of Drivers' Perception of Proximity Risk to the Lead Vehicle in Car-Following Situations. Journal of Mechanical Systems for Transportation and Logistics 1, 2, 170-180. Koreeda, Y., Kobayashi, M., Kato, H., 2013. Development of image-processing vehicle detector for DSSS (Driving Safety Support Systems), 20th ITS World Congress. Tokyo, Japan. Matsumoto, Y., Oshima, T., Iwamoto, R., 2014. Effect of Information Provision around Signalized Intersection on Reduction of CO2 Emission from Vehicles. Procedia - Social and Behavioral Sciences 111, 1015-1024. Matsumoto, Y., Peng, G., 2015. Analysis of Driving Behavior with Information for Passing Through Signalized Intersection by Driving Simulator. Transportation Research Procedia 10, 103-112. Niu, D., Sun, J., 2013. Eco-driving Versus Green Wave Speed Guidance for Signalized Highway Traffic: A Multi-Vehicle Driving Simulator Study. Procedia - Social and Behavioral Sciences 96, 1079-1090. Rakha, H., Kamalanathsharma, R. K., 2011. Eco-driving at signalized intersections using V2I communication, 14th International IEEE Conference on Intelligent Transportation Systems. 341-346. Sueki, T., Harada, T., Yamamoto, S., Kamata, K., 2009. The expansion of driving safety support system by utilizing the road waves, 16th World Congress on ITS. Stockholm, Sweden. Taniguchi, Y., Oota, T., Kato, H., 2013. Development and verification tests of driving safety support systems utilizing ITS radio system, 20th ITS World Congress. Tokyo, Japan. Tielert, T., Killat, M., Hartenstein, H., Luz, R., Hausberger, S., Benz, T., 2010. The Impact of traffic-light-to-vehicle communication on fuel consumption and emissions, Internet of Things (IOT), IEEE. 1-8. Yoshizawa, R., Shiomi, Y., Uno, N., Iida, K., Yamaguchi, M., 2012. Analysis of Car-following Behavior on Sag and Curve Sections at Intercity Expressways with Driving Simulator. International Journal of Intelligent Transportation Systems Research 10, 2, 56–65.