Simulated Highway Lane Change Warning System (HLCWS) showed a potential of significantly reducing collisions caused by lane changes.

Vehicle infrastructure integration (VII) based road-condition warning system for highway collision prevention

Summary Information

The Vehicle Infrastructure Integration (VII) program was a major ITS initiative designed to create an enabling communication infrastructure that would open up a wide range of safety applications. The road-condition warning system was an application of VII technology, meant to provide drivers with real-time information about unexpected roadway conditions ahead, such as accidents, speed reduction zones, hazardous weather conditions. This study investigated three different types of warning systems: Rural Highway Driver Warning Systems (RHDWS), Highway Lane Change Warning Systems (HLCWS) and Work Zone Driver Warning Systems (WZDWS), These systems were designed and tested in the designed highway scenarios by driving simulator experiments. The experimental results show that all three systems can reduce the crashes in the designed environment.

The Highway Lane Change Warning System (HLCWS) is designed for preventing collisions associated with lane changes. The designed system is tested on an urban highway with heavy traffic volume and high speed limits by driving simulator experiments. The test results show that this system will help drivers avoid unsafe lane changes and that the system has the potential to reduce collisions. According to a survey of the tested drivers, the system is easy for drivers to use and helpful in making safe lane changes.


The HLCWS system was tested by conducting driving simulator experiments. For the HLCWS, two driving scenarios were created: (1) the baseline scenario: driving a vehicle without any warning system on a three-lane urban highway and (2) the study scenario: driving a vehicle with an on-board HLCWS on the same urban highway.

After conducting the driving simulation experiments, the participants’ driving performances under different driving scenarios were evaluated. In this study, the following measures of effectiveness (MOE) were used for analyzing the drivers’ performances.
  • Number of Lane Change Collisions
  • Number of critical events defined by Time-to-Collision (TTC)
  • Number of critical events defined by deceleration rate


For comparing the MOEs from both driving scenarios, the paired ttest, a statistical method for comparing the means of two groups of related samples, was used. The results show:
  • The average number of lane change collisions in the study scenario were significantly less than the number in the baseline scenario (t = 4.54, P < 0.0001). This result indicated that the HLCWS can significantly reduce collisions (up to 79%) caused by lane changes.
  • The average numbers of two critical events were all significantly reduced (by 33% and 60%) in the study scenario compared with the numbers in the baseline scenario (Pvalues are all less than 5 percent). This result further proved that the HWLCS helped drivers make lane changes safely and that it could significantly reduce the risk of accidents associated with lane changes.

After the experiments, the participants were surveyed to obtain their opinions of the driving warning system.
  • Survey results showed overall more than 85 percent of participants stated that the HLCWS was "Helpful" or better (23 percent extremely helpful, 43 percent very helpful, 20 percent helpful).
  • When asked whether the participants were used to the warning system, 63 percent reported that the system was easy for them to accommodate to and 10 percent reported that it was hard. This result indicates that the HLCWS would be accepted by most drivers.
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Vehicle infrastructure integration (VII) based road-condition warning system for highway collision prevention

Vehicle infrastructure integration (VII) based road-condition warning system for highway collision prevention
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Yi Qi, Xin Chen, Lane Yang, Bin Wang and Lei Yu
Southwest Region University Transportation CenterTexas Transportation InstituteTexas A&M University SystemCollege Station, Texas 77843-3135
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