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Driver Reaction To Unreliable Traffic Information

While transportation engineers would like to provide reliable traffic information to motorists, the highway system, at times, has operating situations that make it difficult to achieve this goal. Congestion, delays, and accidents can sometimes make information provided to motorists unreliable when it is received. Such unreliability may cause drivers to discount, or even ignore, traffic messages displayed on programmable road signs or other information–delivery systems. Currently, there are few results based on empirical studies to guide the highway engineer concerning what level of accuracy is needed to gain driver acceptance and trust. In some domains, a single bad experience is enough to prevent people from using a service or machine again. For example, few people continue to put coins into a defective vending machine. Traffic information systems must be sufficiently reliable so that motorists continue to accept and use the systems. The goal of this research is to acquire data that the highway engineer can use to select a level of information reliability that will maintain the driver's acceptance and use of route guidance information.

Method

The Battelle Route Guidance Simulator was used to collect data in two experiments. This simulator consists of two linked 486 computers driving two displays (figure 1). One display provided a real–time video of Seattle traffic that had been digitized and stored on hard disks. The other display featured a map of Seattle with a touch screen. The driver used this screen to obtain traffic information and to select traffic links. A moving dot represented the driver's vehicle. When the dot entered a traffic link, the appropriate video was rapidly retrieved from the hard disk and displayed in real time on the other monitor.

In the first experiment, 26 links were displayed, giving the driver 29 possible routes between the origin, Westlake Center in downtown Seattle, and the destination, Bellevue Square Mall. The second experiment used 31 links and 33 possible routes. These routes traversed a variety of roads, including congested city streets, four–lane State roads, and an interstate highway in an urban setting. Links had either light traffic (level of service A) or heavy traffic (level of service E or F). Due to the topography of Seattle, the driver must cross Lake Washington to reach the destination. Since there are only two bridges across the lake, the experimenters retained some control over traffic congestion encountered by the driver regardless of the route selected. Simulated trips took about 22 minutes in light traffic and 37 minutes in heavy traffic.

In the first experiment, 48 drivers were tested; and in the second experiment, 24 were tested (table 1). All drivers were familiar with the Seattle area and drove on Seattle highways at least twice per week.

The driver's goal was to reach the destination as quickly as possible by choosing links that he/she thought had the least amount of traffic and the shortest travel time. A penalty was assessed for selecting links that were not optimal. The maximum penalty per trip was $13.59. In Experiment 1, drivers were charged $0.10 to query a link. Link information was free in Experiment 2. Furthermore, an additional penalty was assessed whenever a driver encountered heavy traffic. These penalties simulated the effects of traffic delays on the road.

Results

Figure 2 shows how the penalty changed with the reliability of traffic information. In the first experiment, traffic information whether traffic flow on the selected link was light or heavy was either 100 percent or 77 percent accurate. In the second experiment, traffic information was either 100 percent, 71 percent, or 43 percent accurate. In both experiments, drivers reached their destination faster and had lower penalties when traffic information was accurate. Thus, drivers were able to benefit from using the traffic information system. One possible explanation for the results is that drivers are only willing to purchase or to use traffic information when it is 100 percent accurate. However, in the first experiment, drivers in both reliability conditions spent the same amount of money for information. In the second experiment, information was free. Therefore, this possible explanation is not satisfactory, and the benefit of using the traffic information system is real.

Figure 3 shows how driver trust in the simulated traffic information system, rated on a scale from zero to 100, changed over the four trials of the first experiment. For the first two trials, when information was 100 percent accurate, trust increased. But for the last two trials, when information was 77 percent accurate, trust decreased after participants drove over inaccurate links. However, trust was restored by subsequent accurate links.

Figure 4 shows driver trust for the second experiment. Trust was high for the first two trials when information was 100 percent accurate. Trust decreased on the last two trials, especially for the less accurate (43 percent) condition. Again, trust was restored for links on which accurate information was presented. Furthermore, the trust decrement relative to 100 percent accurate information was small for the 71 percent condition.

Study Implications

The following points may be useful for highway engineers who provide traffic information to drivers:

• Drivers use and benefit from accurate traffic information.
• Information that is less than 100 percent accurate can be useful.
• Driver trust in an unreliable system recovers when accurate information is presented, but the recovery is not always complete.
• Traffic information reliability above 70 percent is recommended.

For More Information

This research was conducted by Battelle.

Form more information, contact:

M. Joseph Moyer
Engineering Research Psychologist, HSR–30
703 285–2008.

FHWA-RD-95-128