Impact of Crash Fact Signs on Driver Speeding Behavior: Evidence from the Sahrawi Highway

1. Review and Analysis of Related Work

Speed limit is considered one of the essential components in providing safe roads. Most of the existing research has shown that higher speed limits on highways result in higher rates of fatal crashes. The latest research conducted in the United States that studied fatal crashes on rural interstates showed that states with 70 -75 mph speed limits faced more fatal crashes than states with 60 or 65 mph by around 31-54 percent, respectively [1,2,3,4,5,6,7,8,9,10,11,12,13,14,15]. Taylor [2] studied the impact of increased speed limits on the 1500 miles by conducting crash severities analysis. The study found a 10.5 percent increase in crash occurrences on roads where the speed limits were raised. The potential impact on the anticipated speed limit changed from 55 to 65 mph on non-freeway was studied by Gates et al.[3] . The study predicted an annual increase of 40.3 fatal crashes, 74.6 incapacitating crashes, and 631.8 property damage only.

Digital message signs which are also referred as dynamic message signs (DMS), variable message signs (VMS) or changeable message signs (CMS) are the vital part of the advanced traveller information systems (ATIS) that disseminates various real-time travel information to the road users. The DMS are digital devices that can display one or more alternative messages. The DMS usually displays traffic, operational, regulatory, warning, and guidance information. Specific examples of the information displayed on DMS include traffic diversion, travel time, congestion, upcoming roadwork, lane closures, incidences such as accidents and inclement weather, speed regulations, special events, and safety-related messages such as seatbelt usage campaigns [4,5]. The information provided by DMS such as incidences and route alternatives enhances the even distribution of traffic in the roadway network, thus improving the overall performance of the traffic system and reducing potential traffic delays [6]. The Manual on Uniform Traffic Control Devices (MUTCD), Chapter 2L, stipulates various aspects of DMS, which include the descriptions, applications, legibility design, message length and units of information and installation of permanent DMS [4]. The MUTCD refers readers to the Federal Highway Administration (FHWA)’s Changeable Message Sign Operation and Messaging Handbook, which provides DMS operational policies [5]. Also, each state Department of Transportation DOT has guidelines that supplement the DMS design and operational practices provided by the FHWA manuals and handbooks. Such guidelines and policies include how each message type should be posted, a list of message types that are prohibited and procedures on how message types are designed and approved [7].

A number of studies have been conducted to explore the effectiveness of DMS in terms of its design and the way it is operated. The design aspect includes installation details of DMS technologies such as vertical and horizontal location, size, font, color, light intensity and units of information. Operational factors include proximity of the DMS location relative to the specific event, when the message is displayed and message display duration. The most important measure of DMS effectiveness is the travelers’ compliance rate to the specific instructions being communicated (displayed) by the DMS. It is challenging to assess this measure quantitatively as it is hard to associate specific driver responses with the DMS information in a complex driving environment. However, various methods have been used to qualitatively and quantitatively estimate the effectiveness of DMS devices. Each study that evaluated the effectiveness of DMS used one or more of the following methods: stated preference survey, driving simulation, analysis of traffic flow, vehicle speeds or travel time data. Studies that carried out a cost-benefit analysis of DMSs utilized results from surveys, driving simulator or before-and-after studies of traffic flows to quantify the benefits or disbenefits of DMS relative to DMS installation and operational costs. However, benefit-cost analysis of DMS is very challenging as it is difficult to isolate the benefits of DMS from other sources of traveler route information such as smartphones, newspapers and TV [8].

There are different types of tools that are used in traffic safety research to gather driver behavior information. Driving simulators are considered one of the most important sources to acquire such information. Driving simulators have many benefits over other empirical methods because they allow for control over variables under study and provide safe operational environments.

The behavior of drivers with different skills and characteristics in a certain area can be analyzed on disaggregate basis by using driving simulator capability. Bella [9] examined the speed research validity of the driving simulator by copying a real work zone located in a driving simulator environment. 35 participants were recruited to test the scenario; it was found that the speeds were lower in the driving simulator compared to the field measurements. Nevertheless, the two speeds in the driving simulator and the field were not statically different. Bella [9] concluded that whenever the maneuver become simpler in the driving simulator, the validity of speed measurement improved.

[10] conducted a study to validate the driving simulator on road safety and highway geometric design based on continuous speed profiles. The study recruited 28 subjects; each participant had 30-km drives. The author concluded that simpler geometrics provide a larger difference in average speeds between the simulator and field data, and that was because of the difference in realized risk.

Bella [11] studied a driver’s speed behavior on curves to test the speed perception differences between real-life speed data and driving simulator data. 35 participants were recruited, based on annual driving distance, and driving experience, to ride the driving simulator on-road scenarios. The author found that there is no statistical difference in speed behavior between the driving simulator and reference data in the two types of curves that were studied.

In the literature, however, there is no research has been conducted to investigate the effectiveness of DWCFS on the Speeding behavior on Sahrawi Highway. Therefore, this project aims to behaviourally investigate the DWCFS effectiveness and public perception. A driving simulator non- will be used to capture and link actual drivers’ responses with performance with respect to various DWCFS designs. Subsequently, traffic flow and speed data measures will be performed to measure speed profiles for Sahrawi highways and determine the suggested location for DWCFS.