## 2 Related Work
It is also difficult for a wired cable system to measure multiple lanes of traffic. The last types of evaluation systems can be designed with helps of other sensors such as Passive Infrared (PIR) or magneto-resistive (MR) sensors [20]. A PIR detects the radiation emitted from vehicles and road surfaces, since any object with a temperature higher than absolute zero emits radiation in the far IR part of the electromagnetic spectrum depending on the object's surface temperature, size and structure [20]. However, PIR performance is highly degraded by the environmental factors such as sunlight, fog, rain, and atmosphere, and the overall speed accuracy measured on a PIR sensor is reported as 90% [20], which is quite poor for an evaluation system. Recently, a magneto-resistive senor has been utilized in a vehicle detection system [21, 22]. As long as simple self-calibration and detection algorithms are adopted, it can detect the disturbance of the Earth's magnetic field caused by vehicles despite slow changes in the ambient magnetic field caused by environmental factors. Since the MR sensor is small and draws a low average current with the help of duty cycling or other wakeup sensors such as an optical sensor [23], it is adopted in wireless sensor nodes. Some papers report the research results on WSN applications to intelligent transportation systems for safe driving, traffic monitoring and control, but their main concerns are early warning of potential dangerous situations [24], signal control with traffic information gathered by in-vehicle sensor nodes [25], and traffic estimation and control with small sets of sensor nodes [26] rather than evaluation of other VDSs. By now some VDS based wireless sensor networks have been developed, but no evaluation system based on them proposed yet meets all of the requirements (Table 1). Although there are some pilot programs for traffic measurement based on a wireless sensor node with a magneto-resistive sensor, the accuracy, portability, and the traceability are not satisfactory and the systems without fault-tolerance are prone to malfunction and accuracy degradation due to wireless interference [21, 22, 27]. Therefore, to attack the aforementioned problems of existing VDS evaluation systems, we propose our PES meeting the requirements (Table 1) of a portable VDS evaluation system. Our PES operates autonomously, so unlike video analysis, the evaluation is objective. In addition, unlike laser or piezoelectric cable evaluation systems, the PES can easily \begin{table}
\begin{tabular}{c c c c c c} \hline  & **Video** & **Portable** & **Piezoelectric** & **Existing** & **PES** \\  & **Frame** & **Laser** & **Cable** & **MR VDSs** & **PES** \\ \hline Cost & High & High & High (Maintenance) & Economic & Economic \\ Easy/fast to install & Yes & Yes & Yes & Yes & Yes \\ Accuracy & Good & High & High & High & High \\ Objectivity & Low & High & High & High & High \\ Multi-lane Scalability & Yes & Difficult & Difficult & Yes & Yes \\ Traceability & Yes & Yes & Yes & No & Yes \\ Real-time monitoring & Yes & Yes & Yes & No & Yes \\ Fault-tolerance & Yes & Yes & Yes & Some & Yes \\ \hline \end{tabular}
\end{table} 
Table 2: Overall comparison between the existing portable evaluation systems (or VDSs)of traffic at a time. Finally, comparing the existing WSN-based VDS, our PES offers high accuracy, portability, traceability, and fault-tolerance. Table 2 compares the existing portable evaluation systems and the proposed PES. For the cost, referring to [20,28], we compare the minimum device costs for some types of evaluation systems assuming two lanes. PES is the most cost-effective, since the device cost of the PES is $200 \(\times\)2 \(\times\)2 + $1,200 = $2,000, while the costs for a video image processing-based VDS and a laser based one (excluding video recording system) are $4,900 and $31,580, respectively.