## 2 Related Works
### Technology for Vehicle Idling Control  
[PERSON] et al. (2013), [PERSON] et al. (2013), [PERSON] et al. (2014), and [PERSON] et al. (2016) underscored the importance of adopting idle-reduction strategies to mitigate the adverse effects of vehicle idling on air quality at signalized intersections in urban areas and suggested multiple mitigation measures, such as auxiliary power units (APUs), direct-fired heaters, fuel cells, truck stop electrification, improving signal timing, promoting public transport, implementing land use and transport policies, encouraging non-motorized transport modes, and so forth [17; 18; 19; 20]. This study mainly focused on stop-and-go technology and traffic signal operations aided with the sophisticated systems among the existing research efforts on alleviating the environmental effect of vehicle idling. Stop-and-go technology allows vehicles to automatically turn off the internal combustion engine (ICE) during idling periods and restart it when the driver restarts, which is particularly beneficial in urban traffic conditions where vehicles frequently stop and start, leading to higher environmental pollution, thereby enabling significant improvements in reducing CO\({}_{2}\) emissions [21; 22; 23; 24]. [PERSON] et al. (2012) employed an ultrasonic sensor to estimate frontal traffic conditions and developed a neural network-based fuzzy logic algorithm to control engine idling for the idle stop-and-go system [25]. [PERSON] et al. (2017) analyzed vehicle specific power (_VSP_) to understand the impact of stop-and-go driving behaviors at intersections on emissions by employing a high-resolution driving simulator to analyze acceleration and deceleration behaviors [26]. [PERSON] et al. (2022) investigated the effects of stop-and-go systems on particulate emissions in gasoline direct injection vehicles under varying temperature conditions with testing vehicles equipped with stop-and-go systems [27]. [PERSON] et al. (2015), [PERSON] et al. (2020), [PERSON] et al. (2022), and [PERSON] et al. (2022) introduced an enhanced control algorithm to stop-and-go technology by determining the optimal time to turn off the engine based on traffic light information disseminated through vehicle-to-infrastructure (V2I) communication, which is a significant step in integrating traffic signal information into idle stop-and-go systems [28; 29; 30; 31]. [PERSON] et al. (2018) showed that stop-and-go technology can reduce CO\({}_{2}\) emissions by more than 4-7% in urban traffic from a field test using three cars equipped with portable emission systems (PEMSs) to measure emissions in Napoli [22]. [PERSON] et al. (2011) found that a vehicle equipped with a stop-and-go system reduced more than 20% of CO\({}_{2}\) emissions compared with one without the system in urban traffic conditions [32]. Also, [PERSON] et al. (2017) proved that the automatic stop-and-go function in hybrid electric vehicles (HEVs) can save over 16% of emissions [23]. Many researchers inspected the optimal time duration to control vehicle idling; that is, [PERSON] et al. (2018) revealed that idling for over 13 s leads to greater emissions than stopping and restarting the engine [33]. The U.S. Department of Energy (2015) highlighted that idling for more than 10 s produces more emissions than restarting the engine [34]. [PERSON] et al. (2017) indicated that it is more efficient to turn off the engine if idling is expected to last over 10 s [35]. [PERSON] et al. (2011) investigated the emissions associated with idling versus restarting the engine by comparing actual idling emissions, aiming to determine the impact of idling over various durations by the Argonne National Laboratory, finding that idling for more than 10 s emits more CO\({}_{2}\) than restarting the engine [36]. [PERSON] et al. (2017) recommended switching off vehicle engines if the waiting time is more than 15-20 s [37]. Besides the stop-and-go technology, numerous studies on the optimal operation of traffic signal and vehicle speed adjustment have been conducted.